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Feng W, Ding Z, Chen Q, She H, Du YP. Whole brain multiparametric mapping in two minutes using a dual-flip-angle stack-of-stars blipped multi-gradient-echo acquisition. Neuroimage 2024; 297:120689. [PMID: 38880311 DOI: 10.1016/j.neuroimage.2024.120689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 06/11/2024] [Accepted: 06/14/2024] [Indexed: 06/18/2024] Open
Abstract
A new MRI technique is presented for three-dimensional fast simultaneous whole brain mapping of myelin water fraction (MWF), T1, proton density (PD), R2*, magnetic susceptibility (QSM), and B1 transmit field (B1+). Phantom and human (N = 9) datasets were acquired using a dual-flip-angle blipped multi-gradient-echo (DFA-mGRE) sequence with a stack-of-stars (SOS) trajectory. Images were reconstructed using a subspace-based algorithm with a locally low-rank constraint. A novel joint-sparsity-constrained multicomponent T2*-T1 spectrum estimation (JMSE) algorithm is proposed to correct for the T1 saturation effect and B1+/B1- inhomogeneities in the quantification of MWF. A tissue-prior-based B1+ estimation algorithm was adapted for B1 correction in the mapping of T1 and PD. In the phantom study, measurements obtained at an acceleration factor (R) of 12 using prospectively under-sampled SOS showed good consistency (R2 > 0.997) with Cartesian reference for R2*/T1app/M0app. In the in vivo study, results of retrospectively under-sampled SOS with R = 6, 12, 18, showed good quality (structure similarity index measure > 0.95) compared with those of fully-sampled SOS. Besides, results of prospectively under-sampled SOS with R = 12 showed good consistency (intraclass correlation coefficient > 0.91) with Cartesian reference for T1/PD/B1+/MWF/QSM/R2*, and good reproducibility (coefficient of variation < 7.0 %) in the test-retest analysis for T1/PD/B1+/MWF/R2*. This study has demonstrated the feasibility of simultaneous whole brain multiparametric mapping with a two-minute scan using the DFA-mGRE SOS sequence, which may overcome a major obstacle for neurological applications of multiparametric MRI.
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Affiliation(s)
- Wenlong Feng
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zekang Ding
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Quan Chen
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Huajun She
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
| | - Yiping P Du
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
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Sandgaard AD, Shemesh N, Østergaard L, Kiselev VG, Jespersen SN. The Larmor frequency shift of a white matter magnetic microstructure model with multiple sources. NMR IN BIOMEDICINE 2024; 37:e5150. [PMID: 38553824 DOI: 10.1002/nbm.5150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/15/2024] [Accepted: 02/28/2024] [Indexed: 07/11/2024]
Abstract
Magnetic susceptibility imaging may provide valuable information about chemical composition and microstructural organization of tissue. However, its estimation from the MRI signal phase is particularly difficult as it is sensitive to magnetic tissue properties ranging from the molecular to the macroscopic scale. The MRI Larmor frequency shift measured in white matter (WM) tissue depends on the myelinated axons and other magnetizable sources such as iron-filled ferritin. We have previously derived the Larmor frequency shift arising from a dense medium of cylinders with scalar susceptibility and arbitrary orientation dispersion. Here, we extend our model to include microscopic WM susceptibility anisotropy as well as spherical inclusions with scalar susceptibility to represent subcellular structures, biologically stored iron, and so forth. We validate our analytical results with computer simulations and investigate the feasibility of estimating susceptibility using simple iterative linear least squares without regularization or preconditioning. This is done in a digital brain phantom synthesized from diffusion MRI measurements of an ex vivo mouse brain at ultra-high field.
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Affiliation(s)
- Anders Dyhr Sandgaard
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Noam Shemesh
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Leif Østergaard
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Valerij G Kiselev
- Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | - Sune Nørhøj Jespersen
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
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Faulkner ME, Gong Z, Guo A, Laporte JP, Bae J, Bouhrara M. Harnessing myelin water fraction as an imaging biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination: A review. J Neurochem 2024. [PMID: 38973579 DOI: 10.1111/jnc.16170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 06/12/2024] [Accepted: 06/19/2024] [Indexed: 07/09/2024]
Abstract
Myelin water fraction (MWF) imaging has emerged as a promising magnetic resonance imaging (MRI) biomarker for investigating brain function and composition. This comprehensive review synthesizes the current state of knowledge on MWF as a biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination. The databases used include Web of Science, Scopus, Science Direct, and PubMed. We begin with a brief discussion of the theoretical foundations of MWF imaging, including its basis in MR physics and the mathematical modeling underlying its calculation, with an overview of the most adopted MRI methods of MWF imaging. Next, we delve into the clinical and research applications that have been explored to date, highlighting its advantages and limitations. Finally, we explore the potential of MWF to serve as a predictive biomarker for neurological disorders and identify future research directions for optimizing MWF imaging protocols and interpreting MWF in various contexts. By harnessing the power of MWF imaging, we may gain new insights into brain health and disease across the human lifespan, ultimately informing novel diagnostic and therapeutic strategies.
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Affiliation(s)
- Mary E Faulkner
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Alex Guo
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - John P Laporte
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Jonghyun Bae
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
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Kurian D, Hagberg GE, Scheffler K, Paul JS. A predictor-corrector phase unwrapping algorithm for temporally undersampled gradient-echo MRI. Magn Reson Med 2024; 91:1707-1722. [PMID: 38084410 DOI: 10.1002/mrm.29964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 11/18/2023] [Accepted: 11/19/2023] [Indexed: 02/03/2024]
Abstract
PURPOSE To develop a method for unwrapping temporally undersampled and nonlinear gradient recalled echo (GRE) phase. THEORY AND METHODS Temporal unwrapping is performed as a sequential one step prediction of the echo phase, followed by a correction to the nearest integer wrap-count. A spatio-temporal extension of the 1D predictor corrector unwrapping (PCU) algorithm improves the prediction accuracy, and thereby maintains spatial continuity. The proposed method is evaluated using numerical phantom, physical phantom, and in vivo brain data at both 3 T and 9.4 T. The unwrapping performance is compared with the state-of-the-art temporal and spatial unwrapping algorithms, and the spatio-temporal iterative virtual-echo based Nyquist sampled (iVENyS) algorithm. RESULTS Simulation results showed significant reduction in unwrapping errors at higher echoes compared with the state-of-the-art algorithms. Similar to the iVENyS algorithm, the PCU algorithm was able to generate spatially smooth phase images for in vivo data acquired at 3 T and 9.4 T, bypassing the use of additional spatial unwrapping step. A key advantage over iVENyS algorithm is the superior performance of PCU algorithm at higher echoes. CONCLUSION PCU algorithm serves as a robust phase unwrapping method for temporally undersampled and nonlinear GRE phase, particularly in the presence of high field gradients.
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Affiliation(s)
- Deepu Kurian
- School of Electronic Systems & Automation, Digital University Kerala, Trivandrum, Kerala, India
| | - Gisela E Hagberg
- High Field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
- Biomedical Magnetic Resonance, Department of Radiology, Eberhard Karl's University and University Hospital, Tübingen, Germany
| | - Klaus Scheffler
- High Field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
- Biomedical Magnetic Resonance, Department of Radiology, Eberhard Karl's University and University Hospital, Tübingen, Germany
| | - Joseph Suresh Paul
- School of Electronic Systems & Automation, Digital University Kerala, Trivandrum, Kerala, India
- School of Informatics, Digital University Kerala, Trivandrum, Kerala, India
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Chen L, Shin HG, van Zijl PC, Li X. Exploiting gradient-echo frequency evolution: Probing white matter microstructure and extracting bulk susceptibility-induced frequency for quantitative susceptibility mapping. Magn Reson Med 2024; 91:1676-1693. [PMID: 38102838 PMCID: PMC10880384 DOI: 10.1002/mrm.29958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Revised: 10/08/2023] [Accepted: 11/17/2023] [Indexed: 12/17/2023]
Abstract
PURPOSE This work is to investigate the microstructure-induced frequency shift in white matter (WM) with crossing fibers and to separate the microstructure-related frequency shift from the bulk susceptibility-induced frequency shift by model fitting the gradient-echo (GRE) frequency evolution for potentially more accurate quantitative susceptibility mapping (QSM). METHODS A hollow-cylinder fiber model (HCFM) with two fiber populations was developed to investigate GRE frequency evolutions in WM voxels with microstructural orientation dispersion. The simulated and experimentally measured TE-dependent local frequency shift was then fitted to a simplified frequency evolution model to obtain a microstructure-related frequency difference parameter (∆ f $$ \Delta f $$ ) and a TE-independent bulk susceptibility-induced frequency shift (C f $$ {C}_f $$ ). The obtainedC f $$ {C}_f $$ was then used for QSM reconstruction. Reconstruction performances were evaluated using a numerical head phantom and in vivo data and then compared to other multi-echo combination methods. RESULTS GRE frequency evolutions and∆ f $$ \Delta f $$ -based tissue parameters in both parallel and crossing fibers determined from our simulations were comparable to those observed in vivo. The TE-dependent frequency fitting method outperformed other multi-echo combination methods in estimatingC f $$ {C}_f $$ in simulations. The fitted∆ f $$ \Delta f $$ ,C f $$ {C}_f $$ , and QSM could be improved further by navigator-based B0 fluctuation correction. CONCLUSION A HCFM with two fiber populations can be used to characterize microstructure-induced frequency shifts in WM regions with crossing fibers. HCFM-based TE-dependent frequency fitting provides tissue contrast related to microstructure (∆ f $$ \Delta f $$ ) and in addition may help improve the quantification accuracy ofC f $$ {C}_f $$ and the corresponding QSM.
