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Lin Y, Chan KH, Mak HKF, Yau KX, Cao P. Quantitative myelin water assessment for multiple sclerosis using multi-inversion magnetic resonance fingerprinting. Med Phys 2024. [PMID: 39388122 DOI: 10.1002/mp.17461] [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: 06/18/2024] [Revised: 09/05/2024] [Accepted: 09/27/2024] [Indexed: 10/15/2024] Open
Abstract
BACKGROUND Multiple sclerosis (MS) is a demyelination disease. Myelin water is a biomarker of myelin and thus myelin water imaging is a vital tool to provide insight into the demyelination process. PURPOSE This study aimed to characterize the multiple compartments including myelin water fraction (MWF), gray matter (GM) cellular water, white matter (WM) cellular water, and cerebrospinal fluid (CSF) using multiple inversion recovery (mIR) magnetic resonance fingerprinting (MRF) on a clinical MS cohort. METHODS The Phantom experiment was conducted with tubes containing different WM and GM concentrations extracted from pig brains. For the in-vivo experiment, 23 healthy control (HC) volunteers and 18 MS patients were recruited for this study. The experiments were performed using a clinical 3T MRI. A multi-slice, fast imaging with a steady-state precession (FISP) based mIR MRF protocol was used to obtain the MWF measurements, with 6 min of scan time for each volunteer. The quantification was based on the iterative non-negative least squares (NNLS) with reweighting. The brain compartments quantified were myelin water, WM cellular water, GM cellular water, and CSF. A radiologist with 6 years of experience labeled the MS lesions on FLAIR, MPRAGE, and MWF. Statistical analysis was performed by applying unpaired and paired student's t-tests to compare the MWF results in different groups and in normal-appearing white matter (NAWM) and MS lesions. RESULTS The phantom result demonstrated the ability to detect MWF with various myelin concentrations. The maps derived from mIR MRF, including MWF, WM cellular water, GM cellular water, and CSF were consistent with the anatomical structures observed in FLAIR and MPRAGE. The MWF values in the NAWM of MS patients were significantly different from those in HC, with values of 0.32 ± 0.025 and 0.25 ± 0.036, respectively. Additionally, the MWF values in WM lesions were significantly smaller than in NAWM at 0.034 ± 0.036. CONCLUSION The mIR-MRF technique, using multi-compartment analysis, can simultaneously generate maps of MWF, WM cellular water, GM cellular water, and CSF with sufficient brain coverage and in a reasonably short scan time. The MWF map might provide insights into the demyelination associated with MS.
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Affiliation(s)
- Yingying Lin
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
| | - Koon-Ho Chan
- Department of Medicine, The University of Hong Kong, Hong Kong, China
| | - Henry Ka-Fung Mak
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
| | | | - Peng Cao
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
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Kitano S, Kanazawa Y, Harada M, Taniguchi Y, Hayashi H, Matsumoto Y, Ito K, Bito Y, Haga A. Conversion map from quantitative parameter mapping to myelin water fraction: comparison with R 1·R 2* and myelin water fraction in white matter. MAGMA (NEW YORK, N.Y.) 2024; 37:887-898. [PMID: 38581455 DOI: 10.1007/s10334-024-01155-w] [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: 12/27/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 04/08/2024]
Abstract
OBJECTIVE To clarify the relationship between myelin water fraction (MWF) and R1⋅R2* and to develop a method to calculate MWF directly from parameters derived from QPM, i.e., MWF converted from QPM (MWFQPM). MATERIALS AND METHODS Subjects were 12 healthy volunteers. On a 3 T MR scanner, dataset was acquired using spoiled gradient-echo sequence for QPM. MWF and R1⋅R2* maps were derived from the multi-gradient-echo (mGRE) dataset. Volume-of-interest (VOI) analysis using the JHU-white matter (WM) atlas was performed. All the data in the 48 WM regions measured VOI were plotted, and quadratic polynomial approximations of each region were derived from the relationship between R1·R2* and the two-pool model-MWF. The R1·R2* map was converted to MWFQPM map. MWF atlas template was generated using converted to MWF from R1·R2* per WM region. RESULTS The mean MWF and R1·R2* values for the 48 WM regions were 11.96 ± 6.63%, and 19.94 ± 4.59 s-2, respectively. A non-linear relationship in 48 regions of the WM between MWF and R1·R2* values was observed by quadratic polynomial approximation (R2 ≥ 0.963, P < 0.0001). DISCUSSION MWFQPM map improved image quality compared to the mGRE-MWF map. Myelin water atlas template derived from MWFQPM may be generated with combined multiple WM regions.
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Affiliation(s)
- Shun Kitano
- Graduate of Health Science, Tokushima University, 3-18-15 Kuramoto-cho, Tokushima, Tokushima, 770-8503, Japan
- Clinical Radiology Service, Kyoto University Hospital, Kyoto, 606-8507, Japan
| | - Yuki Kanazawa
- Graduate School of Biomedical Sciences, Tokushima University, 3-18-15 Kuramoto-cho, Tokushima, Tokushima, 770-8503, Japan.
| | - Masafumi Harada
- Graduate School of Biomedical Sciences, Tokushima University, 3-18-15 Kuramoto-cho, Tokushima, Tokushima, 770-8503, Japan
| | - Yo Taniguchi
- FUJIFILM Healthcare Corporation, 2-1 Shintoyofuta, Kashiwa, Chiba, 277-0804, Japan
| | - Hiroaki Hayashi
- College of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa, 920-0942, Japan
| | - Yuki Matsumoto
- Graduate School of Biomedical Sciences, Tokushima University, 3-18-15 Kuramoto-cho, Tokushima, Tokushima, 770-8503, Japan
| | - Kosuke Ito
- FUJIFILM Healthcare Corporation, 2-1 Shintoyofuta, Kashiwa, Chiba, 277-0804, Japan
| | - Yoshitaka Bito
- FUJIFILM Healthcare Corporation, 2-1 Shintoyofuta, Kashiwa, Chiba, 277-0804, Japan
| | - Akihiro Haga
- Graduate School of Biomedical Sciences, Tokushima University, 3-18-15 Kuramoto-cho, Tokushima, Tokushima, 770-8503, Japan
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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; 168:2243-2263. [PMID: 38973579 DOI: 10.1111/jnc.16170] [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: 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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Köhler C, Kuntke P, Sahoo P, Wahl H, Deoni SCL, Gärtner J, Dreha-Kulaczewski S, Kitzler HH. Atlas-based assessment of hypomyelination: Quantitative MRI in Pelizaeus-Merzbacher disease. Hum Brain Mapp 2024; 45:e70014. [PMID: 39230009 PMCID: PMC11372820 DOI: 10.1002/hbm.70014] [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: 02/27/2024] [Revised: 08/07/2024] [Accepted: 08/14/2024] [Indexed: 09/05/2024] Open
Abstract
Pelizaeus-Merzbacher disease (PMD) is a rare childhood hypomyelinating leukodystrophy. Quantification of the pronounced myelin deficit and delineation of subtle myelination processes are of high clinical interest. Quantitative magnetic resonance imaging (qMRI) techniques can provide in vivo insights into myelination status, its spatial distribution, and dynamics during brain maturation. They may serve as potential biomarkers to assess the efficacy of myelin-modulating therapies. However, registration techniques for image quantification and statistical comparison of affected pediatric brains, especially those of low or deviant image tissue contrast, with healthy controls are not yet established. This study aimed first to develop and compare postprocessing pipelines for atlas-based quantification of qMRI data in pediatric patients with PMD and evaluate their registration accuracy. Second, to apply an optimized pipeline to investigate spatial myelin deficiency using myelin water imaging (MWI) data from patients with PMD and healthy controls. This retrospective single-center study included five patients with PMD (mean age, 6 years ± 3.8) who underwent conventional brain MRI and diffusion tensor imaging (DTI), with MWI data available for a subset of patients. Three methods of registering PMD images to a pediatric template were investigated. These were based on (a) T1-weighted (T1w) images, (b) fractional anisotropy (FA) maps, and (c) a combination of T1w, T2-weighted, and FA images in a multimodal approach. Registration accuracy was determined by visual inspection and calculated using the structural similarity index method (SSIM). SSIM values for the registration approaches were compared using a t test. Myelin water fraction (MWF) was quantified from MWI data as an assessment of relative myelination. Mean MWF was obtained from two PMDs (mean age, 3.1 years ± 0.3) within four major white matter (WM) pathways of a pediatric atlas and compared to seven healthy controls (mean age, 3 years ± 0.2) using a Mann-Whitney U test. Our results show that visual registration accuracy estimation and computed SSIM were highest for FA-based registration, followed by multimodal, and T1w-based registration (SSIMFA = 0.67 ± 0.04 vs. SSIMmultimodal = 0.60 ± 0.03 vs. SSIMT1 = 0.40 ± 0.14). Mean MWF of patients with PMD within the WM pathways was significantly lower than in healthy controls MWFPMD = 0.0267 ± 0.021 vs. MWFcontrols = 0.1299 ± 0.039. Specifically, MWF was measurable in brain structures known to be myelinated at birth (brainstem) or postnatally (projection fibers) but was scarcely detectable in other brain regions (commissural and association fibers). Taken together, our results indicate that registration accuracy was highest with an FA-based registration pipeline, providing an alternative to conventional T1w-based registration approaches in the case of hypomyelinating leukodystrophies missing normative intrinsic tissue contrasts. The applied atlas-based analysis of MWF data revealed that the extent of spatial myelin deficiency in patients with PMD was most pronounced in commissural and association and to a lesser degree in brainstem and projection pathways.
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Affiliation(s)
- Caroline Köhler
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Paul Kuntke
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Prativa Sahoo
- Department of Pediatrics and Adolescent Medicine, University Medical Center Göttingen, Göttingen, Germany
| | - Hannes Wahl
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Sean C L Deoni
- Advanced Baby Imaging Lab, School of Engineering, Brown University, Providence, Rhode Island, USA
- Maternal, Newborn, and Child Health Discovery and Tools, Bill and Melinda Gates Foundation, Seattle, Washington, USA
| | - Jutta Gärtner
- Department of Pediatrics and Adolescent Medicine, University Medical Center Göttingen, Göttingen, Germany
| | - Steffi Dreha-Kulaczewski
- Department of Pediatrics and Adolescent Medicine, University Medical Center Göttingen, Göttingen, Germany
| | - Hagen H Kitzler
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
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Mendez Colmenares A, Thomas ML, Anderson C, Arciniegas DB, Calhoun V, Choi IY, Kramer AF, Li K, Lee J, Lee P, Burzynska AZ. Testing the structural disconnection hypothesis: Myelin content correlates with memory in healthy aging. Neurobiol Aging 2024; 141:21-33. [PMID: 38810596 PMCID: PMC11290458 DOI: 10.1016/j.neurobiolaging.2024.05.013] [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: 03/12/2024] [Revised: 05/07/2024] [Accepted: 05/21/2024] [Indexed: 05/31/2024]
Abstract
INTRODUCTION The "structural disconnection" hypothesis of cognitive aging suggests that deterioration of white matter (WM), especially myelin, results in cognitive decline, yet in vivo evidence is inconclusive. METHODS We examined age differences in WM microstructure using Myelin Water Imaging and Diffusion Tensor Imaging in 141 healthy participants (age 20-79). We used the Virginia Cognitive Aging Project and the NIH Toolbox® to generate composites for memory, processing speed, and executive function. RESULTS Voxel-wise analyses showed that lower myelin water fraction (MWF), predominantly in prefrontal WM, genu of the corpus callosum, and posterior limb of the internal capsule was associated with reduced memory performance after controlling for age, sex, and education. In structural equation modeling, MWF in the prefrontal white matter and genu of the corpus callosum significantly mediated the effect of age on memory, whereas fractional anisotropy (FA) did not. DISCUSSION Our findings support the disconnection hypothesis, showing that myelin decline contributes to age-related memory loss and opens avenues for interventions targeting myelin health.
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Affiliation(s)
- Andrea Mendez Colmenares
- The BRAiN lab, Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Behavioral Sciences Building, 303, 410 W Pitkin St, Fort Collins, CO 80523, USA
| | - Michael L Thomas
- Department of Psychology, Colorado State University, Behavioral Sciences Building, 303, 410 W Pitkin, St, Fort Collins, CO 80523, USA
| | - Charles Anderson
- Department of Computer Science, Colorado State University, 456 University Ave #444, Fort Collins, CO 80521, USA
| | - David B Arciniegas
- Marcus Institute for Brain Health, University of Colorado Anschutz Medical Campus, 12348 E Montview Blvd, Aurora, CO 80045, USA
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, 55 Park Pl NE, Atlanta, GA 30303, USA
| | - In-Young Choi
- Department of Neurology, Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, 3805 Eaton St, Kansas City, KS 66103, USA
| | - Arthur F Kramer
- Beckman Institute for Advanced Science and Technology at the University of Illinois, 405 N Mathews Ave, Urbana, IL 61801, USA; Center for Cognitive & Brain Health, Northeastern University, Address: 360 Huntington Ave, Boston, MA 02115, USA
| | - Kaigang Li
- Department of Health and Exercise Science, Colorado State University, 951 W Plum St, Fort Collins, CO 80521, USA
| | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, 232 Gongneung-ro, Nowon-gu, Seoul 01811, South Korea
| | - Phil Lee
- Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, 3805 Eaton St, Kansas City, KS 66103, USA
| | - Agnieszka Z Burzynska
- The BRAiN lab, Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Behavioral Sciences Building, 303, 410 W Pitkin St, Fort Collins, CO 80523, USA.
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Lee JJ, Scheuren PS, Liu H, Loke RWJ, Laule C, Loucks CM, Kramer JLK. The myelin water imaging transcriptome: myelin water fraction regionally varies with oligodendrocyte-specific gene expression. Mol Brain 2024; 17:45. [PMID: 39044257 PMCID: PMC11264438 DOI: 10.1186/s13041-024-01115-4] [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: 02/28/2024] [Accepted: 06/19/2024] [Indexed: 07/25/2024] Open
Abstract
Identifying sensitive and specific measures that can quantify myelin are instrumental in characterizing microstructural changes in neurological conditions. Neuroimaging transcriptomics is emerging as a valuable technique in this regard, offering insights into the molecular basis of promising candidates for myelin quantification, such as myelin water fraction (MWF). We aimed to demonstrate the utility of neuroimaging transcriptomics by validating MWF as a myelin measure. We utilized data from a normative MWF brain atlas, comprised of 50 healthy subjects (mean age = 25 years, range = 17-42 years) scanned at 3 Tesla. Magnetic resonance imaging data included myelin water imaging to extract MWF and T1 anatomical scans for image registration and segmentation. We investigated the inter-regional distributions of gene expression data from the Allen Human Brain Atlas in conjunction with inter-regional MWF distribution patterns. Pearson correlations were used to identify genes with expression profiles mirroring MWF. The Single Cell Type Atlas from the Human Protein Atlas was leveraged to classify genes into gene sets with high cell type specificity, and a control gene set with low cell type specificity. Then, we compared the Pearson correlation coefficients for each gene set to determine if cell type-specific gene expression signatures correlate with MWF. Pearson correlation coefficients between MWF and gene expression for oligodendrocytes and adipocytes were significantly higher than for the control gene set, whereas correlations between MWF and inhibitory/excitatory neurons were significantly lower. Our approach in integrating transcriptomics with neuroimaging measures supports an emerging technique for understanding and validating MRI-derived markers such as MWF.
