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Alzaidi AA, Panek R, Blockley NP. Quantitative BOLD (qBOLD) imaging of oxygen metabolism and blood oxygenation in the human body: A scoping review. Magn Reson Med 2024; 92:1822-1837. [PMID: 39072791 DOI: 10.1002/mrm.30165] [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: 10/19/2023] [Revised: 05/06/2024] [Accepted: 05/08/2024] [Indexed: 07/30/2024]
Abstract
PURPOSE There are many approaches to the quantitative BOLD (qBOLD) technique described in the literature, differing in pulse sequences, MRI parameters and data processing. Thus, in this review, we summarized the acquisition methods, approaches used for oxygenation quantification and clinical populations investigated. METHODS Three databases were systematically searched (Medline, Embase, and Web of Science) for published research that used qBOLD methods for quantification of oxygen metabolism. Data extraction and synthesis were performed by one author and reviewed by a second author. RESULTS A total of 93 relevant papers were identified. Acquisition strategies were summarized, and oxygenation parameters were found to have been investigated in many pathologies such as steno-occlusive diseases, stroke, glioma, and multiple sclerosis disease. CONCLUSION A summary of qBOLD approaches for oxygenation measurements and applications could help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.
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Affiliation(s)
- Ahlam A Alzaidi
- David Greenfield Human Physiology Unit, School of Life Sciences, University of Nottingham, Nottingham, UK
- Radiology Department, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
| | - Rafal Panek
- Medical Physics and Clinical Engineering, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Nicholas P Blockley
- David Greenfield Human Physiology Unit, School of Life Sciences, University of Nottingham, Nottingham, UK
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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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3
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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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Lee J, Ji S, Oh SH. So You Want to Image Myelin Using MRI: Magnetic Susceptibility Source Separation for Myelin Imaging. Magn Reson Med Sci 2024; 23:291-306. [PMID: 38644201 PMCID: PMC11234950 DOI: 10.2463/mrms.rev.2024-0001] [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: 01/05/2024] [Accepted: 03/19/2024] [Indexed: 04/23/2024] Open
Abstract
In MRI, researchers have long endeavored to effectively visualize myelin distribution in the brain, a pursuit with significant implications for both scientific research and clinical applications. Over time, various methods such as myelin water imaging, magnetization transfer imaging, and relaxometric imaging have been developed, each carrying distinct advantages and limitations. Recently, an innovative technique named as magnetic susceptibility source separation has emerged, introducing a novel surrogate biomarker for myelin in the form of a diamagnetic susceptibility map. This paper comprehensively reviews this cutting-edge method, providing the fundamental concepts of magnetic susceptibility, susceptibility imaging, and the validation of the diamagnetic susceptibility map as a myelin biomarker that indirectly measures myelin content. Additionally, the paper explores essential aspects of data acquisition and processing, offering practical insights for readers. A comparison with established myelin imaging methods is also presented, and both current and prospective clinical and scientific applications are discussed to provide a holistic understanding of the technique. This work aims to serve as a foundational resource for newcomers entering this dynamic and rapidly expanding field.
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Affiliation(s)
- Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Sooyeon Ji
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Se-Hong Oh
- Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Korea
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Huang Y, Chen L, Li X, Liu J. Improved test-retest reliability of R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and susceptibility quantification using multishot multi-echo 3D EPI. Magn Reson Med 2024; 91:2310-2319. [PMID: 38156825 PMCID: PMC10997481 DOI: 10.1002/mrm.29992] [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: 08/04/2023] [Revised: 12/07/2023] [Accepted: 12/12/2023] [Indexed: 01/03/2024]
Abstract
PURPOSE This study aimed to evaluate the potential of 3D EPI for improving the reliability ofT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted data and quantification ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ decay rate and susceptibility (χ) compared with conventional gradient-echo (GRE)-based acquisition. METHODS Eight healthy subjects in a wide age range were recruited. Each subject received repeated scans for both GRE and EPI acquisitions with an isotropic 1 mm resolution at 3 T. Maps ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ were quantified, and their interscan differences were used to evaluate the test-retest reliability. Interprotocol differences ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ between GRE and EPI were also measured voxel by voxel and in selected regions of interest to test the consistency between the two acquisition methods. RESULTS The quantifications ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ using EPI protocols showed increased test-retest reliability with higher EPI factors up to 5 as performed in the experiment and were consistent with those based on GRE. CONCLUSION The result suggests that multishot multi-echo 3D EPI can be a useful alternative acquisition method forT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted MRI and quantification ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ with reduced scan time, improved test-retest reliability, and similar accuracy compared with commonly used 3D GRE.
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Affiliation(s)
- Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Lin Chen
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
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Yablonskiy DA, Sukstanskii AL. Quantum dipole interactions and transient hydrogen bond orientation order in cells, cellular membranes and myelin sheath: Implications for MRI signal relaxation, anisotropy, and T 1 magnetic field dependence. Magn Reson Med 2024; 91:2597-2611. [PMID: 38241135 PMCID: PMC10997466 DOI: 10.1002/mrm.29996] [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: 10/10/2023] [Revised: 12/12/2023] [Accepted: 12/14/2023] [Indexed: 01/21/2024]
Abstract
PURPOSE Despite significant impact on the study of human brain, MRI lacks a theory of signal formation that integrates quantum interactions involving proton dipoles (a primary MRI signal source) with brain intricate cellular environment. The purpose of the present study is developing such a theory. METHODS We introduce the Transient Hydrogen Bond (THB) model, where THB-mediated quantum dipole interactions between water and protons of hydrophilic heads of amphipathic biomolecules forming cells, cellular membranes and myelin sheath serve as a major source of MR signal relaxation. RESULTS The THB theory predicts the existence of a hydrogen-bond-driven structural order of dipole-dipole connections within THBs as a primary factor for the anisotropy observed in MRI signal relaxation. We have also demonstrated that the conventional Lorentzian spectral density function decreases too fast at high frequencies to adequately capture the field dependence of brain MRI signal relaxation. To bridge this gap, we introduced a stretched spectral density function that surpasses the limitations of Lorentzian dispersion. In human brain, our findings reveal that at any time point only about 4% to 7% of water protons are engaged in quantum encounters within THBs. These ultra-short (2 to 3 ns), but frequent quantum spin exchanges lead to gradual recovery of magnetization toward thermodynamic equilibrium, that is, relaxation of MRI signal. CONCLUSION By incorporating quantum proton interactions involved in brain imaging, the THB approach introduces new insights on the complex relationship between brain tissue cellular structure and MRI measurements, thus offering a promising new tool for better understanding of brain microstructure in health and disease.
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Affiliation(s)
- Dmitriy A. Yablonskiy
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis MO, 63110
- Hope Center for Neurological Disorder, 660 S. Euclid Ave., St. Louis, Missouri 63110
- Knight Alzheimer Disease Research Center, 4488 Forest Park Ave., St. Louis, MO 63108
- Department of Biomedical Engineering, Washington University in St. Louis, 1 Brookings Drive, St. Louis, MO 63130
| | - Alexander L. Sukstanskii
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis MO, 63110
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Bilgic B, Costagli M, Chan KS, Duyn J, Langkammer C, Lee J, Li X, Liu C, Marques JP, Milovic C, Robinson SD, Schweser F, Shmueli K, Spincemaille P, Straub S, van Zijl P, Wang Y. Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group. Magn Reson Med 2024; 91:1834-1862. [PMID: 38247051 PMCID: PMC10950544 DOI: 10.1002/mrm.30006] [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: 07/11/2023] [Revised: 10/31/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024]
Abstract
This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.
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Affiliation(s)
- Berkin Bilgic
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
| | - Mauro Costagli
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Kwok-Shing Chan
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Jeff Duyn
- Advanced MRI Section, NINDS, National Institutes of Health, Bethesda, Maryland, USA
| | | | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
| | - Xu Li
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA
| | - José P Marques
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Carlos Milovic
- School of Electrical Engineering (EIE), Pontificia Universidad Catolica de Valparaiso, Valparaiso, Chile
| | - Simon Daniel Robinson
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Centre of Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo, Buffalo, New York, USA
- Center for Biomedical Imaging, Clinical and Translational Science Institute at the University at Buffalo, Buffalo, New York, USA
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Pascal Spincemaille
- MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Sina Straub
- Department of Radiology, Mayo Clinic, Jacksonville, Florida, USA
| | - Peter van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Yi Wang
- MRI Research Institute, Departments of Radiology and Biomedical Engineering, Cornell University, New York, New York, 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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11
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Cho H, Han S, Cho HJ. Empirical relationship between TEM-derived myelin volume fraction and MRI-R 2 values in aging ex vivo rat corpus callosum. Magn Reson Imaging 2023; 103:75-83. [PMID: 37451521 DOI: 10.1016/j.mri.2023.07.006] [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: 03/16/2023] [Revised: 05/26/2023] [Accepted: 07/09/2023] [Indexed: 07/18/2023]
Abstract
Ex vivo ratiometric measurements of short- and long-T2 components using the multiple spin echo sequence of MRI are often employed to evaluate alterations in myelin content in the white matter (WM) of the brain. However, the relationship between absolute MRI-T2 values (long-T2 component) and myelin volumetric information in aged ex vivo rodent WM appears to be influenced by factors such as animal species, field strength, and fixation durations/washing. Here, multiple spin echo sequence-based MRI-R2 (the reciprocal of T2) values were measured in the corpus callosum (CC) region in the post-mortem rat brains (n = 9) of different age groups with common fixation techniques without washing at 7 T. Transmission electron microscopy (TEM)-based quantification of myelin volume fraction (MVF) and corresponding Monte-Carlo simulation to estimate relaxation rates (R2,IE) due to diffusion in the presence of inhomogeneous magnetic field perturbation in intra- and extra-cellular (IE) spaces were respectively performed. To determine whether the short-T2 components originating from myelin water were mixed with long-T2 components from IE water or were undetectable, the MVF values obtained from TEM results were respectively compared with MRI-R2 and R2,IE values. A significant correlation (Pearson's correlation coefficient r = 0.8763; p < 0.01) of average MRI-R2 and MVF values was observed. Estimated R2,IE values from Monte-Carlo simulations in IE water signals were also positively correlated (r = 0.8281; p < 0.01) with MVF values. However, the magnitudes of R2,IE values were much smaller than those observed for MRI-R2 values, indicating that changes in R2 related MVF are likely dominated by myelin water components. Such comparisons between independent parameters from MRI, TEM, and simulations support the suggestion that myelin water signals were indistinguishably mixed to exhibit mono-exponential T2 relaxation, and multiple spin echo sequence-based MRI-R2 values in aging ex vivo rat CC without prolonged washing still reflect the volumetric information of myelin, likely due to enhanced water exchange across the myelin.