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Affiliation(s)
- Lin Chen
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
| | - Hyeong-Geol Shin
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
| | - Peter C.M. van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
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Sandgaard AD, Kiselev VG, Henriques RN, Shemesh N, Jespersen SN. Incorporating the effect of white matter microstructure in the estimation of magnetic susceptibility in ex vivo mouse brain. Magn Reson Med 2024; 91:699-715. [PMID: 37772624 DOI: 10.1002/mrm.29867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 08/07/2023] [Accepted: 08/25/2023] [Indexed: 09/30/2023]
Abstract
PURPOSE To extend quantitative susceptibility mapping to account for microstructure of white matter (WM) and demonstrate its effect on ex vivo mouse brain at 16.4T. THEORY AND METHODS Previous studies have shown that the MRI measured Larmor frequency also depends on local magnetic microstructure at the mesoscopic scale. Here, we include effects from WM microstructure using our previous results for the mesoscopic Larmor frequencyΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ of cylinders with arbitrary orientations. We scrutinize the validity of our model and QSM in a digital brain phantom includingΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ from a WM susceptibility tensor and biologically stored iron with scalar susceptibility. We also apply susceptibility tensor imaging to the phantom and investigate how the fitted tensors are biased fromΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ . Last, we demonstrate how to combine multi-gradient echo and diffusion MRI images of ex vivo mouse brains acquired at 16.4T to estimate an apparent scalar susceptibility without sample rotations. RESULTS Our new model improves susceptibility estimation compared to QSM for the brain phantom. Applying susceptibility tensor imaging to the phantom withΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ from WM axons with scalar susceptibility produces a highly anisotropic susceptibility tensor that mimics results from previous susceptibility tensor imaging studies. For the ex vivo mouse brain we find theΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ due to WM microstructure to be substantial, changing susceptibility in WM up to 25% root-mean-squared-difference. CONCLUSION Ω ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ impacts susceptibility estimates and biases susceptibility tensor imaging fitting substantially. Hence, it should not be neglected when imaging structurally anisotropic tissue such as brain WM.
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Affiliation(s)
- Anders Dyhr Sandgaard
- Center for Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Valerij G Kiselev
- Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | | | - Noam Shemesh
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Sune Nørhøj Jespersen
- Center for Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
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Tourais J, Ploem T, van Zadelhoff TA, van de Steeg-Henzen C, Oei EHG, Weingartner S. Rapid Whole-Knee Quantification of Cartilage Using T 1, T 2*, and T RAFF2 Mapping With Magnetic Resonance Fingerprinting. IEEE Trans Biomed Eng 2023; 70:3197-3205. [PMID: 37227911 DOI: 10.1109/tbme.2023.3280115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
OBJECTIVE Quantitative Magnetic Resonance Imaging (MRI) holds great promise for the early detection of cartilage deterioration. Here, a Magnetic Resonance Fingerprinting (MRF) framework is proposed for comprehensive and rapid quantification of T1, T2*, and TRAFF2 with whole-knee coverage. METHODS A MRF framework was developed to achieve quantification of Relaxation Along a Fictitious Field in the 2nd rotating frame of reference ( TRAFF2) along with T1 and T2*. The proposed sequence acquires 65 measurements of 25 high-resolution slices, interleaved with 7 inversion pulses and 40 RAFF2 trains, for whole-knee quantification in a total acquisition time of 3:25 min. Comparison with reference T1, T2*, and TRAFF2 methods was performed in phantom and in seven healthy subjects at 3 T. Repeatability (test-retest) with and without repositioning was also assessed. RESULTS Phantom measurements resulted in good agreement between MRF and the reference with mean biases of -54, 2, and 5 ms for T1, T2*, and TRAFF2, respectively. Complete characterization of the whole-knee cartilage was achieved for all subjects, and, for the femoral and tibial compartments, a good agreement between MRF and reference measurements was obtained. Across all subjects, the proposed MRF method yielded acceptable repeatability without repositioning ( R2 ≥ 0.94) and with repositioning ( R2 ≥ 0.57) for T1, T2*, and TRAFF2. SIGNIFICANCE The short scan time combined with the whole-knee coverage makes the proposed MRF framework a promising candidate for the early assessment of cartilage degeneration with quantitative MRI, but further research may be warranted to improve repeatability after repositioning and assess clinical value in patients.
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Shen X, Özen AC, Sunjar A, Ilbey S, Sawiak S, Shi R, Chiew M, Emir U. Ultra-short T 2 components imaging of the whole brain using 3D dual-echo UTE MRI with rosette k-space pattern. Magn Reson Med 2023; 89:508-521. [PMID: 36161728 PMCID: PMC9712161 DOI: 10.1002/mrm.29451] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 07/26/2022] [Accepted: 08/22/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE This study aimed to develop a new 3D dual-echo rosette k-space trajectory, specifically designed for UTE MRI applications. The imaging of the ultra-short transverse relaxation time (uT2 ) of brain was acquired to test the performance of the proposed UTE sequence. THEORY AND METHODS The rosette trajectory was developed based on rotations of a "petal-like" pattern in the kx -ky plane, with oscillated extensions in the kz -direction for 3D coverage. Five healthy volunteers underwent 10 dual-echo 3D rosette UTE scans with various TEs. Dual-exponential complex model fitting was performed on the magnitude data to separate uT2 signals, with the output of uT2 fraction, uT2 value, and long-T2 value. RESULTS The 3D rosette dual-echo UTE sequence showed better performance than a 3D radial UTE acquisition. More significant signal intensity decay in white matter than gray matter was observed along with the TEs. The white matter regions had higher uT2 fraction values than gray matter (10.9% ± 1.9% vs. 5.7% ± 2.4%). The uT2 value was approximately 0.10 ms in white matter . CONCLUSION The higher uT2 fraction value in white matter compared to gray matter demonstrated the ability of the proposed sequence to capture rapidly decaying signals.
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Affiliation(s)
- Xin Shen
- Weldon School of Biomedical Engineering, Purdue University
| | - Ali Caglar Özen
- Department of Radiology, Medical Physics, Medical Center–University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg
| | - Antonia Sunjar
- Weldon School of Biomedical Engineering, Purdue University
| | - Serhat Ilbey
- Department of Radiology, Medical Physics, Medical Center–University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg
| | - Stephen Sawiak
- Department of Clinical Neurosciences, University of Cambridge, UK,Department of Psychology, University of Cambridge, UK
| | - Riyi Shi
- Weldon School of Biomedical Engineering, Purdue University,College of Veterinary Medicine, Purdue University
| | - Mark Chiew
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | - Uzay Emir
- Weldon School of Biomedical Engineering, Purdue University,Health Science Department, Purdue University
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Xu G, He Y, Yu Q, He H, Zhao Z, Fan M, Li J, Xu D. Improved magnetic resonance myelin water imaging using multi-channel denoising convolutional neural networks (MCDnCNN). Quant Imaging Med Surg 2022; 12:1716-1737. [PMID: 35284287 PMCID: PMC8899954 DOI: 10.21037/qims-21-404] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 11/05/2021] [Indexed: 08/18/2023]
Abstract
BACKGROUND Myelin water imaging (MWI) is powerful and important for studying and diagnosing neurological and psychiatric diseases. In particular, myelin water fraction (MWF) is derived from MWI data for quantifying myelination. However, MWF estimation is typically sensitive to noise. Improving the accuracy of MWF estimation based on WMI data acquired using a magnetic resonance (MR) multiple gradient recalled echo (mGRE) imaging sequence is desired. METHODS The proposed method employs a recently introduced the multi-channel denoising convolutional neural networks (MCDnCNN). Five different MCDnCNN models, denoted as Delevel1, Delevel2, Delevel3, Delevel4 and DelevelMix corresponding to five noise levels (Level1, Level2, Level3, Level4 and LevelMix), were trained using the data of the first echo of the mGRE brain images acquired from 15 healthy human subjects. Using simulated noisy data that employed a hollow cylinder model, we first evaluated the improvement in estimating MWF based on data denoised by the five different MCDnCNNs, by comparing the MWF maps calculated from the denoised data with ground truth. Next, we again evaluated the improvement using real-world in vivo datasets of 11 human participants acquired using the mGRE sequence. The datasets were first denoised by five different MCDnCNNs (Delevel1, 2, 3, 4 and DelevelMix), and subsequently their MWF maps were calculated and compared with the MWF maps directly calculated from the raw mGRE images without being denoised. RESULTS Experiments using the simulation data denoised by the appropriate MCDnCNN models showed that the standard deviation (SD) of the absolute error (AE) of the derived MWF results was significantly reduced (maximal reduction =15.5%, Level3 simulated noisy data, orientation angle =0, all the five MCDnCNN models). In the test using in vivo data, estimating MWF based on data particularly denoised by the appropriate MCDnCNN models was found to be the best, compared to otherwise not using the appropriate models. The results demonstrated that the appropriate MCDnCNN models may permit high-quality MWF mapping, i.e., substantial reduction of random variation in estimating MWF-maps while preserving accuracy and structural details. CONCLUSIONS Appropriate MCDnCNN models as proposed may improve both the accuracy and precision in estimating MWF maps, thereby making it a more clinically feasible alternative.
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Affiliation(s)
- Guojun Xu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
- Molecular Imaging and Neuropathology Division, Columbia University Department of Psychiatry & New York State Psychiatric Institute, New York, NY, USA
| | - Yongquan He
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Qiurong Yu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Zhiyong Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Mingxia Fan
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Jianqi Li
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Dongrong Xu
- Molecular Imaging and Neuropathology Division, Columbia University Department of Psychiatry & New York State Psychiatric Institute, New York, NY, USA
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Song JE, Kim DH. Improved Multi-Echo Gradient-Echo-Based Myelin Water Fraction Mapping Using Dimensionality Reduction. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:27-38. [PMID: 34357864 DOI: 10.1109/tmi.2021.3102977] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Multi-echo gradient-echo (mGRE)-based myelin water fraction (MWF) mapping is a promising myelin water imaging (MWI) modality but is vulnerable to noise and artifact corruption. The linear dimensionality reduction (LDR) method has recently shown improvements with regard to these challenges. However, the magnitude value based low rank operators have been shown to misestimate the MWF for regions with [Formula: see text] anisotropy. This paper presents a nonlinear dimensionality reduction (NLDR) method to estimate the MWF map better by encouraging nonlinear low dimensionality of mGRE signal sources. Specifically, we implemented a fully connected deep autoencoder to extract the low-dimensional features of complex-valued signals and incorporated a sparse regularization to separate the anomaly sources that do not reside in the low-dimensional manifold. Simulations and in vivo experiments were performed to evaluate the accuracy of the MWF map under various situations. The proposed NLDR-based MWF improves the accuracy of the MWF map over the conventional nonlinear least-squares method and the LDR-based MWF and maintains robustness against noise and artifact corruption.