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Affiliation(s)
- Jaimie J Lee
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Paulina S Scheuren
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Hanwen Liu
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Ryan W J Loke
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Catrina M Loucks
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC, Canada
- Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - John L K Kramer
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada.
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC, Canada.
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Parker KJ, Kabir IE, Doyley MM, Faiyaz A, Uddin MN, Flores G, Schifitto G. Brain elastography in aging relates to fluid/solid trendlines. Phys Med Biol 2024; 69:115037. [PMID: 38670141 DOI: 10.1088/1361-6560/ad4446] [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: 01/23/2024] [Accepted: 04/26/2024] [Indexed: 04/28/2024]
Abstract
The relatively new tools of brain elastography have established a general trendline for healthy, aging adult humans, whereby the brain's viscoelastic properties 'soften' over many decades. Earlier studies of the aging brain have demonstrated a wide spectrum of changes in morphology and composition towards the later decades of lifespan. This leads to a major question of causal mechanisms: of the many changes documented in structure and composition of the aging brain, which ones drive the long term trendline for viscoelastic properties of grey matter and white matter? The issue is important for illuminating which factors brain elastography is sensitive to, defining its unique role for study of the brain and clinical diagnoses of neurological disease and injury. We address these issues by examining trendlines in aging from our elastography data, also utilizing data from an earlier landmark study of brain composition, and from a biophysics model that captures the multiscale biphasic (fluid/solid) structure of the brain. Taken together, these imply that long term changes in extracellular water in the glymphatic system of the brain along with a decline in the extracellular matrix have a profound effect on the measured viscoelastic properties. Specifically, the trendlines indicate that water tends to replace solid fraction as a function of age, then grey matter stiffness decreases inversely as water fraction squared, whereas white matter stiffness declines inversely as water fraction to the 2/3 power, a behavior consistent with the cylindrical shape of the axons. These unique behaviors point to elastography of the brain as an important macroscopic measure of underlying microscopic structural change, with direct implications for clinical studies of aging, disease, and injury.
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Affiliation(s)
- Kevin J Parker
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
- Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14642, United States of America
| | - Irteza Enan Kabir
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
| | - Marvin M Doyley
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
- Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14642, United States of America
| | - Abrar Faiyaz
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
| | - Md Nasir Uddin
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
- Department of Neurology, University of Rochester Medical Center, 601 Elmwood Ave, Box 673, Rochester, NY 14642, United States of America
| | - Gilmer Flores
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
| | - Giovanni Schifitto
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
- Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14642, United States of America
- Department of Neurology, University of Rochester Medical Center, 601 Elmwood Ave, Box 673, Rochester, NY 14642, United States of America
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Liu J, Jakary A, Villanueva-Meyer JE, Butowski NA, Saloner D, Clarke JL, Taylor JW, Oberheim Bush NA, Chang SM, Xu D, Lupo JM. Automatic Brain Tissue and Lesion Segmentation and Multi-Parametric Mapping of Contrast-Enhancing Gliomas without the Injection of Contrast Agents: A Preliminary Study. Cancers (Basel) 2024; 16:1524. [PMID: 38672606 PMCID: PMC11049314 DOI: 10.3390/cancers16081524] [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: 01/27/2024] [Revised: 04/08/2024] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
This study aimed to develop a rapid, 1 mm3 isotropic resolution, whole-brain MRI technique for automatic lesion segmentation and multi-parametric mapping without using contrast by continuously applying balanced steady-state free precession with inversion pulses throughout incomplete inversion recovery in a single 6 min scan. Modified k-means clustering was performed for automatic brain tissue and lesion segmentation using distinct signal evolutions that contained mixed T1/T2/magnetization transfer properties. Multi-compartment modeling was used to derive quantitative multi-parametric maps for tissue characterization. Fourteen patients with contrast-enhancing gliomas were scanned with this sequence prior to the injection of a contrast agent, and their segmented lesions were compared to conventionally defined manual segmentations of T2-hyperintense and contrast-enhancing lesions. Simultaneous T1, T2, and macromolecular proton fraction maps were generated and compared to conventional 2D T1 and T2 mapping and myelination water fraction mapping acquired with MAGiC. The lesion volumes defined with the new method were comparable to the manual segmentations (r = 0.70, p < 0.01; t-test p > 0.05). The T1, T2, and macromolecular proton fraction mapping values of the whole brain were comparable to the reference values and could distinguish different brain tissues and lesion types (p < 0.05), including infiltrating tumor regions within the T2-lesion. Highly efficient, whole-brain, multi-contrast imaging facilitated automatic lesion segmentation and quantitative multi-parametric mapping without contrast, highlighting its potential value in the clinic when gadolinium is contraindicated.
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Affiliation(s)
- Jing Liu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
| | - Angela Jakary
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
| | - Javier E. Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
| | - Nicholas A. Butowski
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
| | - David Saloner
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
- Radiology Service, VA Medical Center, San Francisco, CA 94121, USA
| | - Jennifer L. Clarke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jennie W. Taylor
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Nancy Ann Oberheim Bush
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Susan M. Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
- UCSF/UC Berkeley Graduate Program in Bioengineering, University of California San Francisco and Berkeley, San Francisco, CA 94143, USA
| | - Janine M. Lupo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
- UCSF/UC Berkeley Graduate Program in Bioengineering, University of California San Francisco and Berkeley, San Francisco, CA 94143, USA
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Kirby ED, Andrushko JW, Rinat S, D'Arcy RCN, Boyd LA. Investigating female versus male differences in white matter neuroplasticity associated with complex visuo-motor learning. Sci Rep 2024; 14:5951. [PMID: 38467763 PMCID: PMC10928090 DOI: 10.1038/s41598-024-56453-z] [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: 05/25/2023] [Accepted: 03/06/2024] [Indexed: 03/13/2024] Open
Abstract
Magnetic resonance imaging (MRI) has increasingly been used to characterize structure-function relationships during white matter neuroplasticity. Biological sex differences may be an important factor that affects patterns of neuroplasticity, and therefore impacts learning and rehabilitation. The current study examined a participant cohort before and after visuo-motor training to characterize sex differences in microstructural measures. The participants (N = 27) completed a 10-session (4 week) complex visuo-motor training task with their non-dominant hand. All participants significantly improved movement speed and their movement speed variability over the training period. White matter neuroplasticity in females and males was examined using fractional anisotropy (FA) and myelin water fraction (MWF) along the cortico-spinal tract (CST) and the corpus callosum (CC). FA values showed significant differences in the middle portion of the CST tract (nodes 38-51) across the training period. MWF showed a similar cluster in the inferior portion of the tract (nodes 18-29) but did not reach significance. Additionally, at baseline, males showed significantly higher levels of MWF measures in the middle body of the CC. Combining data from females and males would have resulted in reduced sensitivity, making it harder to detect differences in neuroplasticity. These findings offer initial insights into possible female versus male differences in white matter neuroplasticity during motor learning. This warrants investigations into specific patterns of white matter neuroplasticity for females versus males across the lifespan. Understanding biological sex-specific differences in white matter neuroplasticity may have significant implications for the interpretation of change associated with learning or rehabilitation.
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Affiliation(s)
- Eric D Kirby
- BrainNet, Health and Technology District, Vancouver, BC, Canada
- Faculty of Individualized Interdisciplinary Studies, Simon Fraser University, Burnaby, BC, Canada
- Faculty of Science, Simon Fraser University, Burnaby, BC, Canada
| | - Justin W Andrushko
- DM Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, Canada
- Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University, Newcastle Upon Tyne, UK
- Brain Behaviour Laboratory, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Shie Rinat
- Brain Behaviour Laboratory, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Ryan C N D'Arcy
- BrainNet, Health and Technology District, Vancouver, BC, Canada.
- DM Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, Canada.
- Faculty of Applied Sciences, Simon Fraser University, Burnaby, BC, Canada.
| | - Lara A Boyd
- DM Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, Canada.
- Brain Behaviour Laboratory, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada.
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Khormi I, Al-Iedani O, Alshehri A, Ramadan S, Lechner-Scott J. MR myelin imaging in multiple sclerosis: A scoping review. J Neurol Sci 2023; 455:122807. [PMID: 38035651 DOI: 10.1016/j.jns.2023.122807] [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: 07/24/2023] [Revised: 10/20/2023] [Accepted: 11/19/2023] [Indexed: 12/02/2023]
Abstract
The inability of disease-modifying therapies to stop the progression of multiple sclerosis (MS), has led to the development of a new therapeutic strategy focussing on myelin repair. While conventional MRI lacks sensitivity for quantifying myelin damage, advanced MRI techniques are proving effective. The development of targeted therapeutics requires histological validation of myelin imaging results, alongside the crucial task of establishing correlations between myelin imaging results and clinical assessments, so that the effectiveness of therapeutic interventions can be evaluated. The aims of this scoping review were to identify myelin imaging methods - some of which have been histologically validated, and to determine how these approaches correlate with clinical assessments of people with MS (pwMS), thus allowing for effective therapeutic evaluation. A search of two databases was undertaken for publications relating to studies on adults MS using either MRI/MR-histology of the MS brain in the range 1990-to-2022. The myelin imaging methods specified were relaxometry, magnetization transfer, and quantitative susceptibility. Relaxometry was used most frequently, with myelin water fraction (MWF) being the primary metric. Studies conducted on tissue from various regions of the brain showed that MWF was significantly lower in pwMS than in healthy controls. Magnetization transfer ratio indicated that the macromolecular content of lesions was lower than that of normal-appearing tissue. Higher magnetic susceptibility of lesions were indicative of myelin breakdown and iron accumulation. Several myelin imaging metrics were correlated with disability, disease severity and duration. Many studies showed a good correlation between myelin measured histologically and by MR myelin imaging techniques.
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Affiliation(s)
- Ibrahim Khormi
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia
| | - Oun Al-Iedani
- Hunter Medical Research Institute, New Lambton Heights, Australia; School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
| | - Abdulaziz Alshehri
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Radiology, King Fahd Hospital of the University, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Saadallah Ramadan
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia.
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Neurology, John Hunter Hospital, New Lambton Heights, Australia; School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
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11
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Stephens JA, Hernandez-Sarabia JA, Sharp JL, Leach HJ, Bell C, Thomas ML, Burzynska A, Weaver JA, Schmid AA. Adaptive yoga versus low-impact exercise for adults with chronic acquired brain injury: a pilot randomized control trial protocol. Front Hum Neurosci 2023; 17:1291094. [PMID: 38077184 PMCID: PMC10701427 DOI: 10.3389/fnhum.2023.1291094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/27/2023] [Indexed: 02/12/2024] Open
Abstract
Background Each year, millions of Americans sustain acquired brain injuries (ABI) which result in functional impairments, such as poor balance and autonomic nervous system (ANS) dysfunction. Although significant time and energy are dedicated to reducing functional impairment in acute phase of ABI, many individuals with chronic ABI have residual impairments that increase fall risk, decrease quality of life, and increase mortality. In previous work, we have found that yoga can improve balance in adults with chronic (i.e., ≥6 months post-injury) ABI. Moreover, yoga has been shown to improve ANS and brain function in healthy adults. Thus, adults with chronic ABI may show similar outcomes. This protocol details the methods used to examine the effects of a group yoga program, as compared to a group low-impact exercise, on primary and secondary outcomes in adults with chronic ABI. Methods This study is a single-blind randomized controlled trial comparing group yoga to group low-impact exercise. Participants must be ≥18 years old with chronic ABI and moderate balance impairments. Group yoga and group exercise sessions occur twice a week for 1 h for 8 weeks. Sessions are led by trained adaptive exercise specialists. Primary outcomes are balance and ANS function. Secondary outcomes are brain function and structure, cognition, quality of life, and qualitative experiences. Data analysis for primary and most secondary outcomes will be completed with mixed effect statistical methods to evaluate the within-subject factor of time (i.e., pre vs. post intervention), the between-subject factor of group (yoga vs. low-impact exercise), and interaction effects. Deductive and inductive techniques will be used to analyze qualitative data. Discussion Due to its accessibility and holistic nature, yoga has significant potential for improving balance and ANS function, along with other capacities, in adults with chronic ABI. Because there are also known benefits of exercise and group interaction, this study compares yoga to a similar, group exercise intervention to explore if yoga has a unique benefit for adults with chronic ABI.Clinical trial registration:ClinicalTrials.gov, NCT05793827. Registered on March 31, 2023.
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Affiliation(s)
- Jaclyn A. Stephens
- Department of Occupational Therapy, Colorado State University, Fort Collins, CO, United States
- Molecular Cellular and Integrative Neuroscience Program, Colorado State University, Fort Collins, CO, United States
- Sharp Analytics, LCC, Fort Collins, CO, United States
| | | | - Julia L. Sharp
- Department of Health and Exercise Science, Colorado State University, Fort Collins, CO, United States
| | | | | | - Michael L. Thomas
- Molecular Cellular and Integrative Neuroscience Program, Colorado State University, Fort Collins, CO, United States
- Department of Psychology, Colorado State University, Fort Collins, CO, United States
| | - Agnieszka Burzynska
- Molecular Cellular and Integrative Neuroscience Program, Colorado State University, Fort Collins, CO, United States
- Department of Human Development and Family Studies, Colorado State University, Fort Collins, CO, United States
| | - Jennifer A. Weaver
- Department of Occupational Therapy, Colorado State University, Fort Collins, CO, United States
| | - Arlene A. Schmid
- Department of Occupational Therapy, Colorado State University, Fort Collins, CO, United States
- Center for Healthy Aging, Fort Collins, CO, United States
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Dvorak AV, Kumar D, Zhang J, Gilbert G, Balaji S, Wiley N, Laule C, Moore GW, MacKay AL, Kolind SH. The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity. SCIENCE ADVANCES 2023; 9:eadh9853. [PMID: 37910622 PMCID: PMC10619933 DOI: 10.1126/sciadv.adh9853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 09/28/2023] [Indexed: 11/03/2023]
Abstract
Quantitative magnetic resonance imaging (MRI) techniques are powerful tools for the study of human tissue, but, in practice, their utility has been limited by lengthy acquisition times. Here, we introduce the Constrained, Adaptive, Low-dimensional, Intrinsically Precise Reconstruction (CALIPR) framework in the context of myelin water imaging (MWI); a quantitative MRI technique generally regarded as the most rigorous approach for noninvasive, in vivo measurement of myelin content. The CALIPR framework exploits data redundancy to recover high-quality images from a small fraction of an imaging dataset, which allowed MWI to be acquired with a previously unattainable sequence (fully sampled acquisition 2 hours:57 min:20 s) in 7 min:26 s (4.2% of the dataset, acceleration factor 23.9). CALIPR quantitative metrics had excellent precision (myelin water fraction mean coefficient of variation 3.2% for the brain and 3.0% for the spinal cord) and markedly increased sensitivity to demyelinating disease pathology compared to a current, widely used technique. The CALIPR framework facilitates drastically improved MWI and could be similarly transformative for other quantitative MRI applications.
