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Lee J, Ji S, Oh SH. So You Want to Image Myelin Using MRI: Magnetic Susceptibility Source Separation for Myelin Imaging. Magn Reson Med Sci 2024:rev.2024-0001. [PMID: 38644201 DOI: 10.2463/mrms.rev.2024-0001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/23/2024] Open
Abstract
In MRI, researchers have long endeavored to effectively visualize myelin distribution in the brain, a pursuit with significant implications for both scientific research and clinical applications. Over time, various methods such as myelin water imaging, magnetization transfer imaging, and relaxometric imaging have been developed, each carrying distinct advantages and limitations. Recently, an innovative technique named as magnetic susceptibility source separation has emerged, introducing a novel surrogate biomarker for myelin in the form of a diamagnetic susceptibility map. This paper comprehensively reviews this cutting-edge method, providing the fundamental concepts of magnetic susceptibility, susceptibility imaging, and the validation of the diamagnetic susceptibility map as a myelin biomarker that indirectly measures myelin content. Additionally, the paper explores essential aspects of data acquisition and processing, offering practical insights for readers. A comparison with established myelin imaging methods is also presented, and both current and prospective clinical and scientific applications are discussed to provide a holistic understanding of the technique. This work aims to serve as a foundational resource for newcomers entering this dynamic and rapidly expanding field.
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Affiliation(s)
- Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Sooyeon Ji
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Se-Hong Oh
- Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Korea
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2
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Hara S, Kikuta J, Takabayashi K, Kamagata K, Hayashi S, Inaji M, Tanaka Y, Hori M, Ishii K, Nariai T, Taoka T, Naganawa S, Aoki S, Maehara T. Decreased diffusivity along the perivascular space and cerebral hemodynamic disturbance in adult moyamoya disease. J Cereb Blood Flow Metab 2024:271678X241245492. [PMID: 38574287 DOI: 10.1177/0271678x241245492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
Moyamoya disease (MMD) causes cerebral arterial stenosis and hemodynamic disturbance, the latter of which may disrupt glymphatic system activity, the waste clearance system. We evaluated 46 adult patients with MMD and 33 age- and sex-matched controls using diffusivity along the perivascular space (ALPS) measured with diffusion tensor imaging (ALPS index), which may partly reflect glymphatic system activity, and multishell diffusion MRI to generate freewater maps. Twenty-three patients were also evaluated via 15O-gas positron emission tomography (PET), and all patients underwent cognitive tests. Compared to controls, patients (38.4 (13.2) years old, 35 females) had lower ALPS indices in the left and right hemispheres (1.94 (0.27) vs. 1.65 (0.25) and 1.94 (0.22) vs. 1.65 (0.19), P < 0.001). While the right ALPS index showed no correlation, the left ALPS index was correlated with parenchymal freewater (ρ = -0.47, P < 0.001); perfusion measured with PET (cerebral blood flow, ρ = 0.70, P < 0.001; mean transit time, ρ = -0.60, P = 0.003; and oxygen extraction fraction, ρ = -0.52, P = 0.003); and cognitive tests (trail making test part B for executive function; ρ = -0.37, P = 0.01). Adult patients with MMD may exhibit decreased glymphatic system activity, which is correlated with the degree of hemodynamic disturbance, increased interstitial freewater, and cognitive dysfunction, but further investigation is needed.
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Affiliation(s)
- Shoko Hara
- Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
- Department of Radiology, Juntendo University, Tokyo, Japan
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Junko Kikuta
- Department of Radiology, Juntendo University, Tokyo, Japan
| | | | - Koji Kamagata
- Department of Radiology, Juntendo University, Tokyo, Japan
| | - Shihori Hayashi
- Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Motoki Inaji
- Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Yoji Tanaka
- Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
| | - Masaaki Hori
- Department of Radiology, Juntendo University, Tokyo, Japan
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - Kenji Ishii
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Tadashi Nariai
- Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Toshiaki Taoka
- Department of Innovative Biomedical Visualization, Nagoya University Graduate School of Medicine, Aichi, Japan
| | | | - Shigeki Aoki
- Department of Radiology, Juntendo University, Tokyo, Japan
| | - Taketoshi Maehara
- Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
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3
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Wiltgen T, Voon C, Van Leemput K, Wiestler B, Mühlau M. Intensity scaling of conventional brain magnetic resonance images avoiding cerebral reference regions: A systematic review. PLoS One 2024; 19:e0298642. [PMID: 38483873 PMCID: PMC10939249 DOI: 10.1371/journal.pone.0298642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 01/26/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND Conventional brain magnetic resonance imaging (MRI) produces image intensities that have an arbitrary scale, hampering quantification. Intensity scaling aims to overcome this shortfall. As neurodegenerative and inflammatory disorders may affect all brain compartments, reference regions within the brain may be misleading. Here we summarize approaches for intensity scaling of conventional T1-weighted (w) and T2w brain MRI avoiding reference regions within the brain. METHODS Literature was searched in the databases of Scopus, PubMed, and Web of Science. We included only studies that avoided reference regions within the brain for intensity scaling and provided validating evidence, which we divided into four categories: 1) comparative variance reduction, 2) comparative correlation with clinical parameters, 3) relation to quantitative imaging, or 4) relation to histology. RESULTS Of the 3825 studies screened, 24 fulfilled the inclusion criteria. Three studies used scaled T1w images, 2 scaled T2w images, and 21 T1w/T2w-ratio calculation (with double counts). A robust reduction in variance was reported. Twenty studies investigated the relation of scaled intensities to different types of quantitative imaging. Statistically significant correlations with clinical or demographic data were reported in 8 studies. Four studies reporting the relation to histology gave no clear picture of the main signal driver of conventional T1w and T2w MRI sequences. CONCLUSIONS T1w/T2w-ratio calculation was applied most often. Variance reduction and correlations with other measures suggest a biologically meaningful signal harmonization. However, there are open methodological questions and uncertainty on its biological underpinning. Validation evidence on other scaling methods is even sparser.