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11
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Casella C, Kleban E, Rosser AE, Coulthard E, Rickards H, Fasano F, Metzler-Baddeley C, Jones DK. Multi-compartment analysis of the complex gradient-echo signal quantifies myelin breakdown in premanifest Huntington's disease. Neuroimage Clin 2021; 30:102658. [PMID: 33865029 PMCID: PMC8079666 DOI: 10.1016/j.nicl.2021.102658] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 03/25/2021] [Accepted: 03/30/2021] [Indexed: 12/04/2022]
Abstract
White matter (WM) alterations have been identified as a relevant pathological feature of Huntington's disease (HD). Increasing evidence suggests that WM changes in this disorder are due to alterations in myelin-associated biological processes. Multi-compartmental analysis of the complex gradient-echo MRI signal evolution in WM has been shown to quantify myelin in vivo, therefore pointing to the potential of this technique for the study of WM myelin changes in health and disease. This study first characterized the reproducibility of metrics derived from the complex multi-echo gradient-recalled echo (mGRE) signal across the corpus callosum in healthy participants, finding highest reproducibility in the posterior callosal segment. Subsequently, the same analysis pipeline was applied in this callosal region in a sample of premanifest HD patients (n = 19) and age, sex and education matched healthy controls (n = 21). In particular, we focused on two myelin-associated derivatives: i. the myelin water signal fraction (fm), a parameter dependent on myelin content; and ii. The difference in frequency between myelin and intra-axonal water pools (Δω), a parameter dependent on the ratio between the inner and the outer axonal radii. fm was found to be lower in HD patients (β = -0.13, p = 0.03), while Δω did not show a group effect. Performance in tests of working memory, executive function, social cognition and movement was also assessed, and a greater age-related decline in executive function was detected in HD patients (β = -0.06, p = 0.006), replicating previous evidence of executive dysfunction in HD. Finally, the correlation between fm, executive function, and proximity to disease onset was explored in patients, and a positive correlation between executive function and fm was detected (r = 0.542; p = 0.02). This study emphasises the potential of complex mGRE signal analysis for aiding understanding of HD pathogenesis and progression. Moreover, expanding on evidence from pathology and animal studies, it provides novel in vivo evidence supporting myelin breakdown as an early feature of HD.
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Affiliation(s)
- Chiara Casella
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF 24 4HQ, UK.
| | - Elena Kleban
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF 24 4HQ, UK
| | - Anne E Rosser
- Department of Neurology and Psychological Medicine, Hayden Ellis Building, Maindy Road, Cardiff CF24 4HQ, UK; School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, UK
| | | | - Hugh Rickards
- Birmingham and Solihull Mental Health NHS Foundation Trust, 50 Summer Hill Road, Birmingham B1 3RB, UK; Institute of Clinical Sciences, College of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Fabrizio Fasano
- Siemens Healthcare Ltd, Camberly, UK; Siemens Healthcare GmbH, Erlangen, Germany
| | - Claudia Metzler-Baddeley
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF 24 4HQ, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF 24 4HQ, UK
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12
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Variable flip angle echo planar time-resolved imaging (vFA-EPTI) for fast high-resolution gradient echo myelin water imaging. Neuroimage 2021; 232:117897. [PMID: 33621694 PMCID: PMC8221177 DOI: 10.1016/j.neuroimage.2021.117897] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 02/01/2021] [Accepted: 02/16/2021] [Indexed: 12/14/2022] Open
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 min at 1.5 mm isotropic resolution and 24 min at 1 mm isotropic resolution at 3T. Additionally, ultra-high resolution data at 600 μm 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.
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13
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Kleban E, Gowland P, Bowtell R. Probing the myelin water compartment with a saturation-recovery, multi-echo gradient-recalled echo sequence. Magn Reson Med 2021; 86:167-181. [PMID: 33576521 DOI: 10.1002/mrm.28695] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 12/24/2020] [Accepted: 01/04/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE To investigate the effect of varying levels of T 1 -weighting on the evolution of the complex signal from white matter in a multi-echo gradient-recalled echo (mGRE) saturation-recovery sequence. THEORY AND METHODS Analysis of the complex signal evolution in an mGRE sequence allows the contributions from short- and long- T 2 ∗ components to be separated, thus providing a measure of the relative strength of signals from the myelin water, and the external and intra-axonal compartments. Here we evaluated the effect of different levels of T 1 -weighting on these signals, expecting that the previously reported, short T 1 of the myelin water would lead to a relative enhancement of the myelin water signal in the presence of signal saturation. Complex, saturation-recovery mGRE data from the splenium of the corpus callosum from 5 healthy volunteers were preprocessed using a frequency difference mapping (FDM) approach and analyzed using the 3-pool model of complex signal evolution in white matter. RESULTS An increase in the apparent T 1 as a function of echo time was demonstrated, but this increase was an order of magnitude smaller than that expected from previously reported myelin water T 1 -values. This suggests the presence of magnetization transfer and exchange effects which counteract the T 1 -weighting. CONCLUSION Variation of the B 1 + amplitude in a saturation-recovery mGRE sequence can be used to modulate the relative strength of signals from the different compartments in white matter, but the modulation is less than predicted from previously reported T 1 -values.
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Affiliation(s)
- Elena Kleban
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK.,Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
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14
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Wiggermann V, Vavasour IM, Kolind SH, MacKay AL, Helms G, Rauscher A. Non-negative least squares computation for in vivo myelin mapping using simulated multi-echo spin-echo T 2 decay data. NMR IN BIOMEDICINE 2020; 33:e4277. [PMID: 32124505 DOI: 10.1002/nbm.4277] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 01/20/2020] [Accepted: 01/26/2020] [Indexed: 06/10/2023]
Abstract
Multi-compartment T2 mapping has gained particular relevance for the study of myelin water in the brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non-negative least squares fitting of multi-echo T2 data has been widely employed for the computation of the myelin water fraction (MWF), and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B1+ homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi-compartment T2 and MWF maps. We generated multi-echo spin-echo T2 decay curves following the Carr-Purcell-Meiboom-Gill approach for various myelin concentrations and myelin T2 scenarios by simulating the evolution of the magnetization vector between echoes based on the Bloch equations. We demonstrated that noise and imperfect refocusing flip angles yield systematic underestimations in MWF and intra-/extracellular water geometric mean T2 (gmT2 ). MWF estimates were more stable than myelin water gmT2 time across different settings of the T2 analysis. We observed that the lower limit of the T2 distribution grid should be slightly shorter than TE1 . Both TE1 and the acquisition echo spacing also have to be sufficiently short to capture the rapidly decaying myelin water T2 signal. Among all parameters of interest, the estimated MWF and intra-/extracellular water gmT2 differed by approximately 0.13-4 percentage points and 3-4 ms, respectively, from the true values, with larger deviations observed in the presence of greater B1+ inhomogeneities and at lower signal-to-noise ratio. Tailoring acquisition strategies may allow us to better characterize the T2 distribution, including the myelin water, in vivo.
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Affiliation(s)
- V Wiggermann
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, Canada
- UBC MRI Research Center, University of British Columbia, Vancouver, Canada
| | - I M Vavasour
- UBC MRI Research Center, University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - S H Kolind
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
- UBC MRI Research Center, University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
- Department of Medicine (Division Neurology), University of British Columbia, Vancouver, Canada
| | - A L MacKay
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
- UBC MRI Research Center, University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - G Helms
- Department of Clinical Sciences Lund (IKVL), Medical Radiation Physics, Lund University, Lund, Sweden
| | - A Rauscher
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, Canada
- UBC MRI Research Center, University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
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15
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Piredda GF, Hilbert T, Thiran JP, Kober T. Probing myelin content of the human brain with MRI: A review. Magn Reson Med 2020; 85:627-652. [PMID: 32936494 DOI: 10.1002/mrm.28509] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 08/12/2020] [Accepted: 08/17/2020] [Indexed: 12/11/2022]
Abstract
Rapid and efficient transmission of electric signals among neurons of vertebrates is ensured by myelin-insulating sheaths surrounding axons. Human cognition, sensation, and motor functions rely on the integrity of these layers, and demyelinating diseases often entail serious cognitive and physical impairments. Magnetic resonance imaging radically transformed the way these disorders are monitored, offering an irreplaceable tool to noninvasively examine the brain structure. Several advanced techniques based on MRI have been developed to provide myelin-specific contrasts and a quantitative estimation of myelin density in vivo. Here, the vast offer of acquisition strategies developed to date for this task is reviewed. Advantages and pitfalls of the different approaches are compared and discussed.
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Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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16
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Soellradl M, Strasser J, Lesch A, Stollberger R, Ropele S, Langkammer C. Adaptive slice-specific z-shimming for 2D spoiled gradient-echo sequences. Magn Reson Med 2020; 85:818-830. [PMID: 32909334 PMCID: PMC7693070 DOI: 10.1002/mrm.28468] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 07/01/2020] [Accepted: 07/16/2020] [Indexed: 12/22/2022]
Abstract
Purpose To reduce the misbalance between compensation gradients and macroscopic field gradients, we introduce an adaptive slice‐specific z‐shimming approach for 2D spoiled multi‐echo gradient‐echoe sequences in combination with modeling of the signal decay. Methods Macroscopic field gradients were estimated for each slice from a fast prescan (15 seconds) and then used to calculate slice‐specific compensation moments along the echo train. The coverage of the compensated field gradients was increased by applying three positive and three negative moments. With a forward model, which considered the effect of the slice profile, the z‐shim moment, and the field gradient, R2∗ maps were estimated. The method was evaluated in phantom and in vivo measurements at 3 T and compared with a spoiled multi‐echo gradient‐echo and a global z‐shimming approach without slice‐specific compensation. Results The proposed method yielded higher SNR in R2∗ maps due to a broader range of compensated macroscopic field gradients compared with global z‐shimming. In global white matter, the mean interquartile range, proxy for SNR, could be decreased to 3.06 s−1 with the proposed approach, compared with 3.37 s−1 for global z‐shimming and 3.52 s−1 for uncompensated multi‐echo gradient‐echo. Conclusion Adaptive slice‐specific compensation gradients between echoes substantially improved the SNR of R2∗ maps, and the signal could also be rephased in anatomical areas, where it has already been completely dephased.