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Affiliation(s)
- Adam V. Dvorak
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
| | - Dushyant Kumar
- Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Jing Zhang
- Global MR Applications & Workflow, GE HealthCare Canada, Mississauga, ON, Canada
| | | | - Sharada Balaji
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
| | - Neale Wiley
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
- Radiology, University of British Columbia, Vancouver, BC, Canada
- Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - G.R. Wayne Moore
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
- Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Alex L. MacKay
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Radiology, University of British Columbia, Vancouver, BC, Canada
- Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Shannon H. Kolind
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
- Radiology, University of British Columbia, Vancouver, BC, Canada
- Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
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13
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Wiggermann V, Endmayr V, Hernández‐Torres E, Höftberger R, Kasprian G, Hametner S, Rauscher A. Quantitative magnetic resonance imaging reflects different levels of histologically determined myelin densities in multiple sclerosis, including remyelination in inactive multiple sclerosis lesions. Brain Pathol 2023; 33:e13150. [PMID: 36720269 PMCID: PMC10580011 DOI: 10.1111/bpa.13150] [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: 05/05/2022] [Accepted: 11/16/2022] [Indexed: 02/02/2023] Open
Abstract
Magnetic resonance imaging (MRI) of focal or diffuse myelin damage or remyelination may provide important insights into disease progression and potential treatment efficacy in multiple sclerosis (MS). We performed post-mortem MRI and histopathological myelin measurements in seven progressive MS cases to evaluate the ability of three myelin-sensitive MRI scans to distinguish different stages of MS pathology, particularly chronic demyelinated and remyelinated lesions. At 3 Tesla, we acquired two different myelin water imaging (MWI) scans and magnetisation transfer ratio (MTR) data. Histopathology included histochemical stainings for myelin phospholipids (LFB) and iron as well as immunohistochemistry for myelin proteolipid protein (PLP), CD68 (phagocytosing microglia/macrophages) and BCAS1 (remyelinating oligodendrocytes). Mixed-effects modelling determined which histopathological metric best predicted MWF and MTR in normal-appearing and diffusely abnormal white matter, active/inactive, inactive, remyelinated and ischemic lesions. Both MWI measures correlated well with each other and histology across regions, reflecting the different stages of MS pathology. MTR data showed a considerable influence of components other than myelin and a strong dependency on tissue storage duration. Both MRI and histology revealed increased myelin densities in inactive compared with active/inactive lesions. Chronic inactive lesions harboured single scattered myelin fibres indicative of low-level remyelination. Mixed-effects modelling showed that smaller differences between white matter areas were linked to PLP densities and only to a small extent confounded by iron. MWI reflects differences in myelin lipids and proteins across various levels of myelin densities encountered in MS, including low-level remyelination in chronic inactive lesions.
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Affiliation(s)
- Vanessa Wiggermann
- Department of Physics and AstronomyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of PediatricsUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Danish Research Centre for Magnetic ResonanceCopenhagen University Hospital Amager & HvidovreCopenhagenDenmark
| | - Verena Endmayr
- Division of Neuropathology and Neurochemistry, Department of NeurologyMedical University of ViennaViennaAustria
- Centre for Brain ResearchMedical University of ViennaViennaAustria
| | - Enedino Hernández‐Torres
- Danish Research Centre for Magnetic ResonanceCopenhagen University Hospital Amager & HvidovreCopenhagenDenmark
- Faculty of Medicine (Division Neurology)University of British ColumbiaVancouverBritish ColumbiaCanada
| | - Romana Höftberger
- Division of Neuropathology and Neurochemistry, Department of NeurologyMedical University of ViennaViennaAustria
| | - Gregor Kasprian
- Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Simon Hametner
- Division of Neuropathology and Neurochemistry, Department of NeurologyMedical University of ViennaViennaAustria
- Centre for Brain ResearchMedical University of ViennaViennaAustria
| | - Alexander Rauscher
- Department of Physics and AstronomyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of PediatricsUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of RadiologyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- BC Children's Hospital Research InstituteUniversity of British ColumbiaVancouverBritish ColumbiaCanada
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14
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Li H, Zu T, Chen R, Ba R, Hsu YC, Sun Y, Zhang Y, Wu D. 3D diffusion MRI with twin navigator-based GRASE and comparison with 2D EPI for tractography in the human brain. Magn Reson Med 2023; 90:1969-1978. [PMID: 37345706 DOI: 10.1002/mrm.29769] [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: 10/10/2022] [Revised: 05/13/2023] [Accepted: 06/01/2023] [Indexed: 06/23/2023]
Abstract
PURPOSE 3D pulse sequences enable high-resolution acquisition with a high SNR and ideal slice profiles, which, however, is particularly difficult for diffusion MRI (dMRI) due to the additional phase errors from diffusion encoding. METHODS We proposed a twin navigator-based 3D diffusion-weighted gradient spin-echo (GRASE) sequence to correct the phase errors between shots and between odd and even spin echoes for human whole-brain acquisition. We then compared the SNR of 3D GRASE and 2D simultaneous multi-slice EPI within the same acquisition time. We further tested the performance of 2D versus 3D acquisition at equivalent SNR on fiber tracking and microstructural mapping, using the diffusion tensor and high-order fiber orientation density-based metrics. RESULTS The proposed twin navigator approach removed multi-shot phase errors to some extent in the whole brain dMRI, and the 2D navigator performed better than the 1D navigator. Comparisons of SNR between the 2D simultaneous multi-slice EPI and 3D GRASE sequences demonstrated that the SNR of the GRASE sequence was 1.4-1.5-fold higher than the EPI sequence at an equivalent scan time. More importantly, we found a significantly higher fiber cross-section in the cerebrospinal tract, as well as richer subcortical fibers (U-fibers) using the 3D GRASE sequence compared to 2D EPI. CONCLUSION The twin navigator-based 3D diffusion-weighted-GRASE sequence minimized the multishot phase error and effectively improved the SNR for whole-brain dMRI acquisition. We found differences in fiber tracking and microstructural mapping between 2D and 3D acquisitions, possibly due to the different slice profiles.
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Affiliation(s)
- Haotian Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Tao Zu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Ruike Chen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Ruicheng Ba
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare China, Shanghai, People's Republic of China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare China, Shanghai, People's Republic of China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
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15
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Economou M, Bempt FV, Van Herck S, Wouters J, Ghesquière P, Vanderauwera J, Vandermosten M. Myelin plasticity during early literacy training in at-risk pre-readers. Cortex 2023; 167:86-100. [PMID: 37542803 DOI: 10.1016/j.cortex.2023.05.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 04/09/2023] [Accepted: 05/31/2023] [Indexed: 08/07/2023]
Abstract
A growing body of neuroimaging evidence shows that white matter can change as a result of experience and structured learning. Although the majority of previous work has used diffusion MRI to characterize such changes in white matter, diffusion metrics offer limited biological specificity about which microstructural features may be driving white matter plasticity. Recent advances in myelin-specific MRI techniques offer a promising opportunity to assess the specific contribution of myelin in learning-related plasticity. Here we describe the application of such an approach to examine structural plasticity during an early intervention in preliterate children at risk for dyslexia. To this end, myelin water imaging data were collected before and after a 12-week period in (1) at-risk children following early literacy training (n = 13-24), (2) at-risk children engaging with other non-literacy games (n = 10-17) and (3) children without a risk receiving no training (n = 11-22). Before the training, regional risk-related differences were identified, showing higher myelin water fraction (MWF) in right dorsal white matter in at-risk children compared to the typical control group. Concerning intervention-specific effects, our results revealed an increase across left-hemispheric and right ventral MWF over the course of training in the at-risk children receiving early literacy training, but not in the at-risk active control group or the no-risk typical control group. Overall, our results provide support for the use of myelin water imaging as a sensitive tool to investigate white matter and offer a first indication of myelin plasticity in young children at the onset of literacy acquisition.
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Affiliation(s)
- Maria Economou
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium; Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium
| | - Femke Vanden Bempt
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium; Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium
| | - Shauni Van Herck
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium; Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium
| | - Jan Wouters
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium
| | - Pol Ghesquière
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium
| | - Jolijn Vanderauwera
- Psychological Sciences Research Institute, Université Catholique de Louvain, 1348, Louvain-la-Neuve, Belgium; Institute of Neuroscience, Université Catholique de Louvain, 1348, Louvain-la-Neuve, Belgium
| | - Maaike Vandermosten
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium.
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16
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Shaterian Mohammadi H, Moazamian D, Athertya JS, Shin SH, Lo J, Suprana A, Malhi BS, Ma Y. Quantitative myelin water imaging using short TR adiabatic inversion recovery prepared echo-planar imaging (STAIR-EPI) sequence. FRONTIERS IN RADIOLOGY 2023; 3:1263491. [PMID: 37840897 PMCID: PMC10568074 DOI: 10.3389/fradi.2023.1263491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 09/18/2023] [Indexed: 10/17/2023]
Abstract
Introduction Numerous techniques for myelin water imaging (MWI) have been devised to specifically assess alterations in myelin. The biomarker employed to measure changes in myelin content is known as the myelin water fraction (MWF). The short TR adiabatic inversion recovery (STAIR) sequence has recently been identified as a highly effective method for calculating MWF. The purpose of this study is to develop a new clinical transitional myelin water imaging (MWI) technique that combines STAIR preparation and echo-planar imaging (EPI) (STAIR-EPI) sequence for data acquisition. Methods Myelin water (MW) in the brain has shorter T1 and T2 relaxation times than intracellular and extracellular water. In the proposed STAIR-EPI sequence, a short TR (e.g., ≤300 ms) together with an optimized inversion time enable robust long T1 water suppression with a wide range of T1 values [i.e., (600, 2,000) ms]. The EPI allows fast data acquisition of the remaining MW signals. Seven healthy volunteers and seven patients with multiple sclerosis (MS) were recruited and scanned in this study. The apparent myelin water fraction (aMWF), defined as the signal ratio of MW to total water, was measured in the lesions and normal-appearing white matter (NAWM) in MS patients and compared with those measured in the normal white matter (NWM) in healthy volunteers. Results As seen in the STAIR-EPI images acquired from MS patients, the MS lesions show lower signal intensities than NAWM do. The aMWF measurements for both MS lesions (3.6 ± 1.3%) and NAWM (8.6 ± 1.2%) in MS patients are significantly lower than NWM (10 ± 1.3%) in healthy volunteers (P < 0.001). Discussion The proposed STAIR-EPI technique, which can be implemented in MRI scanners from all vendors, is able to detect myelin loss in both MS lesions and NAWM in MS patients.
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Affiliation(s)
| | | | | | | | | | | | | | - Yajun Ma
- Department of Radiology, University of California San Diego, San Diego, CA, United States
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Şişman M, Nguyen TD, Roberts AG, Romano DJ, Dimov AV, Kovanlikaya I, Spincemaille P, Wang Y. Microstructure-Informed Myelin Mapping (MIMM) from Gradient Echo MRI using Stochastic Matching Pursuit. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.22.23295993. [PMID: 37808826 PMCID: PMC10557811 DOI: 10.1101/2023.09.22.23295993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Quantification of the myelin content of the white matter is important for studying demyelination in neurodegenerative diseases such as Multiple Sclerosis (MS), particularly for longitudinal monitoring. A novel noninvasive MRI method, called Microstructure-Informed Myelin Mapping (MIMM), is developed to quantify the myelin volume fraction (MVF) by utilizing a multi gradient echo sequence (mGRE) and a detailed biophysical model of tissue microstructure. Myelin is modeled as anisotropic negative susceptibility source based on the Hollow Cylindrical Fiber Model (HCFM), and iron as isotropic positive susceptibility source in the extracellular region. Voxels with a range of biophysical parameters are simulated to create a dictionary of MR echo time magnitude signals and total susceptibility values. MRI signals measured using a mGRE sequence are then matched voxel-by-voxel to the created dictionary to obtain the spatial distributions of myelin and iron. Three different MIMM versions are presented to deal with the fiber orientation dependent susceptibility effects of the myelin sheaths: a basic variation, which assumes fiber orientation is an unknown to fit, two orientation informed variations, which assume the fiber orientation distribution is available either from a separate diffusion tensor imaging (DTI) acquisition or from a DTI atlas based fiber orientation map. While all showed a significant linear correlation with the reference method based on T2-relaxometry (p < 0.0001), DTI orientation informed and atlas orientation informed variations reduced overestimation at white matter tracts compared to the basic variation. Finally, the implications and usefulness of attaining an additional iron susceptibility distribution map are discussed. Highlights novel stochastic matching pursuit algorithm called microstructure-informed myelin mapping (MIMM) is developed to quantify Myelin Volume Fraction (MVF) using Magnetic Resonance Imaging (MRI) and microstructural modeling.utilizes a detailed biophysical model to capture the susceptibility effects on both magnitude and phase to quantify myelin and iron.matter fiber orientation effects are considered for the improved MVF quantification in the major fiber tracts.acquired myelin and iron maps may be utilized to monitor longitudinal disease progress.
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Gong Z, Khattar N, Kiely M, Triebswetter C, Bouhrara M. REUSED: A deep neural network method for rapid whole-brain high-resolution myelin water fraction mapping from extremely under-sampled MRI. Comput Med Imaging Graph 2023; 108:102282. [PMID: 37586261 PMCID: PMC10528830 DOI: 10.1016/j.compmedimag.2023.102282] [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: 01/05/2023] [Revised: 07/23/2023] [Accepted: 07/24/2023] [Indexed: 08/18/2023]
Abstract
Changes in myelination are a cardinal feature of brain development and the pathophysiology of several central nervous system diseases, including multiple sclerosis and dementias. Advanced magnetic resonance imaging (MRI) methods have been developed to probe myelin content through the measurement of myelin water fraction (MWF). However, the prolonged data acquisition and post-processing times of current MWF mapping methods pose substantial hurdles to their clinical implementation. Recently, fast steady-state MRI sequences have been implemented to produce high-spatial resolution whole-brain MWF mapping within ∼20 min. Despite the subsequent significant advances in the inversion algorithm to derive MWF maps from steady-state MRI, the high-dimensional nature of such inversion does not permit further reduction of the acquisition time by data under-sampling. In this work, we present an unprecedented reduction in the computation (∼30 s) and the acquisition time (∼7 min) required for whole-brain high-resolution MWF mapping through a new Neural Network (NN)-based approach, named NN-Relaxometry of Extremely Under-SamplEd Data (NN-REUSED). Our analyses demonstrate virtually similar accuracy and precision in derived MWF values using NN-REUSED compared to results derived from the fully sampled reference method. The reduction in the acquisition and computation times represents a breakthrough toward clinically practical MWF mapping.
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Affiliation(s)
- Zhaoyuan Gong
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
| | | | - Matthew Kiely
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Curtis Triebswetter
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Mustapha Bouhrara
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
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19
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Burzynska AZ, Anderson C, Arciniegas DB, Calhoun V, Choi IY, Colmenares AM, Hiner G, Kramer AF, Li K, Lee J, Lee P, Oh SH, Umland S, Thomas ML. Metabolic syndrome and adiposity: Risk factors for decreased myelin in cognitively healthy adults. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2023; 5:100180. [PMID: 38162292 PMCID: PMC10757180 DOI: 10.1016/j.cccb.2023.100180] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 08/11/2023] [Accepted: 08/17/2023] [Indexed: 01/03/2024]
Abstract
Metabolic syndrome (MetS) is a cluster of conditions that affects ∼25% of the global population, including excess adiposity, hyperglycemia, dyslipidemia, and elevated blood pressure. MetS is one of major risk factors not only for chronic diseases, but also for dementia and cognitive dysfunction, although the underlying mechanisms remain poorly understood. White matter is of particular interest in the context of MetS due to the metabolic vulnerability of myelin maintenance, and the accumulating evidence for the importance of the white matter in the pathophysiology of dementia. Therefore, we investigated the associations of MetS risk score and adiposity (combined body mass index and waist circumference) with myelin water fraction measured with myelin water imaging. In 90 cognitively and neurologically healthy adults (20-79 years), we found that both high MetS risk score and adiposity were correlated with lower myelin water fraction in late-myelinating prefrontal and associative fibers, controlling for age, sex, race, ethnicity, education and income. Our findings call for randomized clinical trials to establish causality between MetS, adiposity, and myelin content, and to explore the potential of weight loss and visceral adiposity reduction as means to support maintenance of myelin integrity throughout adulthood, which could open new avenues for prevention or treatment of cognitive decline and dementia.
