Bio


Kawin Setsompop is an Associate Professor of Radiology and, by courtesy, of Electrical Engineering. His research focuses on the development of novel MRI acquisition methods, with the goal of creating imaging technologies that can be used to help better understand brain structure and function for applications in Healthcare and Health sciences. He received his Master’s degree in Engineering Science from Oxford University and his PhD in Electrical Engineering and Computer Science from MIT. For the last decade, prior to joining Stanford in 2020, he led a research group at Harvard/MIT that pioneered a number of widely used MRI acquisition technologies. A number of these technologies have been successfully translated into FDA-approved software products that are being used daily on MRI scanners across the world, in both the clinical and neuroscientific fields.

Academic Appointments


Administrative Appointments


  • Associate Chair of Research Strategic Development, Department of Radiology (2020 - Present)

Honors & Awards


  • K99/R00 Career development award, National Institute of Health (2010)
  • NIBIB New Horizon planery lecture, International Society of Magnetic Resonance in Medicine (2016)
  • Fellow, International Society of Magnetic Resonance in Medicine (2020)

Boards, Advisory Committees, Professional Organizations


  • Advisory Board, Subtle Medical (2021 - Present)
  • Advisory Board, Kineticor (2018 - Present)

Professional Education


  • PostDoc, Harvard University/Massachusetts General Hospital, Radiology (2010)
  • Ph.D., MIT, Electrical Engineering and Computer Science (2008)
  • M.Eng, Oxford University, Engineering Science (2003)

Patents


  • Cauley, Bilgic, Setsompop, Wald. "United States Patent US10126397 Systems and methods for fast magnetic resonance image reconstruction using a heirarchically semiseparable solver"
  • Hoge, Polimeni, Setsompop. "United States Patent US10175328B2 System and method for reconstructing ghost-free images from data acquired using simultaneous multislice magnetic resonance imaging"
  • Zhao, Setsompop, Wald. "United States Patent US10241176B2 Systems and methods for statistical reconstruction of magnetic resonance fingerprinting data"
  • Cauley, Polimeni, Setsompop, Wald. "United States Patent US10310042B2 Hierrarchical mapping framework for coil compression in magnetic resonance image reconstruction"
  • Setsompop, Stockmann, Wald, Witzel. "United States Patent US10324149B2 Systems and methods for generalized slice dithered enhanced resolution magnetic resonance imaging"
  • Eichner, Wald, Setsompop. "United States Patent US10345409B2 System and method for simultaneous multislice excitation using combined multiband and periodic slice"
  • Cauley, Setsompop, Wald. "United States Patent US10408910B2 Systems and methods for joint trajectory and parallel magnetic resonance imaging optimization for auto-calibrated image reconstruction"
  • Polimeni, Setsompop, Wald. "United States Patent US10429475B2 Method for increasing signal-to-noise ratio in magnetic resonance imaging using per-voxel noise"
  • Setsompop, Bilgic, Wald. "United States Patent US10436866B2 Simultaneous multislice MRI with random gradient encoding"
  • Gulani, Griswold, Yang, Jiang, Setsompop. "United States Patent US10598747 System and method for simultaneous multislice magnetic resonance fingerprinting with variable radio frequency encoding"
  • Eichner, Setsompop, Wald, Cauley. "United States Patent US10605882 Systems and methods for removing background phase variations in diffusionweighted magnetic resonance imaging"
  • Setsompop, Wald, Dong, Guo, Wang, Reese. "United States Patent US10871534 Accelerated magnetic resonance imaging using tilted reconstruction kernel in phase encoded and point spread function encoded k-space"
  • Polak, Raithel, Setsompop. "United States Patent US10895622 Noise suppression for wave-CAIPI"
  • Setsompop, Wald, Dong, Guo, Wang, Reese. "United States Patent US10901061 Accelerated diffusion-weighted magnetic resonance imaging with self-navigated, phase corrected titled kernel reconstruction of phase encode and point spread function encoded k-space"
  • Setsompop, Bilgic, Wald, Witzel. "United States Patent US10908248 Systems and methods for slice dithered enhanced resolution simultaneous multislice magnetic resonance imaging"
  • Bilgic Setsompop, Polak, Ye, Wald. "United States Patent US11009675 Method for simultaneous time-interleaved multislice magnetic resonance imaging"
  • Polak, Setsompop. "United States Patent US20200249301 Reconstruction of Magnetic-Resonance Datasets using Machine Learning"
  • Polak, Setsompop. "United States Patent US20200341094 Multi-contrast MRI Imaging Reconstruction using Machine Learning"
  • Zelinski, Adalsteinsson, Setsompop, Wald, Fontius. "United States Patent US7336145 Method for designing RF excitation pulses in magnetic resonance tomography"
  • Setsompop, Alagappan, Adalsteinsson, Wald. "United States Patent US8076939 Method for Fast Magnetic Resonance Radiofrequency Coil Transmission Profile Mapping."
  • Setsompop, Alagappan, Adalsteinsson, Wald. "United States Patent US8076939 Method for Fast Magnetic Resonance Radiofrequency Coil Transmission Profile Mapping"
  • Setsompop, Alagappan, Gagoski, Wald, Adalsteinsson. "United States Patent US8085044 Method for producing spectral-spatial parallel RF excitations for magnetic resonance imaging"
  • Zelinski, Setsompop, Adalsteinsson, Goyal. "United States Patent US8148985 Method for Reducing Maximum Local Specific Absorption Rate in Magnetic Resonance Imaging"
  • Setsompop, Wald. "United States Patent US8405395 Method for Simultaneous Multi-slice Magnetic Resonance Imaging"
  • Adalsteinsson, Fautz, Setsompop, Wald. "United States Patent US8866478 Method and processor and magnetic resonance apparatus for designing RF pulses to mitigate off-resonance effects"
  • Setsompop, Wald. "United States Patent US8981776 Method for magnetic resonance imaging with controlled aliasing"
  • Setsompop, Wald. "United States Patent US9081055 Method for Reducing Local Specific Absorption Rate in Magnetic Resonance Imaging Using Radio Frequency Coil Array Dark Modes"
  • Setsompop, Bilgic. "United States Patent US9542763 Systems and methods for fast reconstruction for Quantitative Susceptibility Mapping using Magnetic Resonance Imaging"
  • Polimeni, Bhat, Heberlein, Setsompop, Witzel, Cauley. "United States Patent US9588208 Methods, systems and apparatuses for rapid segmented, accelerated, and simultaneous multi-slice echo planar imaging"
  • Polimeni, Wald, Setsompop. "United States Patent US9778336 System and method for rapid, multi-shot segmented magnetic resonance imaging"
  • Setsompop, Griswold, Ye, Wald, Ma, Jiang. "United States Patent US9897675B2 Magnetic resonance fingerprinting (MRF) with simultaneous multivolume acquisition"
  • Cauley, Griswold, Setsompop, Wald. "United States Patent US9964616B2 Fast group matching for magnetic resonance fingerprinting reconstruction"

2020-21 Courses


Stanford Advisees


All Publications


  • MRI Highly Accelerated Wave-CAIPI T1-SPACE versus Standard T1-SPACE to detect brain gadolinium-enhancing lesions at 3T. Journal of neuroimaging : official journal of the American Society of Neuroimaging Goncalves Filho, A. L., Longo, M. G., Conklin, J., Cauley, S. F., Polak, D., Liu, W., Splitthoff, D. N., Lo, W., Kirsch, J. E., Setsompop, K., Schaefer, P. W., Huang, S. Y., Rapalino, O. 2021

    Abstract

    BACKGROUND AND PURPOSE: High-resolution three-dimensional (3D) post-contrast imaging of the brain is essential for comprehensive evaluation of inflammatory, neoplastic, and neurovascular diseases of the brain. 3D T1-weighted spin-echo-based sequences offer increased sensitivity for the detection of enhancing lesions but are relatively prolonged examinations. We evaluated whether a highly accelerated Wave-controlled aliasing in parallel imaging (Wave-CAIPI) post-contrast 3D T1-sampling perfection with application-optimized contrasts using different flip angle evolutions (T1-SPACE) sequence (Wave-T1-SPACE) was noninferior to the standard high-resolution 3D T1-SPACE sequence for visualizing enhancing lesions with comparable diagnostic quality.METHODS: One hundred and three consecutive patients were prospectively evaluated with a standard post-contrast 3D T1-SPACE sequence (acquisition time [TA] = 4 min 19 s) and an optimized Wave-CAIPI 3D T1-SPACE sequence (TA = 1 min 40 s) that was nearly three times faster than the standard sequence. Two blinded neuroradiologists performed a head-to-head comparison to evaluate the visualization of enhancing pathology, perception of artifacts, and overall diagnostic quality. A 15% margin was used to test whether post-contrast Wave-T1-SPACE was noninferior to standard T1-SPACE.RESULTS: Wave-T1-SPACE was noninferior to standard T1-SPACE for delineating parenchymal and meningeal enhancing pathology (p<0.01). Wave-T1-SPACE showed marginally higher background noise compared to the standard sequence and was noninferior in the overall diagnostic quality (p = 0.03).CONCLUSIONS: Our findings show that Wave-T1-SPACE was noninferior to standard T1-SPACE for visualization of enhancing pathology and overall diagnostic quality with a three-fold reduction in acquisition time compared to the standard sequence. Wave-T1-SPACE may be used to accelerate 3D post-contrast T1-weighted spin-echo imaging without loss of clinically important information.

    View details for DOI 10.1111/jon.12893

    View details for PubMedID 34081374

  • Efficient T2 mapping with blip-up/down EPI and gSlider-SMS (T2 -BUDA-gSlider). Magnetic resonance in medicine Cao, X., Wang, K., Liao, C., Zhang, Z., Srinivasan Iyer, S., Chen, Z., Lo, W., Liu, H., He, H., Setsompop, K., Zhong, J., Bilgic, B. 2021

    Abstract

    PURPOSE: To rapidly obtain high isotropic-resolution T2 maps with whole-brain coverage and high geometric fidelity.METHODS: A T2 blip-up/down EPI acquisition with generalized slice-dithered enhanced resolution (T2 -BUDA-gSlider) is proposed. A RF-encoded multi-slab spin-echo (SE) EPI acquisition with multiple TEs was developed to obtain high SNR efficiency with reduced TR. This was combined with an interleaved 2-shot EPI acquisition using blip-up/down phase encoding. An estimated field map was incorporated into the joint multi-shot EPI reconstruction with a structured low rank constraint to achieve distortion-free and robust reconstruction for each slab without navigation. A Bloch simulated subspace model was integrated into gSlider reconstruction and used for T2 quantification.RESULTS: In vivo results demonstrated that the T2 values estimated by the proposed method were consistent with gold standard spin-echo acquisition. Compared to the reference 3D fast spin echo (FSE) images, distortion caused by off-resonance and eddy current effects were effectively mitigated.CONCLUSION: BUDA-gSlider SE-EPI acquisition and gSlider-subspace joint reconstruction enabled distortion-free whole-brain T2 mapping in 2 min at ~1 mm3 isotropic resolution, which could bring significant benefits to related clinical and neuroscience applications.

    View details for DOI 10.1002/mrm.28872

    View details for PubMedID 34046924

  • Segmented simultaneous multi-slice diffusion-weighted imaging with navigated 3D rigid motion correction. Magnetic resonance in medicine Riedel Ne Steinhoff, M., Setsompop, K., Mertins, A., Bornert, P. 2021

    Abstract

    PURPOSE: To improve the robustness of diffusion-weighted imaging (DWI) data acquired with segmented simultaneous multi-slice (SMS) echo-planar imaging (EPI) against in-plane and through-plane rigid motion.THEORY AND METHODS: The proposed algorithm incorporates a 3D rigid motion correction and wavelet denoising into the image reconstruction of segmented SMS-EPI diffusion data. Low-resolution navigators are used to estimate shot-specific diffusion phase corruptions and 3D rigid motion parameters through SMS-to-volume registration. The shot-wise rigid motion and phase parameters are integrated into a SENSE-based full-volume reconstruction for each diffusion direction. The algorithm is compared to a navigated SMS reconstruction without gross motion correction in simulations and in vivo studies with four-fold interleaved 3-SMS diffusion tensor acquisitions.RESULTS: Simulations demonstrate high fidelity was achieved in the SMS-to-volume registration, with submillimeter registration errors and improved image reconstruction quality. In vivo experiments validate successful artifact reduction in 3D motion-compromised in vivo scans with a temporal motion resolution of approximately 0.3 s.CONCLUSION: This work demonstrates the feasibility of retrospective 3D rigid motion correction from shot navigators for segmented SMS DWI.

    View details for DOI 10.1002/mrm.28813

    View details for PubMedID 33955588

  • Coupled Neural, Vascular, and Cerebrospinal Fluid Dynamics in Human Sleep Fultz, N., Bonmassar, G., Setsompop, K., Stickgold, R., Rosen, B., Polimeni, J., Lewis, L. ELSEVIER SCIENCE INC. 2021: S31
  • A multi-inversion multi-echo spin and gradient echo echo planar imaging sequence with low image distortion for rapid quantitative parameter mapping and synthetic image contrasts MAGNETIC RESONANCE IN MEDICINE Manhard, M., Stockmann, J., Liao, C., Park, D., Han, S., Fair, M., van den Boomen, M., Polimeni, J., Bilgic, B., Setsompop, K. 2021

    Abstract

    Brain imaging exams typically take 10-20 min and involve multiple sequential acquisitions. A low-distortion whole-brain echo planar imaging (EPI)-based approach was developed to efficiently encode multiple contrasts in one acquisition, allowing for calculation of quantitative parameter maps and synthetic contrast-weighted images.Inversion prepared spin- and gradient-echo EPI was developed with slice-order shuffling across measurements for efficient acquisition with T1 , T2 , and T 2 ∗ weighting. A dictionary-matching approach was used to fit the images to quantitative parameter maps, which in turn were used to create synthetic weighted images with typical clinical contrasts. Dynamic slice-optimized multi-coil shimming with a B0 shim array was used to reduce B0 inhomogeneity and, therefore, image distortion by >50%. Multi-shot EPI was also implemented to minimize distortion and blurring while enabling high in-plane resolution. A low-rank reconstruction approach was used to mitigate errors from shot-to-shot phase variation.The slice-optimized shimming approach was combined with in-plane parallel-imaging acceleration of 4× to enable single-shot EPI with more than eight-fold distortion reduction. The proposed sequence efficiently obtained 40 contrasts across the whole-brain in just over 1 min at 1.2 × 1.2 × 3 mm resolution. The multi-shot variant of the sequence achieved higher in-plane resolution of 1 × 1 × 4 mm with good image quality in 4 min. Derived quantitative maps showed comparable values to conventional mapping methods.The approach allows fast whole-brain imaging with quantitative parameter maps and synthetic weighted contrasts. The slice-optimized multi-coil shimming and multi-shot reconstruction approaches result in minimal EPI distortion, giving the sequence the potential to be used in rapid screening applications.

    View details for DOI 10.1002/mrm.28761

    View details for Web of Science ID 000632464500001

    View details for PubMedID 33764563

  • Variable flip angle Echo Planar Time-Resolved Imaging (vFA-EPTI) for fast high-resolution gradient echo myelin water imaging. NeuroImage Dong, Z., Wang, F., Chan, K., Reese, T. G., Bilgic, B., Marques, J. P., Setsompop, K. 2021: 117897

    Abstract

    Myelin water imaging techniques based on multi-compartment relaxometry have been developed as an important tool to measure myelin concentration in vivo, but are limited by the long scan time of multi-contrast multi-echo acquisition. In this work, a fast imaging technique, termed variable flip angle Echo Planar Time-Resolved Imaging (vFA-EPTI), is developed to acquire multi-echo and multi-flip-angle gradient-echo data with significantly reduced acquisition time, providing rich information for multi-compartment analysis of gradient-echo myelin water imaging (GRE-MWI). The proposed vFA-EPTI method achieved 26 folds acceleration with good accuracy by utilizing an efficient continuous readout, optimized spatiotemporal encoding across echoes and flip angles, as well as a joint subspace reconstruction. An approach to estimate off-resonance field changes between different flip-angle acquisitions was also developed to ensure high-quality joint reconstruction across flip angles. The accuracy of myelin water fraction (MWF) estimate under high acceleration was first validated by a retrospective undersampling experiment using a lengthy fully-sampled data as reference. Prospective experiments were then performed where whole-brain MWF and multi-compartment quantitative maps were obtained in 5 minutes at 1.5-mm isotropic resolution and 24 minutes at 1-mm isotropic resolution at 3T. Additionally, ultra-high resolution data at 600-m isotropic resolution were acquired at 7T, which show detailed structures within the cortex such as the line of Gennari, demonstrating the ability of the proposed method for submillimeter GRE-MWI that can be used to study cortical myeloarchitecture in vivo.

    View details for DOI 10.1016/j.neuroimage.2021.117897

    View details for PubMedID 33621694

  • In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution. Scientific data Wang, F. n., Dong, Z. n., Tian, Q. n., Liao, C. n., Fan, Q. n., Hoge, W. S., Keil, B. n., Polimeni, J. R., Wald, L. L., Huang, S. Y., Setsompop, K. n. 2021; 8 (1): 122

    Abstract

    We present a whole-brain in vivo diffusion MRI (dMRI) dataset acquired at 760 μm isotropic resolution and sampled at 1260 q-space points across 9 two-hour sessions on a single healthy participant. The creation of this benchmark dataset is possible through the synergistic use of advanced acquisition hardware and software including the high-gradient-strength Connectom scanner, a custom-built 64-channel phased-array coil, a personalized motion-robust head stabilizer, a recently developed SNR-efficient dMRI acquisition method, and parallel imaging reconstruction with advanced ghost reduction algorithm. With its unprecedented resolution, SNR and image quality, we envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance the understanding of human brain structures and connectivity. This comprehensive dataset can also be used as a test bed for new modeling, sub-sampling strategies, denoising and processing algorithms, potentially providing a common testing platform for further development of in vivo high resolution dMRI techniques. Whole brain anatomical T1-weighted and T2-weighted images at submillimeter scale along with field maps are also made available.

    View details for DOI 10.1038/s41597-021-00904-z

    View details for PubMedID 33927203

  • SNR-enhanced diffusion MRI with structure-preserving low-rank denoising in reproducing kernel Hilbert spaces. Magnetic resonance in medicine Ramos-Llordén, G. n., Vegas-Sánchez-Ferrero, G. n., Liao, C. n., Westin, C. F., Setsompop, K. n., Rathi, Y. n. 2021

    Abstract

    To introduce, develop, and evaluate a novel denoising technique for diffusion MRI that leverages nonlinear redundancy in the data to boost the SNR while preserving signal information.We exploit nonlinear redundancy of the dMRI data by means of kernel principal component analysis (KPCA), a nonlinear generalization of PCA to reproducing kernel Hilbert spaces. By mapping the signal to a high-dimensional space, a higher level of redundant information is exploited, thereby enabling better denoising than linear PCA. We implement KPCA with a Gaussian kernel, with parameters automatically selected from knowledge of the noise statistics, and validate it on realistic Monte Carlo simulations as well as with in vivo human brain submillimeter and low-resolution dMRI data. We also demonstrate KPCA denoising on multi-coil dMRI data.SNR improvements up to 2.7 × were obtained in real in vivo datasets denoised with KPCA, in comparison to SNR gains of up to 1.8 × using a linear PCA denoising technique called Marchenko-Pastur PCA (MPPCA). Compared to gold-standard dataset references created from averaged data, we showed that lower normalized root mean squared error was achieved with KPCA compared to MPPCA. Statistical analysis of residuals shows that anatomical information is preserved and only noise is removed. Improvements in the estimation of diffusion model parameters such as fractional anisotropy, mean diffusivity, and fiber orientation distribution functions were also demonstrated.Nonlinear redundancy of the dMRI signal can be exploited with KPCA, which allows superior noise reduction/SNR improvements than the MPPCA method, without loss of signal information.

    View details for DOI 10.1002/mrm.28752

    View details for PubMedID 33834546

  • Distortion-free, high-isotropic-resolution diffusion MRI with gSlider BUDA-EPI and multicoil dynamic B0 shimming. Magnetic resonance in medicine Liao, C. n., Bilgic, B. n., Tian, Q. n., Stockmann, J. P., Cao, X. n., Fan, Q. n., Iyer, S. S., Wang, F. n., Ngamsombat, C. n., Lo, W. C., Manhard, M. K., Huang, S. Y., Wald, L. L., Setsompop, K. n. 2021

    Abstract

    We combine SNR-efficient acquisition and model-based reconstruction strategies with newly available hardware instrumentation to achieve distortion-free in vivo diffusion MRI of the brain at submillimeter-isotropic resolution with high fidelity and sensitivity on a clinical 3T scanner.We propose blip-up/down acquisition (BUDA) for multishot EPI using interleaved blip-up/blip-down phase encoding and incorporate B0 forward-modeling into structured low-rank reconstruction to enable distortion-free and navigator-free diffusion MRI. We further combine BUDA-EPI with an SNR-efficient simultaneous multislab acquisition (generalized slice-dithered enhanced resolution ["gSlider"]), to achieve high-isotropic-resolution diffusion MRI. To validate gSlider BUDA-EPI, whole-brain diffusion data at 860-μm and 780-μm data sets were acquired. Finally, to improve the conditioning and minimize noise penalty in BUDA reconstruction at very high resolutions where B0 inhomogeneity can have a detrimental effect, the level of B0 inhomogeneity was reduced by incorporating slab-by-slab dynamic shimming with a 32-channel AC/DC coil into the acquisition. Whole-brain 600-μm diffusion data were then acquired with this combined approach of gSlider BUDA-EPI with dynamic shimming.The results of 860-μm and 780-μm datasets show high geometry fidelity with gSlider BUDA-EPI. With dynamic shimming, the BUDA reconstruction's noise penalty was further alleviated. This enables whole-brain 600-μm isotropic resolution diffusion imaging with high image quality.The gSlider BUDA-EPI method enables high-quality, distortion-free diffusion imaging across the whole brain at submillimeter resolution, where the use of multicoil dynamic B0 shimming further improves reconstruction performance, which can be particularly useful at very high resolutions.

    View details for DOI 10.1002/mrm.28748

    View details for PubMedID 33748985

  • Robust autocalibrated structured low-rank EPI ghost correction. Magnetic resonance in medicine Lobos, R. A., Hoge, W. S., Javed, A., Liao, C., Setsompop, K., Nayak, K. S., Haldar, J. P. 2020

    Abstract

    PURPOSE: We propose and evaluate a new structured low-rank method for echo-planar imaging (EPI) ghost correction called Robust Autocalibrated LORAKS (RAC-LORAKS). The method can be used to suppress EPI ghosts arising from the differences between different readout gradient polarities and/or the differences between different shots. It does not require conventional EPI navigator signals, and is robust to imperfect autocalibration data.METHODS: Autocalibrated LORAKS is a previous structured low-rank method for EPI ghost correction that uses GRAPPA-type autocalibration data to enable high-quality ghost correction. This method works well when the autocalibration data are pristine, but performance degrades substantially when the autocalibration information is imperfect. RAC-LORAKS generalizes Autocalibrated LORAKS in two ways. First, it does not completely trust the information from autocalibration data, and instead considers the autocalibration and EPI data simultaneously when estimating low-rank matrix structure. Second, it uses complementary information from the autocalibration data to improve EPI reconstruction in a multi-contrast joint reconstruction framework. RAC-LORAKS is evaluated using simulations and in vivo data, including comparisons to state-of-the-art methods.RESULTS: RAC-LORAKS is demonstrated to have good ghost elimination performance compared to state-of-the-art methods in several complicated EPI acquisition scenarios (including gradient-echo brain imaging, diffusion-encoded brain imaging, and cardiac imaging).CONCLUSIONS: RAC-LORAKS provides effective suppression of EPI ghosts and is robust to imperfect autocalibration data.