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Affiliation(s)
- Hwapyeong Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Sohyun Han
- Research Equipment Operations Division, Korea Basic Science Institute, Cheongju, South Korea.
| | - Hyung Joon Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea.
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Kleban E, Jones DK, Tax CM. The impact of head orientation with respect to B 0 on diffusion tensor MRI measures. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2023; 1:1-17. [PMID: 38405373 PMCID: PMC10884544 DOI: 10.1162/imag_a_00012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 07/27/2023] [Indexed: 02/27/2024]
Abstract
Diffusion tensor MRI (DT-MRI) remains the most commonly used approach to characterise white matter (WM) anisotropy. However, DT estimates may be affected by tissue orientation w.r.t. B → 0 due to local gradients and intrinsic T 2 orientation dependence induced by the microstructure. This work aimed to investigate whether and how diffusion tensor MRI-derived measures depend on the orientation of the head with respect to the static magnetic field, B → 0 . By simulating WM as two compartments, we demonstrated that compartmental T 2 anisotropy can induce the dependence of diffusion tensor measures on the angle between WM fibres and the magnetic field. In in vivo experiments, reduced radial diffusivity and increased axial diffusivity were observed in white matter fibres perpendicular to B → 0 compared to those parallel to B → 0 . Fractional anisotropy varied by up to 20 % as a function of the angle between WM fibres and the orientation of the main magnetic field. To conclude, fibre orientation w.r.t. B → 0 is responsible for up to 7 % variance in diffusion tensor measures across the whole brain white matter from all subjects and head orientations. Fibre orientation w.r.t. B → 0 may introduce additional variance in clinical research studies using diffusion tensor imaging, particularly when it is difficult to control for (e.g., fetal or neonatal imaging, or when the trajectories of fibres change due to, e.g., space occupying lesions).
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Affiliation(s)
- Elena Kleban
- CUBRIC, School of Psychology, Cardiff University, Cardiff, United Kingdom
- Inselspital, University of Bern, Bern, Switzerland
| | - Derek K. Jones
- CUBRIC, School of Psychology, Cardiff University, Cardiff, United Kingdom
- MMIHR, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Chantal M.W. Tax
- CUBRIC, School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
- UMC Utrecht, Utrecht University, Utrecht, The Netherlands
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13
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Huang Y, Chen L, Li X, Liu J. Improved test-retest reliability of R2* and susceptibility quantification using multi-shot multi-echo 3D EPI. ARXIV 2023:arXiv:2308.07811v1. [PMID: 37645047 PMCID: PMC10462177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
This study aimed to evaluate the potential of 3D echo-planar imaging (EPI) for improving the reliability of T2*-weighted (T2*w) data and quantification of R2* decay rate and susceptibility (χ) compared to conventional gradient echo (GRE)-based acquisition. Eight healthy subjects in a wide age range were recruited. Each subject received repeated scans for both GRE and EPI acquisitions with an isotropic 1 mm resolution at 3 T. Maps of R2* and χ were quantified and compared using their inter-scan difference to evaluate the test-retest reliability. Inter-protocol differences of R2* and χ between GRE and EPI were also measured voxel by voxel and in selected ROIs to test the consistency between the two acquisition methods. The quantifications of R2* and χ using EPI protocols showed increased test-retest reliability with higher EPI factors up to 5 as performed in the experiment and were consistent with those based on GRE. This result suggested multi-shot multi-echo 3D EPI can be a useful alternative acquisition method for T2*w MRI and quantification of R2* and χ with reduced scan time, improved test-retest reliability and similar accuracy compared to commonly used 3D GRE.
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Affiliation(s)
- Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Lin Chen
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
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14
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Bilgic B, Costagli M, Chan KS, Duyn J, Langkammer C, Lee J, Li X, Liu C, Marques JP, Milovic C, Robinson S, Schweser F, Shmueli K, Spincemaille P, Straub S, van Zijl P, Wang Y. Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group. ARXIV 2023:arXiv:2307.02306v1. [PMID: 37461418 PMCID: PMC10350101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
This article provides recommendations for implementing quantitative susceptibility mapping (QSM) for clinical brain research. It is a consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available give rise to the need in the neuroimaging community for guidelines on implementation. This article describes relevant considerations and provides specific implementation recommendations for all steps in QSM data acquisition, processing, analysis, and presentation in scientific publications. We recommend that data be acquired using a monopolar 3D multi-echo GRE sequence, that phase images be saved and exported in DICOM format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields should be removed within the brain mask using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of whole brain as a region of interest in the analysis, and QSM results should be reported with - as a minimum - the acquisition and processing specifications listed in the last section of the article. These recommendations should facilitate clinical QSM research and lead to increased harmonization in data acquisition, analysis, and reporting.
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Affiliation(s)
- Berkin Bilgic
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Mauro Costagli
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Kwok-Shing Chan
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Jeff Duyn
- Advanced MRI Section, NINDS, National Institutes of Health, Bethesda, MD, United States
| | | | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
| | - Xu Li
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - José P Marques
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Carlos Milovic
- School of Electrical Engineering (EIE), Pontificia Universidad Catolica de Valparaiso, Valparaiso, Chile
| | - Simon Robinson
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo, Buffalo, NY, USA
- Center for Biomedical Imaging, Clinical and Translational Science Institute at the University at Buffalo, Buffalo, NY, United States
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Pascal Spincemaille
- MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Sina Straub
- Department of Radiology, Mayo Clinic, Jacksonville, FL, United States
| | - Peter van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Yi Wang
- MRI Research Institute, Departments of Radiology and Biomedical Engineering, Cornell University, New York, NY, United States
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15
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Fang Z, Lai KW, van Zijl P, Li X, Sulam J. DeepSTI: Towards tensor reconstruction using fewer orientations in susceptibility tensor imaging. Med Image Anal 2023; 87:102829. [PMID: 37146440 PMCID: PMC10288385 DOI: 10.1016/j.media.2023.102829] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 03/11/2023] [Accepted: 04/18/2023] [Indexed: 05/07/2023]
Abstract
Susceptibility tensor imaging (STI) is an emerging magnetic resonance imaging technique that characterizes the anisotropic tissue magnetic susceptibility with a second-order tensor model. STI has the potential to provide information for both the reconstruction of white matter fiber pathways and detection of myelin changes in the brain at mm resolution or less, which would be of great value for understanding brain structure and function in healthy and diseased brain. However, the application of STI in vivo has been hindered by its cumbersome and time-consuming acquisition requirement of measuring susceptibility induced MR phase changes at multiple head orientations. Usually, sampling at more than six orientations is required to obtain sufficient information for the ill-posed STI dipole inversion. This complexity is enhanced by the limitation in head rotation angles due to physical constraints of the head coil. As a result, STI has not yet been widely applied in human studies in vivo. In this work, we tackle these issues by proposing an image reconstruction algorithm for STI that leverages data-driven priors. Our method, called DeepSTI, learns the data prior implicitly via a deep neural network that approximates the proximal operator of a regularizer function for STI. The dipole inversion problem is then solved iteratively using the learned proximal network. Experimental results using both simulation and in vivo human data demonstrate great improvement over state-of-the-art algorithms in terms of the reconstructed tensor image, principal eigenvector maps and tractography results, while allowing for tensor reconstruction with MR phase measured at much less than six different orientations. Notably, promising reconstruction results are achieved by our method from only one orientation in human in vivo, and we demonstrate a potential application of this technique for estimating lesion susceptibility anisotropy in patients with multiple sclerosis.
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Affiliation(s)
- Zhenghan Fang
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Johns Hopkins Kavli Neuroscience Discovery Institute, Baltimore, MD 21218, USA
| | - Kuo-Wei Lai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Peter van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD 21205, USA.
| | - Jeremias Sulam
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Johns Hopkins Kavli Neuroscience Discovery Institute, Baltimore, MD 21218, USA.