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Affiliation(s)
- Agnieszka Z Burzynska
- The BRAiN lab, Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Fort Collins, CO, USA
| | - Charles Anderson
- Department of Computer Science, Colorado State University, Fort Collins, CO, USA
| | - David B Arciniegas
- Marcus Institute for Brain Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Psychiatry and Behavioral Sciences, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - In-Young Choi
- Department of Neurology, Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Andrea Mendez Colmenares
- The BRAiN lab, Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Fort Collins, CO, USA
| | - Grace Hiner
- The BRAiN lab, Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Fort Collins, CO, USA
| | - Arthur F Kramer
- Beckman Institute for Advanced Science and Technology at the University of Illinois, IL, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA, USA
| | - Kaigang Li
- Department of Health and Exercise Science, Colorado State University, Fort Collins, CO, USA
| | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
| | - Phil Lee
- Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Se-Hong Oh
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Gyeonggi-do, Republic of Korea
| | - Samantha Umland
- The BRAiN lab, Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Fort Collins, CO, USA
| | - Michael L Thomas
- Michael Thomas, Department of Psychology, Colorado State University, Fort Collins, CO, USA
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20
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Endt S, Engel M, Naldi E, Assereto R, Molendowska M, Mueller L, Mayrink Verdun C, Pirkl CM, Palombo M, Jones DK, Menzel MI. In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods. APPLIED MAGNETIC RESONANCE 2023; 54:1571-1588. [PMID: 38037641 PMCID: PMC10682074 DOI: 10.1007/s00723-023-01584-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/18/2023] [Accepted: 07/25/2023] [Indexed: 12/02/2023]
Abstract
Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.
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Affiliation(s)
- Sebastian Endt
- Technical University of Munich, Munich, Germany
- AImotion Bavaria, Technische Hochschule Ingolstadt, Ingolstadt, Germany
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Maria Engel
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Emanuele Naldi
- Technische Universität Braunschweig, Braunschweig, Germany
| | | | - Malwina Molendowska
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Medical Radiation Physics, Lund University, Lund, Sweden
| | - Lars Mueller
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM), University of Leeds, Leeds, United Kingdom
| | - Claudio Mayrink Verdun
- Technical University of Munich, Munich, Germany
- Munich Center for Machine Learning, Munich, Germany
| | | | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Marion I. Menzel
- Technical University of Munich, Munich, Germany
- AImotion Bavaria, Technische Hochschule Ingolstadt, Ingolstadt, Germany
- GE HealthCare, Munich, Germany
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21
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Gong Z, Bilgel M, Kiely M, Triebswetter C, Ferrucci L, Resnick SM, Spencer RG, Bouhrara M. Lower myelin content is associated with more rapid cognitive decline among cognitively unimpaired individuals. Alzheimers Dement 2023; 19:3098-3107. [PMID: 36720000 PMCID: PMC10387505 DOI: 10.1002/alz.12968] [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: 10/15/2022] [Revised: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 02/01/2023]
Abstract
INTRODUCTION The influence of myelination on longitudinal changes in cognitive performance remains unclear. METHODS For each participant (N = 123), longitudinal cognitive scores were calculated. Myelin content was probed using myelin water fraction (MWF) or longitudinal relaxation rate (R1 ); both are MRI measures sensitive to myelin, with MWF being specific. RESULTS Lower MWF was associated with steeper declines in executive function (p < .02 in all regions) and lower R1 was associated with steeper declines in verbal fluency (p < .03 in all regions). Additionally, lower R1 was associated with steeper declines in executive function (p < .02 in all regions) and memory (p < .04 in occipital and cerebral white matter) but did not survive Bonferroni correction. DISCUSSION We demonstrate significant relationships between myelin content and the rates of change in cognitive performance among cognitively normal individuals. These findings highlight the importance of myelin in cognitive functioning and suggest MWF and R1 as imaging biomarkers to predict cognitive changes.
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Affiliation(s)
- Zhaoyuan Gong
- Magnetic Resonance Physics of Aging and Dementia (MRPAD) Unit, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, USA
| | - Murat Bilgel
- Brain Aging and Behavior Section, NIA, NIH, Baltimore, Maryland, USA
| | - Matthew Kiely
- Magnetic Resonance Physics of Aging and Dementia (MRPAD) Unit, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, USA
| | - Curtis Triebswetter
- Magnetic Resonance Physics of Aging and Dementia (MRPAD) Unit, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, NIA, NIH, Baltimore, Maryland, USA
| | - Susan M. Resnick
- Brain Aging and Behavior Section, NIA, NIH, Baltimore, Maryland, USA
| | - Richard G. Spencer
- Magnetic Resonance Imaging and Spectroscopy Section, NIA, NIH, Baltimore, Maryland, USA
| | - Mustapha Bouhrara
- Magnetic Resonance Physics of Aging and Dementia (MRPAD) Unit, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, USA
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22
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Zhou L, Li Y, Sweeney EM, Wang XH, Kuceyeski A, Chiang GC, Ivanidze J, Wang Y, Gauthier SA, de Leon MJ, Nguyen TD. Association of brain tissue cerebrospinal fluid fraction with age in healthy cognitively normal adults. Front Aging Neurosci 2023; 15:1162001. [PMID: 37396667 PMCID: PMC10312090 DOI: 10.3389/fnagi.2023.1162001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 05/31/2023] [Indexed: 07/04/2023] Open
Abstract
Background and purpose Our objective was to apply multi-compartment T2 relaxometry in cognitively normal individuals aged 20-80 years to study the effect of aging on the parenchymal CSF fraction (CSFF), a potential measure of the subvoxel CSF space. Materials and methods A total of 60 volunteers (age range, 22-80 years) were enrolled. Voxel-wise maps of short-T2 myelin water fraction (MWF), intermediate-T2 intra/extra-cellular water fraction (IEWF), and long-T2 CSFF were obtained using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) sequence and three-pool non-linear least squares fitting. Multiple linear regression analyses were performed to study the association between age and regional MWF, IEWF, and CSFF measurements, adjusting for sex and region of interest (ROI) volume. ROIs include the cerebral white matter (WM), cerebral cortex, and subcortical deep gray matter (GM). In each model, a quadratic term for age was tested using an ANOVA test. A Spearman's correlation between the normalized lateral ventricle volume, a measure of organ-level CSF space, and the regional CSFF, a measure of tissue-level CSF space, was computed. Results Regression analyses showed that there was a statistically significant quadratic relationship with age for CSFF in the cortex (p = 0.018), MWF in the cerebral WM (p = 0.033), deep GM (p = 0.017) and cortex (p = 0.029); and IEWF in the deep GM (p = 0.033). There was a statistically highly significant positive linear relationship between age and regional CSFF in the cerebral WM (p < 0.001) and deep GM (p < 0.001). In addition, there was a statistically significant negative linear association between IEWF and age in the cerebral WM (p = 0.017) and cortex (p < 0.001). In the univariate correlation analysis, the normalized lateral ventricle volume correlated with the regional CSFF measurement in the cerebral WM (ρ = 0.64, p < 0.001), cortex (ρ = 0.62, p < 0.001), and deep GM (ρ = 0.66, p < 0.001). Conclusion Our cross-sectional data demonstrate that brain tissue water in different compartments shows complex age-dependent patterns. Parenchymal CSFF, a measure of subvoxel CSF-like water in the brain tissue, is quadratically associated with age in the cerebral cortex and linearly associated with age in the cerebral deep GM and WM.
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Affiliation(s)
- Liangdong Zhou
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Yi Li
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Elizabeth M. Sweeney
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Xiuyuan H. Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
- Department of Statistics and Data Science, Cornell University, Ithaca, NY, United States
| | - Gloria C. Chiang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Jana Ivanidze
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Susan A. Gauthier
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Mony J. de Leon
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Thanh D. Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
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23
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Stellingwerff MD, Pouwels PJW, Roosendaal SD, Barkhof F, van der Knaap MS. Quantitative MRI in leukodystrophies. Neuroimage Clin 2023; 38:103427. [PMID: 37150021 PMCID: PMC10193020 DOI: 10.1016/j.nicl.2023.103427] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 04/27/2023] [Accepted: 04/28/2023] [Indexed: 05/09/2023]
Abstract
Leukodystrophies constitute a large and heterogeneous group of genetic diseases primarily affecting the white matter of the central nervous system. Different disorders target different white matter structural components. Leukodystrophies are most often progressive and fatal. In recent years, novel therapies are emerging and for an increasing number of leukodystrophies trials are being developed. Objective and quantitative metrics are needed to serve as outcome measures in trials. Quantitative MRI yields information on microstructural properties, such as myelin or axonal content and condition, and on the chemical composition of white matter, in a noninvasive fashion. By providing information on white matter microstructural involvement, quantitative MRI may contribute to the evaluation and monitoring of leukodystrophies. Many distinct MR techniques are available at different stages of development. While some are already clinically applicable, others are less far developed and have only or mainly been applied in healthy subjects. In this review, we explore the background, current status, potential and challenges of available quantitative MR techniques in the context of leukodystrophies.
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Affiliation(s)
- Menno D Stellingwerff
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Child Neurology, Emma Children's Hospital, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Petra J W Pouwels
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Stefan D Roosendaal
- Amsterdam UMC Location University of Amsterdam, Department of Radiology, Meibergdreef 9, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; University College London, Institutes of Neurology and Healthcare Engineering, London, UK
| | - Marjo S van der Knaap
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Child Neurology, Emma Children's Hospital, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; Vrije Universiteit Amsterdam, Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, De Boelelaan 1105, Amsterdam, the Netherlands.
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24
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Morris SR, Vavasour IM, Smolina A, MacMillan EL, Gilbert G, Lam M, Kozlowski P, Michal CA, Manning A, MacKay AL, Laule C. Myelin biomarkers in the healthy adult brain: Correlation, reproducibility, and the effect of fiber orientation. Magn Reson Med 2023; 89:1809-1824. [PMID: 36511247 DOI: 10.1002/mrm.29552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 10/17/2022] [Accepted: 11/18/2022] [Indexed: 12/15/2022]
Abstract
PURPOSE We investigated the correlation, reproducibility, and effect of white matter fiber orientation for three myelin-sensitive MRI techniques: magnetization transfer ratio (MTR), inhomogeneous magnetization transfer ratio (ihMTR), and gradient and spin echo-derived myelin water fraction (MWF). METHODS We measured the three metrics in 17 white and three deep grey matter regions in 17 healthy adults at 3 T. RESULTS We found a strong correlation between ihMTR and MTR (r = 0.70, p < 0.001) and ihMTR and MWF (r = 0.79, p < 0.001), and a weaker correlation between MTR and MWF (r = 0.54, p < 0.001). The dynamic range in white matter was greatest for MWF (2.0%-27.5%), followed by MTR (14.4%-23.2%) and then ihMTR (1.2%-5.4%). The average scan-rescan coefficient of variation for white matter regions was 0.6% MTR, 0.3% ihMTR, and 0.7% MWF in metric units; however, when adjusted by the dynamic range, these became 6.3%, 6.1% and 2.8%, respectively. All three metrics varied with fiber direction: MWF and ihMTR were lower in white matter fibers perpendicular to B0 by 6% and 1%, respectively, compared with those parallel, whereas MTR was lower by 0.5% at about 40°, with the highest values at 90°. However, separating the apparent orientation dependence by white matter region revealed large dissimilarities in the trends, suggesting that real differences in myelination between regions are confounding the apparent orientation dependence measured using this method. CONCLUSION The strong correlation between ihMTR and MWF suggests that these techniques are measuring the same myelination; however, the larger dynamic range of MWF may provide more power to detect small differences in myelin.
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Affiliation(s)
- Sarah R Morris
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Irene M Vavasour
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada
| | - Anastasia Smolina
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Erin L MacMillan
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada.,MR Clinical Science, Philips Healthcare Canada, Mississauga, Ontario, Canada
| | - Guillaume Gilbert
- MR Clinical Science, Philips Healthcare Canada, Mississauga, Ontario, Canada
| | - Michelle Lam
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada
| | - Piotr Kozlowski
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada
| | - Carl A Michal
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alan Manning
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alex L MacKay
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada.,Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
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25
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Kumar D, Benyard B, Soni ND, Swain A, Wilson N, Reddy R. Feasibility of transient nuclear Overhauser effect imaging in brain at 7 T. Magn Reson Med 2023; 89:1357-1367. [PMID: 36372994 DOI: 10.1002/mrm.29519] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 10/11/2022] [Accepted: 10/19/2022] [Indexed: 11/16/2022]
Abstract
PURPOSE The nuclear Overhauser effect (NOE) quantification from the steady-state NOE imaging suffers from multiple confounding non-NOE-specific sources, including direct saturation, magnetization transfer, and relevant chemical exchange species, and is affected by B0 and B1 + inhomogeneities. The B0 -dependent and B1 + -dependent data needed for deconvolving these confounding effects would increase the scan time substantially, leading to other issues such as patient tolerability. Here, we demonstrate the feasibility of brain lipid mapping using an easily implementable transient NOE (tNOE) approach. METHODS This 7T study used a frequency-selective inversion pulse at a range of frequency offsets between 1.0 and 5.0 parts per million (ppm) and -5.0 and -1.0 ppm relative to bulk water peak. This was followed by a fixed/variable mixing time and then a single-shot 2D turbo FLASH readout. The feasibility of tNOE measurements is demonstrated on bovine serum albumin phantoms and healthy human brains. RESULTS The tNOE measurements from bovine serum albumin phantoms were found to be independent of physiological pH variations. Both bovine serum albumin phantoms and human brains showed broad tNOE contributions centered at approximately -3.5 ppm relative to water peak, with presumably aliphatic moieties in lipids and proteins being the dominant contributors. Less prominent tNOE contributions of approximately +2.5 ppm relative to water, presumably from aromatic moieties, were also detected. These aromatic signals were free from any CEST signals. CONCLUSION In this study, we have demonstrated the feasibility of tNOE in human brain at 7 T. This method is more scan-time efficient than steady-state NOE and provides NOE measurement with minimal confounders.