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Affiliation(s)
- Tun Wiltgen
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Cuici Voon
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Koen Van Leemput
- Department of Neuroscience and Biomedical Engineering, Aalto University Helsinki, Espoo, Finland
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Benedikt Wiestler
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Mark Mühlau
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
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4
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Syed Nasser N, Venugopal VK, Veenstra C, Johansson P, Rajan S, Mahajan K, Naik S, Masand R, Yadav P, Khanduri S, Singhal S, Bhargava R, Kabra U, Gupta S, Saggar K, Varaprasad B, Aggrawal K, Rao A, K S M, Dakhole A, Kelkar A, Benjamin G, Sodani V, Goyal P, Mahajan H. Age-stratified Assessment of Brain Volumetric Segmentation on the Indian Population Using Quantitative Magnetic Resonance Imaging. Clin Neuroradiol 2024:10.1007/s00062-023-01374-z. [PMID: 38253891 DOI: 10.1007/s00062-023-01374-z] [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: 05/06/2023] [Accepted: 12/16/2023] [Indexed: 01/24/2024]
Abstract
BACKGROUND AND PURPOSE Automated methods for quantifying brain tissue volumes have gained clinical interest for their objective assessment of neurological diseases. This study aimed to establish reference curves for brain volumes and fractions in the Indian population using Synthetic MRI (SyMRI), a quantitative imaging technique providing multiple contrast-weighted images through fast postprocessing. METHODS The study included a cohort of 314 healthy individuals aged 15-65 years from multiple hospitals/centers across India. The SyMRI-quantified brain volumes and fractions, including brain parenchymal fraction (BPF), gray matter fraction (GMF), white matter fraction (WMF), and myelin. RESULTS Normative age-stratified quantification curves were created based on the obtained data. The results showed significant differences in brain volumes between the sexes, but not after normalization by intracranial volume. CONCLUSION The findings provide normative data for the Indian population and can be used for comparative analysis of brain structure values. Furthermore, our data indicate that the use of fractions rather than absolute volumes in normative curves, such as BPF, GMF, and WMF, can mitigate sex and population differences as they account for individual differences in head size or brain volume.
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Affiliation(s)
| | | | | | | | | | | | - Swati Naik
- Batra Hospital & Medical Research Centre, New Delhi, India
| | | | - Pratiksha Yadav
- Dr. D. Y. Patil Medical College, Hospital and Research Centre, Pune, India
| | | | | | | | | | | | - Kavita Saggar
- Dayanand Medical College & Hospital, Ludhiana, India
| | | | | | | | - Manoj K S
- Metro Scans and Laboratory, Thiruvananthapuram, India
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Mueller SG. Mapping internal brainstem structures using T1 and T2 weighted 3T images. FRONTIERS IN NEUROIMAGING 2023; 2:1324107. [PMID: 38161488 PMCID: PMC10755028 DOI: 10.3389/fnimg.2023.1324107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 11/17/2023] [Indexed: 01/03/2024]
Abstract
Background Many neurodegenerative diseases affect the brainstem and often do so in an early stage. The overall goal of this project was (a) to develop a method to segment internal brainstem structures from T1 and T2 weighted sequences by taking advantage of the superior myelin contrast of the T1/T2 ratio image (RATIO) and (b) to test if this approach provides biological meaningful information by investigating the effects of aging on different brainstem gray matter structures. Methods 675 T1 and T2 weighted images were obtained from the Human Connectome Project Aging. The intensities of the T1 and T2 images were re-scaled and RATIO images calculated. The brainstem was isolated and k-means clustering used to identify five intensity clusters. Non-linear diffeomorphic mapping was used to warp the five intensity clusters in subject space into a common space to generate probabilistic group averages/priors that were used to inform the final probabilistic segmentations at the single subject level. The five clusters corresponded to five brainstem tissue types (two gray matters, two mixed gray/white, and 1 csf/tissue partial volume). Results These cluster maps were used to calculate Jacobian determinant maps and the mean Jacobians of 48 brainstem gray matter structures extracted. Significant linear or quadratic age effects were found for all but five structures. Conclusions These findings suggest that it is possible to obtain a biologically meaningful segmentation of internal brainstem structures from T1 and T2 weighted sequences using a fully automated segmentation procedure.
