Dr. Erpeng Dai's research interest is focused on advanced neuro MRI technique development and application. Previously, he has developed a series of novel techniques for high-resolution and fast diffusion MRI (dMRI). Currently, he is mainly working on distortion-free dMRI, advanced diffusion encoding, and brain microstructure and connectivity studies.
Bachelor of Engineering, Huazhong University Of Science & Technology (2013)
Doctor of Philosophy, Tsinghua University (2018)
Jennifer McNab, Postdoctoral Faculty Sponsor
Frequency-dependent diffusion kurtosis imaging in the human brain using an oscillating gradient spin echo sequence and a high-performance head-only gradient.
Measuring the time/frequency dependence of diffusion MRI is a promising approach to distinguishing between the effects of different tissue microenvironments, such as membrane restriction, tissue heterogeneity, and compartmental water exchange. In this study, we measure the frequency dependence of diffusivity (D) and kurtosis (K) with the oscillating gradient diffusion encoding waveforms and diffusion kurtosis imaging (DKI) model in human brains in a high-performance, head-only MAGNUS gradient system, with a combination of b-values, oscillating frequencies (f), and echo time that has not been achieved in human studies before. Frequency dependence of diffusivity and kurtosis are observed in both global and regional white matter (WM) and gray matter (GM) regions and characterized with a power-law model ∼Λ*fθ. The frequency dependences of diffusivity and kurtosis (including changes between fmin and fmax, Λ, and θ) vary over different WM and GM regions, indicating potential microstructure changes over different regions. A trend of decreasing kurtosis over frequency in the short-time limit is successfully captured for in vivo human brains. The effects of gradient nonlinearity (GNL) on frequency-dependent diffusivity and kurtosis measurements are investigated and corrected. Our results show that the GNL has prominent scaling effects on the measured diffusivity values (3.5∼5.5% difference in the global WM and 6∼8% difference in the global cortex) and subsequently affects the corresponding power-law parameters (Λ, θ) while having a marginal influence on the measured kurtosis values (<0.05% difference) and power-law parameters (Λ, θ). This study expands previous OGSE studies and further demonstrates the translatability of frequency-dependent diffusivity and kurtosis measurements to human brains, which may provide new opportunities to probe human brain microstructure in health and disease.
View details for DOI 10.1016/j.neuroimage.2023.120328
View details for PubMedID 37586445
Multi-band multi-shot diffusion MRI reconstruction with joint usage of structured low-rank constraints and explicit phase mapping.
Magnetic resonance in medicine
To develop a joint reconstruction method for multi-band multi-shot diffusion MRI.Multi-band multi-shot EPI acquisition is an effective approach for high-resolution diffusion MRI, but requires specific algorithms to correct the inter-shot phase variations. The phase correction can be done by first estimating the explicit phase map and then feeding it into the k-space signal formulation model. Alternatively, the phase information can be used indirectly as structured low-rank constraints in k-space. The 2 methods differ in reconstruction accuracy and efficiency. We aim to combine the 2 different approaches for improved image quality and reconstruction efficiency simultaneously, termed "joint usage of structured low-rank constraints and explicit phase mapping" (JULEP). The proposed JULEP reconstruction is tested on both single-band and multi-band, multi-shot diffusion data, with different resolutions and b values. The results of JULEP are compared with conventional methods with explicit phase mapping (i.e., multiplexed sensitivity-encoding [MUSE]) and structured low-rank constraints (i.e., MUSSELS), and another joint reconstruction method (i.e., network estimated artifacts for tempered reconstruction [NEATR]).JULEP improves the quality of the navigator and subsequently facilitates the reconstruction of final diffusion images. Compared with all 3 other methods (MUSE, MUSSELS, and NEATR), JULEP mitigates residual structural bias and improves temporal SNRs in the final diffusion image, particularly at high multi-band factors. Compared with MUSSELS, JULEP also improves computational efficiency.The proposed JULEP method significantly improves the image quality and reconstruction efficiency of multi-band multi-shot diffusion MRI, which can promote a broader application of high-resolution diffusion MRI.