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Affiliation(s)
- Dushyant Kumar
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Blake Benyard
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Narayan Datt Soni
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Anshuman Swain
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Neil Wilson
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ravinder Reddy
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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26
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Johnson P, Vavasour IM, Stojkova BJ, Abel S, Lee LE, Laule C, Tam R, Li DKB, Ackermans N, Schabas AJ, Chan J, Cross H, Sayao AL, Devonshire V, Carruthers R, Traboulsee A, Kolind SH. Myelin heterogeneity for assessing normal appearing white matter myelin damage in multiple sclerosis. J Neuroimaging 2023; 33:227-234. [PMID: 36443960 DOI: 10.1111/jon.13069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 11/04/2022] [Accepted: 11/08/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND AND PURPOSE Conventional MRI measures of multiple sclerosis (MS) disease severity, such as lesion volume and brain atrophy, do not provide information about microstructural tissue changes, which may be driving physical and cognitive progression. Myelin damage in normal-appearing white matter (NAWM) is likely an important contributor to MS disability. Myelin water fraction (MWF) provides quantitative measurements of myelin. Mean MWF reflects average myelin content, while MWF standard deviation (SD) describes variation in myelin within regions. The myelin heterogeneity index (MHI = SD/mean MWF) is a composite metric of myelin content and myelin variability. We investigated how mean MWF, SD, and MHI compare in differentiating MS from controls and their associations with physical and cognitive disability. METHODS Myelin water imaging data were acquired from 91 MS participants and 31 healthy controls (HC). Segmented whole-brain NAWM and corpus callosum (CC) NAWM, mean MWF, SD, and MHI were compared between groups. Associations of mean MWF, SD, and MHI with Expanded Disability Status Scale and Symbol Digit Modalities Test were assessed. RESULTS NAWM and CC MHI had the highest area under the curve: .78 (95% confidence interval [CI]: .69, .86) and .84 (95% CI: .76, .91), respectively, distinguishing MS from HC. CONCLUSIONS Mean MWF, SD, and MHI provide complementary information when assessing regional and global NAWM abnormalities in MS and associations with clinical outcome measures. Examining all three metrics (mean MWF, SD, and MHI) enables a more detailed interpretation of results, depending on whether regions of interest include areas that are more heterogeneous, earlier in the demyelination process, or uniformly injured.
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Affiliation(s)
- Poljanka Johnson
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Irene M Vavasour
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Shawna Abel
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Lisa Eunyoung Lee
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Roger Tam
- School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada
| | - David K B Li
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Nathalie Ackermans
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Alice J Schabas
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Jillian Chan
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Helen Cross
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Ana-Luiza Sayao
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Virginia Devonshire
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Robert Carruthers
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Anthony Traboulsee
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Shannon H Kolind
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
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27
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Boa Sorte Silva NC, Dao E, Liang Hsu C, Tam RC, Lam K, Alkeridy W, Laule C, Vavasour IM, Stein RG, Liu-Ambrose T. Myelin and Physical Activity in Older Adults With Cerebral Small Vessel Disease and Mild Cognitive Impairment. J Gerontol A Biol Sci Med Sci 2023; 78:545-553. [PMID: 35876839 DOI: 10.1093/gerona/glac149] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Myelin loss is a feature of cerebral small vessel disease (cSVD). Although physical activity levels may exert protective effects over cSVD pathology, its specific relationship with myelin content in people living with the cSVD is unknown. Thus, we investigated whether physical activity levels are associated with myelin in community-dwelling older adults with cSVD and mild cognitive impairment. METHODS Cross-sectional data from 102 individuals with cSVD and mild cognitive impairment were analyzed (mean age [SD] = 74.7 years [5.5], 63.7% female). Myelin was measured using a magnetic resonance gradient and spin echo sequence. Physical activity was estimated using the Physical Activity Scale for the Elderly. Hierarchical regression models adjusting for total intracranial volume, age, sex, body mass index, and education were conducted to determine the associations between myelin content and physical activity. Significant models were further adjusted for white matter hyperintensity volume. RESULTS In adjusted models, greater physical activity was linked to higher myelin content in the whole-brain white matter (R2change = .04, p = .048). Greater physical activity was also associated with myelin content in the sagittal stratum (R2change = .08, p = .004), anterior corona radiata (R2change = .04, p = .049), and genu of the corpus callosum (R2change = .05, p = .018). Adjusting for white matter hyperintensity volume did not change any of these associations. CONCLUSIONS Physical activity may be a strategy to maintain myelin in older adults with cSVD and mild cognitive impairment. Future randomized controlled trials of exercise are needed to determine whether exercise increases myelin content.
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Affiliation(s)
- Nárlon C Boa Sorte Silva
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
| | - Elizabeth Dao
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Chun Liang Hsu
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, Massachusetts, USA
| | - Roger C Tam
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,School of Biomedical Engineering, Faculty of Applied Science and Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Kevin Lam
- Department of Medicine, Division of Neurology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Walid Alkeridy
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Medicine, King Saud University, College of Medicine, Riyadh, Saudi Arabia.,Department of Medicine, Division of Geriatrics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Irene M Vavasour
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Ryan G Stein
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
| | - Teresa Liu-Ambrose
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
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28
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Mapping myelin in white matter with T1-weighted/T2-weighted maps: discrepancy with histology and other myelin MRI measures. Brain Struct Funct 2023; 228:525-535. [PMID: 36692695 PMCID: PMC9944377 DOI: 10.1007/s00429-022-02600-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 11/18/2022] [Indexed: 01/25/2023]
Abstract
The ratio of T1-weighted/T2-weighted magnetic resonance images (T1w/T2w MRI) has been successfully applied at the cortical level since 2011 and is now one of the most used myelin mapping methods. However, no reports have explored the histological validity of T1w/T2w myelin mapping in white matter. Here we compare T1w/T2w with ex vivo postmortem histology and in vivo MRI methods, namely quantitative susceptibility mapping (QSM) and multi-echo T2 myelin water fraction (MWF) mapping techniques. We report a discrepancy between T1w/T2w myelin maps of the human corpus callosum and the histology and analyse the putative causes behind such discrepancy. T1w/T2w does not positively correlate with Luxol Fast Blue (LFB)-Optical Density but shows a weak to moderate, yet significant, negative correlation. On the contrary, MWF is strongly and positively correlated with LFB, whereas T1w/T2w and MWF maps are weakly negatively correlated. The discrepancy between T1w/T2w MRI maps, MWF and histological myelin maps suggests caution in using T1w/T2w as a white matter mapping method at the callosal level. While T1w/T2w imaging may correlate with myelin content at the cortical level, it is not a specific method to map myelin density in white matter.
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29
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Nagtegaal M, Hartsema E, Koolstra K, Vos F. Multicomponent MR fingerprinting reconstruction using joint-sparsity and low-rank constraints. Magn Reson Med 2023; 89:286-298. [PMID: 36121015 PMCID: PMC9825911 DOI: 10.1002/mrm.29442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 08/12/2022] [Accepted: 08/12/2022] [Indexed: 01/11/2023]
Abstract
PURPOSE To develop an efficient algorithm for multicomponent MR fingerprinting (MC-MRF) reconstructions directly from highly undersampled data without making prior assumptions about tissue relaxation times and expected number of tissues. METHODS The proposed method reconstructs MC-MRF maps from highly undersampled data by iteratively applying a joint-sparsity constraint to the estimated tissue components. Intermediate component maps are obtained by a low-rank multicomponent alternating direction method of multipliers (MC-ADMM) including the non-negativity of tissue weights as an extra regularization term. Over iterations, the used dictionary compression is adjusted. The proposed method (k-SPIJN) is compared with a two-step approach in which image reconstruction and multicomponent estimations are performed sequentially and tested in numerical simulations and in vivo by applying different undersampling factors in eight healthy volunteers. In the latter case, fully sampled data serves as the reference. RESULTS The proposed method shows improved precision and accuracy in simulations compared with a state-of-art sequential approach. Obtained in vivo magnetization fraction maps for different tissue types show reduced systematic errors and reduced noise-like effects. Root mean square errors in estimated magnetization fraction maps significantly reduce from 13.0% <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>±</mml:mo></mml:mrow> <mml:annotation>$$ \pm $$</mml:annotation></mml:semantics> </mml:math> 5.8% with the conventional, two-step approach to 9.6% <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>±</mml:mo></mml:mrow> <mml:annotation>$$ \pm $$</mml:annotation></mml:semantics> </mml:math> 3.9% and 9.6% <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>±</mml:mo></mml:mrow> <mml:annotation>$$ \pm $$</mml:annotation></mml:semantics> </mml:math> 3.2% with the proposed MC-ADMM and k-SPIJN methods, respectively. Mean standard deviation in homogeneous white matter regions reduced significantly from 8.6% to 2.9% (two step vs. k-SPIJN). CONCLUSION The proposed MC-ADMM and k-SPIJN reconstruction methods estimate MC-MRF maps from highly undersampled data resulting in improved image quality compared with the existing method.
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Affiliation(s)
- Martijn Nagtegaal
- Department of Imaging PhysicsDelft University of TechnologyDelftThe Netherlands
| | - Emiel Hartsema
- Department of Imaging PhysicsDelft University of TechnologyDelftThe Netherlands
| | - Kirsten Koolstra
- Division of Image Processing, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Frans Vos
- Department of Imaging PhysicsDelft University of TechnologyDelftThe Netherlands,Department of RadiologyErasmus MCRotterdamThe Netherlands
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30
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Orientation dependence of R 2 relaxation in the newborn brain. Neuroimage 2022; 264:119702. [PMID: 36272671 DOI: 10.1016/j.neuroimage.2022.119702] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 09/25/2022] [Accepted: 10/18/2022] [Indexed: 11/09/2022] Open
Abstract
In MRI the transverse relaxation rate, R2 = 1/T2, shows dependence on the orientation of ordered tissue relative to the main magnetic field. In previous studies, orientation effects of R2 relaxation in the mature brain's white matter have been found to be described by a susceptibility-based model of diffusion through local magnetic field inhomogeneities created by the diamagnetic myelin sheaths. Orientation effects in human newborn white matter have not yet been investigated. The newborn brain is known to contain very little myelin and is therefore expected to exhibit a decrease in orientation dependence driven by susceptibility-based effects. We measured R2 orientation dependence in the white matter of human newborns. R2 data were acquired with a 3D Gradient and Spin Echo (GRASE) sequence and fiber orientation was mapped with diffusion tensor imaging (DTI). We found orientation dependence in newborn white matter that is not consistent with the susceptibility-based model and is best described by a model of residual dipolar coupling. In the near absence of myelin in the newborn brain, these findings suggest the presence of residual dipolar coupling between rotationally restricted water molecules. This has important implications for quantitative imaging methods such as myelin water imaging, and suggests orientation dependence of R2 as a potential marker in early brain development.
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31
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Berg RC, Menegaux A, Amthor T, Gilbert G, Mora M, Schlaeger S, Pongratz V, Lauerer M, Sorg C, Doneva M, Vavasour I, Mühlau M, Preibisch C. Comparing myelin-sensitive magnetic resonance imaging measures and resulting g-ratios in healthy and multiple sclerosis brains. Neuroimage 2022; 264:119750. [PMID: 36379421 PMCID: PMC9931395 DOI: 10.1016/j.neuroimage.2022.119750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/11/2022] [Accepted: 11/11/2022] [Indexed: 11/15/2022] Open
Abstract
The myelin concentration and the degree of myelination of nerve fibers can provide valuable information on the integrity of human brain tissue. Magnetic resonance imaging (MRI) of myelin-sensitive parameters can help to non-invasively evaluate demyelinating diseases such as multiple sclerosis (MS). Several different myelin-sensitive MRI methods have been proposed to determine measures of the degree of myelination, in particular the g-ratio. However, variability in underlying physical principles and different biological models influence measured myelin concentrations, and consequently g-ratio values. We therefore investigated similarities and differences between five different myelin-sensitive MRI measures and their effects on g-ratio mapping in the brains of both MS patients and healthy volunteers. We compared two different estimates of the myelin water fraction (MWF) as well as the inhomogeneous magnetization transfer ratio (ihMTR), magnetization transfer saturation (MTsat), and macromolecular tissue volume (MTV) in 13 patients with MS and 14 healthy controls. In combination with diffusion-weighted imaging, we derived g-ratio parameter maps for each of the five different myelin measures. The g-ratio values calculated from different myelin measures varied strongly, especially in MS lesions. While, compared to normal-appearing white matter, MTsat and one estimate of the MWF resulted in higher g-ratio values within lesions, ihMTR, MTV, and the second MWF estimate resulted in lower lesion g-ratio values. As myelin-sensitive measures provide rough estimates of myelin content rather than absolute myelin concentrations, resulting g-ratio values strongly depend on the utilized myelin measure and model used for g-ratio mapping. When comparing g-ratio values, it is, thus, important to utilize the same MRI methods and models or to consider methodological differences. Particular caution is necessary in pathological tissue such as MS lesions.
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Affiliation(s)
- Ronja C. Berg
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Corresponding author at: Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaninger Str. 22, 81675, München, Germany. (R.C. Berg)
| | - Aurore Menegaux
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | | | | | - Maria Mora
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany
| | - Sarah Schlaeger
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany
| | - Viola Pongratz
- Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | - Markus Lauerer
- Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | - Christian Sorg
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany,Technical University of Munich, School of Medicine, Department of Psychiatry, Munich, Germany
| | | | - Irene Vavasour
- University of British Columbia, Department of Radiology, Vancouver, BC, Canada
| | - Mark Mühlau
- Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
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32
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Roy B, Sahib AK, Kang D, Aysola RS, Kumar R. Brain tissue integrity mapping in adults with obstructive sleep apnea using T1-weighted and T2-weighted images. Ther Adv Neurol Disord 2022; 15:17562864221137505. [PMID: 36419869 PMCID: PMC9677310 DOI: 10.1177/17562864221137505] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 10/21/2022] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND Obstructive sleep apnea (OSA) is accompanied by both gray and white matter differences in brain areas that regulate autonomic, cognitive, and mood functions, which are deficient in the condition. Such tissue changes have been examined through diffusion tensor and diffusion kurtosis imaging-based procedures. However, poor in-plane spatial resolution of these techniques precludes precise determination of the extent of tissue injury. Tissue texture maps derived from the ratio of T1-weighted and T2-weighted images can provide more adequate in-plane assessment of brain tissue differences. OBJECTIVES To examine brain tissue integrity in recently diagnosed, treatment-naïve OSA subjects, relative to age- and sex-comparable control subjects using T1-weighted and T2-weighted images. DESIGN A cross-sectional study. METHODS We examined the extent of tissue changes in 106 OSA over 115 control subjects using high-resolution T1- and T2-weighted images collected from a 3.0-Tesla scanner (analysis of covariance; covariates: age, sex, body-mass-index, Pittsburgh sleep quality index, Epworth sleepiness scale, Beck Anxiety Inventory, and Beck Depression Inventory II; false discovery rate corrected; p < 0.01). RESULTS OSA subjects showed significantly lowered tissue integrity in several brain regions, including the frontal, cingulate and insular cortices, cingulum bundle, thalamus, corpus callosum, caudate and putamen, pons, temporal, occipital, and parietal sites, cerebellar peduncles, and medial medullary sites, compared with controls. CONCLUSION OSA subjects show widespread lowered tissue integrity in autonomic, mood, and cognitive control sites over healthy controls. The pathological processes contributing to the alterations may include repetitive hypoxic and hypercarbic processes and excitotoxic injury, leading to altered brain tissue integrity in OSA.