    View details for DOI 10.1002/mrm.28638

    View details for PubMedID 33332652

  • Diffusion-PEPTIDE: Distortion- and blurring-free diffusion imaging with self-navigated motion-correction and relaxometry capabilities. Magnetic resonance in medicine Fair, M. J., Liao, C., Manhard, M. K., Setsompop, K. 2020

    Abstract

    PURPOSE: To implement the time-resolved relaxometry PEPTIDE technique into a diffusion acquisition to provide self-navigated, distortion- and blurring-free diffusion imaging that is robust to motion, while simultaneously providing T2 and T 2 mapping.THEORY AND METHODS: The PEPTIDE readout was implemented into a spin-echo diffusion acquisition, enabling reconstruction of a time-series of T2 - and T 2 -weighted images, free from conventional echo planar imaging (EPI) distortion and blurring, for each diffusion-encoding. Robustness of PEPTIDE to motion and shot-to-shot phase variation was examined through a deliberate motion-corrupted diffusion experiment. Two diffusion-relaxometry in vivo brain protocols were also examined: (1)1 * 1 * 3 mm3 across 32 diffusion directions in 20 min, (2)1.5 * 1.5 * 3.0 mm3 across 6 diffusion-weighted images in 3.4 min. T2 , T 2 , and diffusion parameter maps were calculated from these data. As initial exploration of the rich diffusion-relaxometry data content for use in multi-compartment modeling, PEPTIDE data were acquired of a gadolinium-doped asparagus phantom. These datasets contained two compartments with different relaxation parameters and different diffusion orientation properties, and T2 relaxation variations across these diffusion directions were explored.RESULTS: Diffusion-PEPTIDE showed the capability to provide high quality diffusion images and T2 and T 2 maps from both protocols. The reconstructions were distortion-free, avoided potential resolution losses exceeding 100% in equivalent EPI acquisitions, and showed tolerance to nearly 30° of rotational motion. Expected variation in T2 values as a function of diffusion direction was observed in the two-compartment asparagus phantom (P < .01), demonstrating potential to explore diffusion-PEPTIDE data for multi-compartment modeling.CONCLUSIONS: Diffusion-PEPTIDE provides highly robust diffusion and relaxometry data and offers potential for future applications in diffusion-relaxometry multi-compartment modeling.

    View details for DOI 10.1002/mrm.28579

    View details for PubMedID 33314281

  • Nonlinear dipole inversion (NDI) enables robust quantitative susceptibility mapping (QSM). NMR in biomedicine Polak, D., Chatnuntawech, I., Yoon, J., Iyer, S. S., Milovic, C., Lee, J., Bachert, P., Adalsteinsson, E., Setsompop, K., Bilgic, B. 2020; 33 (12): e4271

    Abstract

    High-quality Quantitative Susceptibility Mapping (QSM) with Nonlinear Dipole Inversion (NDI) is developed with pre-determined regularization while matching the image quality of state-of-the-art reconstruction techniques and avoiding over-smoothing that these techniques often suffer from. NDI is flexible enough to allow for reconstruction from an arbitrary number of head orientations and outperforms COSMOS even when using as few as 1-direction data. This is made possible by a nonlinear forward-model that uses the magnitude as an effective prior, for which we derived a simple gradient descent update rule. We synergistically combine this physics-model with a Variational Network (VN) to leverage the power of deep learning in the VaNDI algorithm. This technique adopts the simple gradient descent rule from NDI and learns the network parameters during training, hence requires no additional parameter tuning. Further, we evaluate NDI at 7 T using highly accelerated Wave-CAIPI acquisitions at 0.5 mm isotropic resolution and demonstrate high-quality QSM from as few as 2-direction data.

    View details for DOI 10.1002/nbm.4271

    View details for PubMedID 32078756

  • Improving in vivo human cerebral cortical surface reconstruction using data-driven super-resolution. Cerebral cortex (New York, N.Y. : 1991) Tian, Q., Bilgic, B., Fan, Q., Ngamsombat, C., Zaretskaya, N., Fultz, N. E., Ohringer, N. A., Chaudhari, A. S., Hu, Y., Witzel, T., Setsompop, K., Polimeni, J. R., Huang, S. Y. 2020

    Abstract

    Accurate and automated reconstruction of the in vivo human cerebral cortical surface from anatomical magnetic resonance (MR) images facilitates the quantitative analysis of cortical structure. Anatomical MR images with sub-millimeter isotropic spatial resolution improve the accuracy of cortical surface and thickness estimation compared to the standard 1-millimeter isotropic resolution. Nonetheless, sub-millimeter resolution acquisitions require averaging multiple repetitions to achieve sufficient signal-to-noise ratio and are therefore long and potentially vulnerable to subject motion. We address this challenge by synthesizing sub-millimeter resolution images from standard 1-millimeter isotropic resolution images using a data-driven supervised machine learning-based super-resolution approach achieved via a deep convolutional neural network. We systematically characterize our approach using a large-scale simulated dataset and demonstrate its efficacy in empirical data. The super-resolution data provide improved cortical surfaces similar to those obtained from native sub-millimeter resolution data. The whole-brain mean absolute discrepancy in cortical surface positioning and thickness estimation is below 100mum at the single-subject level and below 50mum at the group level for the simulated data, and below 200mum at the single-subject level and below 100mum at the group level for the empirical data, making the accuracy of cortical surfaces derived from super-resolution sufficient for most applications.

    View details for DOI 10.1093/cercor/bhaa237

    View details for PubMedID 32887984

  • Axon diameter index estimation independent of fiber orientation distribution using high-gradient diffusion MRI. NeuroImage Fan, Q., Nummenmaa, A., Witzel, T., Ohringer, N., Tian, Q., Setsompop, K., Klawiter, E. C., Rosen, B. R., Wald, L. L., Huang, S. Y. 2020; 222: 117197

    Abstract

    Axon diameter mapping using high-gradient diffusion MRI has generated great interest as a noninvasive tool for studying trends in axonal size in the human brain. One of the main barriers to mapping axon diameter across the whole brain is accounting for complex white matter fiber configurations (e.g., crossings and fanning), which are prevalent throughout the brain. Here, we present a framework for generalizing axon diameter index estimation to the whole brain independent of the underlying fiber orientation distribution using the spherical mean technique (SMT). This approach is shown to significantly benefit from the use of real-valued diffusion data with Gaussian noise, which reduces the systematic bias in the estimated parameters resulting from the elevation of the noise floor when using magnitude data with Rician noise. We demonstrate the feasibility of obtaining whole-brain orientationally invariant estimates of axon diameter index and relative volume fractions in six healthy human volunteers using real-valued diffusion data acquired on a dedicated high-gradient 3-Tesla human MRI scanner with 300mT/m maximum gradient strength. The trends in axon diameter index are consistent with known variations in axon diameter from histology and demonstrate the potential of this generalized framework for revealing coherent patterns in axonal structure throughout the living human brain. The use of real-valued diffusion data provides a viable solution for eliminating the Rician noise floor and should be considered for all spherical mean approaches to microstructural parameter estimation.

    View details for DOI 10.1016/j.neuroimage.2020.117197

    View details for PubMedID 32745680

  • Ultra-high spatial resolution BOLD fMRI in humans using combined segmented-accelerated VFA-FLEET with a recursive RF pulse design MAGNETIC RESONANCE IN MEDICINE Berman, A. L., Grissom, W. A., Witzel, T., Nasr, S., Park, D. J., Setsompop, K., Polimeni, J. R. 2020

    Abstract

    To alleviate the spatial encoding limitations of single-shot echo-planar imaging (EPI) by developing multi-shot segmented EPI for ultra-high-resolution functional MRI (fMRI) with reduced ghosting artifacts from subject motion and respiration.Segmented EPI can reduce readout duration and reduce acceleration factors, however, the time elapsed between segment acquisitions (on the order of seconds) can result in intermittent ghosting, limiting its use for fMRI. Here, "FLEET" segment ordering, where segments are looped over before slices, was combined with a variable flip angle progression (VFA-FLEET) to improve inter-segment fidelity and maximize signal for fMRI. Scaling a sinc pulse's flip angle for each segment (VFA-FLEET-Sinc) produced inconsistent slice profiles and ghosting, therefore, a recursive Shinnar-Le Roux (SLR) radiofrequency (RF) pulse design was developed (VFA-FLEET-SLR) to generate unique pulses for every segment that together produce consistent slice profiles and signals.The temporal stability of VFA-FLEET-SLR was compared against conventional-segmented EPI and VFA-FLEET-Sinc at 3T and 7T. VFA-FLEET-SLR showed reductions in both intermittent and stable ghosting compared to conventional-segmented and VFA-FLEET-Sinc, resulting in improved image quality with a minor trade-off in temporal SNR. Combining VFA-FLEET-SLR with acceleration, we achieved a 0.6-mm isotropic acquisition at 7T, without zoomed imaging or partial Fourier, demonstrating reliable detection of blood oxygenation level-dependent (BOLD) responses to a visual stimulus. To counteract the increased repetition time from segmentation, simultaneous multi-slice VFA-FLEET-SLR was demonstrated using RF-encoded controlled aliasing.VFA-FLEET with a recursive RF pulse design supports acquisitions with low levels of artifact and spatial blur, enabling fMRI at previously inaccessible spatial resolutions with a "full-brain" field of view.

    View details for DOI 10.1002/mrm.28415

    View details for Web of Science ID 000551431800001

    View details for PubMedID 32705723

  • SURE-based automatic parameter selection for ESPIRiT calibration MAGNETIC RESONANCE IN MEDICINE Iyer, S., Ong, F., Setsompop, K., Doneva, M., Lustig, M. 2020

    Abstract

    ESPIRiT is a parallel imaging method that estimates coil sensitivity maps from the auto-calibration region (ACS). This requires choosing several parameters for the optimal map estimation. While fairly robust to these parameter choices, occasionally, poor selection can result in reduced performance. The purpose of this work is to automatically select parameters in ESPIRiT for more robust and consistent performance across a variety of exams.By viewing ESPIRiT as a denoiser, Stein's unbiased risk estimate (SURE) is leveraged to automatically optimize parameter selection in a data-driven manner. The optimum parameters corresponding to the minimum true squared error, minimum SURE as derived from densely sampled, high-resolution, and non-accelerated data and minimum SURE as derived from ACS are compared using simulation experiments. To avoid optimizing the rank of ESPIRiT's auto-calibrating matrix (one of the parameters), a heuristic derived from SURE-based singular value thresholding is also proposed.Simulations show SURE derived from the densely sampled, high-resolution, and non-accelerated data to be an accurate estimator of the true mean squared error, enabling automatic parameter selection. The parameters that minimize SURE as derived from ACS correspond well to the optimal parameters. The soft-threshold heuristic improves computational efficiency while providing similar results to an exhaustive search. In-vivo experiments verify the reliability of this method.Using SURE to determine ESPIRiT parameters allows for automatic parameter selections. In-vivo results are consistent with simulation and theoretical results.

    View details for DOI 10.1002/mrm.28386

    View details for Web of Science ID 000549849000001

    View details for PubMedID 32686178

  • DeepDTI: High-fidelity six-direction diffusion tensor imaging using deep learning. NeuroImage Tian, Q., Bilgic, B., Fan, Q., Liao, C., Ngamsombat, C., Hu, Y., Witzel, T., Setsompop, K., Polimeni, J. R., Huang, S. Y. 2020: 117017

    Abstract

    Diffusion tensor magnetic resonance imaging (DTI) is unsurpassed in its ability to map tissue microstructure and structural connectivity in the living human brain. Nonetheless, the angular sampling requirement for DTI leads to long scan times and poses a critical barrier to performing high-quality DTI in routine clinical practice and large-scale research studies. In this work we present a new processing framework for DTI entitled DeepDTI that minimizes the data requirement of DTI to six diffusion-weighted images (DWIs) required by conventional voxel-wise fitting methods for deriving the six unique unknowns in a diffusion tensor using data-driven supervised deep learning. DeepDTI maps the input b=0 image and six DWI volumes sampled along optimized diffusion-encoding directions, along with T1-weighted and T2-weighted image volumes, to the residuals between the input and high-quality output image volumes using a 10-layer three-dimensional convolutional neural network (CNN). The inputs and outputs of DeepDTI are uniquely formulated, which not only enables residual learning to boost CNN performance but also enables tensor fitting of resultant high-quality DWIs to generate orientational DTI metrics for tractography. The very deep CNN used by DeepDTI leverages the redundancy in local and non-local spatial information and across diffusion-encoding directions and image contrasts in the data. The performance of DeepDTI was systematically quantified in terms of the quality of the output images, DTI metrics, DTI-based tractography and tract-specific analysis results. We demonstrate rotationally-invariant and robust estimation of DTI metrics from DeepDTI that are comparable to those obtained with two b=0 images and 21 DWIs for the primary eigenvector derived from DTI and two b=0 images and 26-30 DWIs for various scalar metrics derived from DTI, achieving 3.3-4.6* acceleration, and twice as good as those of a state-of-the-art denoising algorithm at the group level. The twenty major white-matter tracts can be accurately identified from the tractography of DeepDTI results. The mean distance between the core of the major white-matter tracts identified from DeepDTI results and those from the ground-truth results using 18 b=0 images and 90 DWIs measures around 1-1.5 mm. DeepDTI leverages domain knowledge of diffusion MRI physics and power of deep learning to render DTI, DTI-based tractography, major white-matter tracts identification and tract-specific analysis more feasible for a wider range of neuroscientific and clinical studies.

    View details for DOI 10.1016/j.neuroimage.2020.117017

    View details for PubMedID 32504817

  • Echo planar time-resolved imaging with subspace reconstruction and optimized spatiotemporal encoding MAGNETIC RESONANCE IN MEDICINE Dong, Z., Wang, F., Reese, T. G., Bilgic, B., Setsompop, K. 2020: 2442–55

    Abstract

    To develop new encoding and reconstruction techniques for fast multi-contrast/quantitative imaging.The recently proposed Echo Planar Time-resolved Imaging (EPTI) technique can achieve fast distortion- and blurring-free multi-contrast/quantitative imaging. In this work, a subspace reconstruction framework is developed to improve the reconstruction accuracy of EPTI at high encoding accelerations. The number of unknowns in the reconstruction is significantly reduced by modeling the temporal signal evolutions using low-rank subspace. As part of the proposed reconstruction approach, a B0 -update algorithm and a shot-to-shot B0 variation correction method are developed to enable the reconstruction of high-resolution tissue phase images and to mitigate artifacts from shot-to-shot phase variations. Moreover, the EPTI concept is extended to 3D k-space for 3D GE-EPTI, where a new "temporal-variant" of CAIPI encoding is proposed to further improve performance.The effectiveness of the proposed subspace reconstruction was demonstrated first in 2D GESE EPTI, where the reconstruction achieved higher accuracy when compared to conventional B0 -informed GRAPPA. For 3D GE-EPTI, a retrospective undersampling experiment demonstrates that the new temporal-variant CAIPI encoding can achieve up to 72× acceleration with close to 2× reduction in reconstruction error when compared to conventional spatiotemporal-CAIPI encoding. In a prospective undersampling experiment, high-quality whole-brain T 2 ∗ and tissue phase maps at 1 mm isotropic resolution were acquired in 52 seconds at 3T using 3D GE-EPTI with temporal-variant CAIPI encoding.The proposed subspace reconstruction and optimized temporal-variant CAIPI encoding can further improve the performance of EPTI for fast quantitative mapping.

    View details for DOI 10.1002/mrm.28295

    View details for Web of Science ID 000528243200001

    View details for PubMedID 32333478

    View details for PubMedCentralID PMC7402016

  • Joint multi-contrast variational network reconstruction (jVN) with application to rapid 2D and 3D imaging MAGNETIC RESONANCE IN MEDICINE Polak, D., Cauley, S., Bilgic, B., Gong, E., Bachert, P., Adalsteinsson, E., Setsompop, K. 2020; 84 (3): 1456–69

    Abstract

    To improve the image quality of highly accelerated multi-channel MRI data by learning a joint variational network that reconstructs multiple clinical contrasts jointly.Data from our multi-contrast acquisition were embedded into the variational network architecture where shared anatomical information is exchanged by mixing the input contrasts. Complementary k-space sampling across imaging contrasts and Bunch-Phase/Wave-Encoding were used for data acquisition to improve the reconstruction at high accelerations. At 3T, our joint variational network approach across T1w, T2w and T2-FLAIR-weighted brain scans was tested for retrospective under-sampling at R = 6 (2D) and R = 4 × 4 (3D) acceleration. Prospective acceleration was also performed for 3D data where the combined acquisition time for whole brain coverage at 1 mm isotropic resolution across three contrasts was less than 3 min.Across all test datasets, our joint multi-contrast network better preserved fine anatomical details with reduced image-blurring when compared to the corresponding single-contrast reconstructions. Improvement in image quality was also obtained through complementary k-space sampling and Bunch-Phase/Wave-Encoding where the synergistic combination yielded the overall best performance as evidenced by exemplary slices and quantitative error metrics.By leveraging shared anatomical structures across the jointly reconstructed scans, our joint multi-contrast approach learnt more efficient regularizers, which helped to retain natural image appearance and avoid over-smoothing. When synergistically combined with advanced encoding techniques, the performance was further improved, enabling up to R = 16-fold acceleration with good image quality. This should help pave the way to very rapid high-resolution brain exams.

    View details for DOI 10.1002/mrm.28219

    View details for Web of Science ID 000561631500001

    View details for PubMedID 32129529

    View details for PubMedCentralID PMC7539238

  • High-fidelity, accelerated whole-brain submillimeter in vivo diffusion MRI using gSlider-spherical ridgelets (gSlider-SR) MAGNETIC RESONANCE IN MEDICINE Ramos-Llorden, G., Ning, L., Liao, C., Mukhometzianov, R., Michailovich, O., Setsompop, K., Rathi, Y. 2020; 84 (4): 1781–95

    Abstract

    To develop an accelerated, robust, and accurate diffusion MRI acquisition and reconstruction technique for submillimeter whole human brain in vivo scan on a clinical scanner.We extend the ultra-high resolution diffusion MRI acquisition technique, gSlider, by allowing undersampling in q-space and radiofrequency (RF)-encoding space, thereby dramatically reducing the total acquisition time of conventional gSlider. The novel method, termed gSlider-SR, compensates for the lack of acquired information by exploiting redundancy in the dMRI data using a basis of spherical ridgelets (SR), while simultaneously enhancing the signal-to-noise ratio. Using Monte Carlo simulation with realistic noise levels and several acquisitions of in vivo human brain dMRI data (acquired on a Siemens Prisma 3T scanner), we demonstrate the efficacy of our method using several quantitative metrics.For high-resolution dMRI data with realistic noise levels (synthetically added), we show that gSlider-SR can reconstruct high-quality dMRI data at different acceleration factors preserving both signal and angular information. With in vivo data, we demonstrate that gSlider-SR can accurately reconstruct 860 μm diffusion MRI data (64 diffusion directions at b = 2000 s / mm 2 ), at comparable quality as that obtained with conventional gSlider with four averages, thereby providing an eight-fold reduction in scan time (from 1 hour 20 to 10 minutes).gSlider-SR enables whole-brain high angular resolution dMRI at a submillimeter spatial resolution with a dramatically reduced acquisition time, making it feasible to use the proposed scheme on existing clinical scanners.

    View details for DOI 10.1002/mrm.28232

    View details for Web of Science ID 000517642500001

    View details for PubMedID 32125020

  • Blood Oxygen Level-Dependent MRI of the Myocardium with Multiecho Gradient-Echo Spin-Echo Imaging RADIOLOGY van den Boomen, M., Manhard, M., Snel, G. H., Han, S., Emblem, K. E., Slart, R. A., Sosnovik, D. E., Catana, C., Rosen, B. R., Prakken, N. J., Nguyen, C. T., Borra, R. H., Setsompop, K. 2020; 294 (3): 538–45

    Abstract

    Background Myocardial oxygenation imaging could help determine the presence of microvascular dysfunction associated with increased cardiovascular risk. However, it is challenging to depict the potentially small oxygenation alterations with current noninvasive cardiac MRI blood oxygen level-dependent (BOLD) techniques. Purpose To demonstrate the cardiac application of a gradient-echo spin-echo (GESE) echo-planar imaging sequence for dynamic and quantitative heartbeat-to-heartbeat BOLD MRI and evaluate the sequence in populations both healthy and with hypertension in combination with a breath hold-induced CO2 intervention. Materials and Methods GESE echo-planar imaging sequence was performed in 18 healthy participants and in eight prospectively recruited participants with hypertension on a 3.0-T MRI system. T2 and T2* maps were calculated per heartbeat with a four-parameter fitting technique. Septal regions of interests were used to determine T2 and T2* values per heartbeat and examined over the course of a breath hold to determine BOLD changes. T2 and T2* changes of healthy participants and participants with hypertension were compared by using a nonparametric Mann-Whitney test. Results GESE echo-planar imaging approach gave spatially stable T2 and T2* maps per heartbeat for healthy participants and participants with hypertension, with mean T2 values of 43 msec ± 5 (standard deviation) and 46 msec ± 9, respectively, and mean T2* values of 28 msec ± 5 and 22 msec ± 5, respectively. The healthy participants exhibited increasing T2 and T2* values over the course of a breath hold with a mean positive slope of 0.2 msec per heartbeat ± 0.1 for T2 and 0.2 msec per heartbeat ± 0.1 for T2*, whereas for participants with hypertension these dynamic T2 and T2* values had a mean negative slope of -0.2 msec per heartbeat ± 0.2 for T2 and -0.1 msec per heartbeat ± 0.2 for T2*. The difference in these mean slopes between healthy participants and participants with hypertension was significant for both T2 (P < .001) and T2* (P < .001). Conclusion Gradient-echo spin-echo echo-planar imaging sequence provided quantitative T2 and T2* maps per heartbeat and enabled dynamic heartbeat-to-heartbeat blood oxygen level-dependent (BOLD)-response imaging by analyzing changes in T2 and T2* over the time of a breath-hold intervention. This approach could identify differences in the BOLD response between healthy participants and participants with hypertension. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Friedrich in this issue.

    View details for DOI 10.1148/radiol.2020191845

    View details for Web of Science ID 000514823900010

    View details for PubMedID 31961241

    View details for PubMedCentralID PMC7053244

  • Further Development of Subspace Imaging to Magnetic Resonance Fingerprinting: A Low-rank Tensor Approach. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Zhao, B., Setsompop, K., Salat, D., Wald, L. L. 2020; 2020: 1662–66

    Abstract

    Magnetic resonance fingerprinting is a recent quantitative MRI technique that simultaneously acquires multiple tissue parameter maps (e.g., T1, T2, and spin density) in a single imaging experiment. In our early work, we demonstrated that the low-rank/subspace reconstruction significantly improves the accuracy of tissue parameter maps over the conventional MR fingerprinting reconstruction that utilizes simple pattern matching. In this paper, we generalize the low-rank/subspace reconstruction by introducing a multilinear low-dimensional image model (i.e., a low-rank tensor model). With this model, we further estimate the subspace associated with magnetization evolutions to simplify the image reconstruction problem. The proposed formulation results in a nonconvex optimization problem which we solve by an alternating minimization algorithm. We evaluate the performance of the proposed method with numerical experiments, and demonstrate that the proposed method improves the conventional reconstruction method and the state-of-the-art low-rank reconstruction method.