View details for DOI 10.1002/mrm.29422
View details for PubMedID 36063492
Distortion-Free Diffusion Imaging Using Self-Navigated Cartesian Echo-Planar Time Resolved Acquisition and Joint Magnitude and Phase Constrained Reconstruction
IEEE TRANSACTIONS ON MEDICAL IMAGING
2022; 41 (1): 63-74
Echo-planar time resolved imaging (EPTI) is an effective approach for acquiring high-quality distortion-free images with a multi-shot EPI (ms-EPI) readout. As with traditional ms-EPI acquisitions, inter-shot phase variations present a main challenge when incorporating EPTI into a diffusion-prepared pulse sequence. The aim of this study is to develop a self-navigated Cartesian EPTI-based (scEPTI) acquisition together with a magnitude and phase constrained reconstruction for distortion-free diffusion imaging. A self-navigated Cartesian EPTI-based diffusion-prepared pulse sequence is designed. The different phase components in EPTI diffusion signal are analyzed and an approach to synthesize a fully phase-matched navigator for the inter-shot phase correction is demonstrated. Lastly, EPTI contains richer magnitude and phase information than conventional ms-EPI, such as the magnitude and phase correlations along the temporal dimension. The potential of these magnitude and phase correlations to enhance the reconstruction is explored. The reconstruction results with and without phase matching and with and without phase or magnitude constraints are compared. Compared with reconstruction without phase matching, the proposed phase matching method can improve the accuracy of inter-shot phase correction and reduce signal corruption in the final diffusion images. Magnitude constraints further improve image quality by suppressing the background noise and thereby increasing SNR, while phase constraints can mitigate possible image blurring from adding magnitude constraints. The high-quality distortion-free diffusion images and simultaneous diffusion-relaxometry imaging capacity provided by the proposed EPTI design represent a highly valuable tool for both clinical and neuroscientific assessments of tissue microstructure.
View details for DOI 10.1109/TMI.2021.3104291
View details for Web of Science ID 000736740900007
View details for PubMedID 34383645
High-Resolution Whole-Brain Diffusion MRI at 3T Using Simultaneous Multi-slab (SMSlab) Acquisition.
High-resolution diffusion MRI (dMRI) is a crucial tool in neuroscience studies to detect fine fiber structure, depict complex fiber architecture and analyze cortical anisotropy. However, high-resolution dMRI is limited by its intrinsically low SNR due to diffusion attenuation. A series of techniques have been proposed to improve the SNR performance, but most of them are at the cost of long scan time, which in turn sacrifice the SNR efficiency, especially for large FOV imaging, such as whole-brain imaging. Recently, a combination of 3D multi-slab acquisition and simultaneous multi-slice (SMS) excitation, namely simultaneous multi-slab (SMSlab), has been demonstrated to have potential for high-resolution diffusion imaging with high SNR and SNR efficiency. In our previous work, we have proposed a 3D Fourier encoding and reconstruction framework for SMSlab acquisition. In this study, we extend this 3D k-space framework to diffusion imaging, by developing a novel navigator acquisition strategy and exploring a k-space-based phase correction method. In vivo brain data are acquired using the proposed SMSlab method and compared with a series of different acquisitions, including the traditional 3D multi-slab, 2D SMS and 2D single-shot EPI (ss-EPI) acquisitions. The results demonstrate that SMSlab has a better SNR performance compared with 3D multi-slab and 2D SMS. The detection capacity of fine fiber structures is improved using SMSlab, compared with the low-resolution diffusion imaging using conventional 2D ss-EPI.
View details for DOI 10.1016/j.neuroimage.2021.118099
View details for PubMedID 33940144
Reconstruction for 7T high-resolution whole-brain diffusion MRI using two-stage N/2 ghost correction and L1-SPIRiT without single-band reference.