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16
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van Gelderen P, Li X, de Zwart JA, Beck ES, Okar SV, Huang Y, Lai K, Sulam J, van Zijl PCM, Reich DS, Duyn JH, Liu J. Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R 2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T. Neuroimage 2023; 270:119992. [PMID: 36858332 PMCID: PMC10278242 DOI: 10.1016/j.neuroimage.2023.119992] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 02/17/2023] [Accepted: 02/25/2023] [Indexed: 03/03/2023] Open
Abstract
MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.
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Affiliation(s)
- Peter van Gelderen
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Jacco A de Zwart
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Erin S Beck
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York City, NY, United States of America
| | - Serhat V Okar
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - KuoWei Lai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America; Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Jeremias Sulam
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Daniel S Reich
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America.
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17
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Sandgaard AD, Shemesh N, Kiselev VG, Jespersen SN. Larmor frequency shift from magnetized cylinders with arbitrary orientation distribution. NMR IN BIOMEDICINE 2023; 36:e4859. [PMID: 36285793 PMCID: PMC10078263 DOI: 10.1002/nbm.4859] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 10/22/2022] [Accepted: 10/23/2022] [Indexed: 06/01/2023]
Abstract
The magnetic susceptibility of tissue can provide valuable information about its chemical composition and microstructural organization. However, the relation between the magnetic microstructure and the measurable Larmor frequency shift is understood only for a few idealized cases. Here we analyze the microstructure formed by magnetized, NMR-invisible infinite cylinders suspended in an NMR-reporting fluid. Through simulations, we scrutinize various geometries of mesoscopic Lorentz cavities and inclusions, and show that the cavity size should be approximately one order of magnitude larger than the width of the inclusions. We also analytically derive the Larmor frequency shift for a population of cylinders with arbitrary orientation dispersion and show that it is determined by the l = 2 Laplace expansion coefficients p 2 m of the cylinders' orientation distribution function. Our work underscores the need to account for microstructural organization when estimating magnetic tissue properties.
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Affiliation(s)
- Anders Dyhr Sandgaard
- Center for Functionally Integrative Neuroscience, Department of Clinical MedicineAarhus UniversityDenmark
| | - Noam Shemesh
- Champalimaud ResearchChampalimaud Centre for the UnknownLisbonPortugal
| | - Valerij G. Kiselev
- Division of Medical Physics, Department of RadiologyUniversity Medical Center FreiburgFreiburgGermany
| | - Sune Nørhøj Jespersen
- Center for Functionally Integrative Neuroscience, Department of Clinical MedicineAarhus UniversityDenmark
- Department of Physics and AstronomyAarhus UniversityDenmark
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18
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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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19
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Hill M, Cunniffe N, Franklin R. Seeing is believing: Identifying remyelination in the central nervous system. Curr Opin Pharmacol 2022; 66:102269. [DOI: 10.1016/j.coph.2022.102269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 06/20/2022] [Indexed: 11/03/2022]
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20
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Lancione M, Cencini M, Costagli M, Donatelli G, Tosetti M, Giannini G, Zangaglia R, Calandra-Buonaura G, Pacchetti C, Cortelli P, Cosottini M. Diagnostic accuracy of quantitative susceptibility mapping in multiple system atrophy: The impact of echo time and the potential of histogram analysis. Neuroimage Clin 2022; 34:102989. [PMID: 35303599 PMCID: PMC8927993 DOI: 10.1016/j.nicl.2022.102989] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/25/2022] [Accepted: 03/10/2022] [Indexed: 11/07/2022]
Abstract
We performed histogram analysis on χ maps at different TEs on MSA patients and HC. We found altered χ distribution in Pu, SN, GP, CN for MSAp and in SN, DN for MSAc. QSM diagnostic accuracy is TE-dependent and is enhanced at short TEs. Short TEs capture rapidly-decaying contributions of high χ sources. Histogram features detect χ spatial heterogeneities improving diagnostic accuracy.
The non-invasive quantification of iron stores via Quantitative Susceptibility Mapping (QSM) could play an important role in the diagnosis and the differential diagnosis of atypical Parkinsonisms. However, the susceptibility (χ) values measured via QSM depend on echo time (TE). This effect relates to the microstructural organization within the voxel, whose composition can be altered by the disease. Moreover, pathological iron deposition in a brain area may not be spatially uniform, and conventional Region of Interest (ROI)-based analysis may fail in detecting alterations. Therefore, in this work we evaluated the impact of echo time on the diagnostic accuracy of QSM on a population of patients with Multiple System Atrophy (MSA) of either Parkinsonian (MSAp) or cerebellar (MSAc) phenotypes. In addition, we tested the potential of histogram analysis to improve QSM classification accuracy. We enrolled 32 patients (19 MSAp and 13 MSAc) and 16 healthy controls, who underwent a 7T MRI session including a gradient-recalled multi-echo sequence for χ mapping. Nine histogram features were extracted from the χ maps computed for each TE in atlas-based ROIs covering deep brain nuclei, and compared among groups. Alterations of susceptibility distribution were found in the Putamen, Substantia Nigra, Globus Pallidus and Caudate Nucleus for MSAp and in the Substantia Nigra and Dentate Nucleus for MSAc. Increased iron deposition was observed in a larger number of ROIs for the two shortest TEs and the standard deviation, the 75th and the 90th percentile were the most informative features yielding excellent diagnostic accuracy with area under the ROC curve > 0.9. In conclusion, short TEs may enhance QSM diagnostic performances, as they can capture variations in rapidly-decaying contributions of high χ sources. The analysis of histogram features allowed to reveal fine heterogeneities in the spatial distribution of susceptibility alteration, otherwise undetected by a simple evaluation of ROI χ mean values.
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Affiliation(s)
- Marta Lancione
- IRCCS Stella Maris, Pisa, Italy; IMAGO7 Foundation, Pisa, Italy
| | - Matteo Cencini
- IRCCS Stella Maris, Pisa, Italy; IMAGO7 Foundation, Pisa, Italy
| | - Mauro Costagli
- IRCCS Stella Maris, Pisa, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genova, Genova, Italy.
| | - Graziella Donatelli
- IMAGO7 Foundation, Pisa, Italy; Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Michela Tosetti
- IRCCS Stella Maris, Pisa, Italy; IMAGO7 Foundation, Pisa, Italy
| | - Giulia Giannini
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Roberta Zangaglia
- Parkinson and Movement Disorder Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Giovanna Calandra-Buonaura
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Claudio Pacchetti
- Parkinson and Movement Disorder Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Pietro Cortelli
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
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21
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Chan KS, Hédouin R, Mollink J, Schulz J, van Cappellen van Walsum AM, Marques JP. Imaging white matter microstructure with gradient-echo phase imaging: Is ex vivo imaging with formalin-fixed tissue a good approximation of the in vivo brain? Magn Reson Med 2022; 88:380-390. [PMID: 35344591 PMCID: PMC9314807 DOI: 10.1002/mrm.29213] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 01/17/2022] [Accepted: 02/10/2022] [Indexed: 11/20/2022]
Abstract
Purpose Ex vivo imaging is a commonly used approach to investigate the biophysical mechanism of orientation‐dependent signal phase evolution in white matter. Yet, how phase measurements are influenced by the structural alteration in the tissue after formalin fixation is not fully understood. Here, we study the effects on magnetic susceptibility, microstructural compartmentalization, and chemical exchange measurement with a postmortem formalin‐fixed whole‐brain human tissue. Methods A formalin‐fixed, postmortem human brain specimen was scanned with multiple orientations to the main magnetic field direction for robust bulk magnetic susceptibility measurement with conventional quantitative susceptibility imaging models. White matter samples were subsequently excised from the whole‐brain specimen and scanned in multiple rotations on an MRI scanner to measure the anisotropic magnetic susceptibility and microstructure‐related contributions in the signal phase and to validate the findings of the whole‐brain data. Results The bulk isotropic magnetic susceptibility of ex vivo whole‐brain imaging is comparable to in vivo imaging, with noticeable enhanced nonsusceptibility contributions. The excised specimen experiment reveals that anisotropic magnetic susceptibility and compartmentalization phase effect were considerably reduced in the formalin‐fixed white matter specimens. Conclusions Formalin‐fixed postmortem white matter exhibits comparable isotropic magnetic susceptibility to previous in vivo imaging findings. However, the measured phase and magnitude data of the fixed white matter tissue shows a significantly weaker orientation dependency and compartmentalization effect. Alternatives to formalin fixation are needed to better reproduce the in vivo microstructural effects in postmortem samples.