    View details for DOI 10.1109/EMBC44109.2020.9175853

    View details for PubMedID 33018315

  • FURTHER DEVELOPMENT OF SUBSPACE IMAGING TO MAGNETIC RESONANCE FINGERPRINTING: A LOW-RANK TENSOR APPROACH Zhao, B., Setsompop, K., Salat, D., Wald, L. L., IEEE IEEE. 2020: 1662–66
  • Accelerated Post-contrast Wave-CAIPI T1 SPACE Achieves Equivalent Diagnostic Performance Compared With Standard T1 SPACE for the Detection of Brain Metastases in Clinical 3T MRI. Frontiers in neurology Goncalves Filho, A. L., Conklin, J., Longo, M. G., Cauley, S. F., Polak, D., Liu, W., Splitthoff, D. N., Lo, W., Kirsch, J. E., Setsompop, K., Schaefer, P. W., Huang, S. Y., Rapalino, O. 2020; 11: 587327

    Abstract

    Background and Purpose: Brain magnetic resonance imaging (MRI) examinations using high-resolution 3D post-contrast sequences offer increased sensitivity for the detection of metastases in the central nervous system but are usually long exams. We evaluated whether the diagnostic performance of a highly accelerated Wave-controlled aliasing in parallel imaging (Wave-CAIPI) post-contrast 3D T1 SPACE sequence was non-inferior to the standard high-resolution 3D T1 SPACE sequence for the evaluation of brain metastases. Materials and Methods: Thirty-three patients undergoing evaluation for brain metastases were prospectively evaluated with a standard post-contrast 3D T1 SPACE sequence and an optimized Wave-CAIPI 3D T1 SPACE sequence, which was three times faster than the standard sequence. Two blinded neuroradiologists performed a head-to-head comparison to evaluate the visualization of pathology, perception of artifacts, and the overall diagnostic quality. Wave-CAIPI post-contrast T1 SPACE was tested for non-inferiority relative to standard T1 SPACE using a 15% non-inferiority margin. Results: Wave-CAIPI post-contrast T1 SPACE was non-inferior to the standard T1 SPACE for visualization of enhancing lesions (P < 0.01) and offered equivalent diagnostic quality performance and only marginally higher background noise compared to the standard sequence. Conclusions: Our findings suggest that Wave-CAIPI post-contrast T1 SPACE provides equivalent visualization of pathology and overall diagnostic quality with three times reduced scan time compared to the standard 3D T1 SPACE.

    View details for DOI 10.3389/fneur.2020.587327

    View details for PubMedID 33193054

  • High-fidelity, high-isotropic-resolution diffusion imaging through gSlider acquisition with B 1 + and T1 corrections and integrated ΔB0 /Rx shim array. Magnetic resonance in medicine Liao, C. n., Stockmann, J. n., Tian, Q. n., Bilgic, B. n., Arango, N. S., Manhard, M. K., Huang, S. Y., Grissom, W. A., Wald, L. L., Setsompop, K. n. 2020; 83 (1): 56–67

    Abstract

    B 1 + and T1 corrections and dynamic multicoil shimming approaches were proposed to improve the fidelity of high-isotropic-resolution generalized slice-dithered enhanced resolution (gSlider) diffusion imaging.An extended reconstruction incorporating B 1 + inhomogeneity and T1 recovery information was developed to mitigate slab-boundary artifacts in short-repetition time (TR) gSlider acquisitions. Slab-by-slab dynamic B0 shimming using a multicoil integrated ΔB0 /Rx shim array and high in-plane acceleration (Rinplane = 4) achieved with virtual-coil GRAPPA were also incorporated into a 1-mm isotropic resolution gSlider acquisition/reconstruction framework to achieve a significant reduction in geometric distortion compared to single-shot echo planar imaging (EPI).The slab-boundary artifacts were alleviated by the proposed B 1 + and T1 corrections compared to the standard gSlider reconstruction pipeline for short-TR acquisitions. Dynamic shimming provided >50% reduction in geometric distortion compared to conventional global second-order shimming. One-millimeter isotropic resolution diffusion data show that the typically problematic temporal and frontal lobes of the brain can be imaged with high geometric fidelity using dynamic shimming.The proposed B 1 + and T1 corrections and local-field control substantially improved the fidelity of high-isotropic-resolution diffusion imaging, with reduced slab-boundary artifacts and geometric distortion compared to conventional gSlider acquisition and reconstruction. This enabled high-fidelity whole-brain 1-mm isotropic diffusion imaging with 64 diffusion directions in 20 min using a 3T clinical scanner.

    View details for DOI 10.1002/mrm.27899

    View details for PubMedID 31373048

    View details for PubMedCentralID PMC6778699

  • Linear Predictability in Magnetic Resonance Imaging Reconstruction: Leveraging Shift-Invariant Fourier Structure for Faster and Better Imaging IEEE SIGNAL PROCESSING MAGAZINE Haldar, J. P., Setsompop, K. 2020; 37 (1): 69–82
  • Accelerated spin-echo functional MRI using multisection excitation by simultaneous spin-echo interleaving (MESSI) with complex-encoded generalized slice dithered enhanced resolution (cgSlider) simultaneous multislice echo-planar imaging MAGNETIC RESONANCE IN MEDICINE Han, S., Liao, C., Manhard, M., Park, D., Bilgic, B., Fair, M. J., Wang, F., Blazejewska, A., Grissom, W. A., Polimeni, J. R., Setsompop, K. 2020; 84 (1): 206–20

    Abstract

    Spin-echo functional MRI (SE-fMRI) has the potential to improve spatial specificity when compared with gradient-echo fMRI. However, high spatiotemporal resolution SE-fMRI with large slice-coverage is challenging as SE-fMRI requires a long echo time to generate blood oxygenation level-dependent (BOLD) contrast, leading to long repetition times. The aim of this work is to develop an acquisition method that enhances the slice-coverage of SE-fMRI at high spatiotemporal resolution.An acquisition scheme was developed entitled multisection excitation by simultaneous spin-echo interleaving (MESSI) with complex-encoded generalized slice dithered enhanced resolution (cgSlider). MESSI uses the dead-time during the long echo time by interleaving the excitation and readout of 2 slices to enable 2× slice-acceleration, while cgSlider uses the stable temporal background phase in SE-fMRI to encode/decode 2 adjacent slices simultaneously with a "phase-constrained" reconstruction method. The proposed cgSlider-MESSI was also combined with simultaneous multislice (SMS) to achieve further slice-acceleration. This combined approach was used to achieve 1.5-mm isotropic whole-brain SE-fMRI with a temporal resolution of 1.5 s and was evaluated using sensory stimulation and breath-hold tasks at 3T.Compared with conventional SE-SMS, cgSlider-MESSI-SMS provides 4-fold increase in slice-coverage for the same repetition time, with comparable temporal signal-to-noise ratio. Corresponding fMRI activation from cgSlider-MESSI-SMS for both fMRI tasks were consistent with those from conventional SE-SMS. Overall, cgSlider-MESSI-SMS achieved a 32× encoding-acceleration by combining Rinplane × MB × cgSlider × MESSI = 4 × 2 × 2 × 2.High-quality, high-resolution whole-brain SE-fMRI was acquired at a short repetition time using cgSlider-MESSI-SMS. This method should be beneficial for high spatiotemporal resolution SE-fMRI studies requiring whole-brain coverage.

    View details for DOI 10.1002/mrm.28108

    View details for Web of Science ID 000502704900001

    View details for PubMedID 31840295

    View details for PubMedCentralID PMC7083698

  • Propeller echo-planar time-resolved imaging with dynamic encoding MAGNETIC RESONANCE IN MEDICINE Fair, M. J., Wang, F., Dong, Z., Reese, T. G., Setsompop, K. 2020; 83 (6): 2124–37

    Abstract

    To develop a motion-robust extension to the recently developed echo-planar time-resolved imaging (EPTI) approach, referred to as PROPELLER EPTI with dynamic encoding (PEPTIDE), by incorporating rotations into the rapid, multishot acquisition to enable shot-to-shot motion correction.Echo-planar time-resolved imaging is a multishot EPI-based approach that allows extremely rapid acquisition of distortion-free and blurring-free multicontrast imaging and quantitative mapping. By combining k-space encoding rotations into the EPTI sampling strategy to repeatedly sample the low-resolution k-space center, PEPTIDE enables significant tolerance to shot-to-shot motion and B0 phase variations. Retrospective PEPTIDE data sets are created through a combination of in vivo EPTI data sets with rotationally acquired protocols, to enable direct comparison of the 2 methods and their robustness to identical motion. The PEPTIDE data sets are also prospectively acquired and again compared with EPTI, in the presence of true subject motion.The PEPTIDE approach is shown to be motion-robust to even severe subject motion (demonstrated > 30° in-plane rotation, alongside translational and through-plane motion), while maintaining the rapid encoding benefits of the EPTI technique. The technique enables accurate quantitative maps to be calculated from even severe motion data sets. While the performance of the motion correction depends on the type and severity of motion encountered, in all cases PEPTIDE significantly increases image quality in the presence of motion comparative to conventional EPTI.The newly developed PEPTIDE technique combines a high degree of motion tolerance into the EPTI framework, enabling highly rapid acquisition of distortion-free and blurring-free images at multiple TEs in the presence of motion.

    View details for DOI 10.1002/mrm.28071

    View details for Web of Science ID 000495172500001

    View details for PubMedID 31703154

    View details for PubMedCentralID PMC7047547

  • Coupled electrophysiological, hemodynamic, and cerebrospinal fluid oscillations in human sleep SCIENCE Fultz, N. E., Bonmassar, G., Setsompop, K., Stickgold, R. A., Rosen, B. R., Polimeni, J. R., Lewis, L. D. 2019; 366 (6465): 628-+

    Abstract

    Sleep is essential for both cognition and maintenance of healthy brain function. Slow waves in neural activity contribute to memory consolidation, whereas cerebrospinal fluid (CSF) clears metabolic waste products from the brain. Whether these two processes are related is not known. We used accelerated neuroimaging to measure physiological and neural dynamics in the human brain. We discovered a coherent pattern of oscillating electrophysiological, hemodynamic, and CSF dynamics that appears during non-rapid eye movement sleep. Neural slow waves are followed by hemodynamic oscillations, which in turn are coupled to CSF flow. These results demonstrate that the sleeping brain exhibits waves of CSF flow on a macroscopic scale, and these CSF dynamics are interlinked with neural and hemodynamic rhythms.

    View details for DOI 10.1126/science.aax5440

    View details for Web of Science ID 000494465700047

    View details for PubMedID 31672896

    View details for PubMedCentralID PMC7309589

  • Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction MAGNETIC RESONANCE IN MEDICINE Bilgic, B., Chatnuntawech, I., Manhard, M., Tian, Q., Liao, C., Iyer, S. S., Cauley, S. F., Huang, S. Y., Polimeni, J. R., Wald, L. L., Setsompop, K. 2019; 82 (4): 1343–58

    Abstract

    To introduce a combined machine learning (ML)- and physics-based image reconstruction framework that enables navigator-free, highly accelerated multishot echo planar imaging (msEPI) and demonstrate its application in high-resolution structural and diffusion imaging.Single-shot EPI is an efficient encoding technique, but does not lend itself well to high-resolution imaging because of severe distortion artifacts and blurring. Although msEPI can mitigate these artifacts, high-quality msEPI has been elusive because of phase mismatch arising from shot-to-shot variations which preclude the combination of the multiple-shot data into a single image. We utilize deep learning to obtain an interim image with minimal artifacts, which permits estimation of image phase variations attributed to shot-to-shot changes. These variations are then included in a joint virtual coil sensitivity encoding (JVC-SENSE) reconstruction to utilize data from all shots and improve upon the ML solution.Our combined ML + physics approach enabled Rinplane × multiband (MB) = 8- × 2-fold acceleration using 2 EPI shots for multiecho imaging, so that whole-brain T2 and T2 * parameter maps could be derived from an 8.3-second acquisition at 1 × 1 × 3-mm3 resolution. This has also allowed high-resolution diffusion imaging with high geometrical fidelity using 5 shots at Rinplane × MB = 9- × 2-fold acceleration. To make these possible, we extended the state-of-the-art MUSSELS reconstruction technique to simultaneous multislice encoding and used it as an input to our ML network.Combination of ML and JVC-SENSE enabled navigator-free msEPI at higher accelerations than previously possible while using fewer shots, with reduced vulnerability to poor generalizability and poor acceptance of end-to-end ML approaches.

    View details for DOI 10.1002/mrm.27813

    View details for Web of Science ID 000483917000010

    View details for PubMedID 31106902

    View details for PubMedCentralID PMC6626584

  • Network Accelerated Motion Estimation and Reduction (NAMER): Convolutional neural network guided retrospective motion correction using a separable motion model MAGNETIC RESONANCE IN MEDICINE Haskell, M. W., Cauley, S. F., Bilgic, B., Hossbach, J., Splitthoff, D. N., Pfeuffer, J., Setsompop, K., Wald, L. L. 2019; 82 (4): 1452–61

    Abstract

    We introduce and validate a scalable retrospective motion correction technique for brain imaging that incorporates a machine learning component into a model-based motion minimization.A convolutional neural network (CNN) trained to remove motion artifacts from 2D T2 -weighted rapid acquisition with refocused echoes (RARE) images is introduced into a model-based data-consistency optimization to jointly search for 2D motion parameters and the uncorrupted image. Our separable motion model allows for efficient intrashot (line-by-line) motion correction of highly corrupted shots, as opposed to previous methods which do not scale well with this refinement of the motion model. Final image generation incorporates the motion parameters within a model-based image reconstruction. The method is tested in simulations and in vivo motion experiments of in-plane motion corruption.While the convolutional neural network alone provides some motion mitigation (at the expense of introduced blurring), allowing it to guide the iterative joint-optimization both improves the search convergence and renders the joint-optimization separable. This enables rapid mitigation within shots in addition to between shots. For 2D in-plane motion correction experiments, the result is a significant reduction of both image space root mean square error in simulations, and a reduction of motion artifacts in the in vivo motion tests.The separability and convergence improvements afforded by the combined convolutional neural network+model-based method shows the potential for meaningful postacquisition motion mitigation in clinical MRI.

    View details for DOI 10.1002/mrm.27771

    View details for Web of Science ID 000483917000018

    View details for PubMedID 31045278

    View details for PubMedCentralID PMC6626557

  • Full utilization of conjugate symmetry: combining virtual conjugate coil reconstruction with partial Fourier imaging for g-factor reduction in accelerated MRI MAGNETIC RESONANCE IN MEDICINE Kettinger, A. O., Setsompop, K., Kannengiesser, S. R., Breuer, F. A., Vidnyanszky, Z., Blaimer, M. 2019; 82 (3): 1073–90

    Abstract

    In this study we propose a method to combine the parallel virtual conjugate coil (VCC) reconstruction with partial Fourier (PF) acquisition to improve reconstruction conditioning and reduce noise amplification in accelerated MRI where PF is used.Accelerated measurements are reconstructed in k-space by GRAPPA, with a VCC reconstruction kernel trained and applied in the central, symmetrically sampled part of k-space, while standard reconstruction is performed on the asymmetrically sampled periphery. The two reconstructed regions are merged to form a full reconstructed dataset, followed by PF reconstruction. The method is tested in vivo using T1-weighted spin-echo and T2*-weighted gradient-echo echo planar imaging (EPI) sequences, using both in-plane and simultaneous multislice (SMS) acceleration, at 1.5T and 3T field strengths. Noise amplification is estimated with theoretical calculations and pseudo-multiple-replica computations, for different PF factors, using zero-filling, homodyne, and projection onto convex sets (POCS) PF reconstruction.Depending on the PF algorithm and the inherent benefit of VCC reconstruction without PF, approximately 35% to 80%, 15% to 60%, and 5% to 30% of that intrinsic SNR gain can be retained for PF factors 7/8, 6/8, and 5/8, respectively, by including the VCC signals in the reconstruction. Compared with VCC-reconstructed acquisitions of higher acceleration, without PF, but having the same net acceleration, the combined method can provide a higher SNR if the inherent benefit of VCC is low or moderate.The proposed technique enables the partial application of VCC reconstruction to measurements with PF using either in-plane or SMS acceleration, and therefore can reduce the noise amplification of such acquisitions.

    View details for DOI 10.1002/mrm.27799

    View details for Web of Science ID 000485077600017

    View details for PubMedID 31081561

  • Highly-accelerated volumetric brain examination using optimized wave-CAIPI encoding JOURNAL OF MAGNETIC RESONANCE IMAGING Polak, D., Cauley, S., Huang, S. Y., Longo, M., Conklin, J., Bilgic, B., Ohringer, N., Raithel, E., Bachert, P., Wald, L. L., Setsompop, K. 2019; 50 (3): 961–74

    Abstract

    Rapid volumetric imaging protocols could better utilize limited scanner resources.To develop and validate an optimized 6-minute high-resolution volumetric brain MRI examination using Wave-CAIPI encoding.Prospective.Ten healthy subjects and 20 patients with a variety of intracranial pathologies.At 3 T, MPRAGE, T2 -weighted SPACE, SPACE FLAIR, and SWI were acquired at 9-fold acceleration using Wave-CAIPI and for comparison at 2-4-fold acceleration using conventional GRAPPA.Extensive simulations were performed to optimize the Wave-CAIPI protocol and minimize both g-factor noise amplification and potential T1 /T2 blurring artifacts. Moreover, refinements in the autocalibrated reconstruction of Wave-CAIPI were developed to ensure high-quality reconstructions in the presence of gradient imperfections. In a randomized and blinded fashion, three neuroradiologists assessed the diagnostic quality of the optimized 6-minute Wave-CAIPI exam and compared it to the roughly 3× slower GRAPPA accelerated protocol using both an individual and head-to-head analysis.A noninferiority test was used to test whether the diagnostic quality of Wave-CAIPI was noninferior to the GRAPPA acquisition, with a 15% noninferiority margin.Among all sequences, Wave-CAIPI achieved negligible g-factor noise amplification (gavg  ≤ 1.04) and burring artifacts from T1 /T2 relaxation. Improvements of our autocalibration approach for gradient imperfections enabled increased robustness to gradient mixing imperfections in tilted-field of view (FOV) prescriptions as well as variations in gradient and analog-to-digital converter (ADC) sampling rates. In the clinical evaluation, Wave-CAIPI achieved similar mean scores when compared with GRAPPA (MPRAGE: ØW  = 4.03, ØG  = 3.97; T2 w SPACE: ØW  = 4.00, ØG  = 4.00; SPACE FLAIR: ØW  = 3.97, ØG  = 3.97; SWI: ØW  = 3.93, ØG  = 3.83) and was statistically noninferior (N = 30, P < 0.05 for all sequences).The proposed volumetric brain exam retained comparable image quality when compared with the much longer conventional protocol.2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:961-974.

    View details for DOI 10.1002/jmri.26678

    View details for Web of Science ID 000480583900029

    View details for PubMedID 30734388

    View details for PubMedCentralID PMC6687581

  • Accelerated whole-brain perfusion imaging using a simultaneous multislice spin-echo and gradient-echo sequence with joint virtual coil reconstruction MAGNETIC RESONANCE IN MEDICINE Manhard, M., Bilgic, B., Liao, C., Han, S., Witzel, T., Yen, Y., Setsompop, K. 2019; 82 (3): 973–83

    Abstract

    Dynamic susceptibility contrast imaging requires high temporal sampling, which poses limits on achievable spatial coverage and resolution. Additionally, more encoding-intensive multi-echo acquisitions for quantitative imaging are desired to mitigate contrast leakage effects, which further limits spatial encoding. We present an accelerated sequence that provides whole-brain coverage at an improved spatio-temporal resolution, to allow for dynamic quantitative R2 and R2 * mapping during contrast-enhanced imaging.A multi-echo spin and gradient-echo sequence was implemented with simultaneous multislice acquisition. Complementary k-space sampling between repetitions and joint virtual coil reconstruction were used along with a dynamic phase-matching technique to achieve high-quality reconstruction at 9-fold acceleration, which enabled 2 × 2 × 5 mm whole-brain imaging at TR of 1.5 to 1.7 seconds. The multi-echo images from this sequence were fit to achieve quantitative R2 and R2 * maps for each repetition, and subsequently used to find perfusion measures including cerebral blood flow and cerebral blood volume.Images reconstructed using joint virtual coil show improved image quality and g-factor compared with conventional reconstruction methods, resulting in improved quantitative maps with a 9-fold acceleration factor and whole-brain coverage during the dynamic perfusion acquisition.The method presented shows the advantage of using a joint virtual coil-GRAPPA reconstruction to allow for high acceleration factors while maintaining reliable image quality for quantitative perfusion mapping, with the potential to improve tumor diagnostics and monitoring.

    View details for DOI 10.1002/mrm.27784

    View details for Web of Science ID 000485077600010

    View details for PubMedID 31069861

    View details for PubMedCentralID PMC6692914

  • Phase-matched virtual coil reconstruction for highly accelerated diffusion echo-planar imaging NEUROIMAGE Liao, C., Manhard, M., Bilgic, B., Tian, Q., Fan, Q., Han, S., Wang, F., Park, D., Witzel, T., Zhong, J., Wang, H., Wald, L. L., Setsompop, K. 2019; 194: 291–302

    Abstract

    To propose a virtual coil (VC) acquisition/reconstruction framework to improve highly accelerated single-shot EPI (SS-EPI) and generalized slice dithered enhanced resolution (gSlider) acquisition in high-resolution diffusion imaging (DI).For robust VC-GRAPPA reconstruction, a background phase correction scheme was developed to match the image phase of the reference data with the corrupted phase of the accelerated diffusion-weighted data, where the corrupted phase of the diffusion data varies from shot to shot. A Gy prewinding-blip was also added to the EPI acquisition, to create a shifted-ky sampling strategy that allows for better exploitation of VC concept in the reconstruction. To evaluate the performance of the proposed methods, 1.5 mm isotropic whole-brain SS-EPI and 860 μm isotropic whole-brain gSlider-EPI diffusion data were acquired at an acceleration of 8-9 fold. Conventional and VC-GRAPPA reconstructions were performed and compared, and corresponding g-factors were calculated.The proposed VC reconstruction substantially improves the image quality of both SS-EPI and gSlider-EPI, with reduced g-factor noise and reconstruction artifacts when compared to the conventional method. This has enabled high-quality low-noise diffusion imaging to be performed at 8-9 fold acceleration.The proposed VC acquisition/reconstruction framework improves the reconstruction of DI at high accelerations. The ability to now employ such high accelerations will allow DI with EPI at reduced distortion and faster scan time, which should be beneficial for many clinical and neuroscience applications.

    View details for DOI 10.1016/j.neuroimage.2019.04.002

    View details for Web of Science ID 000468742800024

    View details for PubMedID 30953837

  • Echo planar time-resolved imaging (EPTI) MAGNETIC RESONANCE IN MEDICINE Wang, F., Dong, Z., Reese, T. G., Bilgic, B., Manhard, M., Chen, J., Polimeni, J. R., Wald, L. L., Setsompop, K. 2019; 81 (6): 3599–3615

    Abstract

    To develop an efficient distortion- and blurring-free multi-shot EPI technique for time-resolved multiple-contrast and/or quantitative imaging.EPI is a commonly used sequence but suffers from geometric distortions and blurring. Here, we introduce a new multi-shot EPI technique termed echo planar time-resolved imaging (EPTI), which has the ability to rapidly acquire distortion- and blurring-free multi-contrast data set. The EPTI approach performs encoding in ky -t space and uses a new highly accelerated spatio-temporal CAIPI sampling trajectory to take advantage of signal correlation along these dimensions. Through this acquisition and a B0 -informed parallel imaging reconstruction, hundreds of "time-resolved" distortion- and blurring-free images at different TEs across the EPI readout window can be created at sub-millisecond temporal increments using a small number of EPTI shots. Moreover, a method for self-estimation and correction of shot-to-shot B0 variations was developed. Simultaneous multi-slice acquisition was also incorporated to further improve the acquisition efficiency.We evaluated EPTI under varying simulated acceleration factors, B0 -inhomogeneity, and shot-to-shot B0 variations to demonstrate its ability to provide distortion- and blurring-free images at multiple TEs. Two variants of EPTI were demonstrated in vivo at 3T: (1) a combined gradient- and spin-echo EPTI for quantitative mapping of T2 , T2* , proton density, and susceptibility at 1.1 × 1.1 × 3 mm3 whole-brain in 28 s (0.8 s/slice), and (2) a gradient-echo EPTI, for multi-echo and quantitative T2* fMRI at 2 × 2 × 3 mm3 whole-brain at a 3.3 s temporal resolution.EPTI is a new approach for multi-contrast and/or quantitative imaging that can provide fast acquisition of distortion- and blurring-free images at multiple TEs.