Magnetic resonance in medicine
PURPOSE: To combine a new two-stage N/2 ghost correction and an adapted L1-SPIRiT method for reconstruction of 7T highly accelerated whole-brain diffusion MRI (dMRI) using only autocalibration scans (ACS) without the need of additional single-band reference (SBref) scans.METHODS: The proposed ghost correction consisted of a 3-line reference approach in stage 1 and the reference-free entropy method in stage 2. The adapted L1-SPIRiT method was formulated within the 3D k-space framework. Its efficacy was examined by acquiring two dMRI data sets at 1.05-mm isotropic resolutions with a total acceleration of 6 or 9 (i.e., 2-fold or 3-fold slice and 3-fold in-plane acceleration). Diffusion analysis was performed to derive DTI metrics and estimate fiber orientation distribution functions (fODFs). The results were compared with those of 3D k-space GRAPPA using only ACS, all in reference to 3D k-space GRAPPA using both ACS and SBref (serving as a reference).RESULTS: The proposed ghost correction eliminated artifacts more robustly than conventional approaches. Our adapted L1-SPIRiT method outperformed 3D k-space GRAPPA when using only ACS, improving image quality to what was achievable with 3D k-space GRAPPA using both ACS and SBref scans. The improvement in image quality further resulted in an improvement in estimation performances for DTI and fODFs.CONCLUSION: The combination of our new ghost correction and adapted L1-SPIRiT method can reliably reconstruct 7T highly accelerated whole-brain dMRI without the need of SBref scans, increasing acquisition efficiency and reducing motion sensitivity.
View details for DOI 10.1002/mrm.29573
View details for PubMedID 36594439
SAturation-recovery and Variable-flip-Angle (SAVA) based three-dimensional free-breathing cardiovascular magnetic resonance T1 mapping at 3T.
NMR in biomedicine
PURPOSE: To develop and validate a 3D free-breathing cardiac T1 mapping sequence using SAturation recovery and Variable flip Angles (SAVA).METHODS: SAVA sequentially acquires multiple ECG-triggered volumes using a multi-shot spoiled gradient-echo sequence. The first volume samples the equilibrium signal of the longitudinal magnetization, where a flip angle of 2° is used to reduce the time for the magnetization return to its equilibrium. The succeeding three volumes are saturation prepared with variable delays, and acquired using a 15° flip angle to maintain SNR. A diaphragmatic navigator is used to compensate the respiratory motion. T1 is calculated using a saturation-recovery model which accounts for flip angle. We validated SAVA by simulations, phantom, and human subject experiments at 3T. SAVA was compared to modified Look-Locker inversion recovery (MOLLI) and saturation recovery single-shot acquisition (SASHA) in vivo.RESULTS: In phantoms, T1 by SAVA had good agreement with the reference (R2 =0.99). In vivo 3D T1 mapping by SAVA could achieve an imaging resolution of 1.25*1.25*8 mm3 . Both global and septal T1 values by SAVA (1347±37 ms and 1332±42 ms) were in-between those by SASHA (1612±63 ms and 1618±51 ms) and MOLLI (1143±59 ms and 1188±65 ms). According to the standard deviation (SD) and coefficient of variation (CV), T1 precision measured by SAVA (SD: 99±14 ms and 60±8 ms; CV: 7.4±0.9% and 4.5±0.6%) was comparable to MOLLI (SD: 99±25 ms and 46±12 ms; CV: 8.8±2.5% and 3.9±1.1%) and superior to SASHA (SD: 222±89 ms and 132±33 ms; CV: 13.8±5.5% and 8.1±2.0%).CONCLUSIONS: The proposed free-breathing SAVA sequence enables more efficient 3D whole-heart T1 estimation with good accuracy and precision.
View details for DOI 10.1002/nbm.4755
View details for PubMedID 35485432
Optimized multi-axis spiral projection MR fingerprinting with subspace reconstruction for rapid whole-brain high-isotropic-resolution quantitative imaging.
Magnetic resonance in medicine
PURPOSE: To improve image quality and accelerate the acquisition of 3D MR fingerprinting (MRF).METHODS: Building on the multi-axis spiral-projection MRF technique, a subspace reconstruction with locally low-rank constraint and a modified spiral-projection spatiotemporal encoding scheme called tiny golden-angle shuffling were implemented for rapid whole-brain high-resolution quantitative mapping. Reconstruction parameters such as the locally low-rank regularization parameter and the subspace rank were tuned using retrospective in vivo data and simulated examinations. B0 inhomogeneity correction using multifrequency interpolation was incorporated into the subspace reconstruction to further improve the image quality by mitigating blurring caused by off-resonance effect.RESULTS: The proposed MRF acquisition and reconstruction framework yields high-quality 1-mm isotropic whole-brain quantitative maps in 2min at better quality compared with 6-min acquisitions of prior approaches. The proposed method was validated to not induce bias in T1 and T2 mapping. High-quality whole-brain MRF data were also obtained at 0.66-mm isotropic resolution in 4min using the proposed technique, where the increased resolution was shown to improve visualization of subtle brain structures.CONCLUSIONS: The proposed tiny golden-angle shuffling, MRF with optimized spiral-projection trajectory and subspace reconstruction enables high-resolution quantitative mapping in ultrafast acquisition time.
