Honors & Awards


  • Junior Fellow of the Society, International Society of Magnetic Resonance in Medicine (ISMRM) (Jun 2023)

Stanford Advisors


All Publications


  • [Formula: see text] Field inhomogeneity correction for qDESS [Formula: see text] mapping: application to rapid bilateral knee imaging. Magma (New York, N.Y.) Barbieri, M., Watkins, L. E., Mazzoli, V., Desai, A. D., Rubin, E., Schmidt, A., Gold, G. E., Hargreaves, B. A., Chaudhari, A. S., Kogan, F. 2023

    Abstract

    [Formula: see text] mapping is a powerful tool for studying osteoarthritis (OA) changes and bilateral imaging may be useful in investigating the role of between-knee asymmetry in OA onset and progression. The quantitative double-echo in steady-state (qDESS) can provide fast simultaneous bilateral knee [Formula: see text] and high-resolution morphometry for cartilage and meniscus. The qDESS uses an analytical signal model to compute [Formula: see text] relaxometry maps, which require knowledge of the flip angle (FA). In the presence of [Formula: see text] inhomogeneities, inconsistencies between the nominal and actual FA can affect the accuracy of [Formula: see text] measurements. We propose a pixel-wise [Formula: see text] correction method for qDESS [Formula: see text] mapping exploiting an auxiliary [Formula: see text] map to compute the actual FA used in the model.The technique was validated in a phantom and in vivo with simultaneous bilateral knee imaging. [Formula: see text] measurements of femoral cartilage (FC) of both knees of six healthy participants were repeated longitudinally to investigate the association between [Formula: see text] variation and [Formula: see text].The results showed that applying the [Formula: see text] correction mitigated [Formula: see text] variations that were driven by [Formula: see text] inhomogeneities. Specifically, [Formula: see text] left-right symmetry increased following the [Formula: see text] correction ([Formula: see text] = 0.74 > [Formula: see text] = 0.69). Without the [Formula: see text] correction, [Formula: see text] values showed a linear dependence with [Formula: see text]. The linear coefficient decreased using the [Formula: see text] correction (from 24.3 ± 1.6 ms to 4.1 ± 1.8) and the correlation was not statistically significant after the application of the Bonferroni correction (p value > 0.01).The study showed that [Formula: see text] correction could mitigate variations driven by the sensitivity of the qDESS [Formula: see text] mapping method to [Formula: see text], therefore, increasing the sensitivity to detect real biological changes. The proposed method may improve the robustness of bilateral qDESS [Formula: see text] mapping, allowing for an accurate and more efficient evaluation of OA pathways and pathophysiology through longitudinal and cross-sectional studies.

    View details for DOI 10.1007/s10334-023-01094-y

    View details for PubMedID 37142852

    View details for PubMedCentralID 2268124

  • A method for measuring B0 field inhomogeneity using quantitative double-echo in steady-state. Magnetic resonance in medicine Barbieri, M., Chaudhari, A. S., Moran, C. J., Gold, G. E., Hargreaves, B. A., Kogan, F. 2022

    Abstract

    To develop and validate a method for B 0 $$ {B}_0 $$ mapping for knee imaging using the quantitative Double-Echo in Steady-State (qDESS) exploiting the phase difference ( Δ θ $$ \Delta \theta $$ ) between the two echoes acquired. Contrary to a two-gradient-echo (2-GRE) method, Δ θ $$ \Delta \theta $$ depends only on the first echo time.Bloch simulations were applied to investigate robustness to noise of the proposed methodology and all imaging studies were validated with phantoms and in vivo simultaneous bilateral knee acquisitions. Two phantoms and five healthy subjects were scanned using qDESS, water saturation shift referencing (WASSR), and multi-GRE sequences. Δ B 0 $$ \Delta {B}_0 $$ maps were calculated with the qDESS and the 2-GRE methods and compared against those obtained with WASSR. The comparison was quantitatively assessed exploiting pixel-wise difference maps, Bland-Altman (BA) analysis, and Lin's concordance coefficient ( ρ c $$ {\rho}_c $$ ). For in vivo subjects, the comparison was assessed in cartilage using average values in six subregions.The proposed method for measuring Δ B 0 $$ \Delta {B}_0 $$ inhomogeneities from a qDESS acquisition provided Δ B 0 $$ \Delta {B}_0 $$ maps that were in good agreement with those obtained using WASSR. Δ B 0 $$ \Delta {B}_0 $$ ρ c $$ {\rho}_c $$ values were ≥ $$ \ge $$ 0.98 and 0.90 in phantoms and in vivo, respectively. The agreement between qDESS and WASSR was comparable to that of a 2-GRE method.The proposed method may allow B0 correction for qDESS T 2 $$ {T}_2 $$ mapping using an inherently co-registered Δ B 0 $$ \Delta {B}_0 $$ map without requiring an additional B0 measurement sequence. More generally, the method may help shorten knee imaging protocols that require an auxiliary Δ B 0 $$ \Delta {B}_0 $$ map by exploiting a qDESS acquisition that also provides T 2 $$ {T}_2 $$ measurements and high-quality morphological imaging.