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Affiliation(s)
- Kwok-Shing Chan
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Renaud Hédouin
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.,Empenn, INRIA, INSERM, CNRS, Université de Rennes 1, Rennes, France
| | - Jeroen Mollink
- Department of Medical Imaging, Anatomy, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jenni Schulz
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Anne-Marie van Cappellen van Walsum
- Department of Medical Imaging, Anatomy, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - José P Marques
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
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22
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Xu X, Kothapalli SVVN, Liu J, Kahali S, Gan W, Yablonskiy DA, Kamilov US. Learning-based motion artifact removal networks for quantitative R 2 ∗ mapping. Magn Reson Med 2022; 88:106-119. [PMID: 35257400 DOI: 10.1002/mrm.29188] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 01/11/2022] [Accepted: 01/18/2022] [Indexed: 11/12/2022]
Abstract
PURPOSE To introduce two novel learning-based motion artifact removal networks (LEARN) for the estimation of quantitative motion- and B 0 -inhomogeneity-corrected R 2 ∗ maps from motion-corrupted multi-Gradient-Recalled Echo (mGRE) MRI data. METHODS We train two convolutional neural networks (CNNs) to correct motion artifacts for high-quality estimation of quantitative B 0 -inhomogeneity-corrected R 2 ∗ maps from mGRE sequences. The first CNN, LEARN-IMG, performs motion correction on complex mGRE images, to enable the subsequent computation of high-quality motion-free quantitative R 2 ∗ (and any other mGRE-enabled) maps using the standard voxel-wise analysis or machine learning-based analysis. The second CNN, LEARN-BIO, is trained to directly generate motion- and B 0 -inhomogeneity-corrected quantitative R 2 ∗ maps from motion-corrupted magnitude-only mGRE images by taking advantage of the biophysical model describing the mGRE signal decay. RESULTS We show that both CNNs trained on synthetic MR images are capable of suppressing motion artifacts while preserving details in the predicted quantitative R 2 ∗ maps. Significant reduction of motion artifacts on experimental in vivo motion-corrupted data has also been achieved by using our trained models. CONCLUSION Both LEARN-IMG and LEARN-BIO can enable the computation of high-quality motion- and B 0 -inhomogeneity-corrected R 2 ∗ maps. LEARN-IMG performs motion correction on mGRE images and relies on the subsequent analysis for the estimation of R 2 ∗ maps, while LEARN-BIO directly performs motion- and B 0 -inhomogeneity-corrected R 2 ∗ estimation. Both LEARN-IMG and LEARN-BIO jointly process all the available gradient echoes, which enables them to exploit spatial patterns available in the data. The high computational speed of LEARN-BIO is an advantage that can lead to a broader clinical application.
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Affiliation(s)
- Xiaojian Xu
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Jiaming Liu
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Sayan Kahali
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Weijie Gan
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Dmitriy A Yablonskiy
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Ulugbek S Kamilov
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
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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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Cho H, Lee H, Gong Y, Kim YR, Cho J, Cho HJ. Quantitative susceptibility mapping and R1 measurement: Determination of the myelin volume fraction in the aging ex vivo rat corpus callosum. NMR IN BIOMEDICINE 2022; 35:e4645. [PMID: 34739153 DOI: 10.1002/nbm.4645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 10/03/2021] [Accepted: 10/16/2021] [Indexed: 06/13/2023]
Abstract
In studies of the white matter (WM) in aging brains, both quantitative susceptibility mapping (QSM) and direct R1 measurement offer potentially useful ex vivo MRI tools that allow volumetric characterization of myelin content changes. Despite the technical importance of such MRI methods in numerous age-related diseases, the supposed linear relationship between the estimates of either the QSM or R1 method and age-affected myelin contents has not been validated. In this study, the absolute myelin volume fraction (MVF) was determined by transmission electron microscopy (TEM) as a gold standard measure for comparison with the values obtained by the aforementioned MR methods. To theoretically evaluate and understand the MR signal characteristics, QSM simulations were performed using the finite perturber method (FPM). Specifically, the simulation geometry modeling was based on TEM-derived structures aligned orthogonally to the main magnetic field, the construct of which was used to estimate the magnetic field shift (ΔB) changes arising from the conjectured myelin structures. Experimentally, ex vivo corpus callosum (CC) samples from rat brains obtained at 6 weeks (n = 3), 4 months (n = 3), and 20 months (n = 3) after birth were used to establish the relationship between changes quantified by either QSM or R1 with the absolute MVF by TEM. From the ex vivo brain samples, the scatterplot of mean MVF versus R1 was fitted to a linear equation, where R1mean = 0.7948 × MVFmean + 0.8118 (Pearson's correlation coefficient r = 0.9138; p < 0.01), while the scatterplot of mean MVF versus MRI-derived magnetic susceptibility (χ) was also fitted to a line where χmeasured,mean = -0.1218 × MVFmean - 0.006345 (r = -0.8435; p < 0.01). As a result of the FPM-based QSM simulations, a linearly proportional relationship between the simulated magnetic susceptibility, χsimulated,mean , and MVF (r = -0.9648; p < 0.01) was established. Such a statistically significant linear correlation between MRI-derived values by the QSM (or R1 ) method and MVF demonstrated that variable myelin contents in the WM (i.e., CC) can be quantified across multiple stages of aging. These findings further support that both techniques based on QSM and R1 provide an efficient means of studying the brain-aging process with accurate volumetric quantification of the myelin content in WM.
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Affiliation(s)
- Hwapyeong Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Hansol Lee
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Yelim Gong
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Young Ro Kim
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Hyung Joon Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
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Jung S, Yun J, Kim DY, Kim D. Improved multi‐echo gradient echo myelin water fraction mapping using complex‐valued neural network analysis. Magn Reson Med 2022; 88:492-500. [DOI: 10.1002/mrm.29192] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 01/19/2022] [Accepted: 01/19/2022] [Indexed: 01/20/2023]
Affiliation(s)
- Soozy Jung
- Department of Electrical and Electronic Engineering Yonsei University Seoul Republic of Korea
| | - JiSu Yun
- Department of Electrical and Electronic Engineering Yonsei University Seoul Republic of Korea
| | - Deog Young Kim
- Department and Research Institute of Rehabilitation Medicine Yonsei University College 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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26
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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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Nonparametric D-R 1-R 2 distribution MRI of the living human brain. Neuroimage 2021; 245:118753. [PMID: 34852278 DOI: 10.1016/j.neuroimage.2021.118753] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 11/17/2021] [Accepted: 11/22/2021] [Indexed: 11/23/2022] Open
Abstract
Diffusion-relaxation correlation NMR can simultaneously characterize both the microstructure and the local chemical composition of complex samples that contain multiple populations of water. Recent developments on tensor-valued diffusion encoding and Monte Carlo inversion algorithms have made it possible to transfer diffusion-relaxation correlation NMR from small-bore scanners to clinical MRI systems. Initial studies on clinical MRI systems employed 5D D-R1 and D-R2 correlation to characterize healthy brain in vivo. However, these methods are subject to an inherent bias that originates from not including R2 or R1 in the analysis, respectively. This drawback can be remedied by extending the concept to 6D D-R1-R2 correlation. In this work, we present a sparse acquisition protocol that records all data necessary for in vivo 6D D-R1-R2 correlation MRI across 633 individual measurements within 25 min-a time frame comparable to previous lower-dimensional acquisition protocols. The data were processed with a Monte Carlo inversion algorithm to obtain nonparametric 6D D-R1-R2 distributions. We validated the reproducibility of the method in repeated measurements of healthy volunteers. For a post-therapy glioblastoma case featuring cysts, edema, and partially necrotic remains of tumor, we present representative single-voxel 6D distributions, parameter maps, and artificial contrasts over a wide range of diffusion-, R1-, and R2-weightings based on the rich information contained in the D-R1-R2 distributions.
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28
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Slator PJ, Palombo M, Miller KL, Westin C, Laun F, Kim D, Haldar JP, Benjamini D, Lemberskiy G, de Almeida Martins JP, Hutter J. Combined diffusion-relaxometry microstructure imaging: Current status and future prospects. Magn Reson Med 2021; 86:2987-3011. [PMID: 34411331 PMCID: PMC8568657 DOI: 10.1002/mrm.28963] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 06/25/2021] [Accepted: 07/20/2021] [Indexed: 12/15/2022]
Abstract
Microstructure imaging seeks to noninvasively measure and map microscopic tissue features by pairing mathematical modeling with tailored MRI protocols. This article reviews an emerging paradigm that has the potential to provide a more detailed assessment of tissue microstructure-combined diffusion-relaxometry imaging. Combined diffusion-relaxometry acquisitions vary multiple MR contrast encodings-such as b-value, gradient direction, inversion time, and echo time-in a multidimensional acquisition space. When paired with suitable analysis techniques, this enables quantification of correlations and coupling between multiple MR parameters-such as diffusivity, T 1 , T 2 , and T 2 ∗ . This opens the possibility of disentangling multiple tissue compartments (within voxels) that are indistinguishable with single-contrast scans, enabling a new generation of microstructural maps with improved biological sensitivity and specificity.