View details for DOI 10.1002/mrm.29194
View details for PubMedID 35199877
Slab boundary artifact correction in multislab imaging using convolutional-neural-network-enabled inversion for slab profile encoding.
Magnetic resonance in medicine
PURPOSE: This study aims to propose a novel algorithm for slab boundary artifact correction in both single-band multislab imaging and simultaneous multislab (SMSlab) imaging.THEORY AND METHODS: In image domain, the formation of slab boundary artifacts can be regarded as modulating the artifact-free images using the slab profiles and introducing aliasing along the slice direction. Slab boundary artifact correction is the inverse problem of this process. An iterative algorithm based on convolutional neural networks (CNNs) is proposed to solve the problem, termed CNN-enabled inversion for slab profile encoding (CPEN). Diffusion-weighted SMSlab images and reference images without slab boundary artifacts were acquired in 7 healthy subjects for training. Images of 5 healthy subjects were acquired for testing, including single-band multislab and SMSlab images with 1.3-mm or 1-mm isotropic resolution. CNN-enabled inversion for slab profile encoding was compared with a previously reported method (i.e., nonlinear inversion for slab profile encoding [NPEN]).RESULTS: CNN-enabled inversion for slab profile encoding reduces the slab boundary artifacts in both single-band multislab and SMSlab images. It also suppresses the slab boundary artifacts in the diffusion metric maps. Compared with NPEN, CPEN shows fewer residual artifacts in different acquisition protocols and more significant improvements in quantitative assessment, and it also accelerates the computation by more than 35 times.CONCLUSION: CNN-enabled inversion for slab profile encoding can reduce the slab boundary artifacts in multislab acquisitions. It shows better slab boundary artifact correction capacity, higher robustness, and computation efficiency when compared with NPEN. It has the potential to improve the accuracy of multislab acquisitions in high-resolution DWI and functional MRI.
View details for DOI 10.1002/mrm.29047
View details for PubMedID 34655095
Improving distortion correction for isotropic high-resolution 3D diffusion MRI by optimizing Jacobian modulation.
Magnetic resonance in medicine
PURPOSE: To improve distortion correction for isotropic high-resolution whole-brain 3D diffusion MRI when in a time-saving acquisition scenario.THEORY AND METHODS: Data were acquired using simultaneous multi-slab (SMSlab) acquisitions, with a b = 0 image pair encoded by reversed polarity gradients (RPG) for phase encoding (PE) and diffusion weighted images encoded by a single PE direction. Eddy current-induced distortions were corrected first. During the following susceptibility distortion correction, image deformation was first corrected by the field map estimated from the b = 0 image pair. Intensity variation was subsequently corrected by Jacobian modulation. Two Jacobian modulation methods were compared. They calculated the Jacobian modulation map from the field map, or from the deformation corrected b = 0 image pair, termed as JField and JRPG , respectively. A modified version of the JRPG method, with proper smoothing, was further proposed for improved correction performance, termed as JRPG-smooth .RESULTS: Compared to JField modulation, less remaining distortions are observed when using the JRPG and JRPG-smooth methods, especially in areas with large B0 field inhomogeneity. The original JRPG method causes signal-to-noise ratio (SNR) deficiency problem, which manifests as degraded SNR of the diffusion weighted images, while the JRPG-smooth method maintains the original image SNR. Less estimation errors of diffusion metrics are observed when using the JRPG-smooth method.CONCLUSION: This study improves the distortion correction for isotropic high-resolution whole-brain 3D diffusion MRI by optimizing Jacobian modulation. The optimized method outperforms the conventional JField method regarding intensity variation correction and accuracy of diffusion metrics estimation, and outperforms the original JRPG method regarding SNR performance.