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Affiliation(s)
- Susanne G. Mueller
- Department of Radiology, University of California, San Francisco, San Francisco, CA, United States
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6
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Yamashita K, Yoneyama M, Kikuchi K, Wada T, Murazaki H, Watanuki H, Mikayama R, Ishigami K, Togao O. Reproducibility of quantitative ADC, T1, and T2 measurement on the cerebral cortex: Utility of whole brain echo-planar DWI with compressed SENSE (EPICS-DWI): A pilot study. Eur J Radiol Open 2023; 11:100516. [PMID: 37609044 PMCID: PMC10440392 DOI: 10.1016/j.ejro.2023.100516] [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: 04/24/2023] [Revised: 07/30/2023] [Accepted: 08/08/2023] [Indexed: 08/24/2023] Open
Abstract
Purpose To assess the reproducibility of ADC, T1, T2, and proton density (PD) measurements on the cortex across the entire brain using high-resolution pseudo-3D diffusion-weighted imaging using echo-planar imaging with compressed SENSE (EPICS-DWI) and 3D quantification with an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) in normal healthy adults. Methods Twelve healthy participants (median age, 33 years; range, 28-51 years) were recruited to evaluate the reproducibility of whole-brain EPICS-DWI and synthetic MRI. EPICS-DWI utilizes a compressed SENSE reconstruction framework while maintaining the EPI sampling pattern. The 3D-QALAS sequence is based on multi-acquisition 3D gradient echo, with five acquisitions equally spaced in time, interleaved with a T2 preparation pulse and an inversion pulse. EPICS-DWI (b values, 0 and 1000 s/mm2) and 3D-QALAS sequence with identical voxel size on a 3.0-T MR system were performed twice (for test-retest scan). Intraclass correlation coefficients (ICCs) for ADC, T1, T2, and PD for all parcellated volume of interest (VOI) per subject on scan-rescan tests were calculated to assess reproducibility. Bland-Altman plots were used to investigate discrepancies in ADCs, T1s, T2s, and PDs obtained from the two MR scans. Results The ICC of ADCs was 0.785, indicating "good" reproducibility. The ICCs of T1s, T2s, and PDs were 0.986, 0.978, and 0.968, indicating "excellent" reproducibility. Conclusion The combination of EPICS-DWI and 3D-QALAS sequences with identical voxel size could reproducible ADC, T1, T2, and PD measurements for the cortex across the entire brain in healthy adults.
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Affiliation(s)
- Koji Yamashita
- Departments of Radiology Informatics and Network, Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Masami Yoneyama
- Philips Japan, 13-37, Kohnan 2-chome, Minato-ku, Tokyo 108-8507, Japan
| | - Kazufumi Kikuchi
- Departments of Clinical Radiology, and Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Tatsuhiro Wada
- Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Japan
| | - Hiroo Murazaki
- Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Japan
| | - Hiroaki Watanuki
- Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Japan
| | - Ryoji Mikayama
- Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Japan
| | - Kousei Ishigami
- Departments of Clinical Radiology, and Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Osamu Togao
- Departments of Molecular Imaging and Diagnosis, Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
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7
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Boroshok AL, McDermott CL, Fotiadis P, Park AT, Tooley UA, Gataviņš MM, Tisdall MD, Bassett DS, Mackey AP. Individual differences in T1w/T2w ratio development during childhood. Dev Cogn Neurosci 2023; 62:101270. [PMID: 37348147 PMCID: PMC10439503 DOI: 10.1016/j.dcn.2023.101270] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/12/2023] [Accepted: 06/15/2023] [Indexed: 06/24/2023] Open
Abstract
Myelination is a key developmental process that promotes rapid and efficient information transfer. Myelin also stabilizes existing brain networks and thus may constrain neuroplasticity, defined here as the brain's potential to change in response to experiences rather than the canonical definition as the process of change. Characterizing individual differences in neuroplasticity may shed light on mechanisms by which early experiences shape learning, brain and body development, and response to interventions. The T1-weighted/T2-weighted (T1w/T2w) MRI signal ratio is a proxy measure of cortical microstructure and thus neuroplasticity. Here, in pre-registered analyses, we investigated individual differences in T1w/T2w ratios in children (ages 4-10, n = 157). T1w/T2w ratios were positively associated with age within early-developing sensorimotor and attention regions. We also tested whether socioeconomic status, cognition (crystallized knowledge or fluid reasoning), and biological age (as measured with molar eruption) were related to T1w/T2w signal but found no significant effects. Associations among T1w/T2w ratios, early experiences, and cognition may emerge later in adolescence and may not be strong enough to detect in moderate sample sizes.
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Affiliation(s)
- Austin L Boroshok
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
| | | | - Panagiotis Fotiadis
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Anne T Park
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ursula A Tooley
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, Washington University in St. Louis, USA; Department of Neurology, Washington University in St. Louis, USA
| | - Mārtiņš M Gataviņš
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - M Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Electrical & Systems Engineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Physics & Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Santa Fe Institute, Santa Fe, NM, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
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8
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Rocca MA, Margoni M, Battaglini M, Eshaghi A, Iliff J, Pagani E, Preziosa P, Storelli L, Taoka T, Valsasina P, Filippi M. Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice. Radiology 2023; 307:e221512. [PMID: 37278626 PMCID: PMC10315528 DOI: 10.1148/radiol.221512] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 11/28/2022] [Accepted: 01/17/2023] [Indexed: 06/07/2023]
Abstract
MRI plays a central role in the diagnosis of multiple sclerosis (MS) and in the monitoring of disease course and treatment response. Advanced MRI techniques have shed light on MS biology and facilitated the search for neuroimaging markers that may be applicable in clinical practice. MRI has led to improvements in the accuracy of MS diagnosis and a deeper understanding of disease progression. This has also resulted in a plethora of potential MRI markers, the importance and validity of which remain to be proven. Here, five recent emerging perspectives arising from the use of MRI in MS, from pathophysiology to clinical application, will be discussed. These are the feasibility of noninvasive MRI-based approaches to measure glymphatic function and its impairment; T1-weighted to T2-weighted intensity ratio to quantify myelin content; classification of MS phenotypes based on their MRI features rather than on their clinical features; clinical relevance of gray matter atrophy versus white matter atrophy; and time-varying versus static resting-state functional connectivity in evaluating brain functional organization. These topics are critically discussed, which may guide future applications in the field.