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Affiliation(s)
- Paddy J. Slator
- Centre for Medical Image ComputingDepartment of Computer ScienceUniversity College LondonLondonUK
| | - Marco Palombo
- Centre for Medical Image ComputingDepartment of Computer ScienceUniversity College LondonLondonUK
| | - Karla L. Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Carl‐Fredrik Westin
- Department of RadiologyBrigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA
| | - Frederik Laun
- Institute of RadiologyUniversity Hospital ErlangenFriedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU)ErlangenGermany
| | - Daeun Kim
- Ming Hsieh Department of Electrical and Computer EngineeringUniversity of Southern CaliforniaLos AngelesCAUSA
- Signal and Image Processing InstituteUniversity of Southern CaliforniaLos AngelesCAUSA
| | - Justin P. Haldar
- Ming Hsieh Department of Electrical and Computer EngineeringUniversity of Southern CaliforniaLos AngelesCAUSA
- Signal and Image Processing InstituteUniversity of Southern CaliforniaLos AngelesCAUSA
| | - Dan Benjamini
- The Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentBethesdaMDUSA
- The Center for Neuroscience and Regenerative MedicineUniformed Service University of the Health SciencesBethesdaMDUSA
| | | | - Joao P. de Almeida Martins
- Division of Physical Chemistry, Department of ChemistryLund UniversityLundSweden
- Department of Radiology and Nuclear MedicineSt. Olav’s University HospitalTrondheimNorway
| | - Jana Hutter
- Centre for Biomedical EngineeringSchool of Biomedical Engineering and ImagingKing’s College LondonLondonUK
- Centre for the Developing BrainSchool of Biomedical Engineering and ImagingKing’s College LondonLondonUK
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29
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Schäper J, Bauman G, Ganter C, Bieri O. Pure balanced steady-state free precession imaging (pure bSSFP). Magn Reson Med 2021; 87:1886-1893. [PMID: 34775622 PMCID: PMC9299476 DOI: 10.1002/mrm.29086] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 10/02/2021] [Accepted: 10/28/2021] [Indexed: 12/26/2022]
Abstract
Purpose To show that for tissues the conspicuous asymmetries in the frequency response function of bSSFP can be mitigated by using a short enough TR. Theory and Methods Configuration theory indicates that bSSFP becomes apparently “pure” (i.e., exhibiting a symmetric profile) in the limit of TR →0. To this end, the frequency profile of bSSFP was measured as a function of the TR using a manganese‐doped aqueous probe, as well as brain tissue that was shown to exhibit a pronounced asymmetry due to its microstructure. The frequency response function was sampled using N=72 (phantom) and N=36 (in vivo) equally distributed linear RF phase increments in the interval [0,2π). Imaging was performed with 2.0 mm isotropic resolution over a TR range of 1.5–8 ms at 3 and 1.5 T. Results As expected, pure substances showed a symmetric TR‐independent frequency profile, whereas brain tissue revealed a pronounced asymmetry. The observed asymmetry for the tissue, however, decreases with decreasing TR and gives strong evidence that the frequency response function of bSSFP becomes symmetric in the limit of TR →0, in agreement with theory. The limit of apparently pure bSSFP imaging can thus be achieved for a TR ∼ 1.5 ms at 1.5 T, whereas at 3 T, tissues still show some residual asymmetry. Conclusion In the limit of short enough TR, tissues become apparently pure for bSSFP. This limit can be reached for brain tissue at 1.5 T with TR ∼ 1–2 ms at clinically relevant resolutions.
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Affiliation(s)
- Jessica Schäper
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Grzegorz Bauman
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Carl Ganter
- Department of Diagnostic Radiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Oliver Bieri
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
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30
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Cottaar M, Wu W, Tendler BC, Nagy Z, Miller K, Jbabdi S. Quantifying myelin in crossing fibers using diffusion-prepared phase imaging: Theory and simulations. Magn Reson Med 2021; 86:2618-2634. [PMID: 34254349 PMCID: PMC8581995 DOI: 10.1002/mrm.28907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 06/03/2021] [Accepted: 06/08/2021] [Indexed: 11/24/2022]
Abstract
PURPOSE Myelin has long been the target of neuroimaging research. However, most available techniques can only provide a voxel-averaged estimate of myelin content. In the human brain, white matter fiber pathways connecting different brain areas and carrying different functions often cross each other in the same voxel. A measure that can differentiate the degree of myelination of crossing fibers would provide a more specific marker of myelination. THEORY AND METHODS One MRI signal property that is sensitive to myelin is the phase accumulation. This sensitivity is used by measuring the phase accumulation of the signal remaining after diffusion-weighting, which is called diffusion-prepared phase imaging (DIPPI). Including diffusion-weighting before estimating the phase accumulation has two distinct advantages for estimating the degree of myelination: (1) It increases the relative contribution of intra-axonal water, whose phase is related linearly to the thickness of the surrounding myelin (in particular the log g-ratio); and (2) it gives directional information, which can be used to distinguish between crossing fibers. Here the DIPPI sequence is described, an approach is proposed to estimate the log g-ratio, and simulations are used and DIPPI data acquired in an isotropic phantom to quantify other sources of phase accumulation. RESULTS The expected bias is estimated in the log g-ratio for reasonable in vivo acquisition parameters caused by eddy currents (~4%-10%), remaining extra-axonal signal (~15%), and gradients in the bulk off-resonance field (<10% for most of the brain). CONCLUSION This new sequence may provide a g-ratio estimate per fiber population crossing within a voxel.
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Affiliation(s)
- Michiel Cottaar
- Wellcome Centre for Integrative Neuroimaging—Centre for Functional Magnetic Resonance Imaging of the BrainJohn Radcliffe HospitalUniversity of OxfordOxfordUnited Kingdom
| | - Wenchuan Wu
- Wellcome Centre for Integrative Neuroimaging—Centre for Functional Magnetic Resonance Imaging of the BrainJohn Radcliffe HospitalUniversity of OxfordOxfordUnited Kingdom
| | - Benjamin C. Tendler
- Wellcome Centre for Integrative Neuroimaging—Centre for Functional Magnetic Resonance Imaging of the BrainJohn Radcliffe HospitalUniversity of OxfordOxfordUnited Kingdom
| | - Zoltan Nagy
- Laboratory for Social and Neural Systems ResearchUniversity of ZurichZurichSwitzerland
| | - Karla Miller
- Wellcome Centre for Integrative Neuroimaging—Centre for Functional Magnetic Resonance Imaging of the BrainJohn Radcliffe HospitalUniversity of OxfordOxfordUnited Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging—Centre for Functional Magnetic Resonance Imaging of the BrainJohn Radcliffe HospitalUniversity of OxfordOxfordUnited Kingdom
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31
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Emmerich J, Bachert P, Ladd ME, Straub S. On the separation of susceptibility sources in quantitative susceptibility mapping: Theory and phantom validation with an in vivo application to multiple sclerosis lesions of different age. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 330:107033. [PMID: 34303117 DOI: 10.1016/j.jmr.2021.107033] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 06/14/2021] [Accepted: 07/08/2021] [Indexed: 06/13/2023]
Abstract
PURPOSE In biological tissue, phase contrast is determined by multiple substances such as iron, myelin or calcifications. Often, these substances occur co-located within the same measurement volume. However, quantitative susceptibility mapping can solely measure the average susceptibility per voxel. To provide new insight in disease progression and mechanisms in neurological diseases, where multiple processes such as demyelination and iron accumulation occur simultaneously in the same location, a separation of susceptibility sources is desirable to disentangle the underlying susceptibility proportions. METHODS The basic concept of separating the susceptibility effects from sources with different sign within one voxel is to include information on relaxation rate ΔR2∗ in the quantitative susceptibility mapping reconstruction pipeline. The presented reconstruction algorithm is implemented as a constrained minimization problem and solved using conjugate gradients. The algorithm is evaluated using a software phantom and validated in MRI measurements with a phantom containing mixtures of microscopic positive and negative susceptibility sources. Data from three multiple sclerosis patients are used to show in vivo feasibility. RESULTS In numerical simulations, the feasibility of disentangling susceptibility sources within the same voxel was confirmed provided the critera of the static dephasing regime were fulfilled. In phantom experiments, the magnitude decay kernel, which is an essential reconstruction parameter of the algorithm, was determined to be Dm=194.5T-1s-1ppm-1, and susceptibility sources could be separated in MRI measurement data. CONCLUSIONS In conclusion, in this study a detailed description of the implementation of an algorithm for the separation of positive and negative susceptibility sources within the same volume element as well as its limitations is presented and validated quantitatively in both simulation and phantom experiments for the first time. An application to multiple sclerosis lesions shows promising results for in vivo usability.
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Affiliation(s)
- Julian Emmerich
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany; Faculty of Medicine, Heidelberg University, Heidelberg, Germany
| | - Sina Straub
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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Tax CMW, Kleban E, Chamberland M, Baraković M, Rudrapatna U, Jones DK. Measuring compartmental T 2-orientational dependence in human brain white matter using a tiltable RF coil and diffusion-T 2 correlation MRI. Neuroimage 2021; 236:117967. [PMID: 33845062 PMCID: PMC8270891 DOI: 10.1016/j.neuroimage.2021.117967] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 02/15/2021] [Accepted: 03/08/2021] [Indexed: 02/08/2023] Open
Abstract
The anisotropy of brain white matter microstructure manifests itself in orientational-dependence of various MRI contrasts, and can result in significant quantification biases if ignored. Understanding the origins of this orientation-dependence could enhance the interpretation of MRI signal changes in development, ageing and disease and ultimately improve clinical diagnosis. Using a novel experimental setup, this work studies the contributions of the intra- and extra-axonal water to the orientation-dependence of one of the most clinically-studied parameters, apparent transverse relaxation T2. Specifically, a tiltable receive coil is interfaced with an ultra-strong gradient MRI scanner to acquire multidimensional MRI data with an unprecedented range of acquisition parameters. Using this setup, compartmental T2 can be disentangled based on differences in diffusional-anisotropy, and its orientation-dependence further elucidated by re-orienting the head with respect to the main magnetic field B→0. A dependence of (compartmental) T2 on the fibre orientation w.r.t. B→0 was observed, and further quantified using characteristic representations for susceptibility- and magic angle effects. Across white matter, anisotropy effects were dominated by the extra-axonal water signal, while the intra-axonal water signal decay varied less with fibre-orientation. Moreover, the results suggest that the stronger extra-axonal T2 orientation-dependence is dominated by magnetic susceptibility effects (presumably from the myelin sheath) while the weaker intra-axonal T2 orientation-dependence may be driven by a combination of microstructural effects. Even though the current design of the tiltable coil only offers a modest range of angles, the results demonstrate an overall effect of tilt and serve as a proof-of-concept motivating further hardware development to facilitate experiments that explore orientational anisotropy. These observations have the potential to lead to white matter microstructural models with increased compartmental sensitivity to disease, and can have direct consequences for longitudinal and group-wise T2- and diffusion-MRI data analysis, where the effect of head-orientation in the scanner is commonly ignored.