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Affiliation(s)
- Martin Soellradl
- Department of Neurology, Medical University of Graz, Graz, Austria
| | | | - Andreas Lesch
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Rudolf Stollberger
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
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17
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Foxley S, Wildenberg G, Sampathkumar V, Karczmar GS, Brugarolas P, Kasthuri N. Sensitivity to myelin using model-free analysis of the water resonance line-shape in postmortem mouse brain. Magn Reson Med 2020; 85:667-677. [PMID: 32783262 DOI: 10.1002/mrm.28440] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 06/17/2020] [Accepted: 06/30/2020] [Indexed: 12/18/2022]
Abstract
PURPOSE Dysmyelinating diseases are characterized by abnormal myelin formation and function. Such microstructural abnormalities in myelin have been demonstrated to produce measurable effects on the MR signal. This work examines these effects on measurements of voxel-wise, high-resolution water spectra acquired using a 3D echo-planar spectroscopic imaging (EPSI) pulse sequence from both postmortem fixed control mouse brains and a dysmyelination mouse brain model. METHODS Perfusion fixed, resected control (n = 5) and shiverer (n = 4) mouse brains were imaged using 3D-EPSI with 100 µm isotropic resolution. The free induction decay (FID) was sampled every 2.74 ms over 192 echoes, for a total sampling duration of 526.08 ms. Voxel-wise FIDs were Fourier transformed to produce water spectra with 1.9 Hz resolution. Spectral asymmetry was computed and compared between the two tissue types. RESULTS The water resonance is more asymmetrically broadened in the white matter of control mouse brain compared with dysmyelinated white matter. In control brain, this is modulated by and consistent with previously reported orientationally dependent effects of white matter relative to B0 . Similar sensitivity to orientation is observed in dysmyelinated white matter as well; however, the magnitude of the resonance asymmetry is much lower across all directions. CONCLUSION Results demonstrate that components of the spectra are specifically differentially affected by myelin concentration. This suggests that water proton spectra may be sensitive to the presence of myelin, and as such, could serve as a MRI-based biomarker of dysmyelinating disease, free of mathematical models.
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Affiliation(s)
- Sean Foxley
- Department of Radiology, University of Chicago, Chicago, Illinois, USA
| | - Gregg Wildenberg
- Department of Neurobiology, University of Chicago, Chicago, Illinois, USA
| | | | | | - Pedro Brugarolas
- Department of Radiology, Harvard Medical School, Boston, Maryland, USA.,Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, Maryland, USA
| | - Narayanan Kasthuri
- Department of Neurobiology, University of Chicago, Chicago, Illinois, USA
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18
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Jung S, Lee H, Ryu K, Song JE, Park M, Moon WJ, Kim DH. Artificial neural network for multi-echo gradient echo-based myelin water fraction estimation. Magn Reson Med 2020; 85:380-389. [PMID: 32686208 DOI: 10.1002/mrm.28407] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 06/09/2020] [Accepted: 06/09/2020] [Indexed: 02/01/2023]
Abstract
PURPOSE To demonstrate robust myelin water fraction (MWF) mapping using an artificial neural network (ANN) with multi-echo gradient-echo (GRE) signal. METHODS Multi-echo gradient-echo signals simulated with a three-pool exponential model were used to generate the training data set for the ANN, which was designed to yield the MWF. We investigated the performance of our proposed ANN for various conditions using both numerical simulations and in vivo data. Simulations were conducted with various SNRs to investigate the performance of the ANN. In vivo data with high spatial resolutions were applied in the analyses, and results were compared with MWFs derived by the nonlinear least-squares algorithm using a complex three-pool exponential model. RESULTS The network results for the simulations show high accuracies against noise compared with nonlinear least-squares MWFs: RMS-error value of 5.46 for the nonlinear least-squares MWF and 3.56 for the ANN MWF at an SNR of 150 (relative gain = 34.80%). These effects were also found in the in vivo data, with reduced SDs in the region-of-interest analyses. These effects of the ANN demonstrate the feasibility of acquiring high-resolution myelin water images. CONCLUSION The simulation results and in vivo data suggest that the ANN facilitates more robust MWF mapping in multi-echo gradient-echo sequences compared with the conventional nonlinear least-squares method.
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Affiliation(s)
- Soozy Jung
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Hongpyo Lee
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Kanghyun Ryu
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Jae Eun Song
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Mina Park
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Won-Jin Moon
- Department of Radiology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
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19
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Song JE, Shin J, Lee H, Lee HJ, Moon WJ, Kim DH. Blind Source Separation for Myelin Water Fraction Mapping Using Multi-Echo Gradient Echo Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:2235-2245. [PMID: 31976881 DOI: 10.1109/tmi.2020.2967068] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
In conventional gradient-echo myelin water imaging (GRE-MWI), myelin water fraction (MWF) is estimated by fitting the multi-echo gradient recalled echo (mGRE) signal to a pre-assumed numerical model (e.g., multi-component exponential curves or three component exponential curves). However, in mGRE, imaging artifacts (e.g., voxel spread function and physiological noise) and noise render the signal to deviate from the numerical model, leading to misfit of the model parameters. Here, as an alternative to the model-based GRE-MWI, a blind source separation (BSS) technique for the separation of multi-exponential mGRE signal is proposed. Among the various BSS techniques, a modified robust principal component analysis (rPCA) is presented to separate signal sources by enforcing the data-driven properties such as "low rankness" and "sparsity." Considering the signal evolution of T2∗ relaxation (i.e., non-negative exponential decay), low rankness of exponential decay was enforced by nonnegative matrix factorization (NMF) and hankelization. This method provides the separation of slow-decaying, fast-decaying exponential components and artifact components from mGRE images. After the separation, MWF map is reconstructed as the ratio of the fast-decaying component to the total decaying components. The proposed method was demonstrated in numerical simulations and in vivo scans. The method provided a robust estimation of MWF in the presence of statistical noise and imaging artifacts.
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20
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Sood S, Reutens DC, Kadamangudi S, Barth M, Vegh V. Field strength influences on gradient recalled echo MRI signal compartment frequency shifts. Magn Reson Imaging 2020; 70:98-107. [PMID: 32360972 DOI: 10.1016/j.mri.2020.04.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 04/09/2020] [Accepted: 04/27/2020] [Indexed: 11/20/2022]
Abstract
Different trends of echo time dependent gradient recalled echo MRI signals in different brain regions have been attributed to signal compartments in image voxels. It remains unclear how variations in gradient recalled echo MRI signals change as a function of MRI field strength, and how data processing may impact signal compartment parameters. We used two popular quantitative susceptibility mapping methods of processing raw phase images (Laplacian and path-based unwrapping with V-SHARP) and expressed values in the form of induced frequency shifts (in Hz) in six specific brain regions at 3T and 7T. We found the frequency shift curves to vary with echo time, and a good overlap between 3T and 7T mean frequency shift curves was present. However, the amount of variation across participants was greater at 3T, and we were able to obtain better compartment model fits of the signal at 7T. We also found the temporal trends in the signal and compartment frequency shifts to change with the method used to process images. The inter-participant averaged trends were consistent between 3T and 7T for each quantitative susceptibility pipeline. However, signal compartment frequency shifts generated using different pipelines may not be comparable.
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Affiliation(s)
- Surabhi Sood
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - David C Reutens
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Shrinath Kadamangudi
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Markus Barth
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Viktor Vegh
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia.
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21
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Kleban E, Tax CMW, Rudrapatna US, Jones DK, Bowtell R. Strong diffusion gradients allow the separation of intra- and extra-axonal gradient-echo signals in the human brain. Neuroimage 2020; 217:116793. [PMID: 32335263 PMCID: PMC7613126 DOI: 10.1016/j.neuroimage.2020.116793] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 02/28/2020] [Accepted: 03/19/2020] [Indexed: 12/12/2022] Open
Abstract
The quantification of brain white matter properties is a key area of application of Magnetic Resonance Imaging (MRI), with much effort focused on using MR techniques to quantify tissue microstructure. While diffusion MRI probes white matter (WM) microstructure by characterising the sensitivity of Brownian motion of water molecules to anisotropic structures, susceptibility-based techniques probe the tissue microstructure by observing the effect of interaction between the tissue and the magnetic field. Here, we unify these two complementary approaches by combining ultra-strong (300 mT/m) gradients with a novel Diffusion-Filtered Asymmetric Spin Echo (D-FASE) technique. Using D-FASE we can separately assess the evolution of the intra- and extra-axonal signals under the action of susceptibility effects, revealing differences in the behaviour in different fibre tracts. We observed that the effective relaxation rate of the ASE signal in the corpus callosum decreases with increasing b-value in all subjects (from 17.1 ± 0.7 s−1 at b = 0 s/mm2 to 14.6 ± 0.7 s−1 at b = 4800 s/mm2), while this dependence on b in the corticospinal tract is less pronounced (from 12.0± 1.1 s−1 at b = 0s/mm2 to 10.7 ± 0.5 s−1 at b = 4800 s/mm2). Voxelwise analysis of the signal evolution with respect to b-factor and acquisition delay using a microscopic model demonstrated differences in gradient echo signal evolution between the intra- and extra-axonal pools.
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Affiliation(s)
- Elena Kleban
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK.
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Umesh S Rudrapatna
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK; Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, 3065, Australia
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
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22
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Lee J, Hyun JW, Lee J, Choi EJ, Shin HG, Min K, Nam Y, Kim HJ, Oh SH. So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging. J Magn Reson Imaging 2020; 53:360-373. [PMID: 32009271 DOI: 10.1002/jmri.27059] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 01/01/2020] [Accepted: 01/02/2020] [Indexed: 12/22/2022] Open
Abstract
Myelin water imaging (MWI) is an MRI imaging biomarker for myelin. This method can generate an in vivo whole-brain myelin water fraction map in approximately 10 minutes. It has been applied in various applications including neurodegenerative disease, neurodevelopmental, and neuroplasticity studies. In this review we start with a brief introduction of myelin biology and discuss the contributions of myelin in conventional MRI contrasts. Then the MRI properties of myelin water and four different MWI methods, which are categorized as T2 -, T2 *-, T1 -, and steady-state-based MWI, are summarized. After that, we cover more practical issues such as availability, interpretation, and validation of these methods. To illustrate the utility of MWI as a clinical research tool, MWI studies for two diseases, multiple sclerosis and neuromyelitis optica, are introduced. Additional topics about imaging myelin in gray matter and non-MWI methods for myelin imaging are also included. Although technical and physiological limitations exist, MWI is a potent surrogate biomarker of myelin that carries valuable and useful information of myelin. Evidence Level: 5 Technical Efficacy: 1 J. MAGN. RESON. IMAGING 2021;53:360-373.