View details for DOI 10.1002/mrm.28884
View details for PubMedID 34121222
A 3D k-space Fourier encoding and reconstruction framework for simultaneous multi-slab acquisition
MAGNETIC RESONANCE IN MEDICINE
2019; 82 (3): 1012-1024
To propose a novel 3D k-space Fourier encoding and reconstruction framework for simultaneous multi-slab (SMSlab) acquisition and demonstrate its efficacy in high-resolution imaging.First, it is illustrated in theory how the inter-slab gap interferes with the formation of the SMSlab 3D k-space. Then, joint RF and gradient encoding are applied to remove the inter-slab gap interference and form a SMSlab 3D k-space. In vivo experiments are performed to validate the proposed theory. Acceleration in the proposed SMSlab 3D k-space is also evaluated.High-resolution (1.0 mm isotropic) images can be reconstructed using the proposed SMSlab 3D framework. Controlled aliasing in parallel imaging sampling and 2D GRAPPA reconstruction can also be applied in the SMSlab 3D k-space. Compared with conventional multi-slab acquisition, SMSlab exhibits better SNR maintainability (such as lower g-factors), especially at high acceleration factors.It is demonstrated that the joint application of RF and gradient encoding enables SMSlab within a 3D Fourier encoding framework. Images with high isotropic resolution can be reconstructed, and further acceleration is also applicable. The proposed SMSlab 3D k-space can be valuable for both high-resolution and high-efficiency diffusion and functional MRI.
View details for DOI 10.1002/mrm.27793
View details for Web of Science ID 000485077600013
View details for PubMedID 31045283
View details for PubMedCentralID PMC6831486
Distortion correction for high-resolution single-shot EPI DTI using a modified field-mapping method
NMR IN BIOMEDICINE
2019; 32 (9): e4124
The widely used single-shot EPI (SS-EPI) diffusion tensor imaging (DTI) suffers from strong image distortion due to B0 inhomogeneity, especially for high-resolution imaging. Traditional methods such as the field-mapping method and the top-up method have various deficiencies in high-resolution SS-EPI DTI distortion correction. This study aims to propose a robust distortion correction approach, which combines the advantages of traditional methods and overcomes their deficiencies, for high-resolution SS-EPI DTI.The proposed correction method is based on the echo planar spectroscopic imaging field-mapping followed by an intensity correction procedure. To evaluate the efficacy of distortion correction, the proposed method was compared with the conventional field-mapping method and the top-up method, using a newly developed quantitative evaluation framework. The correction results were also compared with multi-shot EPI DTI to investigate whether the proposed method can provide high-resolution SS-EPI DTI with high geometric fidelity and high time efficiency.The results show that accurate field-mapping and intensity correction are critical to distortion correction in high-resolution SS-EPI DTI. The proposed method can provide more precise field maps and better correction results than the other two methods (p < 0.0001), and the corrected images show higher geometric fidelity than those from MS-EPI DTI.An effective method is proposed to reduce image distortion in high-resolution SS-EPI DTI. It is practical to achieve high-resolution DTI with high time efficiency and high structure accuracy using this method.
View details for DOI 10.1002/nbm.4124
View details for Web of Science ID 000474090600001
View details for PubMedID 31271491
The effects of navigator distortion and noise level on interleaved EPI DWI reconstruction: a comparison between image- and k-space-based method
MAGNETIC RESONANCE IN MEDICINE
2018; 80 (5): 2024-2032
To study the effects of 2D navigator distortion and noise level on interleaved EPI (iEPI) DWI reconstruction, using either the image- or k-space-based method.The 2D navigator acquisition was adjusted by reducing its echo spacing in the readout direction and undersampling in the phase encoding direction. A POCS-based reconstruction using image-space sampling function (IRIS) algorithm (POCSIRIS) was developed to reduce the impact of navigator distortion. POCSIRIS was then compared with the original IRIS algorithm and a SPIRiT-based k-space algorithm, under different navigator distortion and noise levels.Reducing the navigator distortion can improve the reconstruction of iEPI DWI. The proposed POCSIRIS and SPIRiT-based algorithms are more tolerable to different navigator distortion levels, compared to the original IRIS algorithm. SPIRiT may be hindered by low SNR of the navigator.Multi-shot iEPI DWI reconstruction can be improved by reducing the 2D navigator distortion. Different reconstruction methods show variable sensitivity to navigator distortion or noise levels. Furthermore, the findings can be valuable in applications such as simultaneous multi-slice accelerated iEPI DWI and multi-slab diffusion imaging.