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Affiliation(s)
- Maria Assunta Rocca
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Monica Margoni
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Marco Battaglini
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Arman Eshaghi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Jeffrey Iliff
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paolo Preziosa
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Loredana Storelli
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Toshiaki Taoka
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paola Valsasina
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
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9
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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: 0] [Impact Index Per Article: 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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10
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Kilpatrick L, Zhang K, Dong T, Gee G, Beltran-Sanchez H, Wang M, Labus J, Naliboff B, Mayer E, Gupta A. Mediating role of obesity on the association between disadvantaged neighborhoods and intracortical myelination. RESEARCH SQUARE 2023:rs.3.rs-2592087. [PMID: 36993600 PMCID: PMC10055549 DOI: 10.21203/rs.3.rs-2592087/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
We investigated the relationship between neighborhood disadvantage (area deprivation index [ADI]) and intracortical myelination (T1-weighted/T2-weighted ratio at deep to superficial cortical levels), and the potential mediating role of the body mass index (BMI) and perceived stress in 92 adults. Worse ADI was correlated with increased BMI and perceived stress (p's<.05). Non-rotated partial least squares analysis revealed associations between worse ADI and decreased myelination in middle/deep cortex in supramarginal, temporal, and primary motor regions and increased myelination in superficial cortex in medial prefrontal and cingulate regions (p<.001); thus, neighborhood disadvantage may influence the flexibility of information processing involved in reward, emotion regulation, and cognition. Structural equation modelling revealed increased BMI as partially mediating the relationship between worse ADI and observed myelination increases (p=.02). Further, trans-fatty acid intake was correlated with observed myelination increases (p=.03), suggesting the importance of dietary quality. These data further suggest ramifications of neighborhood disadvantage on brain health.
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Affiliation(s)
| | | | - Tien Dong
- University of California Los Angeles
| | | | | | - May Wang
- University of California Los Angeles
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11
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Bero J, Li Y, Kumar A, Humphries C, Nag S, Lee H, Ahn WY, Hahn S, Constable RT, Kim H, Lee D. Coordinated anatomical and functional variability in the human brain during adolescence. Hum Brain Mapp 2023; 44:1767-1778. [PMID: 36479851 PMCID: PMC9921246 DOI: 10.1002/hbm.26173] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 10/26/2022] [Accepted: 11/25/2022] [Indexed: 12/13/2022] Open
Abstract
Adolescence represents a time of unparalleled brain development. In particular, developmental changes in morphometric and cytoarchitectural features are accompanied by maturation in the functional connectivity (FC). Here, we examined how three facets of the brain, including myelination, cortical thickness (CT), and resting-state FC, interact in children between the ages of 10 and 15. We investigated the pattern of coordination in these measures by computing correlation matrices for each measure as well as meta-correlations among them both at the regional and network levels. The results revealed consistently higher meta-correlations among myelin, CT, and FC in the sensory-motor cortical areas than in the association cortical areas. We also found that these meta-correlations were stable and little affected by age-related changes in each measure. In addition, regional variations in the meta-correlations were consistent with the previously identified gradient in the FC and therefore reflected the hierarchy of cortical information processing, and this relationship persists in the adult brain. These results demonstrate that heterogeneity in FC among multiple cortical areas are closely coordinated with the development of cortical myelination and thickness during adolescence.