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Affiliation(s)
- Jongho Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Jae-Won Hyun
- Department of Neurology, Research Institute and Hospital, National Cancer Center, Goyang-si, Korea
| | - Jieun Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Eun-Jung Choi
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Hyeong-Geol Shin
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Kyeongseon Min
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Yoonho Nam
- Department of Radiology, Seoul Saint Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, Korea
| | - Ho Jin Kim
- Department of Neurology, Research Institute and Hospital, National Cancer Center, Goyang-si, Korea
| | - Se-Hong Oh
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Gyeonggi-do, Korea.,Imaging Institute, Cleveland Clinic, Cleveland, OH, USA
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23
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Chen Q, She H, Du YP. Improved quantification of myelin water fraction using joint sparsity of T2* distribution. J Magn Reson Imaging 2019; 52:146-158. [DOI: 10.1002/jmri.27013] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 11/20/2019] [Accepted: 11/20/2019] [Indexed: 12/23/2022] Open
Affiliation(s)
- Quan Chen
- Institute for Medical Imaging Technology, School of Biomedical EngineeringShanghai Jiao Tong University Shanghai China
| | - Huajun She
- Institute for Medical Imaging Technology, School of Biomedical EngineeringShanghai Jiao Tong University Shanghai China
| | - Yiping P. Du
- Institute for Medical Imaging Technology, School of Biomedical EngineeringShanghai Jiao Tong University Shanghai China
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24
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Guglielmetti C, Boucneau T, Cao P, Van der Linden A, Larson PEZ, Chaumeil MM. Longitudinal evaluation of demyelinated lesions in a multiple sclerosis model using ultrashort echo time magnetization transfer (UTE-MT) imaging. Neuroimage 2019; 208:116415. [PMID: 31811900 DOI: 10.1016/j.neuroimage.2019.116415] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 11/16/2019] [Accepted: 11/28/2019] [Indexed: 11/27/2022] Open
Abstract
Alterations in myelin integrity are involved in many neurological disorders and demyelinating diseases, such as multiple sclerosis (MS). Although magnetic resonance imaging (MRI) is the gold standard method to diagnose and monitor MS patients, clinically available MRI protocols show limited specificity for myelin detection, notably in cerebral grey matter areas. Ultrashort echo time (UTE) MRI has shown great promise for direct imaging of lipids and myelin sheaths, and thus holds potential to improve lesion detection. In this study, we used a sequence combining magnetization transfer (MT) with UTE ("UTE-MT", TE = 76 μs) and with short TE ("STE-MT", TE = 3000 μs) to evaluate spatial and temporal changes in brain myelin content in the cuprizone mouse model for MS on a clinical 7 T scanner. During demyelination, UTE-MT ratio (UTE-MTR) and STE-MT ratio (STE-MTR) values were significantly decreased in most white matter and grey matter regions. However, only UTE-MTR detected cortical changes. After remyelination in subcortical and cortical areas, UTE-MTR values remained lower than baseline values, indicating that UTE-MT, but not STE-MT, imaging detected long-lasting changes following a demyelinating event. Next, we evaluated the potential correlations between imaging values and underlying histopathological markers. The strongest correlation was observed between UTE-MTR and percent coverage of myelin basic protein (MBP) immunostaining (r2 = 0.71). A significant, although lower, correlation was observed between STE-MTR and MBP (r2 = 0.48), and no correlation was found between UTE-MTR or STE-MTR and gliosis immunostaining. Interestingly, correlations varied across brain substructures. Altogether, our results demonstrate that UTE-MTR values significantly correlate with myelin content as measured by histopathology, not only in white matter, but also in subcortical and cortical grey matter regions in the cuprizone mouse model for MS. Readily implemented on a clinical 7 T system, this approach thus holds great potential for detecting demyelinating/remyelinating events in both white and grey matter areas in humans. When applied to patients with neurological disorders, including MS patient populations, UTE-MT methods may improve the non-invasive longitudinal monitoring of brain lesions, not only during disease progression but also in response to next generation remyelinating therapies.
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Affiliation(s)
- Caroline Guglielmetti
- Department of Physical Therapy and Rehabilitation Science, University of California, San Francisco, CA, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA; Bio-Imaging Laboratory, Department of Biomedical Sciences, University of Antwerp, 2000, Antwerp, Belgium
| | - Tanguy Boucneau
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Peng Cao
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Annemie Van der Linden
- Bio-Imaging Laboratory, Department of Biomedical Sciences, University of Antwerp, 2000, Antwerp, Belgium
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA; UC Berkeley-UCSF Graduate Program in Bioengineering, Berkeley and University of California, San Francisco, CA, USA
| | - Myriam M Chaumeil
- Department of Physical Therapy and Rehabilitation Science, University of California, San Francisco, CA, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA; UC Berkeley-UCSF Graduate Program in Bioengineering, Berkeley and University of California, San Francisco, CA, USA.
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25
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7T GRE-MRI signal compartments are sensitive to dysplastic tissue in focal epilepsy. Magn Reson Imaging 2019; 61:1-8. [DOI: 10.1016/j.mri.2019.05.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Revised: 04/19/2019] [Accepted: 05/04/2019] [Indexed: 12/11/2022]
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26
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Shin HG, Oh SH, Fukunaga M, Nam Y, Lee D, Jung W, Jo M, Ji S, Choi JY, Lee J. Advances in gradient echo myelin water imaging at 3T and 7T. Neuroimage 2019; 188:835-844. [DOI: 10.1016/j.neuroimage.2018.11.040] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 11/22/2018] [Accepted: 11/22/2018] [Indexed: 12/18/2022] Open
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27
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Tendler BC, Bowtell R. Frequency difference mapping applied to the corpus callosum at 7T. Magn Reson Med 2018; 81:3017-3031. [PMID: 30582226 PMCID: PMC6492142 DOI: 10.1002/mrm.27626] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 10/21/2018] [Accepted: 11/14/2018] [Indexed: 12/19/2022]
Abstract
Purpose Frequency difference mapping (FDM) is a phase processing technique which characterizes the nonlinear temporal evolution of the phase of gradient echo (GE) signals. Here, a novel FDM‐processing algorithm is introduced, which is shown to reveal information about white matter microstructure. Unlike some other phase‐processing techniques, the FDM algorithm presented here does not require the use of phase unwrapping or sophisticated image processing. It uses a series of scaled complex divisions to unwrap phase and remove background fields. Methods Ten healthy subjects underwent a series of single‐slice, sagittal multi‐echo GE scans at 7T with the slice positioned at the midline. Phase data were processed with the novel FDM algorithm, and the temporal evolution of the magnitude signal and frequency difference was examined in 5 regions of the corpus callosum (CC; genu, anterior body, middle body, posterior body, and splenium). Results Consistent frequency difference contrast relative to surrounding tissue was observed in all subjects in the CC and in other white matter regions where the nerve fibers run perpendicular to B0, such as the superior cerebellar peduncle. Examination of the frequency difference curves shows distinct variations over the CC, with the genu and splenium displaying larger frequency differences than the other regions (in addition to a faster decay of signal magnitude). Conclusion The novel FDM algorithm presented here yields images sensitive to tissue microstructure and microstructural differences over the CC in a simple manner, without the requirement for phase unwrapping or sophisticated image processing.
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Affiliation(s)
- Benjamin C Tendler
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, United Kingdom.,Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, United Kingdom
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28
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Kurz FT, Buschle LR, Hahn A, Jende JME, Bendszus M, Heiland S, Ziener CH. Diffusion effects in myelin sheath free induction decay. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2018; 297:61-75. [PMID: 30366221 DOI: 10.1016/j.jmr.2018.10.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Revised: 09/27/2018] [Accepted: 10/01/2018] [Indexed: 06/08/2023]
Abstract
Myelin sheath microstructure and composition produce MR signal decay characteristics that can be used to evaluate status and outcome of demyelinating disease. We extend a recently proposed model of neuronal magnetic susceptibility, that accounts for both the structural and inherent anisotropy of the myelin sheath, by including the whole dynamic range of diffusion effects. The respective Bloch-Torrey equation for local spin dephasing is solved with a uniformly convergent perturbation expansion method, and the resulting magnetization decay is validated with a numerical solution based on a finite difference method. We show that a variation of diffusion strengths can lead to substantially different MR signal decay curves. Our results may be used to adjust or control simulations for water diffusion in neuronal structures.
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Affiliation(s)
- F T Kurz
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany; German Cancer Research Center, INF 280, D-69120 Heidelberg, Germany.
| | - L R Buschle
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany; German Cancer Research Center, INF 280, D-69120 Heidelberg, Germany; Heidelberg University, Faculty of Physics and Astronomy, INF 227, D-69120 Heidelberg, Germany
| | - A Hahn
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany
| | - J M E Jende
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany
| | - M Bendszus
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany
| | - S Heiland
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany
| | - C H Ziener
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany; German Cancer Research Center, INF 280, D-69120 Heidelberg, Germany.