View details for DOI 10.1002/mrm.27190
View details for Web of Science ID 000448872700023
View details for PubMedID 29569741
eIRIS: Eigen-analysis approach for improved spine multi-shot diffusion MRI
MAGNETIC RESONANCE IMAGING
2018; 50: 134-140
Image reconstruction using image-space sampling function (IRIS) corrects motion-induced inter-shot phase variations using phase maps from navigator-echo for multi-shot diffusion MRI. However, the bandwidth along the phase-encoding direction of navigator-echo is usually lower than that of image-echo, and thus their geometric distortions may be different. This geometric mismatch is corrected in IRIS by using the B0 map from an additional scan. In this paper, we present an enhanced IRIS (eIRIS) method that remove the requirement of B0 map. eIRIS treats shots as virtual coils, and then uses an eigen-analysis-based approach, which is insensitive to geometric mismatch, to estimates coil sensitivity maps containing the inter-shot phase variations. The final image is reconstructed under the framework of SENSE. Simulation, phantom, and cervical spine experiments were performed to evaluate the eIRIS method. The images generated by IRIS without B0 correction contain severe artifacts. eIRIS obtains results without noticeable artifacts and comparable to those of IRIS with B0 correction and GRAPPA with a compact kernel (GRAPPA-CK) method. eIRIS slightly outperforms GRAPPA-CK in the terms of normalized root-mean-square error and signal-to-noise ratio. eIRIS has the potential to obtain high-quality diffusion-weighted images and will benefit the research and clinical diagnosis of spinal cord.
View details for DOI 10.1016/j.mri.2018.04.002
View details for Web of Science ID 000434750700017
View details for PubMedID 29626517
Model-based reconstruction for simultaneous multislice and parallel imaging accelerated multishot diffusion tensor imaging
2018; 45 (7): 3196-3204
Multishot interleaved echo-planar imaging (iEPI) can achieve higher image resolution than single-shot EPI for diffusion tensor imaging (DTI), but its application is limited by the prolonged acquisition time. To reduce the acquisition time, a novel model-based reconstruction for simultaneous multislice (SMS) and parallel imaging (PI) accelerated iEPI DTI is proposed.DTI datasets acquired by iEPI with SMS and PI acceleration can be regarded as 3D k-space data, which is undersampled along both the slice and phase encoding directions. Instead of reconstruction of individual diffusion-weighted image, diffusion tensors are directly estimated by the joint reconstruction of undersampled 3D k-space from all diffusion-encoding directions using a model-based formulation to exploit the correlation across different directions. DTI simulation and in vivo acquisition were used to demonstrate the superior performance of the proposed method.The proposed method reduced the estimation errors and artifacts than traditional parallel imaging reconstruction in DTI simulation. In the in vivo DTI experiment, the acquisition time of 4-shot iEPI was reduced from 11 min 7 s to 3 min 53 s with an acceleration factor of 4, and the image quality and precision of quantitative parameters were comparable with the fully sampled acquisition.The proposed model-based reconstruction for iEPI DTI with SMS and PI can achieve fourfold acceleration while maintaining high accuracy for tensor measurements.