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Affiliation(s)
- John Bero
- Neurogazer, Inc.BaltimoreMarylandUSA
| | - Yang Li
- Neurogazer, Inc.BaltimoreMarylandUSA
| | | | | | | | | | - Woo Young Ahn
- Department of PsychologySeoul National UniversitySeoulKorea
| | - Sowon Hahn
- Department of PsychologySeoul National UniversitySeoulKorea
| | - Robert Todd Constable
- Department of Diagnostic Radiology and NeurosurgeryYale School of MedicineNew HavenConnecticutUSA
| | - Hackjin Kim
- Department of PsychologyKorea UniversitySeoulKorea
| | - Daeyeol Lee
- Neurogazer, Inc.BaltimoreMarylandUSA
- The Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreMarylandUSA
- Department of NeuroscienceJohns Hopkins UniversityBaltimoreMarylandUSA
- Department of Psychological and Brain SciencesJohns Hopkins UniversityBaltimoreMarylandUSA
- Kavli Neuroscience Discovery Institute, Johns Hopkins UniversityBaltimoreMarylandUSA
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12
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Deantoni M, Baillet M, Hammad G, Berthomier C, Reyt M, Jaspar M, Meyer C, Van Egroo M, Talwar P, Lambot E, Chellappa SL, Degueldre C, Luxen A, Salmon E, Balteau E, Phillips C, Dijk DJ, Vandewalle G, Collette F, Maquet P, Muto V, Schmidt C. Association between sleep slow-wave activity and in-vivo estimates of myelin in healthy young men. Neuroimage 2023; 272:120045. [PMID: 36997136 PMCID: PMC10112274 DOI: 10.1016/j.neuroimage.2023.120045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 01/18/2023] [Accepted: 03/17/2023] [Indexed: 03/31/2023] Open
Abstract
Sleep has been suggested to contribute to myelinogenesis and associated structural changes in the brain. As a principal hallmark of sleep, slow-wave activity (SWA) is homeostatically regulated but also differs between individuals. Besides its homeostatic function, SWA topography is suggested to reflect processes of brain maturation. Here, we assessed whether interindividual differences in sleep SWA and its homeostatic response to sleep manipulations are associated with in-vivo myelin estimates in a sample of healthy young men. Two hundred twenty-six participants (18-31 y.) underwent an in-lab protocol in which SWA was assessed at baseline (BAS), after sleep deprivation (high homeostatic sleep pressure, HSP) and after sleep saturation (low homeostatic sleep pressure, LSP). Early-night frontal SWA, the frontal-occipital SWA ratio, as well as the overnight exponential SWA decay were computed over sleep conditions. Semi-quantitative magnetization transfer saturation maps (MTsat), providing markers for myelin content, were acquired during a separate laboratory visit. Early-night frontal SWA was negatively associated with regionally decreased myelin estimates in the temporal portion of the inferior longitudinal fasciculus. By contrast, neither the responsiveness of SWA to sleep saturation or deprivation, its overnight dynamics, nor the frontal/occipital SWA ratio were associated with brain structural indices. Our results indicate that frontal SWA generation tracks inter-individual differences in continued structural brain re-organization during early adulthood. This stage of life is not only characterized by ongoing region-specific changes in myelin content, but also by a sharp decrease and a shift towards frontal predominance in SWA generation.
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Affiliation(s)
| | | | | | | | - Mathilde Reyt
- GIGA-CRC in Vivo Imaging, University of Liège, Belgium; Psychology and Neurosciences of Cognition (PsyNCog), Faculty of Psychology, Logopedics and Educational Sciences University of Liège, Belgium
| | - Mathieu Jaspar
- ARCH, Faculty of Psychology, Logopedics and Educational Sciences, University of Liège, Belgium
| | | | - Maxime Van Egroo
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands
| | - Puneet Talwar
- GIGA-CRC in Vivo Imaging, University of Liège, Belgium
| | - Eric Lambot
- GIGA-CRC in Vivo Imaging, University of Liège, Belgium
| | - Sarah L Chellappa
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany
| | | | - André Luxen
- GIGA-CRC in Vivo Imaging, University of Liège, Belgium
| | - Eric Salmon
- GIGA-CRC in Vivo Imaging, University of Liège, Belgium
| | | | | | - Derk-Jan Dijk
- Sleep Research Centre, University of Surrey, Guildford, UK; UK Dementia Research Institute, Care Research & Technology Centre at Imperial College London and the University of Surrey, Guildford, UK
| | | | - Fabienne Collette
- GIGA-CRC in Vivo Imaging, University of Liège, Belgium; Psychology and Neurosciences of Cognition (PsyNCog), Faculty of Psychology, Logopedics and Educational Sciences University of Liège, Belgium
| | - Pierre Maquet
- GIGA-CRC in Vivo Imaging, University of Liège, Belgium; Department of Neurology, University Hospital (CHU) of Liège, Liège, Belgium
| | - Vincenzo Muto
- GIGA-CRC in Vivo Imaging, University of Liège, Belgium.
| | - Christina Schmidt
- GIGA-CRC in Vivo Imaging, University of Liège, Belgium; Psychology and Neurosciences of Cognition (PsyNCog), Faculty of Psychology, Logopedics and Educational Sciences University of Liège, Belgium.
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13
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A longitudinal microstructural MRI dataset in healthy C57Bl/6 mice at 9.4 Tesla. Sci Data 2023; 10:94. [PMID: 36788251 PMCID: PMC9929084 DOI: 10.1038/s41597-023-01942-5] [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: 07/07/2022] [Accepted: 01/06/2023] [Indexed: 02/16/2023] Open
Abstract
Multimodal microstructural MRI has shown increased sensitivity and specificity to changes in various brain disease and injury models in the preclinical setting. Here, we present an in vivo longitudinal dataset, including a subset of ex vivo data, acquired as control data and to investigate microstructural changes in the healthy mouse brain. The dataset consists of structural T2-weighted imaging, magnetization transfer ratio and saturation imaging, and advanced quantitative diffusion MRI (dMRI) methods. The dMRI methods include oscillating gradient spin echo (OGSE) dMRI and microscopic anisotropy (μA) dMRI, which provide additional insight by increasing sensitivity to smaller spatial scales and disentangling fiber orientation dispersion from true microstructural changes, respectively. The technical skills required to analyze microstructural MRI data are complex and include MRI sequence development, acquisition, and computational neuroimaging expertise. Here, we share unprocessed and preprocessed data, and scalar maps of quantitative MRI metrics. We envision utility of this dataset in the microstructural MRI field to develop and test biophysical models, methods that model temporal brain dynamics, and registration and preprocessing pipelines.