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Affiliation(s)
- Bhaswati Roy
- Department of Anesthesiology, University of
California, Los Angeles, Los Angeles, CA, USA
| | - Ashish K. Sahib
- Department of Anesthesiology, University of
California, Los Angeles, Los Angeles, CA, USA
| | - Daniel Kang
- Department of Medicine, University of
California, Los Angeles, Los Angeles, CA, USA
| | - Ravi S. Aysola
- Department of Medicine, University of
California, Los Angeles, Los Angeles, CA, USA
| | - Rajesh Kumar
- Department of Anesthesiology, David Geffen
School of Medicine at UCLA, University of California, Los Angeles, 56-141
CHS, 10833 Le Conte Ave., Los Angeles, CA 90095-1763, USA
- Department of Radiological Sciences, University
of California, Los Angeles, Los Angeles, CA, USA
- Department of Bioengineering, University of
California, Los Angeles, Los Angeles, CA, USA
- Brain Research Institute, University of
California, Los Angeles, Los Angeles, CA, USA
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33
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Wang Y, Zhan M, Roebroeck A, De Weerd P, Kashyap S, Roberts MJ. Inconsistencies in atlas-based volumetric measures of the human nucleus basalis of Meynert: A need for high-resolution alternatives. Neuroimage 2022; 259:119421. [PMID: 35779763 DOI: 10.1016/j.neuroimage.2022.119421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 06/10/2022] [Accepted: 06/28/2022] [Indexed: 10/17/2022] Open
Abstract
The nucleus basalis of Meynert (nbM) is the major source of cortical acetylcholine (ACh) and has been related to cognitive processes and to neurological disorders. However, spatially delineating the human nbM in MRI studies remains challenging. Due to the absence of a functional localiser for the human nbM, studies to date have localised it using nearby neuroanatomical landmarks or using probabilistic atlases. To understand the feasibility of MRI of the nbM we set our four goals; our first goal was to review current human nbM region-of-interest (ROI) selection protocols used in MRI studies, which we found have reported highly variable nbM volume estimates. Our next goal was to quantify and discuss the limitations of existing atlas-based volumetry of nbM. We found that the identified ROI volume depends heavily on the atlas used and on the probabilistic threshold set. In addition, we found large disparities even for data/studies using the same atlas and threshold. To test whether spatial resolution contributes to volume variability, as our third goal, we developed a novel nbM mask based on the normalized BigBrain dataset. We found that as long as the spatial resolution of the target data was 1.3 mm isotropic or above, our novel nbM mask offered realistic and stable volume estimates. Finally, as our last goal we tried to discern nbM using publicly available and novel high resolution structural MRI ex vivo MRI datasets. We find that, using an optimised 9.4T quantitative T2⁎ ex vivo dataset, the nbM can be visualised using MRI. We conclude caution is needed when applying the current methods of mapping nbM, especially for high resolution MRI data. Direct imaging of the nbM appears feasible and would eliminate the problems we identify, although further development is required to allow such imaging using standard (f)MRI scanning.
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Affiliation(s)
- Yawen Wang
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
| | - Minye Zhan
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; U992 (Cognitive neuroimaging unit), NeuroSpin, INSERM-CEA, Gif sur Yvette, France
| | - Alard Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Peter De Weerd
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Sriranga Kashyap
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; Techna Institute, University Health Network, Toronto, ON, Canada
| | - Mark J Roberts
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
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34
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Ma YJ, Jang H, Lombardi AF, Corey-Bloom J, Bydder GM. Myelin water imaging using a short-TR adiabatic inversion-recovery (STAIR) sequence. Magn Reson Med 2022; 88:1156-1169. [PMID: 35613378 PMCID: PMC9867567 DOI: 10.1002/mrm.29287] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/21/2022] [Accepted: 04/13/2022] [Indexed: 01/26/2023]
Abstract
PURPOSE To develop a new myelin water imaging (MWI) technique using a short-TR adiabatic inversion-recovery (STAIR) sequence on a clinical 3T MR scanner. METHODS Myelin water (MW) in the brain has both a much shorter T1 and a much shorter T2 * than intracellular/extracellular water. A STAIR sequence with a short TR was designed to efficiently suppress long T1 signals from intracellular/extracellular water, and therefore allow selective imaging of MW, which has a much shorter T1 . Numerical simulation and phantom studies were performed to investigate the effectiveness of long T1 signal suppression. TheT2 * in white matter (WM) was measured with STAIR and compared with T2 * measured with a conventional gradient recall echo in in vivo study. Four healthy volunteers and 4 patients with multiple sclerosis were recruited for qualitative and quantitative MWI. Apparent MW fraction was generated to compare MW in normal WM in volunteers to MW in lesions in patients with multiple sclerosis. RESULTS Both simulation and phantom studies showed that when TR was sufficiently short (eg, 250 ms), the STAIR sequence effectively suppressed long T1 signals from tissues with a broad range of T1 s using a single TR/TI combination. The volunteer study showed a short T2 * of 9.5 ± 1.7 ms in WM, which is similar to reported values for MW. Lesions in patients with multiple sclerosis showed a significantly lower apparent MW fraction (4.5% ± 1.0%) compared with that of normal WM (9.2% ± 1.5%) in healthy volunteers (p < 0.05). CONCLUSIONS The STAIR sequence provides selective MWI in brain and can quantify reductions in MW content in patients with multiple sclerosis.
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Affiliation(s)
- Ya-Jun Ma
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Hyungseok Jang
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Alecio F. Lombardi
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Jody Corey-Bloom
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA
| | - Graeme M. Bydder
- Department of Radiology, University of California San Diego, San Diego, CA, USA
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35
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Uddin MN, Figley TD, Kornelsen J, Mazerolle EL, Helmick CA, O'Grady CB, Pirzada S, Patel R, Carter S, Wong K, Essig MR, Graff LA, Bolton JM, Marriott JJ, Bernstein CN, Fisk JD, Marrie RA, Figley CR. The comorbidity and cognition in multiple sclerosis (CCOMS) neuroimaging protocol: Study rationale, MRI acquisition, and minimal image processing pipelines. FRONTIERS IN NEUROIMAGING 2022; 1:970385. [PMID: 37555178 PMCID: PMC10406313 DOI: 10.3389/fnimg.2022.970385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 07/29/2022] [Indexed: 08/10/2023]
Abstract
The Comorbidity and Cognition in Multiple Sclerosis (CCOMS) study represents a coordinated effort by a team of clinicians, neuropsychologists, and neuroimaging experts to investigate the neural basis of cognitive changes and their association with comorbidities among persons with multiple sclerosis (MS). The objectives are to determine the relationships among psychiatric (e.g., depression or anxiety) and vascular (e.g., diabetes, hypertension, etc.) comorbidities, cognitive performance, and MRI measures of brain structure and function, including changes over time. Because neuroimaging forms the basis for several investigations of specific neural correlates that will be reported in future publications, the goal of the current manuscript is to briefly review the CCOMS study design and baseline characteristics for participants enrolled in the three study cohorts (MS, psychiatric control, and healthy control), and provide a detailed description of the MRI hardware, neuroimaging acquisition parameters, and image processing pipelines for the volumetric, microstructural, functional, and perfusion MRI data.
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Affiliation(s)
- Md Nasir Uddin
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Teresa D. Figley
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Jennifer Kornelsen
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Erin L. Mazerolle
- Department of Psychology, St. Francis Xavier University, Antigonish, NS, Canada
| | - Carl A. Helmick
- Division of Geriatric Medicine, Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Christopher B. O'Grady
- Department of Anesthesia and Biomedical Translational Imaging Centre, Dalhousie University, Halifax, NS, Canada
| | - Salina Pirzada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Ronak Patel
- Department of Clinical Health Psychology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Sean Carter
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Kaihim Wong
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Marco R. Essig
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Lesley A. Graff
- Department of Clinical Health Psychology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - James M. Bolton
- Department of Psychiatry, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - James J. Marriott
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Charles N. Bernstein
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - John D. Fisk
- Nova Scotia Health Authority and the Departments of Psychiatry, Psychology and Neuroscience, and Medicine, Dalhousie University, Halifax, NS, Canada
| | - Ruth Ann Marrie
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Chase R. Figley
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
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Fischi-Gomez E, Girard G, Koch PJ, Yu T, Pizzolato M, Brügger J, Piredda GF, Hilbert T, Cadic-Melchior AG, Beanato E, Park CH, Morishita T, Wessel MJ, Schiavi S, Daducci A, Kober T, Canales-Rodríguez EJ, Hummel FC, Thiran JP. Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions. FRONTIERS IN RADIOLOGY 2022; 2:930666. [PMID: 37492668 PMCID: PMC10365099 DOI: 10.3389/fradi.2022.930666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 06/30/2022] [Indexed: 07/27/2023]
Abstract
Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acquired in a healthy population. This study focuses on multi-echo T2 relaxometry, a qMRI technique that probes the complex tissue microstructure by differentiating compartment-specific T2 relaxation times. However, estimation methods are still limited by their sensitivity to the underlying noise. Moreover, estimating the model's parameters is challenging because the resulting inverse problem is ill-posed, requiring advanced numerical regularization techniques. As a result, the estimates from distinct regularization strategies are different. In this work, we aimed to investigate the variability and reproducibility of different techniques for estimating the transverse relaxation time of the intra- and extra-cellular space (T2IE) in gray (GM) and white matter (WM) tissue in a clinical setting, using a multi-site, multi-session, and multi-run T2 relaxometry dataset. To this end, we evaluated three different techniques for estimating the T2 spectra (two regularized non-negative least squares methods and a machine learning approach). Two independent analyses were performed to study the effect of using raw and denoised data. For both the GM and WM regions, and the raw and denoised data, our results suggest that the principal source of variance is the inter-subject variability, showing a higher coefficient of variation (CoV) than those estimated for the inter-site, inter-session, and inter-run, respectively. For all reconstruction methods studied, the CoV ranged between 0.32 and 1.64%. Interestingly, the inter-session variability was close to the inter-scanner variability with no statistical differences, suggesting that T2IE is a robust parameter that could be employed in multi-site neuroimaging studies. Furthermore, the three tested methods showed consistent results and similar intra-class correlation (ICC), with values superior to 0.7 for most regions. Results from raw data were slightly more reproducible than those from denoised data. The regularized non-negative least squares method based on the L-curve technique produced the best results, with ICC values ranging from 0.72 to 0.92.
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Affiliation(s)
- Elda Fischi-Gomez
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Translational Machine Learning Lab, Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Gabriel Girard
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Philipp J. Koch
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Department of Neurology, University of Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck, Lübeck, Germany
| | - Thomas Yu
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Marco Pizzolato
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Julia Brügger
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Gian Franco Piredda
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Tom Hilbert
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Andéol G. Cadic-Melchior
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Elena Beanato
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Chang-Hyun Park
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Takuya Morishita
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Maximilian J. Wessel
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Simona Schiavi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Alessandro Daducci
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Tobias Kober
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Erick J. Canales-Rodríguez
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Friedhelm C. Hummel
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Clinical Neuroscience, University Hospital of Geneva (HUG), Geneva, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
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Silva NCBS, Dao E, Hsu CL, Tam RC, Stein R, Alkeridy W, Laule C, Vavasour IM, Liu-Ambrose T. Myelin Content and Gait Impairment in Older Adults with Cerebral Small Vessel Disease and Mild Cognitive Impairment. Neurobiol Aging 2022; 119:56-66. [DOI: 10.1016/j.neurobiolaging.2022.03.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 02/19/2022] [Accepted: 03/15/2022] [Indexed: 11/25/2022]
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Mehdizadeh N, Wilman AH. Myelin water fraction mapping from multiple echo spin echoes and an independent B 1 + map. Magn Reson Med 2022; 88:1380-1390. [PMID: 35576121 PMCID: PMC9321077 DOI: 10.1002/mrm.29286] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 03/23/2022] [Accepted: 04/13/2022] [Indexed: 11/11/2022]
Abstract
Purpose Myelin water fraction (MWF) is often obtained from a multiple echo spin echo (MESE) sequence using multi‐component T2 fitting with non‐negative least squares. This process fits many unknowns including B1+ to produce a T2 spectrum for each voxel. Presented is an alternative using a rapid B1+ mapping sequence to supply B1+ for the MWF fitting procedure. Methods Effects of B1+ errors on MWF calculations were modeled for 2D and 3D MESE using Bloch and extended phase graph simulations, respectively. Variations in SNR and relative refocusing widths were tested. Human brain experiments at 3 T used 2D MESE and an independent B1+ map. MWF maps were produced with the standard approach and with the use of the independent B1+ map. Differences in B1+ and mean MWF in specific brain regions were compared. Results For 2D MESE, MWF with the standard method was strongly affected by B1+ misestimations arising from limited SNR and response asymmetry around 180°, which decreased with increasing relative refocusing width. Using an independent B1+ map increased mean MWF and decreased coefficient of variation. Notable differences in vivo in 2D MESE were in areas of high B1+ such as thalamus and splenium where mean MWF increased by 88% and 31%, respectively (P < 0.001). Simulations also demonstrated the advantages of this approach for 3D MESE when SNR is <500. Conclusion For 2D MESE, because of increased complexity of decay curves and limited SNR, supplying B1+ improves MWF results in peripheral and central brain regions where flip angles differ substantially from 180°.
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Affiliation(s)
- Nima Mehdizadeh
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Alan H Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
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Greeley B, Rubino C, Denyer R, Chau B, Larssen B, Lakhani B, Boyd L. Individuals with Higher Levels of Physical Activity after Stroke Show Comparable Patterns of Myelin to Healthy Older Adults. Neurorehabil Neural Repair 2022; 36:381-389. [PMID: 35533214 PMCID: PMC9127936 DOI: 10.1177/15459683221100497] [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] [Indexed: 11/27/2022]
Abstract
Background Myelin asymmetry ratios (MARs) relate and contribute to motor impairment and
function after stroke. Physical activity (PA) may induce myelin plasticity,
potentially mitigating hemispheric myelin asymmetries that can occur after a
stroke. Objective The aim of this study was to determine whether individuals with higher levels
of PA showed lower MAR compared to individuals with lower levels of PA. Methods Myelin water fraction was obtained from 5 bilateral motor regions in 22
individuals with chronic stroke and 26 healthy older adults. Activity levels
were quantified with wrist accelerometers worn for a period of 72 hours (3
days). Higher and lower PA levels were defined by a cluster analysis within
each group. Results MAR was similar regardless of PA level within the older adult group. Compared
to the higher PA stroke group, lower PA stroke participants displayed
greater MAR. There was no difference in MAR between the stroke and older
adult higher PA groups. Within the lower PA groups, individuals with stroke
showed greater MAR compared to the older adults. Arm impairment, lesion
volume, age, time since stroke, and preferential arm use were not different
between the PA stroke groups, suggesting that motor impairment severity and
extent of brain damage did not drive differences in PA. Conclusion Individuals who have had a stroke and are also physically active display
lower MAR (i.e., similar myelin in both hemispheres) in motor regions. High
levels of PA may be neuroprotective and mitigate myelin asymmetries once a
neurological insult, such as a stroke, occurs. Alternately, it is possible
that promoting high levels of PA after a stroke may reduce myelin
asymmetries.