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Affiliation(s)
- Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, UK; University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Elena Kleban
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Muhamed Baraković
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK; Signal Processing Laboratory 5, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland; Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel, Basel, Switzerland
| | - Umesh Rudrapatna
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK; Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
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Yablonskiy DA, Wen J, Kothapalli SVVN, Sukstanskii AL. In vivo evaluation of heme and non-heme iron content and neuronal density in human basal ganglia. Neuroimage 2021; 235:118012. [PMID: 33838265 PMCID: PMC10468262 DOI: 10.1016/j.neuroimage.2021.118012] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 03/24/2021] [Accepted: 03/25/2021] [Indexed: 12/16/2022] Open
Abstract
Non-heme iron is an important element supporting the structure and functioning of biological tissues. Imbalance in non-heme iron can lead to different neurological disorders. Several MRI approaches have been developed for iron quantification relying either on the relaxation properties of MRI signal or measuring tissue magnetic susceptibility. Specific quantification of the non-heme iron can, however, be constrained by the presence of the heme iron in the deoxygenated blood and contribution of cellular composition. The goal of this paper is to introduce theoretical background and experimental MRI method allowing disentangling contributions of heme and non-heme irons simultaneously with evaluation of tissue neuronal density in the iron-rich basal ganglia. Our approach is based on the quantitative Gradient Recalled Echo (qGRE) MRI technique that allows separation of the total R2* metric characterizing decay of GRE signal into tissue-specific (R2t*) and the baseline blood oxygen level-dependent (BOLD) contributions. A combination with the QSM data (also available from the qGRE signal phase) allowed further separation of the tissue-specific R2t* metric in a cell-specific and non-heme-iron-specific contributions. It is shown that the non-heme iron contribution to R2t* relaxation can be described with the previously developed Gaussian Phase Approximation (GPA) approach. qGRE data were obtained from 22 healthy control participants (ages 26-63 years). Results suggest that the ferritin complexes are aggregated in clusters with an average radius about 100nm comprising approximately 2600 individual ferritin units. It is also demonstrated that the concentrations of heme and non-heme iron tend to increase with age. The strongest age effect was seen in the pallidum region, where the highest age-related non-heme iron accumulation was observed.
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Affiliation(s)
- Dmitriy A Yablonskiy
- Department of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis, MO 63110, United States.
| | - Jie Wen
- Department of Radiology, The First Affiliated Hospital of USTC, Hefei, Anhui 230001, China
| | - Satya V V N Kothapalli
- Department of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis, MO 63110, United States
| | - Alexander L Sukstanskii
- Department of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis, MO 63110, United States
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Shin HG, Lee J, Yun YH, Yoo SH, Jang J, Oh SH, Nam Y, Jung S, Kim S, Fukunaga M, Kim W, Choi HJ, Lee J. χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain. Neuroimage 2021; 240:118371. [PMID: 34242783 DOI: 10.1016/j.neuroimage.2021.118371] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 07/04/2021] [Accepted: 07/05/2021] [Indexed: 11/26/2022] Open
Abstract
Obtaining a histological fingerprint from the in-vivo brain has been a long-standing target of magnetic resonance imaging (MRI). In particular, non-invasive imaging of iron and myelin, which are involved in normal brain functions and are histopathological hallmarks in neurodegenerative diseases, has practical utilities in neuroscience and medicine. Here, we propose a biophysical model that describes the individual contribution of paramagnetic (e.g., iron) and diamagnetic (e.g., myelin) susceptibility sources to the frequency shift and transverse relaxation of MRI signals. Using this model, we develop a method, χ-separation, that generates the voxel-wise distributions of the two sources. The method is validated using computer simulation and phantom experiments, and applied to ex-vivo and in-vivo brains. The results delineate the well-known histological features of iron and myelin in the specimen, healthy volunteers, and multiple sclerosis patients. This new technology may serve as a practical tool for exploring the microstructural information of the brain.
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Affiliation(s)
- Hyeong-Geol Shin
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
| | - Jingu Lee
- AIRS Medical Inc., Seoul, Republic of Korea
| | - Young Hyun Yun
- Department of Medicine, Anatomy and Cell Biology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Seong Ho Yoo
- Department of Forensic Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jinhee Jang
- Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Se-Hong Oh
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea
| | - Yoonho Nam
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea
| | - Sehoon Jung
- Research Institute of Industrial Science and Technology, Pohang, Republic of Korea
| | - Sunhye Kim
- Research Institute of Industrial Science and Technology, Pohang, Republic of Korea
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Okazaki, Japan
| | - Woojun Kim
- Department of Neurology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyung Jin Choi
- Department of Biomedical Sciences, Anatomy and Cell Biology, Neuroscience Research Institute, Wide River Institute of Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jongho Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
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Li Y, Xiong J, Guo R, Zhao Y, Li Y, Liang ZP. Improved estimation of myelin water fractions with learned parameter distributions. Magn Reson Med 2021; 86:2795-2809. [PMID: 34216050 DOI: 10.1002/mrm.28889] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 05/20/2021] [Accepted: 05/21/2021] [Indexed: 11/07/2022]
Abstract
PURPOSE To improve estimation of myelin water fraction (MWF) in the brain from multi-echo gradient-echo imaging data. METHODS A systematic sensitivity analysis was first conducted to characterize the conventional exponential models used for MWF estimation. A new estimation method was then proposed for improved estimation of MWF from practical gradient-echo imaging data. The proposed method uses an extended signal model that includes a finite impulse response filter to compensate for practical signal variations. This new model also enables the use of prelearned parameter distributions as well as low-rank signal structures to improve parameter estimation. The resulting parameter estimation problem was solved optimally in the Bayesian sense. RESULTS Our sensitivity analysis results showed that the conventional exponential models were very sensitive to measurement noise and modeling errors. Our simulation and experimental results showed that our proposed method provided a substantial improvement in reliability, reproducibility, and robustness of MWF estimates over the conventional methods. Clinical results obtained from stroke patients indicated that the proposed method, with its improved capability, could reveal the loss of myelin in lesions, demonstrating its translational potentials. CONCLUSION This paper addressed the problem of robust MWF estimation from gradient-echo imaging data. A new method was proposed to provide improved MWF estimation in the presence of significant noise and modeling errors. The performance of the proposed method has been evaluated using both simulated and experimental data, showing significantly improved robustness over the existing methods. The proposed method may prove useful for quantitative myelin imaging in clinical applications.
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Affiliation(s)
- Yudu Li
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Jiahui Xiong
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Rong Guo
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Yibo Zhao
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Yao Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zhi-Pei Liang
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
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36
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Chen L, Cai S, van Zijl PC, Li X. Single-step calculation of susceptibility through multiple orientation sampling. NMR IN BIOMEDICINE 2021; 34:e4517. [PMID: 33822416 PMCID: PMC8184590 DOI: 10.1002/nbm.4517] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 03/06/2021] [Accepted: 03/14/2021] [Indexed: 06/12/2023]
Abstract
Quantitative susceptibility mapping (QSM) was developed to estimate the spatial distribution of magnetic susceptibility from MR signal phase acquired using a gradient echo (GRE) sequence. The field-to-susceptibility inversion in QSM is known to be ill-posed and needs numerical stabilization through either regularization or data oversampling. The calculation of susceptibility through the multiple orientation sampling (COSMOS) method uses phase data acquired at three or more head orientations to achieve a well-conditioned field-to-susceptibility inversion and is often considered the gold standard for in vivo QSM. However, the conventional COSMOS approach, here named multistep COSMOS (MSCOSMOS), solves the dipole inversion from the local field derived from raw GRE phase through multiple steps of phase preprocessing. Error propagations between these consecutive phase processing steps can thus affect the final susceptibility quantification. On the other hand, recently proposed single-step QSM (SSQSM) methods aim to solve an integrated inversion from unprocessed or total phase to mitigate such error propagations but have been limited to single orientation QSM. This study therefore aimed to test the feasibility of using single-step COSMOS (SSCOSMOS) to jointly perform background field removal and dipole inversion with multiple orientation sampling, which could serve as a better standard for gauging SSQSM methods. We incorporated multiple spherical mean value (SMV) kernels of various radii with the dipole inversion in SSCOSMOS. QSM reconstructions with SSCOSMOS and MSCOSMOS were compared using both simulations with a numerical head phantom and in vivo human brain data. SSCOSMOS permitted integrated background removal and dipole inversion without the need to adjust any regularization parameters. In addition, with sufficiently large SMV kernels, SSCOSMOS performed consistently better than MSCOSMOS in all the tested error metrics in our simulations, giving better susceptibility quantification and smaller reconstruction error. Consistent tissue susceptibility values were obtained between SSCOSMOS and MSCOSMOS.