    View details for DOI 10.1002/mrm.29465

    View details for PubMedID 36161727

  • Circumventing the curse of dimensionality in magnetic resonance fingerprinting through a deep learning approach. NMR in biomedicine Barbieri, M., Lee, P. K., Brizi, L., Giampieri, E., Solera, F., Castellani, G., Hargreaves, B. A., Testa, C., Lodi, R., Remondini, D. 1800: e4670

    Abstract

    Magnetic resonance fingerprinting (MRF) is a rapidly developing approach for fast quantitative MRI. A typical drawback of dictionary-based MRF is an explosion of the dictionary size as a function of the number of reconstructed parameters, according to the "curse of dimensionality", which determines an explosion of resource requirements. Neural networks (NNs) have been proposed as a feasible alternative, but this approach is still in its infancy. In this work, we design a deep learning approach to MRF using a fully connected network (FCN). In the first part we investigate, by means of simulations, how the NN performance scales with the number of parameters to be retrieved in comparison with the standard dictionary approach. Four MRF sequences were considered: IR-FISP, bSSFP, IR-FISP-B1 , and IR-bSSFP-B1 , the latter two designed to be more specific for B 1 + parameter encoding. Estimation accuracy, memory usage, and computational time required to perform the estimation task were considered to compare the scalability capabilities of the dictionary-based and the NN approaches. In the second part we study optimal training procedures by including different data augmentation and preprocessing strategies during training to achieve better accuracy and robustness to noise and undersampling artifacts. The study is conducted using the IR-FISP MRF sequence exploiting both simulations and in vivo acquisitions. Results demonstrate that the NN approach outperforms the dictionary-based approach in terms of scalability capabilities. Results also allow us to heuristically determine the optimal training strategy to make an FCN able to predict T1 , T2 , and M0 maps that are in good agreement with those obtained with the original dictionary approach. k-SVD denoising is proposed and found to be critical as a preprocessing step to handle undersampled data.

    View details for DOI 10.1002/nbm.4670

    View details for PubMedID 35088466

  • A deep learning approach for magnetic resonance fingerprinting: Scaling capabilities and good training practices investigated by simulations. Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Barbieri, M., Brizi, L., Giampieri, E., Solera, F., Manners, D. N., Castellani, G., Testa, C., Remondini, D. 2021; 89: 80-92

    Abstract

    MR fingerprinting (MRF) is an innovative approach to quantitative MRI. A typical disadvantage of dictionary-based MRF is the explosive growth of the dictionary as a function of the number of reconstructed parameters, an instance of the curse of dimensionality, which determines an explosion of resource requirements. In this work, we describe a deep learning approach for MRF parameter map reconstruction using a fully connected architecture. Employing simulations, we have investigated how the performance of the Neural Networks (NN) approach scales with the number of parameters to be retrieved, compared to the standard dictionary approach. We have also studied optimal training procedures by comparing different strategies for noise addition and parameter space sampling, to achieve better accuracy and robustness to noise. Four MRF sequences were considered: IR-FISP, bSSFP, IR-FISP-B1, and IR-bSSFP-B1. A comparison between NN and the dictionary approaches in reconstructing parameter maps as a function of the number of parameters to be retrieved was performed using a numerical brain phantom. Results demonstrated that training with random sampling and different levels of noise variance yielded the best performance. NN performance was at least as good as the dictionary-based approach in reconstructing parameter maps using Gaussian noise as a source of artifacts: the difference in performance increased with the number of estimated parameters because the dictionary method suffers from the coarse resolution of the parameter space sampling. The NN proved to be more efficient in memory usage and computational burden, and has great potential for solving large-scale MRF problems.

    View details for DOI 10.1016/j.ejmp.2021.07.013

    View details for PubMedID 34352679

  • Characterization of Structural Bone Properties through Portable Single-Sided NMR Devices: State of the Art and Future Perspectives. International journal of molecular sciences Barbieri, M., Fantazzini, P., Testa, C., Bortolotti, V., Baruffaldi, F., Kogan, F., Brizi, L. 2021; 22 (14)