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Alonso-Ortiz E, Levesque IR, Pike GB. Impact of magnetic susceptibility anisotropy at 3 T and 7 T on T2*-based myelin water fraction imaging. Neuroimage 2018; 182:370-378. [DOI: 10.1016/j.neuroimage.2017.09.040] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 08/14/2017] [Accepted: 09/20/2017] [Indexed: 10/18/2022] Open
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30
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Wang CY, Coppo S, Mehta BB, Seiberlich N, Yu X, Griswold MA. Magnetic resonance fingerprinting with quadratic RF phase for measurement of T 2 * simultaneously with δ f , T 1 , and T 2. Magn Reson Med 2018; 81:1849-1862. [PMID: 30499221 DOI: 10.1002/mrm.27543] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Revised: 08/29/2018] [Accepted: 08/30/2018] [Indexed: 11/07/2022]
Abstract
PURPOSE This study explores the possibility of using a gradient moment balanced sequence with a quadratically varied RF excitation phase in the magnetic resonance fingerprinting (MRF) framework to quantify T2 * in addition to δ f , T1 , and T2 tissue properties. METHODS The proposed quadratic RF phase-based MRF method (qRF-MRF) combined a varied RF excitation phase with the existing balanced SSFP (bSSFP)-based MRF method to generate signals that were uniquely sensitive to δ f , T1 , T2 , as well as the distribution width of intravoxel frequency dispersion, Γ . A dictionary, generated through Bloch simulation, containing possible signal evolutions within the physiological range of δ f , T1 , T2 , and Γ , was used to perform parameter estimation. The estimated T2 and Γ were subsequently used to estimate T2 * . The proposed method was evaluated in phantom experiments and healthy volunteers (N = 5). RESULTS The T1 and T2 values from the phantom by qRF-MRF demonstrated good agreement with values obtained by traditional gold standard methods (r2 = 0.995 and 0.997, respectively; concordance correlation coefficient = 0.978 and 0.995, respectively). The T2 * values from the phantom demonstrated good agreement with values obtained through the multi-echo gradient-echo method (r2 = 0.972, concordance correlation coefficient = 0.983). In vivo qRF-MRF-measured T1 , T2 , and T2 * values were compared with measurements by existing methods and literature values. CONCLUSION The proposed qRF-MRF method demonstrated the potential for simultaneous quantification of δ f , T1 , T2 , and T2 * tissue properties.
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Affiliation(s)
- Charlie Yi Wang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Simone Coppo
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | | | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | - Xin Yu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | - Mark Alan Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Department of Radiology, Case Western Reserve University, Cleveland, Ohio
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31
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Lee H, Nam Y, Kim D. Echo time‐range effects on gradient‐echo based myelin water fraction mapping at 3T. Magn Reson Med 2018; 81:2799-2807. [DOI: 10.1002/mrm.27564] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2018] [Revised: 09/15/2018] [Accepted: 09/19/2018] [Indexed: 12/19/2022]
Affiliation(s)
- Hongpyo Lee
- Department of Electrical and Electronic Engineering Yonsei University Seoul Korea
| | - Yoonho Nam
- Department of Radiology Seoul St. Mary’s Hospital, College of Medicine, the Catholic University of Korea Seoul Korea
| | - Dong‐Hyun Kim
- Department of Electrical and Electronic Engineering Yonsei University Seoul Korea
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32
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Foxley S, Karczmar GS, Takahashi K. The effects of variations in tissue microstructure from postmortem rat brain on the asymmetry of the water proton resonance. Magn Reson Med 2018; 81:79-89. [PMID: 30014543 DOI: 10.1002/mrm.27338] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 03/23/2018] [Accepted: 04/10/2018] [Indexed: 12/13/2022]
Abstract
PURPOSE This work was performed to investigate the effects of tissue microstructure from postmortem rat brain on the shape of the water proton spectrum. METHODS Perfusion-fixed, resected rat brains (N = 4) were imaged at 9.4T. 3D DTI and 3D echo-planar spectroscopic imaging (EPSI) data were acquired with 150 μm isotropic resolution. DTI data were acquired over 60 directions with b = 3000 s/mm2 . Water spectra were produced from EPSI data acquired over 128 echoes, with 2.9 Hz spectral resolution. A voxel-wise metric reflecting spectral asymmetry about the peak of the resonance was computed and compared with orientation estimates from DTI data by fitting data with the susceptibility anisotropy model. RESULTS Asymmetric broadening of the water resonance was computed for mixed populations of grey and/or white matter as determined by thresholding the fractional anisotropy. Asymmetry was shown to be differentially affected by tract orientation relative to B0 in high FA voxels, whereas low FA voxels exhibited little sensitivity. Anatomic structures in the hippocampus were also found to produce distinct changes in the water resonance. CONCLUSION Present results demonstrate that structural variations in tissue architecture cause characteristic, reproducible changes in the water resonance shape. This suggests that water spectra are sensitive to cytoarchitectural variations in brain tissue.
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Affiliation(s)
- Sean Foxley
- MRI Research Center, Department of Radiology, University of Chicago, Chicago, Illinois
| | - Gregory S Karczmar
- MRI Research Center, Department of Radiology, University of Chicago, Chicago, Illinois
| | - Kazutaka Takahashi
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois
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33
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Kadamangudi S, Reutens D, Sood S, Vegh V. Signal compartments in ultra-high field multi-echo gradient echo MRI reflect underlying tissue microstructure in the brain. Neuroimage 2018; 178:403-413. [PMID: 29852284 DOI: 10.1016/j.neuroimage.2018.05.061] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Revised: 05/24/2018] [Accepted: 05/25/2018] [Indexed: 10/14/2022] Open
Abstract
Gradient recalled echo magnetic resonance imaging (GRE-MRI) at ultra-high field holds great promise for new contrast mechanisms and delineation of putative tissue compartments that contribute to the multi-echo GRE-MRI signal may aid structural characterization. Several studies have adopted the three water-pool compartment model to study white matter brain regions, associating individual compartments with myelin, axonal and extracellular water. However, the number and identifiability of GRE-MRI signal compartments has not been fully explored. We undertook this task for human brain imaging data. Multiple echo time GRE-MRI data were acquired in five healthy participants, specific anatomical structures were segmented in each dataset (substantia nigra, caudate, insula, putamen, thalamus, fornix, internal capsule, corpus callosum and cerebrospinal fluid), and the signal fitted with models comprising one to six signal compartments using a complex-valued plane wave formulation. Information criteria and cluster analysis methods were used to ascertain the number of distinct compartments within the signal from each structure and to determine their respective frequency shifts. We identified five principal signal compartments with different relative contributions to each structure's signal. Voxel-based maps of the volume fraction of each of these compartments were generated and demonstrated spatial correlation with brain anatomy.
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Affiliation(s)
- Shrinath Kadamangudi
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia; Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
| | - David Reutens
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Surabhi Sood
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Viktor Vegh
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia.
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34
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Lee H, Nam Y, Lee HJ, Hsu JJ, Henry RG, Kim DH. Improved three-dimensional multi-echo gradient echo based myelin water fraction mapping with phase related artifact correction. Neuroimage 2018; 169:1-10. [DOI: 10.1016/j.neuroimage.2017.11.058] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Revised: 11/21/2017] [Accepted: 11/25/2017] [Indexed: 12/17/2022] Open
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MRI gradient-echo phase contrast of the brain at ultra-short TE with off-resonance saturation. Neuroimage 2018; 175:1-11. [PMID: 29604452 DOI: 10.1016/j.neuroimage.2018.03.066] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Revised: 03/07/2018] [Accepted: 03/28/2018] [Indexed: 02/06/2023] Open
Abstract
Larmor-frequency shift or image phase measured by gradient-echo sequences has provided a new source of MRI contrast. This contrast is being used to study both the structure and function of the brain. So far, phase images of the brain have been largely obtained at long echo times as maximum phase signal-to-noise ratio (SNR) is achieved at TE = T2* (∼40 ms at 3T). The structures of the brain, however, are compartmentalized and complex with a wide range of signal relaxation times. At such long TE, the short-T2 components are largely attenuated and contribute minimally to phase contrast. The purpose of this study was to determine whether proton gradient-echo images of the brain exhibit phase contrast at ultra-short TE (UTE). Our data showed that UTE images acquired at 7 T without off-resonance saturation do not contain significant phase contrast between gray and white matter. However, UTE images of the brain can attain strong phase contrast even at a nominal TE of 106 μs by using off-resonance RF saturation pulses, which provide direct saturation of ultra-short-T2 components and indirect saturation of longer-T2 components via magnetization transfer. In addition, phase contrast between gray and white matter acquired at UTE with off-resonance saturation is reversed compared to that of the long-T2 signals acquired at long TEs. This finding opens up a potential new way to manipulate image phase contrast of the brain. By accessing short and ultra-short-T2 species, MRI phase images may further improve the characterization of tissue microstructure in the brain.
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36
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Duyn JH. Studying brain microstructure with magnetic susceptibility contrast at high-field. Neuroimage 2018; 168:152-161. [PMID: 28242317 PMCID: PMC5569005 DOI: 10.1016/j.neuroimage.2017.02.046] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 02/03/2017] [Accepted: 02/16/2017] [Indexed: 12/14/2022] Open
Abstract
A rapidly developing application of high field MRI is the study of brain anatomy and function with contrast based on the magnetic susceptibility of tissues. To study the subtle variations in susceptibility contrast between tissues and with changes in brain activity, dedicated scan techniques such as susceptibility-weighted MRI and blood-oxygen level dependent functional MRI have been developed. Particularly strong susceptibility contrast has been observed with systems that operate at 7T and above, and their recent widespread use has led to an improved understanding of contributing sources and mechanisms. To interpret magnetic susceptibility contrast, analysis approaches have been developed with the goal of extracting measures that report on local tissue magnetic susceptibility, a physical quantity that, under certain conditions, allows estimation of blood oxygenation, local tissue iron content, and quantification of its changes with disease. Interestingly, high field studies have also brought to light that not only the makeup of tissues affects MRI susceptibility contrast, but that also a tissue's sub-voxel structure at scales all the way down to the molecular level plays an important role as well. In this review, various ways will be discussed by which sub-voxel structure can affect the MRI signal in general, and magnetic susceptibility in particular, sometimes in a complex fashion. In the light of this complexity, it appears likely that accurate, brain-wide quantification of iron will require the combination of multiple contrasts that may include diffusion and magnetization transfer information with susceptibility-weighted contrast. On the other hand, this complexity also offers opportunities to use magnetic susceptibility contrast to inform about specific microstructural aspects of brain tissue. Details and several examples will be presented in this review.