    View details for DOI 10.1002/mrm.27673

    View details for Web of Science ID 000481978700015

    View details for PubMedID 30714198

    View details for PubMedCentralID PMC6435385

  • The quest for high spatial resolution diffusion-weighted imaging of the human brain in vivo NMR IN BIOMEDICINE Holdsworth, S. J., O'Halloran, R., Setsompop, K. 2019; 32 (4): e4056

    Abstract

    Diffusion-weighted imaging, a contrast unique to MRI, is used for assessment of tissue microstructure in vivo. However, this exquisite sensitivity to finer scales far above imaging resolution comes at the cost of vulnerability to errors caused by sources of motion other than diffusion motion. Addressing the issue of motion has traditionally limited diffusion-weighted imaging to a few acquisition techniques and, as a consequence, to poorer spatial resolution than other MRI applications. Advances in MRI imaging methodology have allowed diffusion-weighted MRI to push to ever higher spatial resolution. In this review we focus on the pulse sequences and associated techniques under development that have pushed the limits of image quality and spatial resolution in diffusion-weighted MRI.

    View details for DOI 10.1002/nbm.4056

    View details for Web of Science ID 000461892300015

    View details for PubMedID 30730591

  • Optimal Experiment Design for Magnetic Resonance Fingerprinting: Cramer-Rao Bound Meets Spin Dynamics IEEE TRANSACTIONS ON MEDICAL IMAGING Zhao, B., Haldar, J. P., Liao, C., Ma, D., Jiang, Y., Griswold, M. A., Setsompop, K., Wald, L. L. 2019; 38 (3): 844–61

    Abstract

    Magnetic resonance (MR) fingerprinting is a new quantitative imaging paradigm, which simultaneously acquires multiple MR tissue parameter maps in a single experiment. In this paper, we present an estimation-theoretic framework to perform experiment design for MR fingerprinting. Specifically, we describe a discrete-time dynamic system to model spin dynamics, and derive an estimation-theoretic bound, i.e., the Cramér-Rao bound, to characterize the signal-to-noise ratio (SNR) efficiency of an MR fingerprinting experiment. We then formulate an optimal experiment design problem, which determines a sequence of acquisition parameters to encode MR tissue parameters with the maximal SNR efficiency, while respecting the physical constraints and other constraints from the image decoding/reconstruction process. We evaluate the performance of the proposed approach with numerical simulations, phantom experiments, and in vivo experiments. We demonstrate that the optimized experiments substantially reduce data acquisition time and/or improve parameter estimation. For example, the optimized experiments achieve about a factor of two improvement in the accuracy of T2 maps, while keeping similar or slightly better accuracy of T1 maps. Finally, as a remarkable observation, we find that the sequence of optimized acquisition parameters appears to be highly structured rather than randomly/pseudo-randomly varying as is prescribed in the conventional MR fingerprinting experiments.

    View details for DOI 10.1109/TMI.2018.2873704

    View details for Web of Science ID 000460662400018

    View details for PubMedID 30295618

    View details for PubMedCentralID PMC6447464

  • Wave-LORAKS: Combining wave encoding with structured low-rank matrix modeling for more highly accelerated 3D imaging MAGNETIC RESONANCE IN MEDICINE Kim, T., Bilgic, B., Polak, D., Setsompop, K., Haldar, J. P. 2019; 81 (3): 1620–33

    Abstract

    Wave-CAIPI is a novel acquisition approach that enables highly accelerated 3D imaging. This paper investigates the combination of Wave-CAIPI with LORAKS-based reconstruction (Wave-LORAKS) to enable even further acceleration.LORAKS is a constrained image reconstruction framework that can impose spatial support, smooth phase, sparsity, and/or parallel imaging constraints. LORAKS requires minimal prior information, and instead uses the low-rank subspace structure of the raw data to automatically learn which constraints to impose and how to impose them. Previous LORAKS implementations addressed 2D image reconstruction problems. In this work, several recent advances in structured low-rank matrix recovery were combined to enable large-scale 3D Wave-LORAKS reconstruction with improved quality and computational efficiency. Wave-LORAKS was investigated by retrospective subsampling of two fully sampled Wave-encoded 3D MPRAGE datasets, and comparisons were made against existing Wave reconstruction approaches.Results show that Wave-LORAKS can yield higher reconstruction quality with 16×-accelerated data than is obtained by traditional Wave-CAIPI with 9×-accerated data.There are strong synergies between Wave encoding and LORAKS, which enables Wave-LORAKS to achieve higher acceleration and more flexible sampling compared to Wave-CAIPI.

    View details for DOI 10.1002/mrm.27511

    View details for Web of Science ID 000462091200013

    View details for PubMedID 30252157

    View details for PubMedCentralID PMC6347537

  • Highly efficient MRI through multi-shot echo planar imaging Liao, C., Cao, X., Cho, J., Zhang, Z., Setsompop, K., Bilgic, B., VanDeVille, D., Papadakis, M., Lu, Y. M. SPIE-INT SOC OPTICAL ENGINEERING. 2019

    View details for DOI 10.1117/12.2527183

    View details for Web of Science ID 000511301800031

  • Tilted-CAIPI for highly accelerated distortion-free EPI with point spread function (PSF) encoding MAGNETIC RESONANCE IN MEDICINE Dong, Z., Wang, F., Reese, T. G., Manhard, M., Bilgic, B., Wald, L. L., Guo, H., Setsompop, K. 2019; 81 (1): 377–92

    Abstract

    To develop a method for fast distortion- and blurring-free imaging.EPI with point-spread-function (PSF) mapping can achieve distortion- and blurring-free imaging at a cost of long acquisition time. In this study, an acquisition/reconstruction technique, termed "tilted-CAIPI," is proposed to achieve >20× acceleration for PSF-EPI. The proposed method systematically optimized the k-space sampling trajectory with B0 -inhomogeneity-informed reconstruction, to exploit the inherent signal correlation in PSF-EPI and take full advantage of coil sensitivity. Susceptibility-induced phase accumulation is regarded as an additional encoding that is estimated by calibration data and integrated into reconstruction. Self-navigated phase correction was developed to correct shot-to-shot phase variation in diffusion imaging.Tilted-CAIPI was implemented at 3T, with incorporation of partial Fourier and simultaneous multislice to achieve further accelerations. T2 -weighted, T2* -weighted, and diffusion-weighted imaging experiments were conducted to evaluate the proposed method.The ability of tilted-CAIPI to provide highly accelerated imaging without distortion and blurring was demonstrated through in vivo brain experiments, where only 8 shots per simultaneous slice group were required to provide high-quality, high-SNR imaging at 0.8-1 mm resolution.Tilted-CAIPI achieved fast distortion- and blurring-free imaging with high SNR. Whole-brain T2 -weighted, T2* -weighted, and diffusion imaging can be obtained in just 15-60 s.

    View details for DOI 10.1002/mrm.27413

    View details for Web of Science ID 000454009000029

    View details for PubMedID 30229562

    View details for PubMedCentralID PMC6258292

  • Motion-robust sub-millimeter isotropic diffusion imaging through motion corrected generalized slice dithered enhanced resolution (MC-gSlider) acquisition MAGNETIC RESONANCE IN MEDICINE Wang, F., Bilgic, B., Dong, Z., Manhard, M., Ohringer, N., Zhao, B., Haskell, M., Cauley, S. F., Fan, Q., Witzel, T., Adalsteinsson, E., Wald, L. L., Setsompop, K. 2018; 80 (5): 1891–1906

    Abstract

    To develop an efficient MR technique for ultra-high resolution diffusion MRI (dMRI) in the presence of motion.gSlider is an SNR-efficient high-resolution dMRI acquisition technique. However, subject motion is inevitable during a prolonged scan for high spatial resolution, leading to potential image artifacts and blurring. In this study, an integrated technique termed Motion Corrected gSlider (MC-gSlider) is proposed to obtain high-quality, high-resolution dMRI in the presence of large in-plane and through-plane motion. A motion-aware reconstruction with spatially adaptive regularization is developed to optimize the conditioning of the image reconstruction under difficult through-plane motion cases. In addition, an approach for intra-volume motion estimation and correction is proposed to achieve motion correction at high temporal resolution.Theoretical SNR and resolution analysis validated the efficiency of MC-gSlider with regularization, and aided in selection of reconstruction parameters. Simulations and in vivo experiments further demonstrated the ability of MC-gSlider to mitigate motion artifacts and recover detailed brain structures for dMRI at 860 μm isotropic resolution in the presence of motion with various ranges.MC-gSlider provides motion-robust, high-resolution dMRI with a temporal motion correction sensitivity of 2 s, allowing for the recovery of fine detailed brain structures in the presence of large subject movements.

    View details for DOI 10.1002/mrm.27196

    View details for Web of Science ID 000448872700012

    View details for PubMedID 29607548

    View details for PubMedCentralID PMC6107445

  • Stimulus-dependent hemodynamic response timing across the human subcortical-cortical visual pathway identified through high spatiotemporal resolution 7T fMRI NEUROIMAGE Lewis, L. D., Setsompop, K., Rosen, B. R., Polimeni, J. R. 2018; 181: 279–91

    Abstract

    Recent developments in fMRI acquisition techniques now enable fast sampling with whole-brain coverage, suggesting fMRI can be used to track changes in neural activity at increasingly rapid timescales. When images are acquired at fast rates, the limiting factor for fMRI temporal resolution is the speed of the hemodynamic response. Given that HRFs may vary substantially in subcortical structures, characterizing the speed of subcortical hemodynamic responses, and how the hemodynamic response shape changes with stimulus duration (i.e. the hemodynamic nonlinearity), is needed for designing and interpreting fast fMRI studies of these regions. We studied the temporal properties and nonlinearities of the hemodynamic response function (HRF) across the human subcortical visual system, imaging superior colliculus (SC), lateral geniculate nucleus of the thalamus (LGN) and primary visual cortex (V1) with high spatiotemporal resolution 7 Tesla fMRI. By presenting stimuli of varying durations, we mapped the timing and nonlinearity of hemodynamic responses in these structures at high spatiotemporal resolution. We found that the hemodynamic response is consistently faster and narrower in subcortical structures than in cortex. However, the nonlinearity in LGN is similar to that in cortex, with shorter duration stimuli eliciting larger and faster responses than would have been predicted by a linear model. Using oscillatory visual stimuli, we tested the frequency response in LGN and found that its BOLD response tracked high-frequency (0.5 Hz) oscillations. The LGN response magnitudes were comparable to V1, allowing oscillatory BOLD signals to be detected in LGN despite the small size of this structure. These results suggest that the increase in the speed and amplitude of the hemodynamic response when neural activity is brief may be the key physiological driver of fast fMRI signals, enabling detection of high-frequency oscillations with fMRI. We conclude that subcortical visual structures exhibit fast and nonlinear hemodynamic responses, and that these dynamics enable detection of fast BOLD signals even within small deep brain structures when imaging is performed at ultra-high field.

    View details for DOI 10.1016/j.neuroimage.2018.06.056

    View details for Web of Science ID 000445165600024

    View details for PubMedID 29935223

    View details for PubMedCentralID PMC6245599

  • Dynamic 2D self-phase-map Nyquist ghost correction for simultaneous multi-slice echo planar imaging MAGNETIC RESONANCE IN MEDICINE Yarach, U., Tung, Y., Setsompop, K., In, M., Chatnuntawech, I., Yakupov, R., Godenschweger, F., Speck, O. 2018; 80 (4): 1577–87

    Abstract

    To develop a reconstruction pipeline that intrinsically accounts for both simultaneous multislice echo planar imaging (SMS-EPI) reconstruction and dynamic slice-specific Nyquist ghosting correction in time-series data.After 1D slice-group average phase correction, the separate polarity (i.e., even and odd echoes) SMS-EPI data were unaliased by slice GeneRalized Autocalibrating Partial Parallel Acquisition. Both the slice-unaliased even and odd echoes were jointly reconstructed using a model-based framework, extended for SMS-EPI reconstruction that estimates a 2D self-phase map, corrects dynamic slice-specific phase errors, and combines data from all coils and echoes to obtain the final images.The percentage ghost-to-signal ratios (%GSRs) and its temporal variations for MB3Ry 2 with a field of view/4 shift in a human brain obtained by the proposed dynamic 2D and standard 1D phase corrections were 1.37 ± 0.11 and 2.66 ± 0.16, respectively. Even with a large regularization parameter λ applied in the proposed reconstruction, the smoothing effect in fMRI activation maps was comparable to a very small Gaussian kernel size 1 × 1 × 1 mm3 .The proposed reconstruction pipeline reduced slice-specific phase errors in SMS-EPI, resulting in reduction of GSR. It is applicable for functional MRI studies because the smoothing effect caused by the regularization parameter selection can be minimal in a blood-oxygen-level-dependent activation map.

    View details for DOI 10.1002/mrm.27123

    View details for Web of Science ID 000448869800026

    View details for PubMedID 29427393

    View details for PubMedCentralID PMC6085172

  • Quantitative susceptibility mapping using deep neural network: QSMnet NEUROIMAGE Yoon, J., Gong, E., Chatnuntawech, I., Bilgic, B., Lee, J., Jung, W., Ko, J., Jung, H., Setsompop, K., Zaharchuk, G., Kim, E., Pauly, J., Lee, J. 2018; 179: 199–206

    Abstract

    Deep neural networks have demonstrated promising potential for the field of medical image reconstruction, successfully generating high quality images for CT, PET and MRI. In this work, an MRI reconstruction algorithm, which is referred to as quantitative susceptibility mapping (QSM), has been developed using a deep neural network in order to perform dipole deconvolution, which restores magnetic susceptibility source from an MRI field map. Previous approaches of QSM require multiple orientation data (e.g. Calculation of Susceptibility through Multiple Orientation Sampling or COSMOS) or regularization terms (e.g. Truncated K-space Division or TKD; Morphology Enabled Dipole Inversion or MEDI) to solve an ill-conditioned dipole deconvolution problem. Unfortunately, they either entail challenges in data acquisition (i.e. long scan time and multiple head orientations) or suffer from image artifacts. To overcome these shortcomings, a deep neural network, which is referred to as QSMnet, is constructed to generate a high quality susceptibility source map from single orientation data. The network has a modified U-net structure and is trained using COSMOS QSM maps, which are considered as gold standard. Five head orientation datasets from five subjects were employed for patch-wise network training after doubling the training data using a model-based data augmentation. Seven additional datasets of five head orientation images (i.e. total 35 images) were used for validation (one dataset) and test (six datasets). The QSMnet maps of the test dataset were compared with the maps from TKD and MEDI for their image quality and consistency with respect to multiple head orientations. Quantitative and qualitative image quality comparisons demonstrate that the QSMnet results have superior image quality to those of TKD or MEDI results and have comparable image quality to those of COSMOS. Additionally, QSMnet maps reveal substantially better consistency across the multiple head orientation data than those from TKD or MEDI. As a preliminary application, the network was further tested for three patients, one with microbleed, another with multiple sclerosis lesions, and the third with hemorrhage. The QSMnet maps showed similar lesion contrasts with those from MEDI, demonstrating potential for future applications.

    View details for PubMedID 29894829

  • Dual-polarity slice-GRAPPA for concurrent ghost correction and slice separation in simultaneous multi-slice EPI MAGNETIC RESONANCE IN MEDICINE Hoge, W., Setsompop, K., Polimeni, J. R. 2018; 80 (4): 1364–75

    Abstract

    A ghost correction strategy for Simultaneous Multi-Slice (SMS) EPI methods that provides improved ghosting artifact reduction compared to conventional methods is presented. Conventional Nyquist ghost correction methods for SMS-EPI rely on navigator data that contain phase errors from all slices in the simultaneously acquired slice-group. These navigator data may contain spatially nonlinear phase differences near regions of B0 inhomogeneity, which violates the linear model employed by most EPI ghost correction algorithms, resulting in poor reconstructions.Dual-Polarity GRAPPA (DPG) was previously shown to accurately model and correct both spatially nonlinear and 2D phase errors in conventional single-slice EPI data. Here, an extension we call Dual-Polarity slice-GRAPPA (DPsG) is adapted to the slice-GRAPPA method and applied to SMS-EPI data for slice separation and ghost correction concurrently-eliminating the need for a separate ghost correction step while also providing improved slice-specific EPI phase error correction.Images from in vivo SMS-EPI data reconstructed using DPsG in place of conventional Nyquist ghost correction and slice-GRAPPA are presented. DPsG is shown to reduce ghosting artifacts and provide improved temporal SNR compared to the conventional reconstruction.The proposed use of DPsG for SMS-EPI reconstruction can provide images with lower artifact levels, higher image fidelity, and improved time-series stability compared to conventional reconstruction methods.

    View details for DOI 10.1002/mrm.27113

    View details for Web of Science ID 000448869800009

    View details for PubMedID 29424460

    View details for PubMedCentralID PMC6085171

  • Wave-CAIPI ViSTa: highly accelerated whole-brain direct myelin water imaging with zero-padding reconstruction MAGNETIC RESONANCE IN MEDICINE Wu, Z., Bilgic, B., He, H., Tong, Q., Sun, Y., Du, Y., Setsompop, K., Zhong, J. 2018; 80 (3): 1061–73

    View details for DOI 10.1002/mrm.27108

    View details for Web of Science ID 000434642900018

    View details for PubMedID 29388254

  • Improving parallel imaging by jointly reconstructing multi-contrast data MAGNETIC RESONANCE IN MEDICINE Bilgic, B., Kim, T., Liao, C., Manhard, M., Wald, L. L., Haldar, J. P., Setsompop, K. 2018; 80 (2): 619–32

    Abstract

    To develop parallel imaging techniques that simultaneously exploit coil sensitivity encoding, image phase prior information, similarities across multiple images, and complementary k-space sampling for highly accelerated data acquisition.We introduce joint virtual coil (JVC)-generalized autocalibrating partially parallel acquisitions (GRAPPA) to jointly reconstruct data acquired with different contrast preparations, and show its application in 2D, 3D, and simultaneous multi-slice (SMS) acquisitions. We extend the joint parallel imaging concept to exploit limited support and smooth phase constraints through Joint (J-) LORAKS formulation. J-LORAKS allows joint parallel imaging from limited autocalibration signal region, as well as permitting partial Fourier sampling and calibrationless reconstruction.We demonstrate highly accelerated 2D balanced steady-state free precession with phase cycling, SMS multi-echo spin echo, 3D multi-echo magnetization-prepared rapid gradient echo, and multi-echo gradient recalled echo acquisitions in vivo. Compared to conventional GRAPPA, proposed joint acquisition/reconstruction techniques provide more than 2-fold reduction in reconstruction error.JVC-GRAPPA takes advantage of additional spatial encoding from phase information and image similarity, and employs different sampling patterns across acquisitions. J-LORAKS achieves a more parsimonious low-rank representation of local k-space by considering multiple images as additional coils. Both approaches provide dramatic improvement in artifact and noise mitigation over conventional single-contrast parallel imaging reconstruction. Magn Reson Med 80:619-632, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.27076

    View details for Web of Science ID 000430469300019

    View details for PubMedID 29322551

    View details for PubMedCentralID PMC5910232

  • Prefrontal Cortex Stimulation Enhances Fear Extinction Memory in Humans BIOLOGICAL PSYCHIATRY Raij, T., Nummenmaa, A., Marin, M., Porter, D., Furtak, S., Setsompop, K., Milad, M. R. 2018; 84 (2): 129–37

    Abstract

    Animal fear conditioning studies have illuminated neuronal mechanisms of learned associations between sensory stimuli and fear responses. In rats, brief electrical stimulation of the infralimbic cortex has been shown to reduce conditioned freezing during recall of extinction memory. Here, we translated this finding to humans with magnetic resonance imaging-navigated transcranial magnetic stimulation (TMS).Subjects (N = 28) were aversively conditioned to two different cues (day 1). During extinction learning (day 2), TMS was paired with one of the conditioned cues but not the other. TMS parameters were similar to those used in rat infralimbic cortex: brief pulse trains (300 ms at 20 Hz) starting 100 ms after cue onset, total of four trains (28 TMS pulses). TMS was applied to one of two targets in the left frontal cortex, one functionally connected (target 1) and the other unconnected (target 2, control) with a human homologue of infralimbic cortex in the ventromedial prefrontal cortex. Skin conductance responses were used as an index of conditioned fear.During extinction recall (day 3), the cue paired with TMS to target 1 showed significantly reduced skin conductance responses, whereas TMS to target 2 had no effect. Further, we built group-level maps that weighted TMS-induced electric fields and diffusion magnetic resonance imaging connectivity estimates with fear level. These maps revealed distinct cortical regions and large-scale networks associated with reduced versus increased fear.The results showed that spatiotemporally focused TMS may enhance extinction learning and/or consolidation of extinction memory and suggested novel cortical areas and large-scale networks for targeting in future studies.

    View details for DOI 10.1016/j.biopsych.2017.10.022

    View details for Web of Science ID 000437351300013

    View details for PubMedID 29246436

    View details for PubMedCentralID PMC5936658

  • Simultaneous Multislice Resting-State Functional Magnetic Resonance Imaging at 3 Tesla: Slice-Acceleration-Related Biases in Physiological Effects BRAIN CONNECTIVITY Golestani, A. M., Faraji-Dana, Z., Kayvanrad, M., Setsompop, K., Graham, S. J., Chen, J. 2018; 8 (2): 82–93

    Abstract

    Simultaneous multislice echo-planar imaging (SMS-EPI) can enhance the spatiotemporal resolution of resting-state functional MRI (rs-fMRI) by encoding and simultaneously imaging "groups" of slices. However, phenomena, including respiration, cardiac pulsatility, respiration volume per time (RVT), and cardiac rate variation (CRV), referred to as "physiological processes," impact SMS-EPI rs-fMRI in a manner that is yet to be well characterized. In particular, physiological noise may incur aliasing and introduce spurious signals from one slice into another within the "slice group" in rs-fMRI data, resulting in a deleterious effect on resting-state functional connectivity MRI (rs-fcMRI) maps. In the present work, we aimed to quantitatively compare the effects of physiological noise on regular EPI and SMS-EPI in terms of rs-fMRI data and resulting functional connectivity measurements. We compare SMS-EPI and regular EPI data acquired from 11 healthy young adults with matching parameters. The physiological noise characteristics were compared between the two data sets through different combinations of physiological regression steps. We observed that the physiological noise characteristics differed between SMS-EPI and regular EPI, with cardiac pulsatility contributing more to noise in regular EPI data but low-frequency heart rate variability contributing more to SMS-EPI. In addition, a significant slice-group bias was observed in the functional connectivity density maps derived from SMS-EPI data. We conclude that making appropriate corrections for physiological noise is likely more important for SMS-EPI than for regular EPI acquisitions.

    View details for DOI 10.1089/brain.2017.0491

    View details for Web of Science ID 000440732500004

    View details for PubMedID 29226689

  • Pulse sequences and parallel imaging for high spatiotemporal resolution MRI at ultra-high field NEUROIMAGE Poser, B. A., Setsompop, K. 2018; 168: 101–18

    Abstract

    The SNR and CNR benefits of ultra-high field (UHF) have helped push the envelope of achievable spatial resolution in MRI. For applications based on susceptibility contrast where there is a large CNR gain, high quality sub-millimeter resolution imaging is now being routinely performed, particularly in fMRI and phase imaging/QSM. This has enabled the study of structure and function of very fine-scale structures in the brain. UHF has also helped push the spatial resolution of many other MRI applications as will be outlined in this review. However, this push in resolution comes at a cost of a large encoding burden leading to very lengthy scans. Developments in parallel imaging with controlled aliasing and the move away from 2D slice-by-slice imaging to much more SNR-efficient simultaneous multi-slice (SMS) and 3D acquisitions have helped address this issue. In particular, these developments have revolutionized the efficiency of UHF MRI to enable high spatiotemporal resolution imaging at an order of magnitude faster acquisition. In addition to describing the main approaches to these techniques, this review will also outline important key practical considerations in using these methods in practice. Furthermore, new RF pulse design to tackle the B1+ and SAR issues of UHF and the increased SAR and power requirement of SMS RF pulses will also be touched upon. Finally, an outlook into new developments of smart encoding in more dimensions, particularly through using better temporal/across-contrast encoding and reconstruction will be described. Just as controlled aliasing fully exploits spatial encoding in parallel imaging to provide large multiplicative gains in accelerations, the complimentary use of these new approaches in temporal and across-contrast encoding are expected to provide exciting opportunities for further large gains in efficiency to further push the spatiotemporal resolution of MRI.