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Affiliation(s)
- Lin Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
- 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
| | - Shuhui Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - 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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37
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Lenz C, Berger C, Bauer M, Scheurer E, Birkl C. Sensitivity of fiber orientation dependent R 2 ∗ to temperature and post mortem interval. Magn Reson Med 2021; 86:2703-2715. [PMID: 34086354 DOI: 10.1002/mrm.28874] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 04/23/2021] [Accepted: 05/10/2021] [Indexed: 12/21/2022]
Abstract
PURPOSE R 2 ∗ imaging of brain white matter is well known for being sensitive to the orientation of nerve fibers with respect to the B0 field of the MRI scanner. The goal of this study was to evaluate whether and to which extent fiber orientation dependent R 2 ∗ differs between in vivo and post mortem in situ examinations, and to investigate the influence of varying temperatures and post mortem intervals (PMI). METHODS Post mortem in situ and in vivo MRI scans were conducted at 3T. R 2 ∗ was acquired with a multi-echo gradient-echo sequence, and the orientation of white matter fibers was computed using diffusion tensor imaging (DTI). Fitting of the measured fiber orientation dependent R 2 ∗ was performed using three different formulations of a previously proposed model. RESULTS R 2 ∗ increased with increasing fiber angle for in vivo and post mortem in situ examinations, whereby the orientation dependency was lower post mortem. The different formulations of the fiber orientation model resulted in an identical fit, but showed large variations of the estimated parameters. The higher order orientation dependent R 2 ∗ components significantly decreased with decreasing temperature, while the orientation independent R 2 ∗ components showed no significant correlation with either temperature or PMI. CONCLUSION Although the mean diffusivity is strongly reduced post mortem, we could successfully estimate the fiber angle using DTI. Due to the strong correlation of the higher order orientation dependent R 2 ∗ components with temperature, the decreased R 2 ∗ fiber orientation dependency post mortem in situ might primarily be attributed to the lower brain temperature.
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Affiliation(s)
- Claudia Lenz
- Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Institute of Forensic Medicine, Health Department Basel-Stadt, Basel, Switzerland
| | - Celine Berger
- Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Institute of Forensic Medicine, Health Department Basel-Stadt, Basel, Switzerland
| | - Melanie Bauer
- Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Institute of Forensic Medicine, Health Department Basel-Stadt, Basel, Switzerland
| | - Eva Scheurer
- Institute of Forensic Medicine, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Institute of Forensic Medicine, Health Department Basel-Stadt, Basel, Switzerland
| | - Christoph Birkl
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria
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38
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Hédouin R, Metere R, Chan KS, Licht C, Mollink J, van Walsum AMC, Marques JP. Decoding the microstructural properties of white matter using realistic models. Neuroimage 2021; 237:118138. [PMID: 33964461 DOI: 10.1016/j.neuroimage.2021.118138] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 04/14/2021] [Accepted: 04/19/2021] [Indexed: 11/24/2022] Open
Abstract
Multi-echo gradient echo (ME-GRE) magnetic resonance signal evolution in white matter has a strong dependence on the orientation of myelinated axons with respect to the main static field. Although analytical solutions have been able to predict some of the white matter (WM) signal behaviour of the hollow cylinder model, it has been shown that realistic models of WM offer a better description of the signal behaviour observed. In this work, we present a pipeline to (i) generate realistic 2D WM models with their microstructure based on real axon morphology with adjustable fiber volume fraction (FVF) and g-ratio. We (ii) simulate their interaction with the static magnetic field to be able to simulate their MR signal. For the first time, we (iii) demonstrate that realistic 2D WM models can be used to simulate a MR signal that provides a good approximation of the signal obtained from a real 3D WM model derived from electron microscopy. We then (iv) demonstrate in silico that 2D WM models can be used to predict microstructural parameters in a robust way if ME-GRE multi-orientation data is available and the main fiber orientation in each pixel is known using DTI. A deep learning network was trained and characterized in its ability to recover the desired microstructural parameters such as FVF, g-ratio, free and bound water transverse relaxation and magnetic susceptibility. Finally, the network was trained to recover these micro-structural parameters from an ex vivo dataset acquired in 9 orientations with respect to the magnetic field and 12 echo times. We demonstrate that this is an overdetermined problem and that as few as 3 orientations can already provide comparable results for some of the decoded metrics.
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Affiliation(s)
- Renaud Hédouin
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands; Empenn, INRIA, INSERM, CNRS, Université de Rennes 1, Rennes, France.
| | - Riccardo Metere
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Kwok-Shing Chan
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Christian Licht
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Jeroen Mollink
- Radboud University Medical Centre, Medical Imaging and Anatomy, Nijmegen, Netherlands
| | | | - José P Marques
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
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39
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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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40
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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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41
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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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42
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Manning AP, MacKay AL, Michal CA. Understanding aqueous and non-aqueous proton T 1 relaxation in brain. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 323:106909. [PMID: 33453678 DOI: 10.1016/j.jmr.2020.106909] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 11/17/2020] [Accepted: 12/23/2020] [Indexed: 06/12/2023]
Abstract
A full picture of longitudinal relaxation in complex heterogeneous environments like white matter brain tissue remains elusive. In tissue, successive approximations, from the solvation layer model to the two pool model, have highlighted how longitudinal magnetization evolution depends on both inter-compartmental exchange and spin-lattice relaxation. In white matter, however, these models fail to capture the behaviour of the two distinct aqueous pools, myelin water and intra/extra-cellular water. A challenge with testing more comprehensive multi-pool models lies in directly observing all pools, both aqueous and non-aqueous. In this work, we advance these efforts by integrating three main experimental and analytical elements: direct observation of the longitudinal relaxation of both the aqueous and the non-aqueous protons in white matter, a wide range of different initial conditions, and application of an analysis pipeline which includes lineshape, CPMG, and fitting of a four pool model. An eigenvector interpretation of the four pool model highlights how longitudinal relaxation in white matter depends on initial conditions. We find that a single set of model parameters is able to describe the entire range of relaxation behaviour observed in all the separable aqueous and non-aqueous pools in experiments involving six different initial conditions. Understanding of the nature and connectedness of the tissue components is crucial in the design and interpretation of many MRI measurements, especially those based on magnetization transfer and longitudinal relaxation. In particular, the dependency of relaxation behaviour on initial conditions is likely the basis for understanding method-dependent discrepancies in in vivo T1.
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Affiliation(s)
- Alan P Manning
- Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada
| | - Alex L MacKay
- Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Department of Radiology, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC V6T 2B5, Canada
| | - Carl A Michal
- Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada.
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Wang H, Wang J, Cai G, Liu Y, Qu Y, Wu T. A Physical Perspective to the Inductive Function of Myelin-A Missing Piece of Neuroscience. Front Neural Circuits 2021; 14:562005. [PMID: 33536878 PMCID: PMC7848263 DOI: 10.3389/fncir.2020.562005] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 12/09/2020] [Indexed: 11/21/2022] Open
Abstract
Starting from the inductance in neurons, two physical origins are discussed, which are the coil inductance of myelin and the piezoelectric effect of the cell membrane. The direct evidence of the coil inductance of myelin is the opposite spiraling phenomenon between adjacent myelin sheaths confirmed by previous studies. As for the piezoelectric effect of the cell membrane, which has been well-known in physics, the direct evidence is the mechanical wave accompany with action potential. Therefore, a more complete physical nature of neural signals is provided. In conventional neuroscience, the neural signal is a pure electrical signal. In our new theory, the neural signal is an energy pulse containing electrical, magnetic, and mechanical components. Such a physical understanding of the neural signal and neural systems significantly improve the knowledge of the neurons. On the one hand, we achieve a corrected neural circuit of an inductor-capacitor-capacitor (LCC) form, whose frequency response and electrical characteristics have been validated by previous studies and the modeling fitting of artifacts in our experiments. On the other hand, a number of phenomena observed in neural experiments are explained. In particular, they are the mechanism of magnetic nerve stimulations and ultrasound nerve stimulations, the MRI image contrast issue and Anode Break Excitation. At last, the biological function of myelin is summarized. It is to provide inductance in the process of neural signal, which can enhance the signal speed in peripheral nervous systems and provide frequency modulation function in central nervous systems.
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Affiliation(s)
- Hao Wang
- Institute of Biomedical & Health Engineering, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen, China.,Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Jiahui Wang
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Guangyi Cai
- Institute of Biomedical & Health Engineering, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen, China
| | - Yonghong Liu
- Institute of Biomedical & Health Engineering, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen, China
| | - Yansong Qu
- Institute of Biomedical & Health Engineering, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen, China
| | - Tianzhun Wu
- Institute of Biomedical & Health Engineering, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen, China.,Key Laboratory of Health Bioinformatics, Chinese Academy of Sciences, Shenzhen, China
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Mohammadi S, Callaghan MF. Towards in vivo g-ratio mapping using MRI: Unifying myelin and diffusion imaging. J Neurosci Methods 2021; 348:108990. [PMID: 33129894 PMCID: PMC7840525 DOI: 10.1016/j.jneumeth.2020.108990] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 09/21/2020] [Accepted: 10/20/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND The g-ratio, quantifying the comparative thickness of the myelin sheath encasing an axon, is a geometrical invariant that has high functional relevance because of its importance in determining neuronal conduction velocity. Advances in MRI data acquisition and signal modelling have put in vivo mapping of the g-ratio, across the entire white matter, within our reach. This capacity would greatly increase our knowledge of the nervous system: how it functions, and how it is impacted by disease. NEW METHOD This is the second review on the topic of g-ratio mapping using MRI. RESULTS This review summarizes the most recent developments in the field, while also providing methodological background pertinent to aggregate g-ratio weighted mapping, and discussing pitfalls associated with these approaches. COMPARISON WITH EXISTING METHODS Using simulations based on recently published data, this review reveals caveats to the state-of-the-art calibration methods that have been used for in vivo g-ratio mapping. It highlights the need to estimate both the slope and offset of the relationship between these MRI-based markers and the true myelin volume fraction if we are really to achieve the goal of precise, high sensitivity g-ratio mapping in vivo. Other challenges discussed in this review further evidence the need for gold standard measurements of human brain tissue from ex vivo histology. CONCLUSIONS We conclude that the quest to find the most appropriate MRI biomarkers to enable in vivo g-ratio mapping is ongoing, with the full potential of many novel techniques yet to be investigated.