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Affiliation(s)
- Brian Greeley
- Department of Physical Therapy, 8166University of British Columbia, Vancouver, BC, Canada
| | - Cristina Rubino
- Graduate Program in Rehabilitation Sciences, 8166University of British Columbia, Vancouver, BC, Canada
| | - Ronan Denyer
- Graduate Program in Neuroscience, 8166University of British Columbia, Vancouver, BC, Canada
| | - Briana Chau
- Graduate Program in Rehabilitation Sciences, 8166University of British Columbia, Vancouver, BC, Canada
| | - Beverley Larssen
- Graduate Program in Rehabilitation Sciences, 8166University of British Columbia, Vancouver, BC, Canada
| | - Bimal Lakhani
- Department of Physical Therapy, 8166University of British Columbia, Vancouver, BC, Canada
| | - Lara Boyd
- Department of Physical Therapy, 8166University of British Columbia, Vancouver, BC, Canada.,Graduate Program in Rehabilitation Sciences, 8166University of British Columbia, Vancouver, BC, Canada.,Graduate Program in Neuroscience, 8166University of British Columbia, Vancouver, BC, Canada
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40
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Economou M, Billiet T, Wouters J, Ghesquière P, Vanderauwera J, Vandermosten M. Myelin water fraction in relation to fractional anisotropy and reading in 10-year-old children. Brain Struct Funct 2022; 227:2209-2217. [PMID: 35403895 DOI: 10.1007/s00429-022-02486-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 03/24/2022] [Indexed: 11/26/2022]
Abstract
Diffusion-weighted imaging studies have repeatedly shown that white matter correlates with reading throughout development. However, the neurobiological interpretation of this relationship is constrained by the limited microstructural specificity of diffusion imaging. A critical component of white matter microstructure is myelin, which can be investigated noninvasively using MRI. Here, we examined the link between myelin water fraction (MWF) and reading ability in 10-year-old children (n = 69). To better understand this relationship, we additionally investigated how these two variables relate to fractional anisotropy (FA; a common index of diffusion-weighted imaging). Our analysis revealed that lower MWF coheres with better reading scores in left-hemispheric tracts relevant for reading. While we replicated previous reports on a positive relationship between FA and MWF, we did not find any evidence for an association between reading and FA. Together, these findings contrast previous research suggesting that poor reading abilities might be rooted in lower myelination and emphasize the need for further longitudinal research to understand how this relationship evolves throughout reading development. Altogether, this study contributes important insights into the role of myelin-related processes in the relationship between reading and white matter structure.
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Affiliation(s)
- Maria Economou
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium.
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium.
- Leuven Brain Institute, KU Leuven, Leuven, Belgium.
| | - Thibo Billiet
- Icometrix, Research and Development, Leuven, Belgium
| | - Jan Wouters
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium
| | - Pol Ghesquière
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium
| | - Jolijn Vanderauwera
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium
- Psychological Sciences Research Institute, Université Catholique de Louvain, 1348, Louvain-la-Neuve, Belgium
- Institute of Neuroscience, Université Catholique de Louvain, 1348, Louvain-la-Neuve, Belgium
| | - Maaike Vandermosten
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
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Kiely M, Triebswetter C, Cortina LE, Gong Z, Alsameen MH, Spencer RG, Bouhrara M. Insights into human cerebral white matter maturation and degeneration across the adult lifespan. Neuroimage 2022; 247:118727. [PMID: 34813969 PMCID: PMC8792239 DOI: 10.1016/j.neuroimage.2021.118727] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 10/15/2021] [Accepted: 11/12/2021] [Indexed: 01/01/2023] Open
Abstract
White matter (WM) microstructural properties change across the adult lifespan and with neuronal diseases. Understanding microstructural changes due to aging is paramount to distinguish them from neuropathological changes. Conducted on a large cohort of 147 cognitively unimpaired subjects, spanning a wide age range of 21 to 94 years, our study evaluated sex- and age-related differences in WM microstructure. Specifically, we used diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) indices, sensitive measures of myelin and axonal density in WM, and myelin water fraction (MWF), a measure of the fraction of the signal of water trapped within the myelin sheets, to probe these differences. Furthermore, we examined regional correlations between MWF and DTI indices to evaluate whether the DTI metrics provide information complementary to MWF. While sexual dimorphism was, overall, nonsignificant, we observed region-dependent differences in MWF, that is, myelin content, and axonal density with age and found that both exhibit nonlinear, but distinct, associations with age. Furthermore, DTI indices were moderately correlated with MWF, indicating their good sensitivity to myelin content as well as to other constituents of WM tissue such as axonal density. The microstructural differences captured by our MRI metrics, along with their weak to moderate associations with MWF, strongly indicate the potential value of combining these outcome measures in a multiparametric approach. Furthermore, our results support the last-in-first-out and the gain-predicts-loss hypotheses of WM maturation and degeneration. Indeed, our results indicate that the posterior WM regions are spared from neurodegeneration as compared to anterior regions, while WM myelination follows a temporally symmetric time course across the adult life span.
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Affiliation(s)
- Matthew Kiely
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Curtis Triebswetter
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Luis E Cortina
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Maryam H Alsameen
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA.
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Johnson P, Chan JK, Vavasour IM, Abel S, Lee LE, Yong H, Laule C, Li DKB, Tam R, Traboulsee A, Carruthers RL, Kolind SH. Quantitative MRI findings indicate diffuse white matter damage in Susac Syndrome. Mult Scler J Exp Transl Clin 2022; 8:20552173221078834. [PMID: 35186315 PMCID: PMC8851927 DOI: 10.1177/20552173221078834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 01/21/2022] [Indexed: 11/15/2022] Open
Abstract
Background Susac Syndrome (SuS) is an autoimmune endotheliopathy impacting the brain, retina and cochlea that can clinically mimic multiple sclerosis (MS). Objective To evaluate non-lesional white matter demyelination changes in SuS compared to MS and healthy controls (HC) using quantitative MRI. Methods 3T MRI including myelin water imaging and diffusion basis spectrum imaging were acquired for 7 SuS, 10 MS and 10 HC participants. Non-lesional white matter was analyzed in the corpus callosum (CC) and normal appearing white matter (NAWM). Groups were compared using ANCOVA with Tukey correction. Results SuS CC myelin water fraction (mean 0.092) was lower than MS(0.11, p = 0.01) and HC(0.11, p = 0.04). Another myelin marker, radial diffusivity, was increased in SuS CC(0.27μm2/ms) compared to HC(0.21μm2/ms, p = 0.008) and MS(0.23μm2/ms, p = 0.05). Fractional anisotropy was lower in SuS CC(0.82) than HC(0.86, p = 0.04). Fiber fraction (reflecting axons) did not differ from HC or MS. In NAWM, radial diffusivity and apparent diffusion coefficient were significantly increased in SuS compared to HC(p < 0.001 for both measures) and MS(p = 0.003, p < 0.001 respectively). Conclusions Our results provided evidence of myelin damage in SuS, particularly in the CC, and more extensive microstructural injury in NAWM, supporting the hypothesis that there are widespread microstructural changes in SuS syndrome including diffuse demyelination.
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Affiliation(s)
| | - JK Chan
- Department of Medicine (Neurology), University of British Columbia, Canada
| | - IM Vavasour
- Department of Radiology, University of British Columbia, Canada
- International Collaboration on Repair Discoveries (ICORD)
| | | | | | - H Yong
- Department of Medicine (Neurology), University of British Columbia, Canada
| | - C Laule
- Department of Radiology, University of British Columbia, Canada
- International Collaboration on Repair Discoveries (ICORD)
- Department of Pathology and Laboratory Medicine, University of British Columbia, Canada
- Department of Physics and Astronomy, University of British Columbia, Canada
| | - DKB Li
- Department of Medicine (Neurology), University of British Columbia, Canada
- Department of Radiology, University of British Columbia, Canada
| | - R Tam
- Department of Radiology, University of British Columbia, Canada
- School of Biomedical Engineering, University of British Columbia, Canada
| | | | - RL Carruthers
- Department of Medicine (Neurology), University of British Columbia, Canada
| | - SH Kolind
- Department of Medicine (Neurology), University of British Columbia, Canada
- Department of Radiology, University of British Columbia, Canada
- International Collaboration on Repair Discoveries (ICORD)
- Department of Physics and Astronomy, University of British Columbia, Canada
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Lim SH, Lee J, Jung S, Kim B, Rhee HY, Oh SH, Park S, Cho AR, Ryu CW, Jahng GH. Myelin-Weighted Imaging Presents Reduced Apparent Myelin Water in Patients with Alzheimer’s Disease. Diagnostics (Basel) 2022; 12:diagnostics12020446. [PMID: 35204537 PMCID: PMC8871299 DOI: 10.3390/diagnostics12020446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 01/27/2022] [Accepted: 02/06/2022] [Indexed: 02/04/2023] Open
Abstract
The purpose of this study was to investigate myelin loss in both AD and mild cognitive impairment (MCI) patients with a new myelin water mapping technique within reasonable scan time and evaluate the clinical relevance of the apparent myelin water fraction (MWF) values by assessing the relationship between decreases in myelin water and the degree of memory decline or aging. Twenty-nine individuals were assigned to the cognitively normal (CN) elderly group, 32 participants were assigned to the MCI group, and 31 patients were assigned to the AD group. A 3D visualization of the short transverse relaxation time component (ViSTa)-gradient and spin-echo (GraSE) sequence was developed to map apparent MWF. Then, the MWF values were compared between the three participant groups and was evaluated the relationship with the degree of memory loss. The AD group showed a reduced apparent MWF compared to the CN and MCI groups. The largest AUC (area under the curve) value was in the corpus callosum and used to classify the CN and AD groups using the apparent MWF. The ViSTa-GraSE sequence can be a useful tool to map the MWF in a reasonable scan time. Combining the MWF in the corpus callosum with the detection of atrophy in the hippocampus can be valuable for group classification.
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Affiliation(s)
- Seung-Hyun Lim
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea; (S.-H.L.); (B.K.); (C.-W.R.)
| | - Jiyoon Lee
- Department of Biomedical Engineering, Undergraduate School, College of Electronics and Information, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si 17104, Korea; (J.L.); (S.J.)
| | - Sumin Jung
- Department of Biomedical Engineering, Undergraduate School, College of Electronics and Information, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si 17104, Korea; (J.L.); (S.J.)
| | - Bokyung Kim
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea; (S.-H.L.); (B.K.); (C.-W.R.)
| | - Hak Young Rhee
- Department of Neurology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea;
- Department of Medicine, College of Medicine, Kyung Hee University, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Korea; (S.P.); (A.R.C.)
| | - Se-Hong Oh
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin 17035, Korea;
| | - Soonchan Park
- Department of Medicine, College of Medicine, Kyung Hee University, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Korea; (S.P.); (A.R.C.)
| | - Ah Rang Cho
- Department of Medicine, College of Medicine, Kyung Hee University, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Korea; (S.P.); (A.R.C.)
- Department of Psychiatry, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea
| | - Chang-Woo Ryu
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea; (S.-H.L.); (B.K.); (C.-W.R.)
- Department of Medicine, College of Medicine, Kyung Hee University, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Korea; (S.P.); (A.R.C.)
| | - Geon-Ho Jahng
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea; (S.-H.L.); (B.K.); (C.-W.R.)
- Department of Medicine, College of Medicine, Kyung Hee University, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Korea; (S.P.); (A.R.C.)
- Correspondence: ; Tel.: +82-2-440-6187; Fax: +82-2-440-6932
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Kim J, Nguyen TD, Zhang J, Gauthier SA, Marcille M, Zhang H, Cho J, Spincemaille P, Wang Y. Subsecond accurate myelin water fraction reconstruction from FAST-T 2 data with 3D UNET. Magn Reson Med 2022; 87:2979-2988. [PMID: 35092094 DOI: 10.1002/mrm.29176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 12/31/2021] [Accepted: 01/08/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE To develop a 3D UNET convolutional neural network for rapid extraction of myelin water fraction (MWF) maps from six-echo fast acquisition with spiral trajectory and T2 -prep data and to evaluate its accuracy in comparison with multilayer perceptron (MLP) network. METHODS The MWF maps were extracted from 138 patients with multiple sclerosis using an iterative three-pool nonlinear least-squares algorithm (NLLS) without and with spatial regularization (srNLLS), which were used as ground-truth labels to train, validate, and test UNET and MLP networks as a means to accelerate data fitting. Network testing was performed in 63 patients with multiple sclerosis and a numerically simulated brain phantom at SNR of 200, 100 and 50. RESULTS Simulations showed that UNET reduced the MWF mean absolute error by 30.1% to 56.4% and 16.8% to 53.6% over the whole brain and by 41.2% to 54.4% and 21.4% to 49.4% over the lesions for predicting srNLLS and NLLS MWF, respectively, compared to MLP, with better performance at lower SNRs. UNET also outperformed MLP for predicting srNLLS MWF in the in vivo multiple-sclerosis brain data, reducing mean absolute error over the whole brain by 61.9% and over the lesions by 67.5%. However, MLP yielded 41.1% and 51.7% lower mean absolute error for predicting in vivo NLLS MWF over the whole brain and the lesions, respectively, compared with UNET. The whole-brain MWF processing time using a GPU was 0.64 seconds for UNET and 0.74 seconds for MLP. CONCLUSION Subsecond whole-brain MWF extraction from fast acquisition with spiral trajectory and T2 -prep data using UNET is feasible and provides better accuracy than MLP for predicting MWF output of srNLLS algorithm.
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Affiliation(s)
- Jeremy Kim
- Department of Computer Science, Stanford University, Stanford, California, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Jinwei Zhang
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA.,Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Susan A Gauthier
- Department of Neurology, Weill Cornell Medicine, New York, New York, USA
| | - Melanie Marcille
- Department of Neurology, Weill Cornell Medicine, New York, New York, USA
| | - Hang Zhang
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Junghun Cho
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | | | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA.,Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
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Figley CR, Uddin MN, Wong K, Kornelsen J, Puig J, Figley TD. Potential Pitfalls of Using Fractional Anisotropy, Axial Diffusivity, and Radial Diffusivity as Biomarkers of Cerebral White Matter Microstructure. Front Neurosci 2022; 15:799576. [PMID: 35095400 PMCID: PMC8795606 DOI: 10.3389/fnins.2021.799576] [Citation(s) in RCA: 83] [Impact Index Per Article: 41.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/17/2021] [Indexed: 01/31/2023] Open
Abstract
Fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) are commonly used as MRI biomarkers of white matter microstructure in diffusion MRI studies of neurodevelopment, brain aging, and neurologic injury/disease. Some of the more frequent practices include performing voxel-wise or region-based analyses of these measures to cross-sectionally compare individuals or groups, longitudinally assess individuals or groups, and/or correlate with demographic, behavioral or clinical variables. However, it is now widely recognized that the majority of cerebral white matter voxels contain multiple fiber populations with different trajectories, which renders these metrics highly sensitive to the relative volume fractions of the various fiber populations, the microstructural integrity of each constituent fiber population, and the interaction between these factors. Many diffusion imaging experts are aware of these limitations and now generally avoid using FA, AD or RD (at least in isolation) to draw strong reverse inferences about white matter microstructure, but based on the continued application and interpretation of these metrics in the broader biomedical/neuroscience literature, it appears that this has perhaps not yet become common knowledge among diffusion imaging end-users. Therefore, this paper will briefly discuss the complex biophysical underpinnings of these measures in the context of crossing fibers, provide some intuitive “thought experiments” to highlight how conventional interpretations can lead to incorrect conclusions, and suggest that future studies refrain from using (over-interpreting) FA, AD, and RD values as standalone biomarkers of cerebral white matter microstructure.