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Affiliation(s)
- Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institutes of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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37
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Lee D, Lee J, Lee J, Nam Y. Single-scan z-shim method for reducing susceptibility artifacts in gradient echo myelin water imaging. Magn Reson Med 2018; 80:1101-1109. [DOI: 10.1002/mrm.27127] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Revised: 01/14/2018] [Accepted: 01/21/2018] [Indexed: 11/11/2022]
Affiliation(s)
- Doohee Lee
- Department of Electrical and Computer Engineering; Seoul National University; Seoul Korea
| | - Jingu Lee
- Department of Electrical and Computer Engineering; Seoul National University; Seoul Korea
| | - Jongho Lee
- Department of Electrical and Computer Engineering; Seoul National University; Seoul Korea
| | - Yoonho Nam
- Department of Radiology; Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea; Seoul Korea
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Does MD. Inferring brain tissue composition and microstructure via MR relaxometry. Neuroimage 2018; 182:136-148. [PMID: 29305163 DOI: 10.1016/j.neuroimage.2017.12.087] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2017] [Revised: 12/25/2017] [Accepted: 12/27/2017] [Indexed: 11/28/2022] Open
Abstract
MRI relaxometry is sensitive to a variety of tissue characteristics in a complex manner, which makes it both attractive and challenging for characterizing tissue. This article reviews the most common water proton relaxometry measures, T1, T2, and T2*, and reports on their development and current potential to probe the composition and microstructure of brain tissue. The development of these relaxometry measures is challenged by the need for suitably accurate tissue models, as well as robust acquisition and analysis methodologies. MRI relaxometry has been established as a tool for characterizing neural tissue, particular with respect to myelination, and the potential for further development exists.
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Affiliation(s)
- Mark D Does
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA.
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39
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Yen CCC, Papoti D, Silva AC. Investigating the spatiotemporal characteristics of the deoxyhemoglobin-related and deoxyhemoglobin-unrelated functional hemodynamic response across cortical layers in awake marmosets. Neuroimage 2018; 164:121-130. [PMID: 28274833 PMCID: PMC5587354 DOI: 10.1016/j.neuroimage.2017.03.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2016] [Revised: 03/01/2017] [Accepted: 03/02/2017] [Indexed: 01/05/2023] Open
Abstract
Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) has become a major tool to map neural activity. However, the spatiotemporal characteristics of the BOLD functional hemodynamic response across the cortical layers remain poorly understood. While human fMRI studies suffer from low spatiotemporal resolution, the use of anesthesia in animal models introduces confounding factors. Additionally, inflow contributions to the fMRI signal become non-negligible when short repetition times (TRs) are used. In the present work, we mapped the BOLD fMRI response to somatosensory stimulation in awake marmosets. To address the above technical concerns, we used a dual-echo gradient-recalled echo planar imaging (GR-EPI) sequence to separate the deoxyhemoglobin-related response (absolute T2* differences) from the deoxyhemoglobin-unrelated response (relative S0 changes). We employed a spatial saturation pulse to saturate incoming arterial spins and reduce inflow effects. Functional GR-EPI images were obtained from a single coronal slice with two different echo times (13.5 and 40.5ms) and TR=0.2s. BOLD, T2*, and S0 images were calculated and their functional responses were detected in both hemispheres of primary somatosensory cortex, from which five laminar regions (L1+2, L3, L4, L5, and L6) were derived. The spatiotemporal distribution of the BOLD response across the cortical layers was heterogeneous, with the middle layers having the highest BOLD amplitudes and shortest onset times. ΔT2* also showed a similar trend. However, functional S0 changes were detected only in L1+2, with a fast onset time. Because inflow effects were minimized, the source of S0 functional changes in L1+2 could be attributed to a reduction of cerebrospinal fluid volume fraction due to the functional increase in cerebral blood volume and to unmodeled T2* changes in the extra- and intra-venous compartments. Caution should be exercised when interpreting laminar BOLD fMRI changes in superficial layers as surrogates of underlying neural activity.
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Affiliation(s)
- Cecil Chern-Chyi Yen
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Daniel Papoti
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Afonso C Silva
- Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
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40
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Boucneau T, Cao P, Tang S, Han M, Xu D, Henry RG, Larson PEZ. In vivo characterization of brain ultrashort-T 2 components. Magn Reson Med 2017; 80:726-735. [PMID: 29194734 DOI: 10.1002/mrm.27037] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2017] [Revised: 11/14/2017] [Accepted: 11/17/2017] [Indexed: 12/22/2022]
Abstract
PURPOSE Recent nuclear magnetic resonance and MRI studies have measured a fast-relaxing signal component with T2∗<1 ms in white matter and myelin extracts. In ex vivo studies, evidence suggests that a large fraction of this component directly arises from bound protons in the myelin phospholipid membranes. Based on these results, this ultrashort-T2 component in nervous tissue is a new potential imaging biomarker of myelination, which plays a critical role in neuronal signal conduction across the brain and loss or degradation of myelin is a key feature of many neurological disorders. The goal of this work was to characterize the relaxation times and frequency shifts of ultrashort-T2 components in the human brain. METHODS This required development of an ultrashort echo time relaxometry acquisition strategy and fitting procedure for robust measurements in the presence of ultrashort T2∗ relaxation times and large frequency shifts. RESULTS We measured an ultrashort-T2 component in healthy volunteers with a median T2∗ between 0.5-0.7 ms at 3T and 0.2-0.3 ms at 7T as well as an approximately -3 ppm frequency shift from water. CONCLUSION To our knowledge, this is the first time a chemical shift of the ultrashort-T2 brain component has been measured in vivo. This chemical shift, at around 1.7 ppm, is similar to the primary resonance of most lipids, indicating that much of the ultrashort-T2 component observed in vivo arises from bound protons in the myelin phospholipid membranes. Magn Reson Med 80:726-735, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Tanguy Boucneau
- Department of Physics, Ecole Normale Supérieure de Cachan, Cachan, France
| | - Peng Cao
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Shuyu Tang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA.,UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley, Berkeley, California, USA
| | - Misung Han
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA.,UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley, Berkeley, California, USA
| | - Roland G Henry
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA.,UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley, Berkeley, California, USA.,Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA.,UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley, Berkeley, California, USA
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41
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Thapaliya K, Vegh V, Bollmann S, Barth M. Assessment of microstructural signal compartments across the corpus callosum using multi-echo gradient recalled echo at 7 T. Neuroimage 2017; 182:407-416. [PMID: 29183776 DOI: 10.1016/j.neuroimage.2017.11.029] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Revised: 11/06/2017] [Accepted: 11/15/2017] [Indexed: 12/18/2022] Open
Abstract
Quantitative assessment of tissue microstructure is important in studying human brain diseases and disorders in which white matter is implicated, as it has been linked to demyelination, re-myelination, and axonal damage in clinical conditions. Ultra-high field magnetic resonance imaging data obtained using a multi-echo gradient echo sequence has been shown to contain information on myelin, axonal and extracellular compartments in white matter. In this study, we aimed to assess the sensitivity of a three-compartment model to estimate the variation of corresponding compartment parameters (water fraction, relaxation time and frequency shift) of the corpus callosum sub-regions, which are known to have different tissue structure. Additionally, we computed the g-ratio using myelin and axonal water fractions and performed a voxel-by-voxel analysis in the corpus callosum. Based on data acquired for ten participants, we show that the myelin compartment water fraction and T2∗ is consistent across the corpus callosum sub-regions, whilst myelin frequency shift varies. The results show that the variation in water fraction, T2∗ and frequency shift for the myelin signal compartment across the corpus callosum is smaller than for the axonal and extracellular signal compartments. The computed g-ratio was comparable to previously published studies in the corpus callosum. Our study suggests that a multi-echo GRE approach in vivo combined with a complex three-compartment model is sensitive to microstructural parameter variations across the human corpus callosum.
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Affiliation(s)
- Kiran Thapaliya
- Centre for Advanced Imaging, The University of Queensland, Queensland, Australia
| | - Viktor Vegh
- Centre for Advanced Imaging, The University of Queensland, Queensland, Australia
| | - Steffen Bollmann
- Centre for Advanced Imaging, The University of Queensland, Queensland, Australia
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, Queensland, Australia.
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42
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Oros-Peusquens A, Loução R, Zimmermann M, Langen KJ, Shah N. Methods for molecular imaging of brain tumours in a hybrid MR-PET context: Water content, T 2 ∗ , diffusion indices and FET-PET. Methods 2017; 130:135-151. [DOI: 10.1016/j.ymeth.2017.07.025] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Revised: 05/22/2017] [Accepted: 07/27/2017] [Indexed: 11/27/2022] Open
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43
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Benjamini D, Basser PJ. Magnetic resonance microdynamic imaging reveals distinct tissue microenvironments. Neuroimage 2017; 163:183-196. [PMID: 28943412 DOI: 10.1016/j.neuroimage.2017.09.033] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2017] [Revised: 09/12/2017] [Accepted: 09/18/2017] [Indexed: 10/18/2022] Open
Abstract
Magnetic resonance imaging (MRI) provides a powerful set of tools with which to investigate biological tissues noninvasively and in vivo. Tissues are heterogeneous in nature; an imaging voxel contains an ensemble of different cells and extracellular matrix components. A long-standing challenge has been to infer the content of and interactions among these microscopic tissue components within a macroscopic imaging voxel. Spatially resolved multidimensional relaxation-diffusion correlation (REDCO) spectroscopy holds the potential to deliver such microdynamic information. However, to date, vast data requirements have mostly relegated these type of measurements to nuclear magnetic resonance applications and prevented them from being widely and successfully used in conjunction with imaging. By using a novel data acquisition and processing strategy in this study, spatially resolved REDCO could be performed in reasonable scanning times with excellent prospects for clinical applications. This new MR imaging framework-which we term "magnetic resonance microdynamic imaging (MRMI)"-permits the simultaneous noninvasive and model-free quantification of multiple subcellular, cellular, and interstitial tissue microenvironments within a voxel. MRMI is demonstrated with a fixed spinal cord specimen, enabling the quantification of microscopic tissue components with unprecedented specificity. Tissue components, such as axons, neuronal and glial soma, and myelin were identified on the basis of their multispectral signature within individual imaging voxels. These tissue elements could then be composed into images and be correlated with immunohistochemistry findings. MRMI provides novel image contrasts of tissue components and a new family of microdynamic biomarkers that could lead to new diagnostic imaging approaches to probe biological tissue alterations accompanied by pathological or developmental changes.