    View details for DOI 10.1016/j.neuroimage.2017.04.006

    View details for Web of Science ID 000427634500007

    View details for PubMedID 28392492

    View details for PubMedCentralID PMC5630499

  • Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling MAGNETIC RESONANCE IN MEDICINE Zhao, B., Setsompop, K., Adalsteinsson, E., Gagoski, B., Ye, H., Ma, D., Jiang, Y., Grant, P., Griswold, M. A., Wald, L. L. 2018; 79 (2): 933–42

    Abstract

    This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF).A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T1 , T2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach.The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short.The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.26701

    View details for Web of Science ID 000419134600033

    View details for PubMedID 28411394

    View details for PubMedCentralID PMC5641478

  • Evaluation of SLIce Dithered Enhanced Resolution Simultaneous MultiSlice (SLIDER-SMS) for human fMRI NEUROIMAGE Vu, A. T., Beckett, A., Setsompop, K., Feinberg, D. A. 2018; 164: 164–71

    Abstract

    High isotropic resolution fMRI is challenging primarily due to long repetition times (TR) and insufficient SNR, especially at lower field strengths. Recently, Simultaneous Multi-Slice (SMS) imaging with blipped-CAIPI has substantially reduced scan time and improved SNR efficiency of fMRI. Similarly, super-resolution techniques utilizing sub- voxel spatial shifts in the slice direction have increased both resolution and SNR efficiency. Here we demonstrate the synergistic combination of SLIce Dithered Enhanced Resolution (SLIDER) and SMS for high-resolution, high-SNR whole brain fMRI in comparison to standard resolution fMRI data as well as high-resolution data. With SLIDER-SMS, high spatial frequency information is recovered (unaliased) even in absence of super-resolution deblurring algorithms. Additionally we find that BOLD CNR (as measured by t-value in a visual checkerboard paradigm) is improved by as much as 100% relative to traditionally acquired high- resolution data. Using this gain in CNR, we are able to obtain unprecedented nominally isotropic resolutions at 3T (0.66 mm) and 7T (0.45 mm).

    View details for DOI 10.1016/j.neuroimage.2017.02.001

    View details for Web of Science ID 000417972000015

    View details for PubMedID 28185951

    View details for PubMedCentralID PMC5547021

  • High-resolution in vivo diffusion imaging of the human brain with generalized slice dithered enhanced resolution: Simultaneous multislice (gSlider-SMS) MAGNETIC RESONANCE IN MEDICINE Setsompop, K., Fan, Q., Stockmann, J., Bilgic, B., Huang, S., Cauley, S. F., Nummenmaa, A., Wang, F., Rathi, Y., Witzel, T., Wald, L. L. 2018; 79 (1): 141–51

    Abstract

    To develop an efficient acquisition for high-resolution diffusion imaging and allow in vivo whole-brain acquisitions at 600- to 700-μm isotropic resolution.We combine blipped-controlled aliasing in parallel imaging simultaneous multislice (SMS) with a novel slab radiofrequency (RF) encoding gSlider (generalized slice-dithered enhanced resolution) to form a signal-to-noise ratio-efficient volumetric simultaneous multislab acquisition. Here, multiple thin slabs are acquired simultaneously with controlled aliasing, and unaliased with parallel imaging. To achieve high resolution in the slice direction, the slab is volumetrically encoded using RF encoding with a scheme similar to Hadamard encoding. However, with gSlider, the RF-encoding bases are specifically designed to be highly independent and provide high image signal-to-noise ratio in each slab acquisition to enable self-navigation of the diffusion's phase corruption. Finally, the method is combined with zoomed imaging (while retaining whole-brain coverage) to facilitate low-distortion single-shot in-plane encoding with echo-planar imaging at high resolution.A 10-slices-per-shot gSlider-SMS acquisition was used to acquire whole-brain data at 660 and 760 μm isotropic resolution with b-values of 1500 and 1800 s/mm2 , respectively. Data were acquired on the Connectome 3 Tesla scanner with 64-channel head coil. High-quality data with excellent contrast were achieved at these resolutions, which enable the visualization of fine-scale structures.The gSlider-SMS approach provides a new, efficient way to acquire high-resolution diffusion data. Magn Reson Med 79:141-151, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.26653

    View details for Web of Science ID 000417926300013

    View details for PubMedID 28261904

    View details for PubMedCentralID PMC5585027

  • Wave-CAIPI for highly accelerated MP-RAGE imaging MAGNETIC RESONANCE IN MEDICINE Polak, D., Setsompop, K., Cauley, S. F., Gagoski, B. A., Bhat, H., Maier, F., Bachert, P., Wald, L. L., Bilgic, B. 2018; 79 (1): 401–6

    Abstract

    To introduce a highly accelerated T1-weighted magnetization-prepared rapid gradient echo (MP-RAGE) acquisition that uses wave-controlled aliasing in parallel imaging (wave-CAIPI) encoding to retain high image quality.Significant acceleration of the MP-RAGE sequence is demonstrated using the wave-CAIPI technique. Here, sinusoidal waveforms are used to spread aliasing in all three directions to improve the g-factor. Combined with a rapid (2 s) coil sensitivity acquisition and data-driven trajectory calibration, we propose an online integrated acquisition-reconstruction pipeline for highly efficient MP-RAGE imaging.The 9-fold accelerated MP-RAGE acquisition can be performed in 71 s, with a maximum and average g-factor of gmax  = 1.27 and gavg  = 1.06 at 3T. Compared with the state-of-the-art method controlled aliasing in parallel imaging results in higher acceleration (2D-CAIPIRINHA), this is a factor of 4.6/1.4 improvement in gmax /gavg . In addition, we demonstrate a 57 s acquisition at 7T with 12-fold acceleration. This acquisition has a g-factor performance of gmax  = 1.15 and gavg  = 1.04.Wave encoding overcomes the g-factor noise amplification penalty and allows for an order of magnitude acceleration of MP-RAGE acquisitions. Magn Reson Med 79:401-406, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.26649

    View details for Web of Science ID 000417926300038

    View details for PubMedID 28220617

    View details for PubMedCentralID PMC5563495

  • 3D MR fingerprinting with accelerated stack-of-spirals and hybrid sliding-window and GRAPPA reconstruction NEUROIMAGE Liao, C., Bilgic, B., Manhard, M., Zhao, B., Cao, X., Zhong, J., Wald, L. L., Setsompop, K. 2017; 162: 13–22

    Abstract

    Whole-brain high-resolution quantitative imaging is extremely encoding intensive, and its rapid and robust acquisition remains a challenge. Here we present a 3D MR fingerprinting (MRF) acquisition with a hybrid sliding-window (SW) and GRAPPA reconstruction strategy to obtain high-resolution T1, T2 and proton density (PD) maps with whole brain coverage in a clinically feasible timeframe.3D MRF data were acquired using a highly under-sampled stack-of-spirals trajectory with a steady-state precession (FISP) sequence. For data reconstruction, kx-ky under-sampling was mitigated using SW combination along the temporal axis. Non-uniform fast Fourier transform (NUFFT) was then applied to create Cartesian k-space data that are fully-sampled in the in-plane direction, and Cartesian GRAPPA was performed to resolve kz under-sampling to create an alias-free SW dataset. T1, T2 and PD maps were then obtained using dictionary matching.Phantom study demonstrated that the proposed 3D-MRF acquisition/reconstruction method is able to produce quantitative maps that are consistent with conventional quantification techniques. Retrospectively under-sampled in vivo acquisition revealed that SW + GRAPPA substantially improves quantification accuracy over the current state-of-the-art accelerated 3D MRF. Prospectively under-sampled in vivo study showed that whole brain T1, T2 and PD maps with 1 mm3 resolution could be obtained in 7.5 min.3D MRF stack-of-spirals acquisition with hybrid SW + GRAPPA reconstruction may provide a feasible approach for rapid, high-resolution quantitative whole-brain imaging.

    View details for DOI 10.1016/j.neuroimage.2017.08.030

    View details for Web of Science ID 000416502800002

    View details for PubMedID 28842384

    View details for PubMedCentralID PMC6031129

  • Use of Pattern Recognition for Unaliasing Simultaneously Acquired Slices in Simultaneous Multislice MR Fingerprinting MAGNETIC RESONANCE IN MEDICINE Jiang, Y., Ma, D., Bhat, H., Ye, H., Cauley, S. F., Wald, L. L., Setsompop, K., Griswold, M. A. 2017; 78 (5): 1870–76

    Abstract

    The purpose of this study is to accelerate an MR fingerprinting (MRF) acquisition by using a simultaneous multislice method.A multiband radiofrequency (RF) pulse was designed to excite two slices with different flip angles and phases. The signals of two slices were driven to be as orthogonal as possible. The mixed and undersampled MRF signal was matched to two dictionaries to retrieve T1 and T2 maps of each slice. Quantitative results from the proposed method were validated with the gold-standard spin echo methods in a phantom. T1 and T2 maps of in vivo human brain from two simultaneously acquired slices were also compared to the results of fast imaging with steady-state precession based MRF method (MRF-FISP) with a single-band RF excitation.The phantom results showed that the simultaneous multislice imaging MRF-FISP method quantified the relaxation properties accurately compared to the gold-standard spin echo methods. T1 and T2 values of in vivo brain from the proposed method also matched the results from the normal MRF-FISP acquisition.T1 and T2 values can be quantified at a multiband acceleration factor of two using our proposed acquisition even in a single-channel receive coil. Further acceleration could be achieved by combining this method with parallel imaging or iterative reconstruction. Magn Reson Med 78:1870-1876, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.26572

    View details for Web of Science ID 000416390700021

    View details for PubMedID 28019022

    View details for PubMedCentralID PMC5484752

  • Advancing RF pulse design using an open-competition format: Report from the 2015 ISMRM challenge MAGNETIC RESONANCE IN MEDICINE Grissom, W. A., Setsompop, K., Hurley, S. A., Tsao, J., Velikina, J. V., Samsonov, A. A. 2017; 78 (4): 1352–61

    Abstract

    To advance the best solutions to two important RF pulse design problems with an open head-to-head competition.Two sub-challenges were formulated in which contestants competed to design the shortest simultaneous multislice (SMS) refocusing pulses and slice-selective parallel transmission (pTx) excitation pulses, subject to realistic hardware and safety constraints. Short refocusing pulses are needed for spin echo SMS imaging at high multiband factors, and short slice-selective pTx pulses are needed for multislice imaging in ultra-high field MRI. Each sub-challenge comprised two phases, in which the first phase posed problems with a low barrier of entry, and the second phase encouraged solutions that performed well in general. The Challenge ran from October 2015 to May 2016.The pTx Challenge winners developed a spokes pulse design method that combined variable-rate selective excitation with an efficient method to enforce SAR constraints, which achieved 10.6 times shorter pulse durations than conventional approaches. The SMS Challenge winners developed a time-optimal control multiband pulse design algorithm that achieved 5.1 times shorter pulse durations than conventional approaches.The Challenge led to rapid step improvements in solutions to significant problems in RF excitation for SMS imaging and ultra-high field MRI. Magn Reson Med 78:1352-1361, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.26512

    View details for Web of Science ID 000411186100011

    View details for PubMedID 27790754

    View details for PubMedCentralID PMC5408273

  • Autocalibrated wave-CAIPI reconstruction; Joint optimization of k-space trajectory and parallel imaging reconstruction MAGNETIC RESONANCE IN MEDICINE Cauley, S. F., Setsompop, K., Bilgic, B., Bhat, H., Gagoski, B., Wald, L. L. 2017; 78 (3): 1093–99

    Abstract

    Fast MRI acquisitions often rely on efficient traversal of k-space and hardware limitations, or other physical effects can cause the k-space trajectory to deviate from a theoretical path in a manner dependent on the image prescription and protocol parameters. Additional measurements or generalized calibrations are typically needed to characterize the discrepancies. We propose an autocalibrated technique to determine these discrepancies.A joint optimization is used to estimate the trajectory simultaneously with the parallel imaging reconstruction, without the need for additional measurements. Model reduction is introduced to make this optimization computationally efficient, and to ensure final image quality.We demonstrate our approach for the wave-CAIPI fast acquisition method that uses a corkscrew k-space path to efficiently encode k-space and spread the voxel aliasing. Model reduction allows for the 3D trajectory to be automatically calculated in fewer than 30 s on standard vendor hardware. The method achieves equivalent accuracy to full-gradient calibration scans.The proposed method allows for high-quality wave-CAIPI reconstruction across wide ranges of protocol parameters, such as field of view (FOV) location/orientation, bandwidth, echo time (TE), resolution, and sinusoidal amplitude/frequency. Our framework should allow for the autocalibration of gradient trajectories from many other fast MRI techniques in clinically relevant time. Magn Reson Med 78:1093-1099, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.26499

    View details for Web of Science ID 000407855700028

    View details for PubMedID 27770457

    View details for PubMedCentralID PMC5400736

  • New insights about time-varying diffusivity and its estimation from diffusion MRI MAGNETIC RESONANCE IN MEDICINE Ning, L., Setsompop, K., Westin, C., Rathi, Y. 2017; 78 (2): 763–74

    Abstract

    Characterizing the relation between the applied gradient sequences and the measured diffusion MRI signal is important for estimating the time-dependent diffusivity, which provides important information about the microscopic tissue structure.In this article, we extend the classical theory of Stepišnik for measuring time-dependent diffusivity under the Gaussian phase approximation. In particular, we derive three novel expressions which represent the diffusion MRI signal in terms of the mean-squared displacement, the instantaneous diffusivity, and the velocity autocorrelation function. We present the explicit signal expressions for the case of single diffusion encoding and oscillating gradient spin-echo sequences. Additionally, we also propose three different models to represent time-varying diffusivity and test them using Monte-Carlo simulations and in vivo human brain data.The time-varying diffusivities are able to distinguish the synthetic structures in the Monte-Carlo simulations. There is also strong statistical evidence about time-varying diffusivity from the in vivo human data set.The proposed theory provides new insights into our understanding of the time-varying diffusivity using different gradient sequences. The proposed models for representing time-varying diffusivity can be utilized to study time-varying diffusivity using in vivo human brain diffusion MRI data. Magn Reson Med 78:763-774, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.26403

    View details for Web of Science ID 000405637000035

    View details for PubMedID 27611013

    View details for PubMedCentralID PMC5344793

  • Simultaneous Time Interleaved MultiSlice (STIMS) for Rapid Susceptibility Weighted acquisition NEUROIMAGE Bilgic, B., Ye, H., Wald, L. L., Setsompop, K. 2017; 155: 577–86

    Abstract

    T2* weighted 3D Gradient Echo (GRE) acquisition is the main sequence used for Susceptibility Weighted Imaging (SWI) and Quantitative Susceptibility Mapping (QSM). These applications require a long echo time (TE) to build up phase contrast, requiring a long repetition time (TR), and leading to excessively lengthy scans. The long TE acquisition creates a significant amount of unused time within each TR, which can be utilized for either multi-echo sampling or additional image encoding with the echo-shift technique. The latter leads to significant saving in acquisition time while retaining the desired phase and T2* contrast. In this work, we introduce the Simultaneous Time Interleaved MultiSlice (STIMS) echo-shift technique, which mitigates slab boundary artifacts by interleaving comb-shaped slice groups with Simultaneous MultiSlice (SMS) excitation. This enjoys the same SNR benefit of 3D signal averaging as previously introduced multi-slab version, where each slab group is sub-resolved with kz phase encoding. Further, we combine SMS echo-shift with Compressed Sensing (CS) Wave acceleration, which enhances Wave-CAIPI acquisition/reconstruction with random undersampling and sparsity prior. STIMS and CS-Wave combination thus yields up to 45-fold acceleration over conventional full encoding, allowing a 15sec full-brain acquisition with 1.5 mm isotropic resolution at long TE of 39 ms at 3T. In addition to utilizing empty sequence time due to long TE, STIMS is a general concept that could exploit gaps due to e.g. inversion modules in magnetization-prepared rapid gradient-echo (MPRAGE) and fluid attenuated inversion recovery (FLAIR) sequences.

    View details for DOI 10.1016/j.neuroimage.2017.04.036

    View details for Web of Science ID 000405460900047

    View details for PubMedID 28435102

    View details for PubMedCentralID PMC5511575

  • Simultaneous multislice magnetic resonance fingerprinting (SMS-MRF) with direct-spiral slice-GRAPPA (ds-SG) reconstruction MAGNETIC RESONANCE IN MEDICINE Ye, H., Cauley, S. F., Gagoski, B., Bilgic, B., Ma, D., Jiang, Y., Du, Y. P., Griswold, M. A., Wald, L. L., Setsompop, K. 2017; 77 (5): 1966–74

    Abstract

    To develop a reconstruction method to improve SMS-MRF, in which slice acceleration is used in conjunction with highly undersampled in-plane acceleration to speed up MRF acquisition.In this work two methods are employed to efficiently perform the simultaneous multislice magnetic resonance fingerprinting (SMS-MRF) data acquisition and the direct-spiral slice-GRAPPA (ds-SG) reconstruction. First, the lengthy training data acquisition is shortened by employing the through-time/through-k-space approach, in which similar k-space locations within and across spiral interleaves are grouped and are associated with a single set of kernel. Second, inversion recovery preparation (IR prepped), variable flip angle (FA), and repetition time (TR) are used for the acquisition of the training data, to increase signal variation and to improve the conditioning of the kernel fitting.The grouping of k-space locations enables a large reduction in the number of kernels required, and the IR-prepped training data with variable FA and TR provide improved ds-SG kernels and reconstruction performance. With direct-spiral slice-GRAPPA, tissue parameter maps comparable to that of conventional MRF were obtained at multiband (MB) = 3 acceleration using t-blipped SMS-MRF acquisition with 32-channel head coil at 3 Tesla (T).The proposed reconstruction scheme allows MB = 3 accelerated SMS-MRF imaging with high-quality T1 , T2 , and off-resonance maps, and can be used to significantly shorten MRF acquisition and aid in its adoption in neuro-scientific and clinical settings. Magn Reson Med 77:1966-1974, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.26271

    View details for Web of Science ID 000399666400023

    View details for PubMedID 27220881

    View details for PubMedCentralID PMC5123982

  • Single-step quantitative susceptibility mapping with variational penalties Chatnuntawech, I., McDaniel, P., Cauley, S. F., Gagoski, B. A., Langkammer, C., Martin, A., Grantc, P., Wald, L. L., Setsompop, K., Adalsteinsson, E., Bilgic, B. WILEY. 2017

    Abstract

    Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from the gradient echo (GRE) phase signal through background phase removal and dipole inversion steps. Each of these steps typically requires the solution of an ill-posed inverse problem and thus necessitates additional regularization. Recently developed single-step QSM algorithms directly relate the unprocessed GRE phase to the unknown susceptibility distribution, thereby requiring the solution of a single inverse problem. In this work, we show that such a holistic approach provides susceptibility estimation with artifact mitigation and develop efficient algorithms that involve simple analytical solutions for all of the optimization steps. Our methods employ total variation (TV) and total generalized variation (TGV) to jointly perform the background removal and dipole inversion in a single step. Using multiple spherical mean value (SMV) kernels of varying radii permits high-fidelity background removal whilst retaining the phase information in the cortex. Using numerical simulations, we demonstrate that the proposed single-step methods reduce the reconstruction error by up to 66% relative to the multi-step methods that involve SMV background filtering with the same number of SMV kernels, followed by TV- or TGV-regularized dipole inversion. In vivo single-step experiments demonstrate a dramatic reduction in dipole streaking artifacts and improved homogeneity of image contrast. These acquisitions employ the rapid three-dimensional echo planar imaging (3D EPI) and Wave-CAIPI (controlled aliasing in parallel imaging) trajectories for signal-to-noise ratio-efficient whole-brain imaging. Herein, we also demonstrate the multi-echo capability of the Wave-CAIPI sequence for the first time, and introduce an automated, phase-sensitive coil sensitivity estimation scheme based on a 4-s calibration acquisition. Copyright © 2016 John Wiley & Sons, Ltd.

    View details for DOI 10.1002/nbm.3570

    View details for Web of Science ID 000398100400027

    View details for PubMedID 27332141

    View details for PubMedCentralID PMC5179325

  • Diffusion Tractography of the Entire Left Ventricle by Using Free-breathing Accelerated Simultaneous Multisection Imaging RADIOLOGY Mekkaoui, C., Reese, T. G., Jackowski, M. P., Cauley, S. F., Setsompop, K., Bhat, H., Sosnovik, D. E. 2017; 282 (3): 850–56

    Abstract

    Purpose To develop a clinically feasible whole-heart free-breathing diffusion-tensor (DT) magnetic resonance (MR) imaging approach with an imaging time of approximately 15 minutes to enable three-dimensional (3D) tractography. Materials and Methods The study was compliant with HIPAA and the institutional review board and required written consent from the participants. DT imaging was performed in seven healthy volunteers and three patients with pulmonary hypertension by using a stimulated echo sequence. Twelve contiguous short-axis sections and six four-chamber sections that covered the entire left ventricle were acquired by using simultaneous multisection (SMS) excitation with a blipped-controlled aliasing in parallel imaging readout. Rate 2 and rate 3 SMS excitation was defined as two and three times accelerated in the section axis, respectively. Breath-hold and free-breathing images with and without SMS acceleration were acquired. Diffusion-encoding directions were acquired sequentially, spatiotemporally registered, and retrospectively selected by using an entropy-based approach. Myofiber helix angle, mean diffusivity, fractional anisotropy, and 3D tractograms were analyzed by using paired t tests and analysis of variance. Results No significant differences (P > .63) were seen between breath-hold rate 3 SMS and free-breathing rate 2 SMS excitation in transmural myofiber helix angle, mean diffusivity (mean ± standard deviation, [0.89 ± 0.09] × 10-3 mm2/sec vs [0.9 ± 0.09] × 10-3 mm2/sec), or fractional anisotropy (0.43 ± 0.05 vs 0.42 ± 0.06). Three-dimensional tractograms of the left ventricle with no SMS and rate 2 and rate 3 SMS excitation were qualitatively similar. Conclusion Free-breathing DT imaging of the entire human heart can be performed in approximately 15 minutes without section gaps by using SMS excitation with a blipped-controlled aliasing in parallel imaging readout, followed by spatiotemporal registration and entropy-based retrospective image selection. This method may lead to clinical translation of whole-heart DT imaging, enabling broad application in patients with cardiac disease. © RSNA, 2016 Online supplemental material is available for this article.

    View details for DOI 10.1148/radiol.2016152613

    View details for Web of Science ID 000401895600026

    View details for PubMedID 27681278

    View details for PubMedCentralID PMC5318239

  • LORAKS Makes Better SENSE: Phase-Constrained Partial Fourier SENSE Reconstruction Without Phase Calibration MAGNETIC RESONANCE IN MEDICINE Kim, T., Setsompop, K., Haldar, J. P. 2017; 77 (3): 1021–35

    Abstract

    Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information.The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely used calibrationless uniformly undersampled trajectories.Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches.The SENSE-LORAKS framework provides promising new opportunities for highly accelerated MRI. Magn Reson Med 77:1021-1035, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.26182

    View details for Web of Science ID 000397407800012

    View details for PubMedID 27037836

    View details for PubMedCentralID PMC5045741

  • SIMULTANEOUS MULTISLICE MAGNETIC RESONANCE FINGERPRINTING WITH LOW-RANK AND SUBSPACE MODELING Zhao, B., Bilgic, B., Adalsteinsson, E., Griswold, M. A., Wald, L. L., Setsompop, K., IEEE IEEE. 2017: 3264–68

    Abstract

    Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T1, T2, and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3× speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice.