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14
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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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15
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Oishi H, Takemura H, Amano K. Macromolecular tissue volume mapping of lateral geniculate nucleus subdivisions in living human brains. Neuroimage 2023; 265:119777. [PMID: 36462730 DOI: 10.1016/j.neuroimage.2022.119777] [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: 03/08/2022] [Revised: 11/26/2022] [Accepted: 11/29/2022] [Indexed: 12/03/2022] Open
Abstract
The lateral geniculate nucleus (LGN) is a key thalamic nucleus in the visual system, which has an important function in relaying retinal visual input to the visual cortex. The human LGN is composed mainly of magnocellular (M) and parvocellular (P) subdivisions, each of which has different stimulus selectivity in neural response properties. Previous studies have discussed the potential relationship between LGN subdivisions and visual disorders based on psychophysical data on specific types of visual stimuli. However, these relationships remain speculative because non-invasive measurements of these subdivisions are difficult due to the small size of the LGN. Here we propose a method to identify these subdivisions by combining two structural MR measures: high-resolution proton-density weighted images and macromolecular tissue volume (MTV) maps. We defined the M and P subdivisions based on MTV fraction data and tested the validity of the definition by (1) comparing the data with that from human histological studies, (2) comparing the data with functional magnetic resonance imaging measurements on stimulus selectivity, and (3) analyzing the test-retest reliability. The findings demonstrated that the spatial organization of the M and P subdivisions was consistent across subjects and in line with LGN subdivisions observed in human histological data. Moreover, the difference in stimulus selectivity between the subdivisions identified using MTV was consistent with previous physiology literature. The definition of the subdivisions based on MTV was shown to be robust over measurements taken on different days. These results suggest that MTV mapping is a promising approach for evaluating the tissue properties of LGN subdivisions in living humans. This method potentially will enable neuroscientific and clinical hypotheses about the human LGN subdivisions to be tested.
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Affiliation(s)
- Hiroki Oishi
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita 565-0871, Japan; Department of Psychology, University of California, Berkeley, Berkeley, CA 94704, United States.
| | - Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita 565-0871, Japan; Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki 444-8585, Japan; Department of Physiological Sciences, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Hayama 240-0193, Japan.
| | - Kaoru Amano
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita 565-0871, Japan; Graduate School of Information Science and Technology, The University of Tokyo, Tokyo 113-8656, Japan
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16
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Mendelsohn Z, Pemberton HG, Gray J, Goodkin O, Carrasco FP, Scheel M, Nawabi J, Barkhof F. Commercial volumetric MRI reporting tools in multiple sclerosis: a systematic review of the evidence. Neuroradiology 2023; 65:5-24. [PMID: 36331588 PMCID: PMC9816195 DOI: 10.1007/s00234-022-03074-w] [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: 06/13/2022] [Accepted: 09/29/2022] [Indexed: 11/06/2022]
Abstract
PURPOSE MRI is integral to the diagnosis of multiple sclerosis (MS) and is important for clinical prognostication. Quantitative volumetric reporting tools (QReports) can improve the accuracy and objectivity of MRI-based assessments. Several QReports are commercially available; however, validation can be difficult to establish and does not currently follow a common pathway. To aid evidence-based clinical decision-making, we performed a systematic review of commercial QReports for use in MS including technical details and published reports of validation and in-use evaluation. METHODS We categorized studies into three types of testing: technical validation, for example, comparison to manual segmentation, clinical validation by clinicians or interpretation of results alongside clinician-rated variables, and in-use evaluation, such as health economic assessment. RESULTS We identified 10 companies, which provide MS lesion and brain segmentation and volume quantification, and 38 relevant publications. Tools received regulatory approval between 2006 and 2020, contextualize results to normative reference populations, ranging from 620 to 8000 subjects, and require T1- and T2-FLAIR-weighted input sequences for longitudinal assessment of whole-brain volume and lesions. In MS, six QReports provided evidence of technical validation, four companies have conducted clinical validation by correlating results with clinical variables, only one has tested their QReport by clinician end-users, and one has performed a simulated in-use socioeconomic evaluation. CONCLUSION We conclude that there is limited evidence in the literature regarding clinical validation and in-use evaluation of commercial MS QReports with a particular lack of clinician end-user testing. Our systematic review provides clinicians and institutions with the available evidence when considering adopting a quantitative reporting tool for MS.