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Affiliation(s)
- Dan Benjamini
- Section on Quantitative Imaging and Tissue Sciences, NICHD, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Peter J Basser
- Section on Quantitative Imaging and Tissue Sciences, NICHD, National Institutes of Health, Bethesda, MD 20892, USA
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44
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Alonso-Ortiz E, Levesque IR, Pike GB. Multi-gradient-echo myelin water fraction imaging: Comparison to the multi-echo-spin-echo technique. Magn Reson Med 2017; 79:1439-1446. [DOI: 10.1002/mrm.26809] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Revised: 05/06/2017] [Accepted: 05/31/2017] [Indexed: 12/19/2022]
Affiliation(s)
- Eva Alonso-Ortiz
- Department of Medical Physics; The Ottawa Hospital Cancer Centre; Ottawa Canada
| | - Ives R. Levesque
- Medical Physics Unit, McGill University; Montreal Canada
- Department of Oncology; McGill University; Montreal Canada
- Research Institute of the McGill University Health Centre; McGill University; Montreal Canada
| | - G. Bruce Pike
- Medical Physics Unit, McGill University; Montreal Canada
- McConnell Brain Imaging Centre, McGill University; Montreal Canada
- Department of Radiology and Hotchkiss Brain Institute; University of Calgary; Calgary Canada
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45
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Wu Z, He H, Sun Y, Du Y, Zhong J. High resolution myelin water imaging incorporating local tissue susceptibility analysis. Magn Reson Imaging 2017. [PMID: 28629954 DOI: 10.1016/j.mri.2017.06.005] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Quantitative myelin water imaging (MWI) from signal T2* decay acquired with multiple Gradient-Recalled Echo (mGRE) sequence has been widely used since its first report. A recent study showed that with low resolution data (2mm isotropic voxels), direct application of complex fitting to a three-pool WM model with frequency shift terms could produce more stable parameter estimation for myelin water fraction mapping. MWI maps of higher spatial resolution resulting in more detailed tissue structures and reduced partial volume effects around white matter/gray matter (WM/GM) interface, however, is more desirable. Furthermore, as signal-to-noise ratio (SNR) of original images decreases due to reduced voxel size, the direct complex fitting procedure of myelin water imaging becomes more prone to systematic errors which severely compromised stability and reliability of the result. Instead of using the original part of T2* decay, this work presents a new method based on the WM-induced phase from tissue susceptibility calculated with the same mGRE dataset, in a three-pool WM model (water of myelin, axonal and extracellular water), to improve high resolution MWI. Compared with direct complex fitting for the higher spatial resolution case, the proposed method is shown to provide a more stable and accurate estimation of MWI parameters, and finer details near WM/GM boundaries with greatly reduced partial volume effects.
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Affiliation(s)
- Zhe Wu
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Yi Sun
- MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China
| | - Yiping Du
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China; Center for Innovative and Collaborative Detection and Treatment of Infectious Diseases, Zhejiang University, Hangzhou, Zhejiang, China; Department of Imaging Sciences, University of Rochester, NY, USA.
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46
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Nguyen TD, Spincemaille P, Gauthier SA, Wang Y. Rapid whole brain myelin water content mapping without an external water standard at 1.5 T. Magn Reson Imaging 2017; 39:82-88. [DOI: 10.1016/j.mri.2016.12.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Revised: 12/20/2016] [Accepted: 12/21/2016] [Indexed: 12/18/2022]
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47
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Shcherbakova Y, van den Berg CAT, Moonen CTW, Bartels LW. PLANET: An ellipse fitting approach for simultaneous T 1 and T 2 mapping using phase-cycled balanced steady-state free precession. Magn Reson Med 2017; 79:711-722. [PMID: 28543430 PMCID: PMC5811804 DOI: 10.1002/mrm.26717] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Revised: 03/23/2017] [Accepted: 03/26/2017] [Indexed: 11/09/2022]
Abstract
Purpose To demonstrate the feasibility of a novel, ellipse fitting approach, named PLANET, for simultaneous estimation of relaxation times T1 and T2 from a single 3D phase‐cycled balanced steady‐state free precession (bSSFP) sequence. Methods A method is presented in which the elliptical signal model is used to describe the phase‐cycled bSSFP steady‐state signal. The fitting of the model to the acquired data is reformulated into a linear convex problem, which is solved directly by a linear least squares method, specific to ellipses. Subsequently, the relaxation times T1 and T2, the banding free magnitude, and the off‐resonance are calculated from the fitting results. Results Maps of T1 and T2, as well as an off‐resonance and a banding free magnitude can be simultaneously, quickly, and robustly estimated from a single 3D phase‐cycled bSSFP sequence. The feasibility of the method was demonstrated in a phantom and in the brain of healthy volunteers on a clinical MR scanner. The results were in good agreement for the phantom, but a systematic underestimation of T1 was observed in the brain. Conclusion The presented method allows for accurate mapping of relaxation times and off‐resonance, and for the reconstruction of banding free magnitude images at realistic signal‐to‐noise ratios. Magn Reson Med 79:711–722, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
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Affiliation(s)
- Yulia Shcherbakova
- Center for Image Sciences, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelis A T van den Berg
- Department of Radiotherapy, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Chrit T W Moonen
- Center for Image Sciences, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lambertus W Bartels
- Center for Image Sciences, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
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48
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Ruh A, Scherer H, Kiselev VG. The larmor frequency shift in magnetically heterogeneous media depends on their mesoscopic structure. Magn Reson Med 2017; 79:1101-1110. [PMID: 28524556 DOI: 10.1002/mrm.26753] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Revised: 04/19/2017] [Accepted: 04/20/2017] [Indexed: 11/08/2022]
Abstract
PURPOSE Recent studies have addressed the determination of the NMR precession frequency in biological tissues containing magnetic susceptibility differences between cell types. The purpose of this study is to investigate the dependence of the precession frequency on medium microstructure using a simple physical model. THEORY This dependence is governed by diffusion of NMR-visible molecules in magnetically heterogeneous microenvironments. In the limit of fast diffusion, the precession frequency is determined by the average susceptibility-induced magnetic field, whereas in the limit of slow diffusion it is determined by the average local phase factor of precessing spins. METHODS The main method used is Monte Carlo simulation of isotropic suspensions of impermeable magnetized spheres. In addition, NMR spectroscopy was performed in aqueous suspensions of polystyrene microbeads. RESULTS The precession frequency depends on the structural organization of magnetized objects in the medium. Monte Carlo simulations demonstrated a nonmonotonic transition between the regimes of fast and slow diffusion. NMR experiments confirmed the transition, but were unable to confirm its precise form. Results for a given pattern of structural organization obey a scaling law. CONCLUSION The NMR precession frequency exhibits a complex dependence on medium structure. Our results suggest that the commonly assumed limit of fast water diffusion holds for biological tissues with small cells. Magn Reson Med 79:1101-1110, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Alexander Ruh
- Medical Physics, Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Harald Scherer
- Institute of Inorganic and Analytical Chemistry, University of Freiburg, Freiburg, Germany
| | - Valerij G Kiselev
- Medical Physics, Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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49
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Duyn JH, Schenck J. Contributions to magnetic susceptibility of brain tissue. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3546. [PMID: 27240118 PMCID: PMC5131875 DOI: 10.1002/nbm.3546 10.1002/nbm.3546] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 02/19/2016] [Accepted: 03/31/2016] [Indexed: 11/17/2023]
Abstract
This review discusses the major contributors to the subtle magnetic properties of brain tissue and how they affect MRI contrast. With the increased availability of high-field scanners, the use of magnetic susceptibility contrast for the study of human brain anatomy and function has increased dramatically. This has not only led to novel applications, but has also improved our understanding of the complex relationship between MRI contrast and magnetic susceptibility. Chief contributors to the magnetic susceptibility of brain tissue have been found to include myelin as well as iron. In the brain, iron exists in various forms with diverse biological roles, many of which are now only starting to be uncovered. An interesting aspect of magnetic susceptibility contrast is its sensitivity to the microscopic distribution of iron and myelin, which provides opportunities to extract information at spatial scales well below MRI resolution. For example, in white matter, the myelin sheath that surrounds the axons can provide tissue contrast that is dependent on the axonal orientation and reflects the relative size of intra- and extra-axonal water compartments. The extraction of such ultrastructural information, together with quantitative information about iron and myelin concentrations, is an active area of research geared towards the characterization of brain structure and function, and their alteration in disease. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Jeff H. Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular
Imaging, National Institutes of Neurological Disorders and Stroke, National
Institutes of Health, Bethesda, Maryland 20892, USA
| | - John Schenck
- MRI Technologies and Systems, General Electric
Global Research Center, 1 Research Circle, Schenectady, New York 12309, USA
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50
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Duyn JH, Schenck J. Contributions to magnetic susceptibility of brain tissue. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3546. [PMID: 27240118 PMCID: PMC5131875 DOI: 10.1002/nbm.3546] [Citation(s) in RCA: 102] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 02/19/2016] [Accepted: 03/31/2016] [Indexed: 05/08/2023]
Abstract
This review discusses the major contributors to the subtle magnetic properties of brain tissue and how they affect MRI contrast. With the increased availability of high-field scanners, the use of magnetic susceptibility contrast for the study of human brain anatomy and function has increased dramatically. This has not only led to novel applications, but has also improved our understanding of the complex relationship between MRI contrast and magnetic susceptibility. Chief contributors to the magnetic susceptibility of brain tissue have been found to include myelin as well as iron. In the brain, iron exists in various forms with diverse biological roles, many of which are now only starting to be uncovered. An interesting aspect of magnetic susceptibility contrast is its sensitivity to the microscopic distribution of iron and myelin, which provides opportunities to extract information at spatial scales well below MRI resolution. For example, in white matter, the myelin sheath that surrounds the axons can provide tissue contrast that is dependent on the axonal orientation and reflects the relative size of intra- and extra-axonal water compartments. The extraction of such ultrastructural information, together with quantitative information about iron and myelin concentrations, is an active area of research geared towards the characterization of brain structure and function, and their alteration in disease. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Jeff H. Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular
Imaging, National Institutes of Neurological Disorders and Stroke, National
Institutes of Health, Bethesda, Maryland 20892, USA
| | - John Schenck
- MRI Technologies and Systems, General Electric
Global Research Center, 1 Research Circle, Schenectady, New York 12309, USA
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