    View details for Web of Science ID 000427085303172

    View details for PubMedID 29060594

    View details for PubMedCentralID PMC5895455

  • A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging (vol 125, pg 386, 2016) NEUROIMAGE Ning, L., Setsompop, K., Michailovich, O., Makris, N., Shenton, M. E., Westin, C., Rathi, Y. 2016; 142: 696
  • Fast fMRI can detect oscillatory neural activity in humans PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Lewis, L. D., Setsompop, K., Rosen, B. R., Polimeni, J. R. 2016; 113 (43): E6679–E6685

    Abstract

    Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG-fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain.

    View details for DOI 10.1073/pnas.1608117113

    View details for Web of Science ID 000386087100018

    View details for PubMedID 27729529

    View details for PubMedCentralID PMC5087037

  • Vectorial total generalized variation for accelerated multi-channel multi-contrast MRI MAGNETIC RESONANCE IMAGING Chatnuntawech, I., Martin, A., Bilgic, B., Setsompop, K., Adalsteinsson, E., Schiavi, E. 2016; 34 (8): 1161–70

    Abstract

    To develop and implement an efficient reconstruction technique to improve accelerated multi-channel multi-contrast MRI.The vectorial total generalized variation (TGV) operator is used as a regularizer for the sensitivity encoding (SENSE) technique to improve image quality of multi-channel multi-contrast MRI. The alternating direction method of multipliers (ADMM) is used to efficiently reconstruct the data. The performance of the proposed method (MC-TGV-SENSE) is assessed on two healthy volunteers at several acceleration factors.As demonstrated on the in vivo results, MC-TGV-SENSE had the lowest root-mean-square error (RMSE), highest structural similarity index, and best visual quality at all acceleration factors, compared to other methods under consideration. MC-TGV-SENSE yielded up to 17.3% relative RMSE reduction compared to the widely used total variation regularized SENSE. Furthermore, we observed that the reconstruction time of MC-TGV-SENSE is reduced by approximately a factor of two with comparable RMSEs by using the proposed ADMM-based algorithm as opposed to the more commonly used Chambolle-Pock primal-dual algorithm for the TGV-based reconstruction.MC-TGV-SENSE is a better alternative than the existing reconstruction methods for accelerated multi-channel multi-contrast MRI. The proposed method exploits shared information among the images (MC), mitigates staircasing artifacts (TGV), and uses the encoding power of multiple receiver coils (SENSE).

    View details for DOI 10.1016/j.mri.2016.05.014

    View details for Web of Science ID 000382416500017

    View details for PubMedID 27262829

  • Rapid brain MRI acquisition techniques at ultra-high fields NMR IN BIOMEDICINE Setsompop, K., Feinberg, D. A., Polimeni, J. R. 2016; 29 (9): 1198–1221

    Abstract

    Ultra-high-field MRI provides large increases in signal-to-noise ratio (SNR) as well as enhancement of several contrast mechanisms in both structural and functional imaging. Combined, these gains result in a substantial boost in contrast-to-noise ratio that can be exploited for higher-spatial-resolution imaging to extract finer-scale information about the brain. With increased spatial resolution, however, there is a concurrent increased image-encoding burden that can cause unacceptably long scan times for structural imaging and slow temporal sampling of the hemodynamic response in functional MRI - particularly when whole-brain imaging is desired. To address this issue, new directions of imaging technology development - such as the move from conventional 2D slice-by-slice imaging to more efficient simultaneous multislice (SMS) or multiband imaging (which can be viewed as "pseudo-3D" encoding) as well as full 3D imaging - have provided dramatic improvements in acquisition speed. Such imaging paradigms provide higher SNR efficiency as well as improved encoding efficiency. Moreover, SMS and 3D imaging can make better use of coil sensitivity information in multichannel receiver arrays used for parallel imaging acquisitions through controlled aliasing in multiple spatial directions. This has enabled unprecedented acceleration factors of an order of magnitude or higher in these imaging acquisition schemes, with low image artifact levels and high SNR. Here we review the latest developments of SMS and 3D imaging methods and related technologies at ultra-high field for rapid high-resolution functional and structural imaging of the brain. Copyright © 2016 John Wiley & Sons, Ltd.

    View details for DOI 10.1002/nbm.3478

    View details for Web of Science ID 000383271800007

    View details for PubMedID 26835884

    View details for PubMedCentralID PMC5245168

  • Maximum Likelihood Reconstruction for Magnetic Resonance Fingerprinting IEEE TRANSACTIONS ON MEDICAL IMAGING Zhao, B., Setsompop, K., Ye, H., Cauley, S. F., Wald, L. L. 2016; 35 (8): 1812–23

    Abstract

    This paper introduces a statistical estimation framework for magnetic resonance (MR) fingerprinting, a recently proposed quantitative imaging paradigm. Within this framework, we present a maximum likelihood (ML) formalism to estimate multiple MR tissue parameter maps directly from highly undersampled, noisy k-space data. A novel algorithm, based on variable splitting, the alternating direction method of multipliers, and the variable projection method, is developed to solve the resulting optimization problem. Representative results from both simulations and in vivo experiments demonstrate that the proposed approach yields significantly improved accuracy in parameter estimation, compared to the conventional MR fingerprinting reconstruction. Moreover, the proposed framework provides new theoretical insights into the conventional approach. We show analytically that the conventional approach is an approximation to the ML reconstruction; more precisely, it is exactly equivalent to the first iteration of the proposed algorithm for the ML reconstruction, provided that a gridding reconstruction is used as an initialization.

    View details for DOI 10.1109/TMI.2016.2531640

    View details for Web of Science ID 000381436000003

    View details for PubMedID 26915119

    View details for PubMedCentralID PMC5271418

  • Music-Based Magnetic Resonance Fingerprinting to Improve Patient Comfort During MRI Examinations MAGNETIC RESONANCE IN MEDICINE Ma, D., Pierre, E. Y., Jiang, Y., Schluchter, M. D., Setsompop, K., Gulani, V., Griswold, M. A. 2016; 75 (6): 2303–14

    Abstract

    Unpleasant acoustic noise is a drawback of almost every MRI scan. Instead of reducing acoustic noise to improve patient comfort, we propose a technique for mitigating the noise problem by producing musical sounds directly from the switching magnetic fields while simultaneously quantifying multiple important tissue properties.MP3 music files were converted to arbitrary encoding gradients, which were then used with varying flip angles and repetition times in a two- and three-dimensional magnetic resonance fingerprinting (MRF) examination. This new acquisition method, named MRF-Music, was used to quantify T1 , T2 , and proton density maps simultaneously while providing pleasing sounds to the patients.MRF-Music scans improved patient comfort significantly during MRI examinations. The T1 and T2 values measured from phantom are in good agreement with those from the standard spin echo measurements. T1 and T2 values from the brain scan are also close to previously reported values.MRF-Music sequence provides significant improvement in patient comfort compared with the MRF scan and other fast imaging techniques such as echo planar imaging and turbo spin echo scans. It is also a fast and accurate quantitative method that quantifies multiple relaxation parameters simultaneously. Magn Reson Med 75:2303-2314, 2016. © 2015 Wiley Periodicals, Inc.

    View details for DOI 10.1002/mrm.25818

    View details for Web of Science ID 000384994700009

    View details for PubMedID 26178439

    View details for PubMedCentralID PMC4715797

  • In vivo functional connectome of human brainstem nuclei of the ascending arousal, autonomic, and motor systems by high spatial resolution 7-Tesla fMRI MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE Bianciardi, M., Toschi, N., Eichner, C., Polimeni, J. R., Setsompop, K., Brown, E. N., Hamalainen, M. S., Rosen, B. R., Wald, L. L. 2016; 29 (3): 451–62

    Abstract

    Our aim was to map the in vivo human functional connectivity of several brainstem nuclei with the rest of the brain by using seed-based correlation of ultra-high magnetic field functional magnetic resonance imaging (fMRI) data.We used the recently developed template of 11 brainstem nuclei derived from multi-contrast structural MRI at 7 Tesla as seed regions to determine their connectivity to the rest of the brain. To achieve this, we used the increased contrast-to-noise ratio of 7-Tesla fMRI compared with 3 Tesla and time-efficient simultaneous multi-slice imaging to cover the brain with high spatial resolution (1.1-mm isotropic nominal resolution) while maintaining a short repetition time (2.5 s).The delineated Pearson's correlation-based functional connectivity diagrams (connectomes) of 11 brainstem nuclei of the ascending arousal, motor, and autonomic systems from 12 controls are presented and discussed in the context of existing histology and animal work.Considering that the investigated brainstem nuclei play a crucial role in several vital functions, the delineated preliminary connectomes might prove useful for future in vivo research and clinical studies of human brainstem function and pathology, including disorders of consciousness, sleep disorders, autonomic disorders, Parkinson's disease, and other motor disorders.

    View details for DOI 10.1007/s10334-016-0546-3

    View details for Web of Science ID 000377457400013

    View details for PubMedID 27126248

    View details for PubMedCentralID PMC4892960

  • Accelerating magnetic resonance fingerprinting (MRF) using t-blipped simultaneous multislice (SMS) acquisition MAGNETIC RESONANCE IN MEDICINE Ye, H., Ma, D., Jiang, Y., Cauley, S. F., Du, Y., Wald, L. L., Griswold, M. A., Setsompop, K. 2016; 75 (5): 2078–85

    Abstract

    We incorporate simultaneous multislice (SMS) acquisition into MR fingerprinting (MRF) to accelerate the MRF acquisition.The t-Blipped SMS-MRF method is achieved by adding a Gz blip before each data acquisition window and balancing it with a Gz blip of opposing polarity at the end of each TR. Thus the signal from different simultaneously excited slices are encoded with different phases without disturbing the signal evolution. Furthermore, by varying the Gz blip area and/or polarity as a function of repetition time, the slices' differential phase can also be made to vary as a function of time. For reconstruction of t-Blipped SMS-MRF data, we demonstrate a combined slice-direction SENSE and modified dictionary matching method.In Monte Carlo simulation, the parameter mapping from multiband factor (MB) = 2 t-Blipped SMS-MRF shows good accuracy and precision when compared with results from reference conventional MRF data with concordance correlation coefficients (CCC) of 0.96 for T1 estimates and 0.90 for T2 estimates. For in vivo experiments, T1 and T2 maps from MB=2 t-Blipped SMS-MRF have a high agreement with ones from conventional MRF.The MB=2 t-Blipped SMS-MRF acquisition/reconstruction method has been demonstrated and validated to provide more rapid parameter mapping in the MRF framework.

    View details for DOI 10.1002/mrm.25799

    View details for Web of Science ID 000374495600025

    View details for PubMedID 26059430

    View details for PubMedCentralID PMC4673043

  • A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging NEUROIMAGE Ning, L., Setsompop, K., Michailovich, O., Makris, N., Shenton, M. E., Westin, C., Rathi, Y. 2016; 125: 386–400

    Abstract

    Diffusion MRI (dMRI) can provide invaluable information about the structure of different tissue types in the brain. Standard dMRI acquisitions facilitate a proper analysis (e.g. tracing) of medium-to-large white matter bundles. However, smaller fiber bundles connecting very small cortical or sub-cortical regions cannot be traced accurately in images with large voxel sizes. Yet, the ability to trace such fiber bundles is critical for several applications such as deep brain stimulation and neurosurgery. In this work, we propose a novel acquisition and reconstruction scheme for obtaining high spatial resolution dMRI images using multiple low resolution (LR) images, which is effective in reducing acquisition time while improving the signal-to-noise ratio (SNR). The proposed method called compressed-sensing super resolution reconstruction (CS-SRR), uses multiple overlapping thick-slice dMRI volumes that are under-sampled in q-space to reconstruct diffusion signal with complex orientations. The proposed method combines the twin concepts of compressed sensing and super-resolution to model the diffusion signal (at a given b-value) in a basis of spherical ridgelets with total-variation (TV) regularization to account for signal correlation in neighboring voxels. A computationally efficient algorithm based on the alternating direction method of multipliers (ADMM) is introduced for solving the CS-SRR problem. The performance of the proposed method is quantitatively evaluated on several in-vivo human data sets including a true SRR scenario. Our experimental results demonstrate that the proposed method can be used for reconstructing sub-millimeter super resolution dMRI data with very good data fidelity in clinically feasible acquisition time.

    View details for DOI 10.1016/j.neuroimage.2015.10.061

    View details for Web of Science ID 000366647500036

    View details for PubMedID 26505296

    View details for PubMedCentralID PMC4691422

  • Rapid multi-orientation quantitative susceptibility mapping NEUROIMAGE Bilgic, B., Xie, L., Dibb, R., Langkammer, C., Mutluay, A., Ye, H., Polimeni, J. R., Augustinack, J., Liu, C., Wald, L. L., Setsompop, K. 2016; 125: 1131–41

    Abstract

    Three-dimensional gradient echo (GRE) is the main workhorse sequence used for susceptibility weighted imaging (SWI), quantitative susceptibility mapping (QSM), and susceptibility tensor imaging (STI). Achieving optimal phase signal-to-noise ratio requires late echo times, thus necessitating a long repetition time (TR). Combined with the large encoding burden of whole-brain coverage with high resolution, this leads to increased scan time. Further, the dipole kernel relating the tissue phase to the underlying susceptibility distribution undersamples the frequency content of the susceptibility map. Scans at multiple head orientations along with calculation of susceptibility through multi-orientation sampling (COSMOS) are one way to effectively mitigate this issue. Additionally, STI requires a minimum of 6 head orientations to solve for the independent tensor elements in each voxel. The requirements of high-resolution imaging with long TR at multiple orientations substantially lengthen the acquisition of COSMOS and STI. The goal of this work is to dramatically speed up susceptibility mapping at multiple head orientations. We demonstrate highly efficient acquisition using 3D-GRE with Wave-CAIPI and dramatically reduce the acquisition time of these protocols. Using R=15-fold acceleration with Wave-CAIPI permits acquisition per head orientation in 90s at 1.1mm isotropic resolution, and 5:35min at 0.5mm isotropic resolution. Since Wave-CAIPI fully harnesses the 3D spatial encoding capability of receive arrays, the maximum g-factor noise amplification remains below 1.30 at 3T and 1.12 at 7T. This allows a 30-min exam for STI with 12 orientations, thus paving the way to its clinical application.

    View details for DOI 10.1016/j.neuroimage.2015.08.015

    View details for Web of Science ID 000366647500105

    View details for PubMedID 26277773

    View details for PubMedCentralID PMC4691433

  • OPTIMAL EXPERIMENT DESIGN FOR MAGNETIC RESONANCE FINGERPRINTING Zhao, B., Haldar, J. P., Setsompop, K., Wald, L. L., Patton, J., Barbieri, R., Ji, J., Jabbari, E., Dokos, S., Mukkamala, R., Guiraud, D., Jovanov, E., Dhaher, Y., Panescu, D., Vangils, M., Wheeler, B., Dhawan, A. P. IEEE. 2016: 453–56

    Abstract

    Magnetic resonance (MR) fingerprinting is an emerging quantitative MR imaging technique that simultaneously acquires multiple tissue parameters in an efficient experiment. In this work, we present an estimation-theoretic framework to evaluate and design MR fingerprinting experiments. More specifically, we derive the Cramér-Rao bound (CRB), a lower bound on the covariance of any unbiased estimator, to characterize parameter estimation for MR fingerprinting. We then formulate an optimal experiment design problem based on the CRB to choose a set of acquisition parameters (e.g., flip angles and/or repetition times) that maximizes the signal-to-noise ratio efficiency of the resulting experiment. The utility of the proposed approach is validated by numerical studies. Representative results demonstrate that the optimized experiments allow for substantial reduction in the length of an MR fingerprinting acquisition, and substantial improvement in parameter estimation performance.

    View details for Web of Science ID 000399823500111

    View details for PubMedID 28268369

    View details for PubMedCentralID PMC5464426

  • A 32-Channel Combined RF and B-0 Shim Array for 3T Brain Imaging MAGNETIC RESONANCE IN MEDICINE Stockmann, J. P., Witzel, T., Keil, B., Polimeni, J. R., Mareyam, A., LaPierre, C., Setsompop, K., Wald, L. L. 2016; 75 (1): 441–51

    Abstract

    We add user-controllable direct currents (DC) to the individual elements of a 32-channel radio-frequency (RF) receive array to provide B0 shimming ability while preserving the array's reception sensitivity and parallel imaging performance.Shim performance using constrained DC current (± 2.5A) is simulated for brain arrays ranging from 8 to 128 elements. A 32-channel 3-tesla brain array is realized using inductive chokes to bridge the tuning capacitors on each RF loop. The RF and B0 shimming performance is assessed in bench and imaging measurements.The addition of DC currents to the 32-channel RF array is achieved with minimal disruption of the RF performance and/or negative side effects such as conductor heating or mechanical torques. The shimming results agree well with simulations and show performance superior to third-order spherical harmonic (SH) shimming. Imaging tests show the ability to reduce the standard frontal lobe susceptibility-induced fields and improve echo planar imaging geometric distortion. The simulation of 64- and 128-channel brain arrays suggest that even further shimming improvement is possible (equivalent to up to 6th-order SH shim coils).Including user-controlled shim currents on the loops of a conventional highly parallel brain array coil is feasible with modest current levels and produces improved B0 shimming performance over standard second-order SH shimming.

    View details for DOI 10.1002/mrm.25587

    View details for Web of Science ID 000367739200045

    View details for PubMedID 25689977

    View details for PubMedCentralID PMC4771493

  • Toward an In Vivo Neuroimaging Template of Human Brainstem Nuclei of the Ascending Arousal, Autonomic, and Motor Systems BRAIN CONNECTIVITY Bianciardi, M., Toschi, N., Edlow, B. L., Eichner, C., Setsompop, K., Polimeni, J. R., Brown, E. N., Kinney, H. C., Rosen, B. R., Wald, L. L. 2015; 5 (10): 597–607

    Abstract

    Brainstem nuclei (Bn) in humans play a crucial role in vital functions, such as arousal, autonomic homeostasis, sensory and motor relay, nociception, sleep, and cranial nerve function, and they have been implicated in a vast array of brain pathologies. However, an in vivo delineation of most human Bn has been elusive because of limited sensitivity and contrast for detecting these small regions using standard neuroimaging methods. To precisely identify several human Bn in vivo, we employed a 7 Tesla scanner equipped with multi-channel receive-coil array, which provided high magnetic resonance imaging sensitivity, and a multi-contrast (diffusion fractional anisotropy and T2-weighted) echo-planar-imaging approach, which provided complementary contrasts for Bn anatomy with matched geometric distortions and resolution. Through a combined examination of 1.3 mm(3) multi-contrast anatomical images acquired in healthy human adults, we semi-automatically generated in vivo probabilistic Bn labels of the ascending arousal (median and dorsal raphe), autonomic (raphe magnus, periaqueductal gray), and motor (inferior olivary nuclei, two subregions of the substantia nigra compatible with pars compacta and pars reticulata, two subregions of the red nucleus, and, in the diencephalon, two subregions of the subthalamic nucleus) systems. These labels constitute a first step toward the development of an in vivo neuroimaging template of Bn in standard space to facilitate future clinical and research investigations of human brainstem function and pathology. Proof-of-concept clinical use of this template is demonstrated in a minimally conscious patient with traumatic brainstem hemorrhages precisely localized to the raphe Bn involved in arousal.

    View details for DOI 10.1089/brain.2015.0347

    View details for Web of Science ID 000448191900001

    View details for PubMedID 26066023

    View details for PubMedCentralID PMC4684653

  • Real diffusion-weighted MRI enabling true signal averaging and increased diffusion contrast NEUROIMAGE Eichner, C., Cauley, S. F., Cohen-Adad, J., Moeller, H. E., Turner, R., Setsompop, K., Wald, L. L. 2015; 122: 373–84

    Abstract

    This project aims to characterize the impact of underlying noise distributions on diffusion-weighted imaging. The noise floor is a well-known problem for traditional magnitude-based diffusion-weighted MRI (dMRI) data, leading to biased diffusion model fits and inaccurate signal averaging. Here, we introduce a total-variation-based algorithm to eliminate shot-to-shot phase variations of complex-valued diffusion data with the intention to extract real-valued dMRI datasets. The obtained real-valued diffusion data are no longer superimposed by a noise floor but instead by a zero-mean Gaussian noise distribution, yielding dMRI data without signal bias. We acquired high-resolution dMRI data with strong diffusion weighting and, thus, low signal-to-noise ratio. Both the extracted real-valued and traditional magnitude data were compared regarding signal averaging, diffusion model fitting and accuracy in resolving crossing fibers. Our results clearly indicate that real-valued diffusion data enables idealized conditions for signal averaging. Furthermore, the proposed method enables unbiased use of widely employed linear least squares estimators for model fitting and demonstrates an increased sensitivity to detect secondary fiber directions with reduced angular error. The use of phase-corrected, real-valued data for dMRI will therefore help to clear the way for more detailed and accurate studies of white matter microstructure and structural connectivity on a fine scale.

    View details for DOI 10.1016/j.neuroimage.2015.07.074

    View details for Web of Science ID 000363125200036

    View details for PubMedID 26241680

    View details for PubMedCentralID PMC4651971

  • In vivo mapping of human spinal cord microstructure at 300 mT/m NEUROIMAGE Duval, T., McNab, J. A., Setsompop, K., Witzel, T., Schneider, T., Huang, S. Y., Keil, B., Klawiter, E. C., Wald, L. L., Cohen-Adad, J. 2015; 118: 494-507

    Abstract

    The ability to characterize white matter microstructure non-invasively has important applications for the diagnosis and follow-up of several neurological diseases. There exists a family of diffusion MRI techniques, such as AxCaliber, that provide indices of axon microstructure, such as axon diameter and density. However, to obtain accurate measurements of axons with small diameters (<5μm), these techniques require strong gradients, i.e. an order of magnitude higher than the 40-80mT/m currently available in clinical systems. In this study we acquired AxCaliber diffusion data at a variety of different q-values and diffusion times in the spinal cord of five healthy subjects using a 300mT/m whole body gradient system. Acquisition and processing were optimized using state-of-the-art methods (e.g., 64-channel coil, template-based analysis). Results consistently show an average axon diameter of 4.5+/-1.1μm in the spinal cord white matter. Diameters ranged from 3.0μm (gracilis) to 5.9μm (spinocerebellar tracts). Values were similar across laterality (left-right), but statistically different across spinal cord pathways (p<10(-5)). The observed trends are similar to those observed in animal histology. This study shows, for the first time, in vivo mapping of axon diameter in the spinal cord at 300mT/m, thus creating opportunities for applications in spinal cord diseases.

    View details for DOI 10.1016/j.neuroimage.2015.06.038

    View details for Web of Science ID 000360630200047

    View details for PubMedCentralID PMC4562035

  • Fast group matching for MR fingerprinting reconstruction MAGNETIC RESONANCE IN MEDICINE Cauley, S. F., Setsompop, K., Ma, D., Jiang, Y., Ye, H., Adalsteinsson, E., Griswold, M. A., Wald, L. L. 2015; 74 (2): 523–28

    Abstract

    MR fingerprinting (MRF) is a technique for quantitative tissue mapping using pseudorandom measurements. To estimate tissue properties such as T1 , T2 , proton density, and B0 , the rapidly acquired data are compared against a large dictionary of Bloch simulations. This matching process can be a very computationally demanding portion of MRF reconstruction.We introduce a fast group matching algorithm (GRM) that exploits inherent correlation within MRF dictionaries to create highly clustered groupings of the elements. During matching, a group specific signature is first used to remove poor matching possibilities. Group principal component analysis (PCA) is used to evaluate all remaining tissue types. In vivo 3 Tesla brain data were used to validate the accuracy of our approach.For a trueFISP sequence with over 196,000 dictionary elements, 1000 MRF samples, and image matrix of 128 × 128, GRM was able to map MR parameters within 2s using standard vendor computational resources. This is an order of magnitude faster than global PCA and nearly two orders of magnitude faster than direct matching, with comparable accuracy (1-2% relative error).The proposed GRM method is a highly efficient model reduction technique for MRF matching and should enable clinically relevant reconstruction accuracy and time on standard vendor computational resources.