View details for DOI 10.1002/mp.12974
View details for Web of Science ID 000438211400032
View details for PubMedID 29758101
Motion-corrected k-space reconstruction for interleaved EPI diffusion imaging
MAGNETIC RESONANCE IN MEDICINE
2018; 79 (4): 1992-2002
To develop a new approach to correct for physiological and macroscopic motion in multishot, interleaved echo-planar diffusion imaging.This work built on the previous SPIRiT (iterative self-consistent parallel imaging reconstruction) based reconstruction for physiological motion correction in multishot diffusion-weighted imaging to account for macroscopic motion. In-plane rotation, translation correction, data rejection, and weighted combination are integrated in SPIRiT-based reconstruction to correct for ghosting artifacts, blurring, altered b-matrix, and residual artifacts caused by motion.Numerical simulations (one data set was obtained from the Human Connectome Project) and in vivo experiments with deliberate bulk motion were performed to demonstrate the effectiveness of the proposed method. Diffusion images and quantitative tensor parameters were calculated to evaluate the correction performance.The proposed method provided images with reduced artifacts and diffusion tensors with improved accuracy in both simulations and in vivo experiments. For in vivo experiments with deliberate motion, the percentage error of fractional anisotropy in the genu of the corpus callosum was significantly reduced from 17.01 ± 12.64 to 5.73 ± 3.77 through motion correction.The proposed method can effectively correct for physiological and macroscopic motion artifacts in multishot interleaved echo-planar imaging, generate high resolution diffusion images, and improve the accuracy of tensor calculation. Magn Reson Med 79:1992-2002, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
View details for DOI 10.1002/mrm.26861
View details for Web of Science ID 000425026800016
View details for PubMedID 28771867
A comparison of readout segmented EPI and interleaved EPI in high resolution diffusion weighted imaging
MAGNETIC RESONANCE IMAGING
2018; 47: 39-47
To provide a comprehensive understanding of multi-shot EPI diffusion imaging methods by comparing Readout segmented EPI (RS-EPI) and interleaved EPI (iEPI).RS-EPI and iEPI were compared on the same 3T scanner. A 2D navigator was used for both RS-EPI and iEPI for phase correction. Signal to noise ratio (SNR), fractional anisotropy (FA) and distortion level were compared using phantom data. Distortion reduction capability and scan efficiency were compared with different protocols with simulations. In addition, distortion reduction capability and diffusion tensor imaging performance were compared using in vivo data.Our phantom data showed that the mean SNRs were 50.5, 86.6 and 45.4 for RS-EPI using GRAPPA=3, fully sampled iEPI and iEPI using GRAPPA=2 respectively. The mean FA values were 0.08, 0.05 and 0.09 for RS-EPI using GRAPPA=3, fully sampled iEPI and iEPI using GRAPPA=2 respectively. The distortion levels were 1.34mm, 1.29mm and 0.61mm for RS-EPI using GRAPPA=3, fully sampled iEPI and iEPI using GRAPPA=2 respectively. The effective echo spacing could be reduced by increasing the number of shots for both methods but more prominent for iEPI. The scan time was approximately proportional to the number of shots for both methods and RS-EPI showed a shorter scan time. Our in vivo data for distortion comparison showed consistent results with the effective echo spacing study. The mean difference of the FA and MD values between the high resolution sequences and SS-EPI was all within 7%.For high resolution diffusion imaging, iEPI has more potential in distortion reduction than RS-EPI when increasing the number of shots. RS-EPI can achieve a reasonable SNR with a shorter scan time than iEPI. RS-EPI and iEPI have similar performance in FA and MD quantifications as well as showing structure details when using eleven shots for in vivo diffusion tensor imaging.
View details for DOI 10.1016/j.mri.2017.11.011
View details for Web of Science ID 000428004500006
View details for PubMedID 29175470
Interleaved EPI diffusion imaging using SPIRiT-based reconstruction with virtual coil compression
MAGNETIC RESONANCE IN MEDICINE
2018; 79 (3): 1525-1531
To develop a novel diffusion imaging reconstruction framework based on iterative self-consistent parallel imaging reconstruction (SPIRiT) for multishot interleaved echo planar imaging (iEPI), with computation acceleration by virtual coil compression.As a general approach for autocalibrating parallel imaging, SPIRiT improves the performance of traditional generalized autocalibrating partially parallel acquisitions (GRAPPA) methods in that the formulation with self-consistency is better conditioned, suggesting SPIRiT to be a better candidate in k-space-based reconstruction. In this study, a general SPIRiT framework is adopted to incorporate both coil sensitivity and phase variation information as virtual coils and then is applied to 2D navigated iEPI diffusion imaging. To reduce the reconstruction time when using a large number of coils and shots, a novel shot-coil compression method is proposed for computation acceleration in Cartesian sampling. Simulations and in vivo experiments were conducted to evaluate the performance of the proposed method.Compared with the conventional coil compression, the shot-coil compression achieved higher compression rates with reduced errors. The simulation and in vivo experiments demonstrate that the SPIRiT-based reconstruction outperformed the existing method, realigned GRAPPA, and provided superior images with reduced artifacts.The SPIRiT-based reconstruction with virtual coil compression is a reliable method for high-resolution iEPI diffusion imaging. Magn Reson Med 79:1525-1531, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