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Affiliation(s)
- Chase R. Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
- *Correspondence: Chase R. Figley,
| | - Md Nasir Uddin
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Department of Neurology, University of Rochester, Rochester, NY, United States
| | - Kaihim Wong
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
| | - Jennifer Kornelsen
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
| | - Josep Puig
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Girona Biomedical Research Institute (IDIBGI), Hospital Universitari de Girona Dr. Josep Trueta, Girona, Spain
| | - Teresa D. Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
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Omer N, Galun M, Stern N, Blumenfeld-Katzir T, Ben-Eliezer N. Data-driven algorithm for myelin water imaging: Probing subvoxel compartmentation based on identification of spatially global tissue features. Magn Reson Med 2021; 87:2521-2535. [PMID: 34958690 DOI: 10.1002/mrm.29125] [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: 07/19/2021] [Revised: 11/23/2021] [Accepted: 11/26/2021] [Indexed: 01/10/2023]
Abstract
PURPOSE Multicomponent analysis of MRI T2 relaxation time (mcT2 ) is commonly used for estimating myelin content by separating the signal at each voxel into its underlying distribution of T2 values. This voxel-based approach is challenging due to the large ambiguity in the multi-T2 space and the low SNR of MRI signals. Herein, we present a data-driven mcT2 analysis, which utilizes the statistical strength of identifying spatially global mcT2 motifs in white matter segments before deconvolving the local signal at each voxel. METHODS Deconvolution is done using a tailored optimization scheme, which incorporates the global mcT2 motifs without additional prior assumptions regarding the number of microscopic components. The end results of this process are voxel-wise myelin water fraction maps. RESULTS Validations are shown for computer-generated signals, uniquely designed subvoxel mcT2 phantoms, and in vivo human brain. Results demonstrated excellent fitting accuracy, both for the numerical and the physical mcT2 phantoms, exhibiting excellent agreement between calculated myelin water fraction and ground truth. Proof-of-concept in vivo validation is done by calculating myelin water fraction maps for white matter segments of the human brain. Interscan stability of myelin water fraction values was also estimated, showing good correlation between scans. CONCLUSION We conclude that studying global tissue motifs prior to performing voxel-wise mcT2 analysis stabilizes the optimization scheme and efficiently overcomes the ambiguity in the T2 space. This new approach can improve myelin water imaging and the investigation of microstructural compartmentation in general.
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Affiliation(s)
- Noam Omer
- The Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | - Meirav Galun
- Department of Computer Science and Applied Mathematics, Weitzman Institute of Science, Rehovot, Israel
| | - Neta Stern
- The Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | | | - Noam Ben-Eliezer
- The Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University Langone Medical Center, New York, New York, USA
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Snyder J, McPhee KC, Wilman AH. T 2 quantification in brain using 3D fast spin-echo imaging with long echo trains. Magn Reson Med 2021; 87:2145-2160. [PMID: 34894641 PMCID: PMC9299830 DOI: 10.1002/mrm.29113] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 11/16/2021] [Accepted: 11/17/2021] [Indexed: 11/15/2022]
Abstract
Purpose Three‐dimensional fast spin‐echo (FSE) sequences commonly use very long echo trains (>64 echoes) and severely reduced refocusing angles. They are increasingly used in brain exams due to high, isotropic resolution and reasonable scan time when using long trains and short interecho spacing. In this study, T2 quantification in 3D FSE is investigated to achieve increased resolution when comparing with established 2D (proton‐density dual‐echo and multi‐echo spin‐echo) methods. Methods The FSE sequence design was explored to use long echo trains while minimizing T2 fitting error and maintaining typical proton density and T2‐weighted contrasts. Constant and variable flip angle trains were investigated using extended phase graph and Bloch equation simulations. Optimized parameters were analyzed in phantom experiments and validated in vivo in comparison to 2D methods for eight regions of interest in brain, including deep gray‐matter structures and white‐matter tracts. Results Phantom and healthy in vivo brain T2 measurements showed that optimized variable echo‐train 3D FSE performs similarly to previous 2D methods, while achieving three‐fold‐higher slice resolution, evident visually in the 3D T2 maps. Optimization resulted in better T2 fitting and compared well with standard multi‐echo spin echo (within the 8‐ms confidence limits defined based on Bland‐Altman analysis). Conclusion T2 mapping using 3D FSE with long echo trains and variable refocusing angles provides T2 accuracy in agreement with 2D methods with additional high‐resolution benefits, allowing isotropic views while avoiding incidental magnetization transfer effects. Consequently, optimized 3D sequences should be considered when choosing T2 mapping methods for high anatomic detail.
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Affiliation(s)
- Jeff Snyder
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | | | - Alan H Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
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Faw TD, Lakhani B, Schmalbrock P, Knopp MV, Lohse KR, Kramer JLK, Liu H, Nguyen HT, Phillips EG, Bratasz A, Fisher LC, Deibert RJ, Boyd LA, McTigue DM, Basso DM. Eccentric rehabilitation induces white matter plasticity and sensorimotor recovery in chronic spinal cord injury. Exp Neurol 2021; 346:113853. [PMID: 34464653 PMCID: PMC10084731 DOI: 10.1016/j.expneurol.2021.113853] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 08/04/2021] [Accepted: 08/26/2021] [Indexed: 12/12/2022]
Abstract
Experience-dependent white matter plasticity offers new potential for rehabilitation-induced recovery after neurotrauma. This first-in-human translational experiment combined myelin water imaging in humans and genetic fate-mapping of oligodendrocyte lineage cells in mice to investigate whether downhill locomotor rehabilitation that emphasizes eccentric muscle actions promotes white matter plasticity and recovery in chronic, incomplete spinal cord injury (SCI). In humans, of 20 individuals with SCI that enrolled, four passed the imaging screen and had myelin water imaging before and after a 12-week (3 times/week) downhill locomotor treadmill training program (SCI + DH). One individual was excluded for imaging artifacts. Uninjured control participants (n = 7) had two myelin water imaging sessions within the same day. Changes in myelin water fraction (MWF), a histopathologically-validated myelin biomarker, were analyzed in a priori motor learning and non-motor learning brain regions and the cervical spinal cord using statistical approaches appropriate for small sample sizes. PDGFRα-CreERT2:mT/mG mice, that express green fluorescent protein on oligodendrocyte precursor cells and subsequent newly-differentiated oligodendrocytes upon tamoxifen-induced recombination, were either naive (n = 6) or received a moderate (75 kilodyne), contusive SCI at T9 and were randomized to downhill training (n = 6) or unexercised groups (n = 6). We initiated recombination 29 days post-injury, seven days prior to downhill training. Mice underwent two weeks of daily downhill training on the same 10% decline grade used in humans. Between-group comparison of functional (motor and sensory) and histological (oligodendrogenesis, oligodendroglial/axon interaction, paranodal structure) outcomes occurred post-training. In humans with SCI, downhill training increased MWF in brain motor learning regions (postcentral, precuneus) and mixed motor and sensory tracts of the ventral cervical spinal cord compared to control participants (P < 0.05). In mice with thoracic SCI, downhill training induced oligodendrogenesis in cervical dorsal and lateral white matter, increased axon-oligodendroglial interactions, and normalized paranodal structure in dorsal column sensory tracts (P < 0.05). Downhill training improved sensorimotor recovery in mice by normalizing hip and knee motor control and reducing hyperalgesia, both of which were associated with new oligodendrocytes in the cervical dorsal columns (P < 0.05). Our findings indicate that eccentric-focused, downhill rehabilitation promotes white matter plasticity and improved function in chronic SCI, likely via oligodendrogenesis in nervous system regions activated by the training paradigm. Together, these data reveal an exciting role for eccentric training in white matter plasticity and sensorimotor recovery after SCI.
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Affiliation(s)
- Timothy D Faw
- Neuroscience Graduate Program, The Ohio State University, Columbus, OH 43210, USA; Center for Brain and Spinal Cord Repair, The Ohio State University, Columbus, OH 43210, USA; Department of Orthopaedic Surgery, Duke University, Durham, NC 27710, USA
| | - Bimal Lakhani
- Department of Physical Therapy, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Petra Schmalbrock
- Department of Radiology, The Ohio State University, Columbus, OH 43210, USA
| | - Michael V Knopp
- Department of Radiology, The Ohio State University, Columbus, OH 43210, USA
| | - Keith R Lohse
- Department of Health, Kinesiology, and Recreation, University of Utah, Salt Lake City, UT 84112, USA; Department of Physical Therapy and Athletic Training, University of Utah, Salt Lake City, UT 84108, USA
| | - John L K Kramer
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC V6T 1Z3, Canada; International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
| | - Hanwen Liu
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC V5Z 1M9, Canada; Department of Physics and Astronomy, University of British Columbia, Vancouver, BC V6T 1Z1, Canada
| | - Huyen T Nguyen
- Department of Radiology, The Ohio State University, Columbus, OH 43210, USA
| | - Eileen G Phillips
- Center for Brain and Spinal Cord Repair, The Ohio State University, Columbus, OH 43210, USA; School of Health and Rehabilitation Sciences, The Ohio State University, Columbus, OH 43210, USA
| | - Anna Bratasz
- Small Animal Imaging Shared Resources, Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH 43210, USA
| | - Lesley C Fisher
- Center for Brain and Spinal Cord Repair, The Ohio State University, Columbus, OH 43210, USA; School of Health and Rehabilitation Sciences, The Ohio State University, Columbus, OH 43210, USA
| | - Rochelle J Deibert
- Center for Brain and Spinal Cord Repair, The Ohio State University, Columbus, OH 43210, USA; School of Health and Rehabilitation Sciences, The Ohio State University, Columbus, OH 43210, USA
| | - Lara A Boyd
- Department of Physical Therapy, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Dana M McTigue
- Neuroscience Graduate Program, The Ohio State University, Columbus, OH 43210, USA; Center for Brain and Spinal Cord Repair, The Ohio State University, Columbus, OH 43210, USA; Department of Neuroscience, The Ohio State University, Columbus, OH 43210, USA
| | - D Michele Basso
- Neuroscience Graduate Program, The Ohio State University, Columbus, OH 43210, USA; Center for Brain and Spinal Cord Repair, The Ohio State University, Columbus, OH 43210, USA; School of Health and Rehabilitation Sciences, The Ohio State University, Columbus, OH 43210, USA.
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Canales-Rodríguez EJ, Pizzolato M, Yu T, Piredda GF, Hilbert T, Radua J, Kober T, Thiran JP. Revisiting the T 2 spectrum imaging inverse problem: Bayesian regularized non-negative least squares. Neuroimage 2021; 244:118582. [PMID: 34536538 DOI: 10.1016/j.neuroimage.2021.118582] [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: 06/04/2021] [Revised: 08/12/2021] [Accepted: 09/14/2021] [Indexed: 01/24/2023] Open
Abstract
Multi-echo T2 magnetic resonance images contain information about the distribution of T2 relaxation times of compartmentalized water, from which we can estimate relevant brain tissue properties such as the myelin water fraction (MWF). Regularized non-negative least squares (NNLS) is the tool of choice for estimating non-parametric T2 spectra. However, the estimation is ill-conditioned, sensitive to noise, and highly affected by the employed regularization weight. The purpose of this study is threefold: first, we want to underline that the apparently innocuous use of two alternative parameterizations for solving the inverse problem, which we called the standard and alternative regularization forms, leads to different solutions; second, to assess the performance of both parameterizations; and third, to propose a new Bayesian regularized NNLS method (BayesReg). The performance of BayesReg was compared with that of two conventional approaches (L-curve and Chi-square (X2) fitting) using both regularization forms. We generated a large dataset of synthetic data, acquired in vivo human brain data in healthy participants for conducting a scan-rescan analysis, and correlated the myelin content derived from histology with the MWF estimated from ex vivo data. Results from synthetic data indicate that BayesReg provides accurate MWF estimates, comparable to those from L-curve and X2, and with better overall stability across a wider signal-to-noise range. Notably, we obtained superior results by using the alternative regularization form. The correlations reported in this study are higher than those reported in previous studies employing the same ex vivo and histological data. In human brain data, the estimated maps from L-curve and BayesReg were more reproducible. However, the T2 spectra produced by BayesReg were less affected by over-smoothing than those from L-curve. These findings suggest that BayesReg is a good alternative for estimating T2 distributions and MWF maps.
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Affiliation(s)
- Erick Jorge Canales-Rodríguez
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-STI-IEL-LTS5, Station 11, CH-1015, Lausanne, Switzerland.
| | - Marco Pizzolato
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark; Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-STI-IEL-LTS5, Station 11, CH-1015, Lausanne, Switzerland
| | - Thomas Yu
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-STI-IEL-LTS5, Station 11, CH-1015, Lausanne, Switzerland; Medical Image Analysis Laboratory, Center for Biomedical Imaging (CIBM), University of Lausanne, Switzerland
| | - Gian Franco Piredda
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-STI-IEL-LTS5, Station 11, CH-1015, Lausanne, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tom Hilbert
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-STI-IEL-LTS5, Station 11, CH-1015, Lausanne, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Joaquim Radua
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain; Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, United Kingdom; Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Stockholm, Sweden
| | - Tobias Kober
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-STI-IEL-LTS5, Station 11, CH-1015, Lausanne, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-STI-IEL-LTS5, Station 11, CH-1015, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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Wang C, Barton J, Kyle K, Ly L, Barnett Y, Hartung HP, Reddel SW, Beadnall H, Taha M, Klistorner A, Barnett MH. Multiple sclerosis: structural and functional integrity of the visual system following alemtuzumab therapy. J Neurol Neurosurg Psychiatry 2021; 92:1319-1324. [PMID: 34187865 DOI: 10.1136/jnnp-2021-326164] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 06/02/2021] [Indexed: 11/04/2022]
Abstract
OBJECTIVE To investigate potential neuroprotective and pro-remyelinating effects of alemtuzumab in multiple sclerosis (MS), using the visual pathway as a model. METHODS We monitored clinical, multifocal visual evoked potential (mfVEP) and MRI outcomes in 30 patients commencing alemtuzumab for relapsing MS, and a reference group of 20 healthy controls (HCs), over 24 months. Change in mfVEP latency was the primary endpoint; change in optic radiation (OR) lesion diffusion metrics and Mars letter contrast sensitivity over the course of the study were secondary endpoints. RESULTS In patients, we observed a mean shortening of mfVEP latency of 1.21 ms over the course of the study (95% CI 0.21 to 2.21, p=0.013), not altered by correction for age, gender, disease duration or change in OR T2 lesion volume. Mean mfVEP latency in the HC group increased over the course of the study by 0.72 ms (not significant). Analysis of chronic OR T2 lesions (patients) showed an increase in normalised fractional anisotropy and axial diffusivity between baseline and 24 months (both p<0.01). Mean Mars letter contrast sensitivity was improved at 24 months vs baseline (p<0.001), and driven by an early improvement, in both patients and HC. CONCLUSION We found evidence of partial lesion remyelination after alemtuzumab therapy, indicating either natural restoration in the context of a 'permissive' local milieu; or potentially an independent, pro-reparative mechanism of action. The visual system presents a unique opportunity to study function-structure specific effects of therapy and inform the design of future phase 2 MS remyelination trials.
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Affiliation(s)
- Chenyu Wang
- Sydney Neuroimaging Analysis Centre, Camperdown, New South Wales, Australia.,Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Joshua Barton
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Kain Kyle
- Sydney Neuroimaging Analysis Centre, Camperdown, New South Wales, Australia.,Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Linda Ly
- Sydney Neuroimaging Analysis Centre, Camperdown, New South Wales, Australia
| | - Yael Barnett
- Sydney Neuroimaging Analysis Centre, Camperdown, New South Wales, Australia.,Radiology Department, St Vincent's Hospital Sydney, Darlinghurst, New South Wales, Australia
| | - Hans-Peter Hartung
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.,Clinic for Neurology, Heinrich Heine University Düsseldorf, Dusseldorf, Germany
| | - Stephen W Reddel
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Heidi Beadnall
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.,Neurology Department, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
| | - Marinda Taha
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Alexander Klistorner
- Sydney Neuroimaging Analysis Centre, Camperdown, New South Wales, Australia.,Save Sight Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Michael Harry Barnett
- Sydney Neuroimaging Analysis Centre, Camperdown, New South Wales, Australia .,Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia.,Neurology Department, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
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