    Abstract

    Nuclear Magnetic Resonance (NMR) is a well-suited methodology to study bone composition and structural properties. This is because the NMR parameters, such as the T2 relaxation time, are sensitive to the chemical and physical environment of the 1H nuclei. Although magnetic resonance imaging (MRI) allows bone structure assessment in vivo, its cost limits the suitability of conventional MRI for routine bone screening. With difficulty accessing clinically suitable exams, the diagnosis of bone diseases, such as osteoporosis, and the associated fracture risk estimation is based on the assessment of bone mineral density (BMD), obtained by the dual-energy X-ray absorptiometry (DXA). However, integrating the information about the structure of the bone with the bone mineral density has been shown to improve fracture risk estimation related to osteoporosis. Portable NMR, based on low-field single-sided NMR devices, is a promising and appealing approach to assess NMR properties of biological tissues with the aim of medical applications. Since these scanners detect the signal from a sensitive volume external to the magnet, they can be used to perform NMR measurement without the need to fit a sample inside a bore of a magnet, allowing, in principle, in vivo application. Techniques based on NMR single-sided devices have the potential to provide a high impact on the clinical routine because of low purchasing and running costs and low maintenance of such scanners. In this review, the development of new methodologies to investigate structural properties of trabecular bone exploiting single-sided NMR devices is reviewed, and current limitations and future perspectives are discussed.

    View details for DOI 10.3390/ijms22147318

    View details for PubMedID 34298936

  • Single-sided NMR to estimate morphological parameters of the trabecular bone structure. Magnetic resonance in medicine Barbieri, M., Fantazzini, P., Bortolotti, V., Baruffaldi, F., Festa, A., Manners, D. N., Testa, C., Brizi, L. 2020

    Abstract

    PURPOSE: Single-sided 1 H-NMR is proposed for the estimation of morphological parameters of trabecular bone, and potentially the detection of pathophysiological alterations of bone structure. In this study, a new methodology was used to estimate such parameters without using an external reference signal, and to study intratrabecular and intertrabecular porosities, with a view to eventually scanning patients.METHODS: Animal trabecular bone samples were analyzed by a single-sided device. The Carr-Purcell-Meiboom-Gill sequence of 1 H nuclei of fluids, including marrow, confined inside the bone, was analyzed by quasi-continuous T2 distributions and separated into two 1 H pools: short and long T2 components. The NMR parameters were estimated using models of trabecular bone structure, and compared with the corresponding micro-CT.RESULTS: Without any further assumptions, the internal reference parameter (short T2 signal intensity fraction) enabled prediction of the micro-CT parameters BV/TV (volume of the trabeculae/total sample volume) and BS/TV (external surface of the trabeculae/total sample volume) with linear correlation coefficient >0.80. The assignment of the two pools to intratrabecular and intertrabecular components yielded an estimate of average intratrabecular porosity (33±5)%. Using the proposed models, the NMR-estimated BV/TV and BS/TV were found to be linearly related to the corresponding micro-CT values with high correlation (>0.90 for BV/TV; >0.80 for BS/TV) and agreement coefficients.CONCLUSION: Low-field, low-cost portable devices that rely on intrinsic magnetic field gradients and do not use ionizing radiation are viable tools for in vitro preclinical studies of pathophysiological structural alterations of trabecular bone.

    View details for DOI 10.1002/mrm.28648

    View details for PubMedID 33349979

  • Single-sided NMR for the diagnosis of osteoporosis: Diffusion weighted pulse sequences for the estimation of trabecular bone volume fraction in the presence of muscle tissue Barbieri, M., Brizi, L., Bortolotti, V., Fantazzini, P., d'Eurydice, M., Obruchkov, S., Liu, H., Galvosas, P. ELSEVIER SCIENCE BV. 2018: 166–70
  • Bone volume-to-total volume ratio measured in trabecular bone by single-sided NMR devices MAGNETIC RESONANCE IN MEDICINE Brizi, L., Barbieri, M., Baruffaldi, F., Bortolotti, V., Fersini, C., Liu, H., d'Eurydice, M., Obruchkov, S., Zong, F., Galvosas, P., Fantazzini, P. 2018; 79 (1): 501–10

    Abstract

    Reduced bone strength is associated with a loss of bone mass, usually evaluated by dual-energy X-ray absorptiometry, although it is known that the bone microstructure also affects the bone strength. Here, a method is proposed to measure (in laboratory) the bone volume-to-total volume ratio by single-sided NMR scanners, which is related to the microstructure of the trabecular bone.Three single-sided scanners were used on animal bone samples. These low-field, mobile, low-cost devices are able to detect the NMR signal, regardless of the sample sizes, without the use of ionizing radiations, with the further advantage of signal localization offered by their intrinsic magnetic field gradients.The performance of the different single-sided scanners have been discussed. The results have been compared with bone volume-to-total volume ratio by micro CT and MRI, obtaining consistent values.Our results demonstrate the feasibility of the method for laboratory analyses, which are useful for measurements like porosity on bone specimens. This can be considered as the first step to develop an NMR method based on the use of a mobile single-sided device, for the diagnosis of osteoporosis, through the acquisition of the signal from the appendicular skeleton, allowing for low-cost, wide screening campaigns. Magn Reson Med 79:501-510, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

    View details for DOI 10.1002/mrm.26697

    View details for Web of Science ID 000417926300049

    View details for PubMedID 28394083