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Affiliation(s)
- Siawoosh Mohammadi
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
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Chan KS, Marques JP. SEPIA-Susceptibility mapping pipeline tool for phase images. Neuroimage 2020; 227:117611. [PMID: 33309901 DOI: 10.1016/j.neuroimage.2020.117611] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 10/14/2020] [Accepted: 11/25/2020] [Indexed: 12/20/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) is a physics-driven computational technique that has a high sensitivity in quantifying iron deposition based on MRI phase images. Furthermore, it has a unique ability to distinguish paramagnetic and diamagnetic contributions such as haemorrhage and calcification based on image contrast. These properties have contributed to a growing interest to use QSM not only in research but also in clinical applications. However, it is challenging to obtain high quality susceptibility map because of its ill-posed nature, especially for researchers who have less experience with QSM and the optimisation of its pipeline. In this paper, we present an open-source processing pipeline tool called SuscEptibility mapping PIpeline tool for phAse images (SEPIA) dedicated to the post-processing of MRI phase images and QSM. SEPIA connects various QSM toolboxes freely available in the field to offer greater flexibility in QSM processing. It also provides an interactive graphical user interface to construct and execute a QSM processing pipeline, simplifying the workflow in QSM research. The extendable design of SEPIA also allows developers to deploy their methods in the framework, providing a platform for developers and researchers to share and utilise the state-of-the-art methods in QSM.
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Affiliation(s)
- Kwok-Shing Chan
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.
| | - José P Marques
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
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Bonny JM, Traore A, Bouhrara M, Spencer RG, Pages G. Parsimonious discretization for characterizing multi-exponential decay in magnetic resonance. NMR IN BIOMEDICINE 2020; 33:e4366. [PMID: 32789944 PMCID: PMC9648165 DOI: 10.1002/nbm.4366] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 04/15/2020] [Accepted: 06/10/2020] [Indexed: 06/11/2023]
Abstract
We address the problem of analyzing noise-corrupted magnetic resonance transverse decay signals as a superposition of underlying independently decaying monoexponentials of positive amplitude. First, we indicate the manner in which this is an ill-conditioned inverse problem, rendering the analysis unstable with respect to noise. Second, we define an approach to this analysis, stabilized solely by the nonnegativity constraint without regularization. This is made possible by appropriate discretization, which is coarser than that often used in practice. Thirdly, we indicate further stabilization by inspecting the plateaus of cumulative distributions. We demonstrate our approach through analysis of simulated myelin water fraction measurements, and compare the accuracy with more conventional approaches. Finally, we apply our method to brain imaging data obtained from a human subject, showing that our approach leads to maps of the myelin water fraction which are much more stable with respect to increasing noise than those obtained with conventional approaches.
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Affiliation(s)
- Jean-Marie Bonny
- INRAE, UR QuaPA, Saint-Genès-Champanelle, France
- AgroResonance, INRAE, 2018, Nuclear Magnetic Resonance Facility for Agronomy, Food and Health, Saint-Genès-Champanelle, France
| | - Amidou Traore
- INRAE, UR QuaPA, Saint-Genès-Champanelle, France
- AgroResonance, INRAE, 2018, Nuclear Magnetic Resonance Facility for Agronomy, Food and Health, Saint-Genès-Champanelle, France
| | | | | | - Guilhem Pages
- INRAE, UR QuaPA, Saint-Genès-Champanelle, France
- AgroResonance, INRAE, 2018, Nuclear Magnetic Resonance Facility for Agronomy, Food and Health, Saint-Genès-Champanelle, France
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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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48
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Kaden E, Gyori NG, Rudrapatna SU, Barskaya IY, Dragonu I, Does MD, Jones DK, Clark CA, Alexander DC. Microscopic susceptibility anisotropy imaging. Magn Reson Med 2020; 84:2739-2753. [PMID: 32378746 PMCID: PMC7402021 DOI: 10.1002/mrm.28303] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 04/07/2020] [Accepted: 04/08/2020] [Indexed: 11/25/2022]
Abstract
PURPOSE The gradient-echo MR signal in brain white matter depends on the orientation of the fibers with respect to the external magnetic field. To map microstructure-specific magnetic susceptibility in orientationally heterogeneous material, it is thus imperative to regress out unwanted orientation effects. METHODS This work introduces a novel framework, referred to as microscopic susceptibility anisotropy imaging, that disentangles the 2 principal effects conflated in gradient-echo measurements, (a) the susceptibility properties of tissue microenvironments, especially the myelin microstructure, and (b) the axon orientation distribution relative to the magnetic field. Specifically, we utilize information about the orientational tissue structure inferred from diffusion MRI data to factor out the B 0 -direction dependence of the frequency difference signal. RESULTS A human pilot study at 3 T demonstrates proxy maps of microscopic susceptibility anisotropy unconfounded by fiber crossings and orientation dispersion as well as magnetic field direction. The developed technique requires only a dual-echo gradient-echo scan acquired at 1 or 2 head orientations with respect to the magnetic field and a 2-shell diffusion protocol achievable on standard scanners within practical scan times. CONCLUSIONS The quantitative recovery of microscopic susceptibility features in the presence of orientational heterogeneity potentially improves the assessment of microstructural tissue integrity.
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Affiliation(s)
- Enrico Kaden
- Centre for Medical Image ComputingUniversity College LondonLondonUK
- Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
| | - Noemi G. Gyori
- Centre for Medical Image ComputingUniversity College LondonLondonUK
- Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
| | | | | | | | - Mark D. Does
- Institute of Imaging ScienceVanderbilt UniversityNashvilleTNUSA
| | - Derek K. Jones
- Cardiff University Brain Research Imaging CentreCardiff UniversityCardiffUK
- School of PsychologyAustralian Catholic UniversityMelbourneVICAustralia
| | - Chris A. Clark
- Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
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Chan KS, Marques JP. Multi-compartment relaxometry and diffusion informed myelin water imaging – Promises and challenges of new gradient echo myelin water imaging methods. Neuroimage 2020; 221:117159. [DOI: 10.1016/j.neuroimage.2020.117159] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 07/06/2020] [Accepted: 07/07/2020] [Indexed: 01/08/2023] Open
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50
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Priovoulos N, van Boxel SCJ, Jacobs HIL, Poser BA, Uludag K, Verhey FRJ, Ivanov D. Unraveling the contributions to the neuromelanin-MRI contrast. Brain Struct Funct 2020; 225:2757-2774. [PMID: 33090274 PMCID: PMC7674382 DOI: 10.1007/s00429-020-02153-z] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 10/01/2020] [Indexed: 12/11/2022]
Abstract
The Locus Coeruleus (LC) and the Substantia Nigra (SN) are small brainstem nuclei that change with aging and may be involved in the development of various neurodegenerative and psychiatric diseases. Magnetization Transfer (MT) MRI has been shown to facilitate LC and the SN visualization, and the observed contrast is assumed to be related to neuromelanin accumulation. Imaging these nuclei may have predictive value for the progression of various diseases, but interpretation of previous studies is hindered by the fact that the precise biological source of the contrast remains unclear, though several hypotheses have been put forward. To inform clinical studies on the possible biological interpretation of the LC- and SN contrast, we examined an agar-based phantom containing samples of natural Sepia melanin and synthetic Cys-Dopa-Melanin and compared this to the in vivo human LC and SN. T1 and T2* maps, MT spectra and relaxation times of the phantom, the LC and the SN were measured, and a two-pool MT model was fitted. Additionally, Bloch simulations and a transient MT experiment were conducted to confirm the findings. Overall, our results indicate that Neuromelanin-MRI contrast in the LC likely results from a lower macromolecular fraction, thus facilitating interpretation of results in clinical populations. We further demonstrate that in older individuals T1 lengthening occurs in the LC.
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Affiliation(s)
- Nikos Priovoulos
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Faculty of Health, Medicine and Life Science, Maastricht University, Maastricht, Netherlands.
| | - Stan C J van Boxel
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Faculty of Health, Medicine and Life Science, Maastricht University, Maastricht, Netherlands
| | - Heidi I L Jacobs
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Faculty of Health, Medicine and Life Science, Maastricht University, Maastricht, Netherlands.,Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.,Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Benedikt A Poser
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Kamil Uludag
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon, Republic of Korea.,Techna Institute and Koerner Scientist in MR Imaging, University Health Network, 121-100 College Street, Toronto, M5G 1L5, Canada
| | - Frans R J Verhey
- School for Mental Health and Neuroscience, Alzheimer Center Limburg, Faculty of Health, Medicine and Life Science, Maastricht University, Maastricht, Netherlands
| | - Dimo Ivanov
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
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