View details for DOI 10.1002/mrm.26768
View details for Web of Science ID 000427184700029
View details for PubMedID 28608411
Simultaneous Multislice Accelerated Interleaved EPI DWI Using Generalized Blipped-CAIPI Acquisition and 3D K-Space Reconstruction
MAGNETIC RESONANCE IN MEDICINE
2017; 77 (4): 1593-1605
Simultaneous multislice (SMS) has been proved to be powerful for accelerating single-shot echo-planar imaging (ssh-EPI) based diffusion-weighted imaging (DWI), but there are some obstacles for applying SMS to interleaved echo-planar imaging (iEPI) DWI. The primary challenge is to effectively combine slice unfolding for SMS and intershot phase correction for multishot DWI. In this study, a novel acquisition and reconstruction method for SMS-accelerated high-resolution iEPI DWI is proposed.The traditional blipped-controlled aliasing in parallel imaging (blipped-CAIPI) for ssh-EPI is generalized for iEPI acquisitions. An SMS three-dimensional (3D) navigator acquisition is designed to record the intershot phase variations. Then, slice unfolding and intershot phase correction are performed simultaneously in an SMS 3D k-space. The performance of the proposed method is demonstrated in both four-shot and eight-shot iEPI DWI and compared with ssh-EPI and unaccelerated iEPI DWI.The proposed method successfully unfolded the simultaneously excited slices and effectively suppressed artifacts from intershot phase variations. The SMS-accelerated iEPI improved the imaging efficiency, while preserving comparable image quality as unaccelerated iEPI DWI.The proposed acquisition and reconstruction is an effective method for accelerating multishot high-resolution DWI, which may be valuable for both neuroscience research and clinical diagnosis. Magn Reson Med 77:1593-1605, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
View details for DOI 10.1002/mrm.26249
View details for Web of Science ID 000398085200022
View details for PubMedID 27090059
Technical Note: Measurement of common carotid artery lumen dynamics using black-blood MR cine imaging
2017; 44 (3): 1105-1112
To demonstrate the feasibility of measuring the common carotid artery (CCA) lumen dynamics using a black-blood cine (BB-cine) imaging method.Motion-sensitized driven-equilibrium (MSDE) prepared spoiled gradient sequence was used for the BB-cine imaging. CCAs of eleven healthy volunteers were studied using this method. Lumen dynamics, including lumen area evolution waveforms and distension values, were measured and evaluated by comparing this method with bright-blood cine (BrB-cine) imaging.Compared with the BrB-cine images, flow artifacts were effectively suppressed in the BB-cine images. BrB-cine images generally show larger lumen areas than BB-cine images. The lumen area waveforms and distension measurements from BB-cine imaging showed smaller variances among different subjects than BrB-cine imaging.The proposed BB-cine imaging technique can suppress the flow artifacts effectively and reduce the partial volume effects from the vessel wall. This might allow more accurate lumen dynamics measurements than traditional BrB-cine imaging, which may further be valuable for investigating biomechanical and functional properties of the cardiovascular system.
View details for DOI 10.1002/mp.12114
View details for Web of Science ID 000397870800027
View details for PubMedID 28100004
Improved multi-shot diffusion imaging using GRAPPA with a compact kernel
2016; 138: 88-99
In multi-shot diffusion imaging, motion induced phase variations are traditionally seen as a source of artifacts and corrected in the image domain using SENSE-based methods. This correction usually requires image echo and navigator echo to be geometrically matched. Recently, a k-space based method, realigned GRAPPA, has been proposed. It realigns data from different shots into the same k-space locations, and then synthesizes the missing data using GRAPPA algorithm. In this study, we refined the theory for GRAPPA-based method. In the revised theory, phase variations are treated as a kind of encoding, similar to coil sensitivity encoding. Based on this, the missing data can be synthesized using k-space correlations among different shots and channels. Then a compact kernel is used which only includes acquired data with significant contribution for the data synthesis, and can generate accurate weights without strict navigator size requirements. Simulation studies as well as brain and cervical spine experiments demonstrate that the proposed reconstruction method can effectively suppress artifacts caused by phase variations, and provide diffusion images with high resolution and low distortion. Compared with SENSE-based methods, the proposed method is less sensitive to mismatch between image echo and navigator echo.
View details for DOI 10.1016/j.neuroimage.2016.05.079
View details for Web of Science ID 000378519500007
View details for PubMedID 27261163