    View details for DOI 10.1002/mrm.25439

    View details for Web of Science ID 000358607700028

    View details for PubMedID 25168690

    View details for PubMedCentralID PMC4700821

  • Accelerated H-1 MRSI using randomly undersampled spiral-based k-space trajectories MAGNETIC RESONANCE IN MEDICINE Chatnuntawech, I., Gagoski, B., Bilgic, B., Cauley, S. F., Setsompop, K., Adalsteinsson, E. 2015; 74 (1): 13–24

    Abstract

    To develop and evaluate the performance of an acquisition and reconstruction method for accelerated MR spectroscopic imaging (MRSI) through undersampling of spiral trajectories.A randomly undersampled spiral acquisition and sensitivity encoding (SENSE) with total variation (TV) regularization, random SENSE+TV, is developed and evaluated on single-slice numerical phantom, in vivo single-slice MRSI, and in vivo three-dimensional (3D)-MRSI at 3 Tesla. Random SENSE+TV was compared with five alternative methods for accelerated MRSI.For the in vivo single-slice MRSI, random SENSE+TV yields up to 2.7 and 2 times reduction in root-mean-square error (RMSE) of reconstructed N-acetyl aspartate (NAA), creatine, and choline maps, compared with the denoised fully sampled and uniformly undersampled SENSE+TV methods with the same acquisition time, respectively. For the in vivo 3D-MRSI, random SENSE+TV yields up to 1.6 times reduction in RMSE, compared with uniform SENSE+TV. Furthermore, by using random SENSE+TV, we have demonstrated on the in vivo single-slice and 3D-MRSI that acceleration factors of 4.5 and 4 are achievable with the same quality as the fully sampled data, as measured by RMSE of reconstructed NAA map, respectively.With the same scan time, random SENSE+TV yields lower RMSEs of metabolite maps than other methods evaluated. Random SENSE+TV achieves up to 4.5-fold acceleration with comparable data quality as the fully sampled acquisition. Magn Reson Med 74:13-24, 2015. © 2014 Wiley Periodicals, Inc.

    View details for DOI 10.1002/mrm.25394

    View details for Web of Science ID 000356451500003

    View details for PubMedID 25079076

  • Wave-CAIPI for highly accelerated 3D imaging MAGNETIC RESONANCE IN MEDICINE Bilgic, B., Gagoski, B. A., Cauley, S. F., Fan, A. P., Polimeni, J. R., Grant, P., Wald, L. L., Setsompop, K. 2015; 73 (6): 2152–62

    Abstract

    To introduce the wave-CAIPI (controlled aliasing in parallel imaging) acquisition and reconstruction technique for highly accelerated 3D imaging with negligible g-factor and artifact penalties.The wave-CAIPI 3D acquisition involves playing sinusoidal gy and gz gradients during the readout of each kx encoding line while modifying the 3D phase encoding strategy to incur interslice shifts as in 2D-CAIPI acquisitions. The resulting acquisition spreads the aliasing evenly in all spatial directions, thereby taking full advantage of 3D coil sensitivity distribution. By expressing the voxel spreading effect as a convolution in image space, an efficient reconstruction scheme that does not require data gridding is proposed. Rapid acquisition and high-quality image reconstruction with wave-CAIPI is demonstrated for high-resolution magnitude and phase imaging and quantitative susceptibility mapping.Wave-CAIPI enables full-brain gradient echo acquisition at 1 mm isotropic voxel size and R = 3 × 3 acceleration with maximum g-factors of 1.08 at 3T and 1.05 at 7T. Relative to the other advanced Cartesian encoding strategies (2D-CAIPI and bunched phase encoding) wave-CAIPI yields up to two-fold reduction in maximum g-factor for nine-fold acceleration at both field strengths.Wave-CAIPI allows highly accelerated 3D acquisitions with low artifact and negligible g-factor penalties, and may facilitate clinical application of high-resolution volumetric imaging.

    View details for DOI 10.1002/mrm.25347

    View details for Web of Science ID 000354729100013

    View details for PubMedID 24986223

    View details for PubMedCentralID PMC4281518

  • Design of Parallel Transmission Pulses for Simultaneous Multislice with Explicit Control for Peak Power and Local Specific Absorption Rate MAGNETIC RESONANCE IN MEDICINE Guerin, B., Setsompop, K., Ye, H., Poser, B. A., Stenger, A. V., Wald, L. L. 2015; 73 (5): 1946–53

    Abstract

    To design parallel transmit (pTx) simultaneous multislice (SMS) spokes pulses with explicit control for peak power and local and global specific absorption rate (SAR).We design SMS pTx least-squares and magnitude least squares spokes pulses while constraining local SAR using the virtual observation points (VOPs) compression of SAR matrices. We evaluate our approach in simulations of a head (7T) and a body (3T) coil with eight channels arranged in two z-rows.For many of our simulations, control of average power by Tikhonov regularization of the SMS pTx spokes pulse design yielded pulses that violated hardware and SAR safety limits. On the other hand, control of peak power alone yielded pulses that violated local SAR limits. Pulses optimized with control of both local SAR and peak power satisfied all constraints and therefore had the best excitation performance under limited power and SAR constraints. These results extend our previous results for single slice pTx excitations but are more pronounced because of the large power demands and SAR of SMS pulses.Explicit control of local SAR and peak power is required to generate optimal SMS pTx excitations satisfying both the system's hardware limits and regulatory safety limits.

    View details for DOI 10.1002/mrm.25325

    View details for Web of Science ID 000353240600027

    View details for PubMedID 24938991

    View details for PubMedCentralID PMC4269582

  • RARE/Turbo Spin Echo Imaging with Simultaneous Multislice Wave-CAIPI MAGNETIC RESONANCE IN MEDICINE Gagoski, B. A., Bilgic, B., Eichner, C., Bhat, H., Grant, P., Wald, L. L., Setsompop, K. 2015; 73 (3): 929–38

    Abstract

    To enable highly accelerated RARE/Turbo Spin Echo (TSE) imaging using Simultaneous MultiSlice (SMS) Wave-CAIPI acquisition with reduced g-factor penalty.SMS Wave-CAIPI incurs slice shifts across simultaneously excited slices while playing sinusoidal gradient waveforms during the readout of each encoding line. This results in an efficient k-space coverage that spreads aliasing in all three dimensions to fully harness the encoding power of coil sensitivities. The novel MultiPINS radiofrequency (RF) pulses dramatically reduce the power deposition of multiband (MB) refocusing pulse, thus allowing high MB factors within the Specific Absorption Rate (SAR) limit.Wave-CAIPI acquisition with MultiPINS permits whole brain coverage with 1 mm isotropic resolution in 70 s at effective MB factor 13, with maximum and average g-factor penalties of gmax  = 1.34 and gavg  = 1.12, and without √R penalty. With blipped-CAIPI, the g-factor performance was degraded to gmax  = 3.24 and gavg  = 1.42; a 2.4-fold increase in gmax relative to Wave-CAIPI. At this MB factor, the SAR of the MultiBand and PINS pulses are 4.2 and 1.9 times that of the MultiPINS pulse, while the peak RF power are 19.4 and 3.9 times higher.Combination of the two technologies, Wave-CAIPI and MultiPINS pulse, enables highly accelerated RARE/TSE imaging with low SNR penalty at reduced SAR.

    View details for DOI 10.1002/mrm.25615

    View details for Web of Science ID 000350279900005

    View details for PubMedID 25640187

    View details for PubMedCentralID PMC4334698

  • Fast Reconstruction for Multichannel Compressed Sensing Using a Hierarchically Semiseparable Solver MAGNETIC RESONANCE IN MEDICINE Cauley, S. F., Xi, Y., Bilgic, B., Xia, J., Adalsteinsson, E., Balakrishnan, V., Wald, L. L., Setsompop, K. 2015; 73 (3): 1034–40

    Abstract

    The adoption of multichannel compressed sensing (CS) for clinical magnetic resonance imaging (MRI) hinges on the ability to accurately reconstruct images from an undersampled dataset in a reasonable time frame. When CS is combined with SENSE parallel imaging, reconstruction can be computationally intensive. As an alternative to iterative methods that repetitively evaluate a forward CS+SENSE model, we introduce a technique for the fast computation of a compact inverse model solution.A recently proposed hierarchically semiseparable (HSS) solver is used to compactly represent the inverse of the CS+SENSE encoding matrix to a high level of accuracy. To investigate the computational efficiency of the proposed HSS-Inverse method, we compare reconstruction time with the current state-of-the-art. In vivo 3T brain data at multiple image contrasts, resolutions, acceleration factors, and number of receive channels were used for this comparison.The HSS-Inverse method allows for >6× speedup when compared to current state-of-the-art reconstruction methods with the same accuracy. Efficient computational scaling is demonstrated for CS+SENSE with respect to image size. The HSS-Inverse method is also shown to have minimal dependency on the number of parallel imaging channels/acceleration factor.The proposed HSS-Inverse method is highly efficient and should enable real-time CS reconstruction on standard MRI vendors' computational hardware.

    View details for DOI 10.1002/mrm.25222

    View details for Web of Science ID 000350279900015

    View details for PubMedID 24639238

    View details for PubMedCentralID PMC4167172

  • Sparse Methods for Quantitative Susceptibility Mapping Bilgic, B., Chatnuntawech, I., Langkammer, C., Setsompop, K., Papadakis, M., Goyal, V. K., VanDeVille, D. SPIE-INT SOC OPTICAL ENGINEERING. 2015

    View details for DOI 10.1117/12.2188535

    View details for Web of Science ID 000366387800028

  • A Compressed-Sensing Approach for Super-Resolution Reconstruction of Diffusion MRI. Information processing in medical imaging : proceedings of the ... conference Ning, L., Setsompop, K., Michailovich, O., Makris, N., Westin, C., Rathi, Y. 2015; 24: 57–68

    Abstract

    We present an innovative framework for reconstructing high-spatial-resolution diffusion magnetic resonance imaging (dMRI) from multiple low-resolution (LR) images. Our approach combines the twin concepts of compressed sensing (CS) and classical super-resolution to reduce acquisition time while increasing spatial resolution. We use subpixel-shifted LR images with down-sampled and non-overlapping diffusion directions to reduce acquisition time. The diffusion signal in the high resolution (HR) image is represented in a sparsifying basis of spherical ridgelets to model complex fiber orientations with reduced number of measurements. The HR image is obtained as the solution of a convex optimization problem which can be solved using the proposed algorithm based on the alternating direction method of multipliers (ADMM). We qualitatively and quantitatively evaluate the performance of our method on two sets of in-vivo human brain data and show its effectiveness in accurately recovering very high resolution diffusion images.

    View details for PubMedID 26221667

  • MAXIMUM LIKELIHOOD RECONSTRUCTION FOR MAGNETIC RESONANCE FINGERPRINTING Zhao, B., Lam, F., Bilgicy, B., Ye, H., Setsompop, K., IEEE IEEE. 2015: 905–9
  • FAST RECONSTRUCTION FOR ACCELERATED MULTI-SLICE MULTI-CONTRAST MRI Chatnuntawech, I., Bilgic, B., Martin, A., Setsompop, K., Adalsteinsson, E., IEEE IEEE. 2015: 335–38
  • Fast Quantitative Susceptibility Mapping with L1-Regularization and Automatic Parameter Selection MAGNETIC RESONANCE IN MEDICINE Bilgic, B., Fan, A. P., Polimeni, J. R., Cauley, S. F., Bianciardi, M., Adalsteinsson, E., Wald, L. L., Setsompop, K. 2014; 72 (5): 1444-1459

    Abstract

    To enable fast reconstruction of quantitative susceptibility maps with total variation penalty and automatic regularization parameter selection.ℓ(1) -Regularized susceptibility mapping is accelerated by variable splitting, which allows closed-form evaluation of each iteration of the algorithm by soft thresholding and fast Fourier transforms. This fast algorithm also renders automatic regularization parameter estimation practical. A weighting mask derived from the magnitude signal can be incorporated to allow edge-aware regularization.Compared with the nonlinear conjugate gradient (CG) solver, the proposed method is 20 times faster. A complete pipeline including Laplacian phase unwrapping, background phase removal with SHARP filtering, and ℓ(1) -regularized dipole inversion at 0.6 mm isotropic resolution is completed in 1.2 min using MATLAB on a standard workstation compared with 22 min using the CG solver. This fast reconstruction allows estimation of regularization parameters with the L-curve method in 13 min, which would have taken 4 h with the CG algorithm. The proposed method also permits magnitude-weighted regularization, which prevents smoothing across edges identified on the magnitude signal. This more complicated optimization problem is solved 5 times faster than the nonlinear CG approach. Utility of the proposed method is also demonstrated in functional blood oxygen level-dependent susceptibility mapping, where processing of the massive time series dataset would otherwise be prohibitive with the CG solver.Online reconstruction of regularized susceptibility maps may become feasible with the proposed dipole inversion.

    View details for DOI 10.1002/mrm.25029

    View details for Web of Science ID 000343873900026

    View details for PubMedID 24259479

    View details for PubMedCentralID PMC4111791

  • A Low Power Radiofrequency Pulse for Simultaneous Multislice Excitation and Refocusing MAGNETIC RESONANCE IN MEDICINE Eichner, C., Wald, L. L., Setsompop, K. 2014; 72 (4): 949–58

    Abstract

    Simultaneous multislice (SMS) acquisition enables increased temporal efficiency of MRI. Nonetheless, MultiBand (MB) radiofrequency (RF) pulses used for SMS can cause large energy deposition. Power independent of number of slices (PINS) pulses reduce RF power at cost of reduced bandwidth and increased off-resonance dependency. This work improves PINS design to further reduce energy deposition, off-resonance dependency and peak power.Modifying the shape of MB RF-pulses allows for mixing with PINS excitation, creating a new pulse type with reduced energy deposition and SMS excitation characteristics. Bloch Simulations were used to evaluate excitation and off-resonance behavior of this "MultiPINS" pulse. In this work, MultiPINS was used for whole-brain MB = 3 acquisition of high angular and spatial resolution diffusion MRI at 7 Tesla in 3 min.By using MultiPINS, energy transmission and peak power for SMS imaging can be significantly reduced compared with PINS and MB pulses. For MB = 3 acquisition in this work, MultiPINS reduces energy transmission by up to ∼50% compared with PINS pulses. The energy reduction was traded off to shorten the MultiPINS pulse, yielding higher signal at off-resonances for spin-echo acquisitions.MB and PINS pulses can be combined to enable low energy and peak power SMS acquisition.

    View details for DOI 10.1002/mrm.25389

    View details for Web of Science ID 000342342300007

    View details for PubMedID 25103999

  • Slice Accelerated Gradient-Echo Spin-Echo Dynamic Susceptibility Contrast Imaging with Blipped CAIPI for Increased Slice Coverage MAGNETIC RESONANCE IN MEDICINE Eichner, C., Jafari-Khouzani, K., Cauley, S., Bhat, H., Polaskova, P., Andronesi, O. C., Rapalino, O., Turner, R., Wald, L. L., Stufflebeam, S., Setsompop, K. 2014; 72 (3): 770–78

    Abstract

    To improve slice coverage of gradient echo spin echo (GESE) sequences for dynamic susceptibility contrast (DSC) MRI using a simultaneous-multiple-slice (SMS) method.Data were acquired on 3 Tesla (T) MR scanners with a 32-channel head coil. To evaluate use of SMS for DSC, an SMS GESE sequence with two-fold slice coverage and same temporal sampling was compared with a standard GESE sequence, both with 2× in-plane acceleration. A signal to noise ratio (SNR) comparison was performed on one healthy subject. Additionally, data with Gadolinium injection were collected on three patients with glioblastoma using both sequences, and perfusion analysis was performed on healthy tissues as well as on tumor.Retained SNR of SMS DSC is 90% for a gradient echo (GE) and 99% for a spin echo (SE) acquisition, compared with a standard acquisition without slice acceleration. Comparing cerebral blood volume maps, it was observed that the results of standard and SMS acquisitions are comparable for both GE and SE images.Two-fold slice accelerated DSC MRI achieves similar SNR and perfusion metrics as a standard acquisition, while allowing a significant increase in slice coverage of the brain. The results also point to a possibility to improve temporal sampling rate, while retaining the same slice coverage.

    View details for DOI 10.1002/mrm.24960

    View details for Web of Science ID 000340552700019

    View details for PubMedID 24285593

    View details for PubMedCentralID PMC4002660

  • Nineteen-Channel Receive Array and Four-Channel Transmit Array Coil for Cervical Spinal Cord Imaging at 7T MAGNETIC RESONANCE IN MEDICINE Zhao, W., Cohen-Adad, J., Polimeni, J. R., Keil, B., Guerin, B., Setsompop, K., Serano, P., Mareyam, A., Hoecht, P., Wald, L. L. 2014; 72 (1): 291–300

    Abstract

    To design and validate a radiofrequency (RF) array coil for cervical spinal cord imaging at 7T.A 19-channel receive array with a four-channel transmit array was developed on a close-fitting coil former at 7T. Transmit efficiency and specific absorption rate were evaluated in a B1 (+) mapping study and an electromagnetic model. Receive signal-to-noise ratio (SNR) and noise amplification for parallel imaging were evaluated and compared with a commercial 3T 19-channel head-neck array and a 7T four-channel spine array. The performance of the array was qualitatively demonstrated in human volunteers using high-resolution imaging (down to 300 μm in-plane).The transmit and receive arrays showed good bench performance. The SNR was approximately 4.2-fold higher in the 7T receive array at the location of the cord with respect to the 3T coil. The g-factor results showed an additional acceleration was possible with the 7T array. In vivo imaging was feasible and showed high SNR and tissue contrast.The highly parallel transmit and receive arrays were demonstrated to be fit for spinal cord imaging at 7T. The high sensitivity of the receive coil combined with ultra-high field will likely improve investigations of microstructure and tissue segmentation in the healthy and pathological spinal cord.

    View details for DOI 10.1002/mrm.24911

    View details for Web of Science ID 000337624400032

    View details for PubMedID 23963998

    View details for PubMedCentralID PMC4761437

  • Fast Image Reconstruction With L2-Regularization JOURNAL OF MAGNETIC RESONANCE IMAGING Bilgic, B., Chatnuntawech, I., Fan, A. P., Setsompop, K., Cauley, S. F., Wald, L. L., Adalsteinsson, E. 2014; 40 (1): 181–91

    Abstract

    We introduce L2-regularized reconstruction algorithms with closed-form solutions that achieve dramatic computational speed-up relative to state of the art L1- and L2-based iterative algorithms while maintaining similar image quality for various applications in MRI reconstruction.We compare fast L2-based methods to state of the art algorithms employing iterative L1- and L2-regularization in numerical phantom and in vivo data in three applications; (i) Fast Quantitative Susceptibility Mapping (QSM), (ii) Lipid artifact suppression in Magnetic Resonance Spectroscopic Imaging (MRSI), and (iii) Diffusion Spectrum Imaging (DSI). In all cases, proposed L2-based methods are compared with the state of the art algorithms, and two to three orders of magnitude speed up is demonstrated with similar reconstruction quality.The closed-form solution developed for regularized QSM allows processing of a three-dimensional volume under 5 s, the proposed lipid suppression algorithm takes under 1 s to reconstruct single-slice MRSI data, while the PCA based DSI algorithm estimates diffusion propagators from undersampled q-space for a single slice under 30 s, all running in Matlab using a standard workstation.For the applications considered herein, closed-form L2-regularization can be a faster alternative to its iterative counterpart or L1-based iterative algorithms, without compromising image quality.

    View details for DOI 10.1002/jmri.24365

    View details for Web of Science ID 000337640700025

    View details for PubMedID 24395184

    View details for PubMedCentralID PMC4106040

  • Interslice Leakage Artifact Reduction Technique for Simultaneous Multislice Acquisitions MAGNETIC RESONANCE IN MEDICINE Cauley, S. F., Polimeni, J. R., Bhat, H., Wald, L. L., Setsompop, K. 2014; 72 (1): 93–102

    Abstract

    Controlled aliasing techniques for simultaneously acquired echo-planar imaging slices have been shown to significantly increase the temporal efficiency for both diffusion-weighted imaging and functional magnetic resonance imaging studies. The "slice-GRAPPA" (SG) method has been widely used to reconstruct such data. We investigate robust optimization techniques for SG to ensure image reconstruction accuracy through a reduction of leakage artifacts.Split SG is proposed as an alternative kernel optimization method. The performance of Split SG is compared to standard SG using data collected on a spherical phantom and in vivo on two subjects at 3 T. Slice-accelerated and nonaccelerated data were collected for a spin-echo diffusion-weighted acquisition. Signal leakage metrics and time-series SNR were used to quantify the performance of the kernel fitting approaches.The Split SG optimization strategy significantly reduces leakage artifacts for both phantom and in vivo acquisitions. In addition, a significant boost in time-series SNR for in vivo diffusion-weighted acquisitions with in-plane 2× and slice 3× accelerations was observed with the Split SG approach.By minimizing the influence of leakage artifacts during the training of SG kernels, we have significantly improved reconstruction accuracy. Our robust kernel fitting strategy should enable better reconstruction accuracy and higher slice-acceleration across many applications.

    View details for DOI 10.1002/mrm.24898

    View details for Web of Science ID 000337624400012

    View details for PubMedID 23963964

    View details for PubMedCentralID PMC4364522

  • Improving the spatial resolution of magnetic resonance inverse imaging via the blipped-CAIPI acquisition scheme NEUROIMAGE Chang, W., Setsompop, K., Ahveninen, J., Belliveau, J. W., Witzel, T., Lin, F. 2014; 91: 401–11

    Abstract

    Using simultaneous acquisition from multiple channels of a radio-frequency (RF) coil array, magnetic resonance inverse imaging (InI) achieves functional MRI acquisitions at a rate of 100ms per whole-brain volume. InI accelerates the scan by leaving out partition encoding steps and reconstructs images by solving under-determined inverse problems using RF coil sensitivity information. Hence, the correlated spatial information available in the coil array causes spatial blurring in the InI reconstruction. Here, we propose a method that employs gradient blips in the partition encoding direction during the acquisition to provide extra spatial encoding in order to better differentiate signals from different partitions. According to our simulations, this blipped-InI (bInI) method can increase the average spatial resolution by 15.1% (1.3mm) across the whole brain and from 32.6% (4.2mm) in subcortical regions, as compared to the InI method. In a visual fMRI experiment, we demonstrate that, compared to InI, the spatial distribution of bInI BOLD response is more consistent with that of a conventional echo-planar imaging (EPI) at the level of individual subjects. With the improved spatial resolution, especially in subcortical regions, bInI can be a useful fMRI tool for obtaining high spatiotemporal information for clinical and cognitive neuroscience studies.

    View details for DOI 10.1016/j.neuroimage.2013.12.037

    View details for Web of Science ID 000338914100041

    View details for PubMedID 24374076

    View details for PubMedCentralID PMC4086630

  • Slice Accelerated Diffusion-Weighted Imaging at Ultra-High Field Strength MAGNETIC RESONANCE IN MEDICINE Eichner, C., Setsompop, K., Koopmans, P. J., Luetzkendorf, R., Norris, D. G., Turner, R., Wald, L. L., Heidemann, R. M. 2014; 71 (4): 1518–25

    Abstract

    Diffusion magnetic resonance imaging (dMRI) data with very high isotropic resolution can be obtained at 7T. However, for extensive brain coverage, a large number of slices is required, resulting in long acquisition times (TAs). Recording multiple slices simultaneously (SMS) promises to reduce the TA.A combination of zoomed and parallel imaging is used to achieve high isotropic resolution dMRI data with a low level of distortions at 7T. The blipped-CAIPI (controlled aliasing in parallel imaging) approach is used to acquire several slices simultaneously. Due to their high radiofrequency (RF) power deposition and ensuing specific absorption rate (SAR) constraints, the commonly used multiband (MB) RF pulses for SMS imaging are inefficient at 7T and entail long repetition times, counteracting the usefulness of SMS acquisitions. To address this issue, low SAR multislice Power Independent of Number of Slices RF pulses are employed.In vivo dMRI results with and without SMS acceleration are presented at different isotropic spatial resolutions at ultra high field strength. The datasets are recorded at a high angular resolution to detect fiber crossings.From the results and compared with earlier studies at these resolutions, it can be seen that scan time is significantly reduced, while image quality is preserved.