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Affiliation(s)
- Zoe Mendelsohn
- grid.83440.3b0000000121901201Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK ,grid.83440.3b0000000121901201Department of Medical Physics and Bioengineering, Centre for Medical Image Computing (CMIC), University College London, London, UK ,grid.83440.3b0000000121901201Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Institute of Neurology, University College London, London, UK ,grid.6363.00000 0001 2218 4662Department of Neuroradiology, Charité School of Medicine and University Hospital Berlin, Berlin, Germany ,grid.6363.00000 0001 2218 4662Department of Radiology, Charité School of Medicine and University Hospital Berlin, Berlin, Germany
| | - Hugh G. Pemberton
- grid.83440.3b0000000121901201Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK ,grid.83440.3b0000000121901201Department of Medical Physics and Bioengineering, Centre for Medical Image Computing (CMIC), University College London, London, UK ,grid.420685.d0000 0001 1940 6527GE Healthcare, Amersham, UK
| | - James Gray
- grid.416626.10000 0004 0391 2793Stepping Hill Hospital, NHS Foundation Trust, Stockport, UK
| | - Olivia Goodkin
- grid.83440.3b0000000121901201Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK ,grid.83440.3b0000000121901201Department of Medical Physics and Bioengineering, Centre for Medical Image Computing (CMIC), University College London, London, UK ,grid.83440.3b0000000121901201Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Institute of Neurology, University College London, London, UK
| | - Ferran Prados Carrasco
- grid.83440.3b0000000121901201Department of Medical Physics and Bioengineering, Centre for Medical Image Computing (CMIC), University College London, London, UK ,grid.83440.3b0000000121901201Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Institute of Neurology, University College London, London, UK ,grid.36083.3e0000 0001 2171 6620E-Health Centre, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Michael Scheel
- grid.6363.00000 0001 2218 4662Department of Neuroradiology, Charité School of Medicine and University Hospital Berlin, Berlin, Germany
| | - Jawed Nawabi
- grid.6363.00000 0001 2218 4662Department of Radiology, Charité School of Medicine and University Hospital Berlin, Berlin, Germany ,grid.484013.a0000 0004 6879 971XBerlin Institute of Health at Charité – Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Berlin, Germany
| | - Frederik Barkhof
- grid.83440.3b0000000121901201Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK ,grid.83440.3b0000000121901201Department of Medical Physics and Bioengineering, Centre for Medical Image Computing (CMIC), University College London, London, UK ,grid.83440.3b0000000121901201Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Institute of Neurology, University College London, London, UK ,grid.12380.380000 0004 1754 9227Radiology & Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, The Netherlands
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17
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Fernandez-Alvarez M, Atienza M, Cantero JL. Effects of non-modifiable risk factors of Alzheimer's disease on intracortical myelin content. Alzheimers Res Ther 2022; 14:202. [PMID: 36587227 PMCID: PMC9805254 DOI: 10.1186/s13195-022-01152-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 12/25/2022] [Indexed: 01/01/2023]
Abstract
BACKGROUND Non-modifiable risk factors of Alzheimer's disease (AD) have lifelong effects on cortical integrity that could be mitigated if identified at early stages. However, it remains unknown whether cortical microstructure is affected in older individuals with non-modifiable AD risk factors and whether altered cortical tissue integrity produces abnormalities in brain functional networks in this AD-risk population. METHODS Using relative T1w/T2w (rT1w/T2w) ratio maps, we have compared tissue integrity of normal-appearing cortical GM between controls and cognitively normal older adults with either APOE4 (N = 50), with a first-degree family history (FH) of AD (N = 52), or with the co-occurrence of both AD risk factors (APOE4+FH) (N = 35). Additionally, individuals with only one risk factor (APOE4 or FH) were combined into one group (N = 102) and compared with controls. The same number of controls matched in age, sex, and years of education was employed for each of these comparisons. Group differences in resting state functional connectivity (rs-FC) patterns were also investigated, using as FC seeds those cortical regions showing significant changes in rT1w/T2w ratios. RESULTS Overall, individuals with non-modifiable AD risk factors exhibited significant variations in rT1w/T2w ratios compared to controls, being APOE4 and APOE4+FH at opposite ends of a continuum. The co-occurrence of APOE4 and FH was further accompanied by altered patterns of rs-FC. CONCLUSIONS These findings may have practical implications for early detection of cortical abnormalities in older populations with APOE4 and/or FH of AD and open new avenues to monitor changes in cortical tissue integrity associated with non-modifiable AD risk factors.
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Affiliation(s)
- Marina Fernandez-Alvarez
- grid.15449.3d0000 0001 2200 2355Laboratory of Functional Neuroscience, Pablo de Olavide University, Ctra. de Utrera Km 1, 41013 Seville, Spain ,grid.418264.d0000 0004 1762 4012CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, Madrid, Spain
| | - Mercedes Atienza
- grid.15449.3d0000 0001 2200 2355Laboratory of Functional Neuroscience, Pablo de Olavide University, Ctra. de Utrera Km 1, 41013 Seville, Spain ,grid.418264.d0000 0004 1762 4012CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, Madrid, Spain
| | - Jose L. Cantero
- grid.15449.3d0000 0001 2200 2355Laboratory of Functional Neuroscience, Pablo de Olavide University, Ctra. de Utrera Km 1, 41013 Seville, Spain ,grid.418264.d0000 0004 1762 4012CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, Madrid, Spain
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18
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Berman S, Drori E, Mezer AA. Spatial profiles provide sensitive MRI measures of the midbrain micro- and macrostructure. Neuroimage 2022; 264:119660. [PMID: 36220534 DOI: 10.1016/j.neuroimage.2022.119660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 09/15/2022] [Accepted: 09/30/2022] [Indexed: 11/09/2022] Open
Abstract
The midbrain is the rostral-most part of the brainstem. It contains numerous nuclei and white matter tracts, which are involved in motor, auditory and visual processing, and changes in their structure and function have been associated with aging, as well as neurodegenerative disorders. Current tools for estimating midbrain subregions and their structure with MRI require high resolution and multi-parametric quantitative MRI measures. We propose an approach that relies on morphology to calculate profiles along the midbrain and show these profiles are sensitive to the underlying macrostructure of the midbrain. First, we show that the midbrain structure can be sampled, within subject space, along three main axes of the left and right midbrain, producing profiles that are similar across subjects. We use two data sets with different field strengths, that contain R1, R2* and QSM maps and show that the profiles are highly correlated both across subjects and between datasets. Next, we compare profiles of the midbrain that sample ROIs, and show that the profiles along the first two axes sample the midbrain in a way that reliably separates the main structures, i.e., the substantia nigra, the red nucleus, and periaqueductal gray. We further show that age differences which are localized to specific nuclei, are reflected in the profiles. Finally, we generalize the same approach to calculate midbrain profiles on a third clinically relevant dataset using HCP subjects, with metrics such as the diffusion tensor and semi-quantitative data such as T1w/T2w maps. Our results suggest that midbrain profiles, both of quantitative and semi-quantitative estimates are sensitive to the underlying macrostructure of the midbrain. The midbrain profiles are calculated in native space, and rely on simple measurements. We show that it is robust and can be easily expanded to different datasets, and as such we hope that it will be of great use to the community and to the study of the midbrain in particular.