    View details for DOI 10.1002/mrm.24809

    View details for Web of Science ID 000333040500018

    View details for PubMedID 23798017

  • Simultaneous Multislice Excitation by Parallel Transmission MAGNETIC RESONANCE IN MEDICINE Poser, B. A., Anderson, R., Guerin, B., Setsompop, K., Deng, W., Mareyam, A., Serano, P., Wald, L. L., Stenger, V. 2014; 71 (4): 1416–27

    Abstract

    A technique is described for simultaneous multislice (SMS) excitation using radiofrequency (RF) parallel transmission (pTX).Spatially distinct slices are simultaneously excited by applying different RF frequencies on groups of elements of a multichannel transmit array. The localized transmit sensitivities of the coil geometry are thereby exploited to reduce RF power. The method is capable of achieving SMS-excitation using single-slice RF pulses, or multiband pulses. SMS-pTX is demonstrated using eight-channel parallel RF transmission on a dual-ring pTX coil at 3 T. The effect on B(1)(+) homogeneity and specific absorption rate (SAR) is evaluated experimentally and by simulations. Slice-GRAPPA reconstruction was used for separation of the collapsed slice signals.Phantom and in vivo brain data acquired with fast low-angle shot (FLASH) and blipped-controlled aliasing results in higher acceleration (CAIPIRINHA) echo-planar imaging are presented at SMS excitation factors of two, four, and six. We also show that with our pTX coil design, slice placement, and binary division of transmitters, SMS-pTX excitations can achieve the same mean flip angles excitations at ∼30% lower RF power than a conventional SMS approach with multiband RF pulses.The proposed SMS-pTX allows SMS excitations at reduced RF power by exploiting the local B(1)(+) sensitivities of suitable multielement pTX arrays.

    View details for DOI 10.1002/mrm.24791

    View details for Web of Science ID 000333040500008

    View details for PubMedID 23716365

    View details for PubMedCentralID PMC3830622

  • Rapid High Spatial Resolution Diffusion MRI at 7 Tesla using Simultaneous MultiSlice Acquisition Eichner, C., Wald, L. L., Setsompop, K., IEEE IEEE. 2014
  • Fast Dictionary-Based Reconstruction for Diffusion Spectrum Imaging IEEE TRANSACTIONS ON MEDICAL IMAGING Bilgic, B., Chatnuntawech, I., Setsompop, K., Cauley, S. F., Yendiki, A., Wald, L. L., Adalsteinsson, E. 2013; 32 (11): 2022–33

    Abstract

    Diffusion spectrum imaging reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using MATLAB running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using principal component analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm.

    View details for DOI 10.1109/TMI.2013.2271707

    View details for Web of Science ID 000326733300006

    View details for PubMedID 23846466

    View details for PubMedCentralID PMC4689148

  • A 64-channel 3T array coil for accelerated brain MRI MAGNETIC RESONANCE IN MEDICINE Keil, B., Blau, J. N., Biber, S., Hoecht, P., Tountcheva, V., Setsompop, K., Triantafyllou, C., Wald, L. L. 2013; 70 (1): 248–58

    Abstract

    A 64-channel brain array coil was developed and compared to a 32-channel array constructed with the same coil former geometry to precisely isolate the benefit of the 2-fold increase in array coil elements. The constructed coils were developed for a standard clinical 3T MRI scanner and used a contoured head-shaped curved former around the occipital pole and tapered in at the neck to both improve sensitivity and patient comfort. Additionally, the design is a compact, split-former design intended for robust daily use. Signal-to-noise ratio and noise amplification (G-factor) for parallel imaging were quantitatively evaluated in human imaging and compared to a size and shape-matched 32-channel array coil. For unaccelerated imaging, the 64-channel array provided similar signal-to-noise ratio in the brain center to the 32-channel array and 1.3-fold more signal-to-noise ratio in the brain cortex. Reduced noise amplification during highly parallel imaging of the 64-channel array provided the ability to accelerate at approximately one unit higher at a given noise amplification compared to the sized-matched 32-channel array. For example, with a 4-fold acceleration rate, the central brain and cortical signal-to-noise ratio of the 64-channel array was 1.2- and 1.4-fold higher, respectively, compared to the 32-channel array. The characteristics of the coil are demonstrated in accelerated brain imaging.

    View details for DOI 10.1002/mrm.24427

    View details for Web of Science ID 000320785900029

    View details for PubMedID 22851312

    View details for PubMedCentralID PMC3538896

  • Ultra-fast MRI of the human brain with simultaneous multi-slice imaging JOURNAL OF MAGNETIC RESONANCE Feinberg, D. A., Setsompop, K. 2013; 229: 90–100

    Abstract

    The recent advancement of simultaneous multi-slice imaging using multiband excitation has dramatically reduced the scan time of the brain. The evolution of this parallel imaging technique began over a decade ago and through recent sequence improvements has reduced the acquisition time of multi-slice EPI by over ten fold. This technique has recently become extremely useful for (i) functional MRI studies improving the statistical definition of neuronal networks, and (ii) diffusion based fiber tractography to visualize structural connections in the human brain. Several applications and evaluations are underway which show promise for this family of fast imaging sequences.

    View details for DOI 10.1016/j.jmr.2013.02.002

    View details for Web of Science ID 000316840700010

    View details for PubMedID 23473893

    View details for PubMedCentralID PMC3793016

  • Diffusion Propagator Estimation from Sparse Measurements in a Tractography Framework Rathi, Y., Gagoski, B., Setsompop, K., Michailovich, O., Grant, P., Westin, C., Mori, K., Sakuma, Sato, Y., Barillot, C., Navab, N. SPRINGER-VERLAG BERLIN. 2013: 510–17

    Abstract

    Estimation of the diffusion propagator from a sparse set of diffusion MRI (dMRI) measurements is a field of active research. Sparse reconstruction methods propose to reduce scan time and are particularly suitable for scanning un-coperative patients. Recent work on reconstructing the diffusion signal from very few measurements using compressed sensing based techniques has focussed on propagator (or signal) estimation at each voxel independently. However, the goal of many neuroscience studies is to use tractography to study the pathology in white matter fiber tracts. Thus, in this work, we propose a joint framework for robust estimation of the diffusion propagator from sparse measurements while simultaneously tracing the white matter tracts. We propose to use a novel multi-tensor model of diffusion which incorporates the biexponential radial decay of the signal. Our preliminary results on in-vivo data show that the proposed method produces consistent and reliable fiber tracts from very few gradient directions while simultaneously estimating the bi-exponential decay of the diffusion propagator.

    View details for Web of Science ID 000333633500064

    View details for PubMedID 24505800

    View details for PubMedCentralID PMC4103161

  • Accelerated diffusion spectrum imaging with compressed sensing using adaptive dictionaries MAGNETIC RESONANCE IN MEDICINE Bilgic, B., Setsompop, K., Cohen-Adad, J., Yendiki, A., Wald, L. L., Adalsteinsson, E. 2012; 68 (6): 1747–54

    Abstract

    Diffusion spectrum imaging offers detailed information on complex distributions of intravoxel fiber orientations at the expense of extremely long imaging times (∼1 h). Recent work by Menzel et al. demonstrated successful recovery of diffusion probability density functions from sub-Nyquist sampled q-space by imposing sparsity constraints on the probability density functions under wavelet and total variation transforms. As the performance of compressed sensing reconstruction depends strongly on the level of sparsity in the selected transform space, a dictionary specifically tailored for diffusion probability density functions can yield higher fidelity results. To our knowledge, this work is the first application of adaptive dictionaries in diffusion spectrum imaging, whereby we reduce the scan time of whole brain diffusion spectrum imaging acquisition from 50 to 17 min while retaining high image quality. In vivo experiments were conducted with the 3T Connectome MRI. The root-mean-square error of the reconstructed "missing" diffusion images were calculated by comparing them to a gold standard dataset (obtained from acquiring 10 averages of diffusion images in these missing directions). The root-mean-square error from the proposed reconstruction method is up to two times lower than that of Menzel et al.'s method and is actually comparable to that of the fully-sampled 50 minute scan. Comparison of tractography solutions in 18 major white-matter pathways also indicated good agreement between the fully-sampled and 3-fold accelerated reconstructions. Further, we demonstrate that a dictionary trained using probability density functions from a single slice of a particular subject generalizes well to other slices from the same subject, as well as to slices from other subjects.

    View details for DOI 10.1002/mrm.24505

    View details for Web of Science ID 000311398600008

    View details for PubMedID 23008145

    View details for PubMedCentralID PMC3504650

  • Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty MAGNETIC RESONANCE IN MEDICINE Setsompop, K., Gagoski, B. A., Polimeni, J. R., Witzel, T., Wedeen, V. J., Wald, L. L. 2012; 67 (5): 1210–24

    Abstract

    Simultaneous multislice Echo Planar Imaging (EPI) acquisition using parallel imaging can decrease the acquisition time for diffusion imaging and allow full-brain, high-resolution functional MRI (fMRI) acquisitions at a reduced repetition time (TR). However, the unaliasing of simultaneously acquired, closely spaced slices can be difficult, leading to a high g-factor penalty. We introduce a method to create interslice image shifts in the phase encoding direction to increase the distance between aliasing pixels. The shift between the slices is induced using sign- and amplitude-modulated slice-select gradient blips simultaneous with the EPI phase encoding blips. This achieves the desired shifts but avoids an undesired "tilted voxel" blurring artifact associated with previous methods. We validate the method in 3× slice-accelerated spin-echo and gradient-echo EPI at 3 T and 7 T using 32-channel radio frequency (RF) coil brain arrays. The Monte-Carlo simulated average g-factor penalty of the 3-fold slice-accelerated acquisition with interslice shifts is <1% at 3 T (compared with 32% without slice shift). Combining 3× slice acceleration with 2× inplane acceleration, the g-factor penalty becomes 19% at 3 T and 10% at 7 T (compared with 41% and 23% without slice shift). We demonstrate the potential of the method for accelerating diffusion imaging by comparing the fiber orientation uncertainty, where the 3-fold faster acquisition showed no noticeable degradation.

    View details for DOI 10.1002/mrm.23097

    View details for Web of Science ID 000302619400003

    View details for PubMedID 21858868

    View details for PubMedCentralID PMC3323676

  • Accelerated Diffusion Spectrum Imaging with Compressed Sensing Using Adaptive Dictionaries Bilgic, B., Setsompop, K., Cohen-Adad, J., Wedeen, V., Wald, L. L., Adalsteinsson, E., Ayache, N., Delingette, H., Golland, P., Mori, K. SPRINGER-VERLAG BERLIN. 2012: 1–9

    Abstract

    Diffusion spectrum imaging (DSI) offers detailed information on complex distributions of intravoxel fiber orientations at the expense of extremely long imaging times (1 hour). It is possible to accelerate DSI by sub-Nyquist sampling of the q-space followed by nonlinear reconstruction to estimate the diffusion probability density functions (pdfs). Recent work by Menzel et al. imposed sparsity constraints on the pdfs under wavelet and total variation (TV) transforms. As the performance of Compressed Sensing (CS) reconstruction depends strongly on the level of sparsity in the selected transform space, a dictionary specifically tailored for sparse representation of diffusion pdfs can yield higher fidelity results. To our knowledge, this work is the first application of adaptive dictionaries in DSI, whereby we reduce the scan time of whole brain DSI acquisition from 50 to 17 min while retaining high image quality. In vivo experiments were conducted with the novel 3T Connectome MRI, whose strong gradients are particularly suited for DSI. The RMSE from the proposed reconstruction is up to 2 times lower than that of Menzel et al.'s method, and is actually comparable to that of the fully-sampled 50 minute scan. Further, we demonstrate that a dictionary trained using pdfs from a single slice of a particular subject generalizes well to other slices from the same subject, as well as to slices from another subject.

    View details for Web of Science ID 000371317400001

    View details for PubMedID 23286107

    View details for PubMedCentralID PMC4679293

  • Broadband Slab Selection with B-1(+) Mitigation at 7T via Parallel Spectral-Spatial Excitation MAGNETIC RESONANCE IN MEDICINE Setsompop, K., Alagappan, V., Gagoski, B. A., Potthast, A., Hebrank, F., Fontius, U., Schmitt, F., Wald, L. L., Adalsteinsson, E. 2009; 61 (2): 493–500

    Abstract

    Chemical shift imaging benefits from signal-to-noise ratio (SNR) and chemical shift dispersion increases at stronger main field such as 7 Tesla, but the associated shorter radiofrequency (RF) wavelengths encountered require B1+ mitigation over both the spatial field of view (FOV) and a specified spectral bandwidth. The bandwidth constraint presents a challenge for previously proposed spatially tailored B1+ mitigation methods, which are based on a type of echovolumnar trajectory referred to as "spokes" or "fast-kz". Although such pulses, in conjunction with parallel excitation methodology, can efficiently mitigate large B1+ inhomogeneities and achieve relatively short pulse durations with slice-selective excitations, they exhibit a narrow-band off-resonance response and may not be suitable for applications that require B1+ mitigation over a large spectral bandwidth. This work outlines a design method for a general parallel spectral-spatial excitation that achieves a target-error minimization simultaneously over a bandwidth of frequencies and a specified spatial-domain. The technique is demonstrated for slab-selective excitation with in-plane B1+ mitigation over a 600-Hz bandwidth. The pulse design method is validated in a water phantom at 7T using an eight-channel transmit array system. The results show significant increases in the pulse's spectral bandwidth, with no additional pulse duration penalty and only a minor tradeoff in spatial B1+ mitigation compared to the standard spoke-based parallel RF design.

    View details for DOI 10.1002/mrm.21834

    View details for Web of Science ID 000262871300030

    View details for PubMedID 19161170

    View details for PubMedCentralID PMC2632721

  • Slice-Selective RF Pulses for In Vivo B(1)(+) Inhomogeneity Mitigation at 7 Tesla Using Parallel RF Excitation With a 16-Element Coil MAGNETIC RESONANCE IN MEDICINE Setsompop, K., Alagappan, V., Gagoski, B., Witzel, T., Polimeni, J., Potthast, A., Hebrank, F., Fontius, U., Schmitt, F., Wald, L. L., Adalsteinsson, E. 2008; 60 (6): 1422–32

    Abstract

    Slice-selective RF waveforms that mitigate severe B1+ inhomogeneity at 7 Tesla using parallel excitation were designed and validated in a water phantom and human studies on six subjects using a 16-element degenerate stripline array coil driven with a butler matrix to utilize the eight most favorable birdcage modes. The parallel RF waveform design applied magnitude least-squares (MLS) criteria with an optimized k-space excitation trajectory to significantly improve profile uniformity compared to conventional least-squares (LS) designs. Parallel excitation RF pulses designed to excite a uniform in-plane flip angle (FA) with slice selection in the z-direction were demonstrated and compared with conventional sinc-pulse excitation and RF shimming. In all cases, the parallel RF excitation significantly mitigated the effects of inhomogeneous B1+ on the excitation FA. The optimized parallel RF pulses for human B1+ mitigation were only 67% longer than a conventional sinc-based excitation, but significantly outperformed RF shimming. For example the standard deviations (SDs) of the in-plane FA (averaged over six human studies) were 16.7% for conventional sinc excitation, 13.3% for RF shimming, and 7.6% for parallel excitation. This work demonstrates that excitations with parallel RF systems can provide slice selection with spatially uniform FAs at high field strengths with only a small pulse-duration penalty.

    View details for DOI 10.1002/mrm.21739

    View details for Web of Science ID 000261225100018

    View details for PubMedID 19025908

    View details for PubMedCentralID PMC2635025

  • High-flip-angle slice-selective parallel RF transmission with 8 channels at 7 T JOURNAL OF MAGNETIC RESONANCE Setsompop, K., Alagappan, V., Zelinski, A. C., Potthast, A., Fontius, U., Hebrank, F., Schmitt, F., Wald, L. L., Adalsteinsson, E. 2008; 195 (1): 76–84

    Abstract

    At high magnetic field, B(1)(+) non-uniformity causes undesired inhomogeneity in SNR and image contrast. Parallel RF transmission using tailored 3D k-space trajectory design has been shown to correct for this problem and produce highly uniform in-plane magnetization with good slice selection profile within a relatively short excitation duration. However, at large flip angles the excitation k-space based design method fails. Consequently, several large-flip-angle parallel transmission designs have recently been suggested. In this work, we propose and demonstrate a large-flip-angle parallel excitation design for 90 degrees and 180 degrees spin-echo slice-selective excitations that mitigate severe B(1)(+) inhomogeneity. The method was validated on an 8-channel transmit array at 7T using a water phantom with B(1)(+) inhomogeneity similar to that seen in human brain in vivo. Slice-selective excitations with parallel RF systems offer means to implement conventional high-flip excitation sequences without a severe pulse-duration penalty, even at very high B(0) field strengths where large B(1)(+) inhomogeneity is present.

    View details for DOI 10.1016/j.jmr.2008.08.012

    View details for Web of Science ID 000260398000011

    View details for PubMedID 18799336

    View details for PubMedCentralID PMC2610679

  • Sparsity-enforced slice-selective MRI RF excitation pulse design IEEE TRANSACTIONS ON MEDICAL IMAGING Zelinski, A. C., Wald, L. L., Setsompop, K., Goyal, V. K., Adalsteinsson, E. 2008; 27 (9): 1213–29

    Abstract

    We introduce a novel algorithm for the design of fast slice-selective spatially-tailored magnetic resonance imaging (MRI) excitation pulses. This method, based on sparse approximation theory, uses a second-order cone optimization to place and modulate a small number of slice-selective sinc-like radio-frequency (RF) pulse segments ("spokes") in excitation k-space, enforcing sparsity on the number of spokes allowed while simultaneously encouraging those that remain to be placed and modulated in a way that best forms a user-defined in-plane target magnetization. Pulses are designed to mitigate B(1) inhomogeneity in a water phantom at 7 T and to produce highly-structured excitations in an oil phantom on an eight-channel parallel excitation system at 3 T. In each experiment, pulses generated by the sparsity-enforced method outperform those created via conventional Fourier-based techniques, e.g., when attempting to produce a uniform magnetization in the presence of severe B(1) inhomogeneity, a 5.7-ms 15-spoke pulse generated by the sparsity-enforced method produces an excitation with 1.28 times lower root mean square error than conventionally-designed 15-spoke pulses. To achieve this same level of uniformity, the conventional methods need to use 29-spoke pulses that are 7.8 ms long.

    View details for DOI 10.1109/TMI.2008.920605

    View details for Web of Science ID 000258949500004

    View details for PubMedID 18779063

    View details for PubMedCentralID PMC2666002

  • Fast slice-selective radio-frequency excitation pulses for mitigating B-1(+) inhomogeneity in the human brain at 7 tesla MAGNETIC RESONANCE IN MEDICINE Zelinski, A. C., Wald, L. L., Setsompop, K., Alagappan, V., Gagoski, B. A., Goyal, V. K., Adalsteinsson, E. 2008; 59 (6): 1355–64

    Abstract

    A novel radio-frequency (RF) pulse design algorithm is presented that generates fast slice-selective excitation pulses that mitigate B+1 inhomogeneity present in the human brain at high field. The method is provided an estimate of the B+1 field in an axial slice of the brain and then optimizes the placement of sinc-like "spokes" in kz via an L1-norm penalty on candidate (kx, ky) locations; an RF pulse and gradients are then designed based on these weighted points. Mitigation pulses are designed and demonstrated at 7T in a head-shaped water phantom and the brain; in each case, the pulses mitigate a significantly nonuniform transmit profile and produce nearly uniform flip angles across the field of excitation (FOX). The main contribution of this work, the sparsity-enforced spoke placement and pulse design algorithm, is derived for conventional single-channel excitation systems and applied in the brain at 7T, but readily extends to lower field systems, nonbrain applications, and multichannel parallel excitation arrays.

    View details for DOI 10.1002/mrm.21585

    View details for Web of Science ID 000256266400018

    View details for PubMedID 18506800

    View details for PubMedCentralID PMC2723802

  • Comparison of three algorithms for solving linearized systems of parallel excitation RF waveform design equations: Experiments on an eight-channel system at 3 tesla CONCEPTS IN MAGNETIC RESONANCE PART B-MAGNETIC RESONANCE ENGINEERING Zelinski, A. C., Wald, L. L., Setsompop, K., Alagappan, V., Gagoski, B. A., Goyal, V. K., Hebrank, F., Fontius, U., Schmitt, F., Adalsteinsson, E. 2007; 31B (3): 176–90
  • Degenerate mode band-pass birdcage coil for accelerated parallel excitation MAGNETIC RESONANCE IN MEDICINE Alagappan, V., Nistler, J., Adalsteinsson, E., Setsompop, K., Fontius, U., Zelinski, A., Vester, M., Wiggins, G. C., Hebrank, F., Renz, W., Schmitt, F., Wald, L. L. 2007; 57 (6): 1148–58

    Abstract

    An eight-rung, 3T degenerate birdcage coil (DBC) was constructed and evaluated for accelerated parallel excitation of the head with eight independent excitation channels. Two mode configurations were tested. In the first, each of the eight loops formed by the birdcage was individually excited, producing an excitation pattern similar to a loop coil array. In the second configuration a Butler matrix transformed this "loop coil" basis set into a basis set representing the orthogonal modes of the birdcage coil. In this case the rung currents vary sinusoidally around the coil and only four of the eight modes have significant excitation capability (the other four produce anticircularly polarized (ACP) fields). The lowest useful mode produces the familiar uniform B(1) field pattern, and the higher-order modes produce center magnitude nulls and azimuthal phase variations. The measured magnitude and phase excitation profiles of the individual modes were used to generate one-, four-, six-, and eightfold-accelerated spatially tailored RF excitations with 2D and 3D k-space excitation trajectories. Transmit accelerations of up to six-fold were possible with acceptable levels of spatial artifact. The orthogonal basis set provided by the Butler matrix was found to be advantageous when an orthogonal subset of these modes was used to mitigate B(1) transmit inhomogeneities using parallel excitation.

    View details for DOI 10.1002/mrm.21247

    View details for Web of Science ID 000246979900019

    View details for PubMedID 17534905

  • Parallel RF transmission with eight channels at 3 Tesla MAGNETIC RESONANCE IN MEDICINE Setsompop, K., Wald, L. L., Alagappan, V., Gagoski, B., Hebrank, F., Fontius, U., Schmitt, F., Adalsteinsson, E. 2006; 56 (5): 1163–71

    Abstract

    Spatially selective RF waveforms were designed and demonstrated for parallel excitation with a dedicated eight-coil transmit array on a modified 3T human MRI scanner. Measured excitation profiles of individual coils in the array were used in a low-flip-angle pulse design to achieve desired spatial target profiles with two- (2D) and three-dimensional (3D) k-space excitation with simultaneous transmission of RF on eight channels. The 2D pulse excited a high-resolution spatial pattern in-plane, while the 3D trajectory produced high-quality slice selection with a uniform in-plane excitation despite the highly nonuniform individual spatial profiles of the coil array. The multichannel parallel RF excitation was used to accelerate the 2D excitation by factors of 2-8, and experimental results were in excellent agreement with simulations based on the measured coil maps. Parallel RF transmission may become critical for robust and routine human studies at very high field strengths where B(1) inhomogeneity is commonly severe.

    View details for DOI 10.1002/mrm.21042

    View details for Web of Science ID 000241761900030

    View details for PubMedID 17036289