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Affiliation(s)
- Shai Berman
- The Edmond and Lily Safra Center for Brain Science, the Hebrew University of Jerusalem, Israel; Mortimer B. Zuckerman Mind, Brain, Behavior Institute, Columbia University, New York, NY, United States.
| | - Elior Drori
- The Edmond and Lily Safra Center for Brain Science, the Hebrew University of Jerusalem, Israel
| | - Aviv A Mezer
- The Edmond and Lily Safra Center for Brain Science, the Hebrew University of Jerusalem, Israel
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19
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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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20
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Sui YV, Masurkar AV, Rusinek H, Reisberg B, Lazar M. Cortical myelin profile variations in healthy aging brain: A T1w/T2w ratio study. Neuroimage 2022; 264:119743. [PMID: 36368498 PMCID: PMC9904172 DOI: 10.1016/j.neuroimage.2022.119743] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 10/31/2022] [Accepted: 11/07/2022] [Indexed: 11/09/2022] Open
Abstract
Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.
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Affiliation(s)
- Yu Veronica Sui
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA,Corresponding author. (Y.V. Sui)
| | - Arjun V. Masurkar
- Department of Neurology, Center for Cognitive Neurology, NYU Grossman School of Medicine, New York, NY, USA,Department of Neuroscience and Physiology, NYU Grossman School of Medicine, New York, NY, USA,Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA
| | - Henry Rusinek
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA,Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Barry Reisberg
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Mariana Lazar
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA
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21
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Cappelle S, Pareto D, Sunaert S, Smets I, Laenen A, Dubois B, Demaerel P. T1w/FLAIR ratio standardization as a myelin marker in MS patients. Neuroimage Clin 2022; 36:103248. [PMID: 36451354 PMCID: PMC9668645 DOI: 10.1016/j.nicl.2022.103248] [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: 03/30/2022] [Revised: 10/20/2022] [Accepted: 10/23/2022] [Indexed: 11/06/2022]
Abstract
INTRODUCTION Calculation of a T1w/T2w ratio was introduced as a proxy for myelin integrity in the brain of multiple sclerosis (MS) patients. Since nowadays 3D FLAIR is commonly used for lesion detection instead of T2w images, we introduce a T1w/FLAIR ratio as an alternative for the T1w/T2w ratio. OBJECTIVES Bias and intensity variation are widely present between different scanners, between subjects and within subjects over time in T1w, T2w and FLAIR images. We present a standardized method for calculating a histogram calibrated T1w/FLAIR ratio to reduce bias and intensity variation in MR sequences from different scanners and at different time-points. MATERIAL AND METHODS 207 Relapsing Remitting MS patients were scanned on 4 different 3 T scanners with a protocol including 3D T1w, 2D T2w and 3D FLAIR images. After bias correction, T1w/FLAIR ratio maps and T1w/T2w ratio maps were calculated in 4 different ways: without calibration, with linear histogram calibration as described by Ganzetti et al. (2014), and by using 2 methods of non-linear histogram calibration. The first nonlinear calibration uses a template of extra-cerebral tissue and cerebrospinal fluid (CSF) brought from Montreal Neurological Institute (MNI) space to subject space; for the second nonlinear method we used an extra-cerebral tissue and CSF template of our own subjects. Additionally, we segmented several brain structures such as Normal Appearing White Matter (NAWM), Normal Appearing Grey Matter (NAGM), corpus callosum, thalami and MS lesions using Freesurfer and Samseg. RESULTS The coefficient of variation of T1w/FLAIR ratio in NAWM for the no calibrated, linear, and 2 nonlinear calibration methods were respectively 24, 19.1, 9.5, 13.8. The nonlinear methods of calibration showed the best results for calculating the T1w/FLAIR ratio with a smaller dispersion of the data and a smaller overlap of T1w/FLAIR ratio in the different segmented brain structures. T1w/T2w and T1w/FLAIR ratios showed a wider range of values compared to MTR values. CONCLUSIONS Calibration of T1w/T2w and T1w/FLAIR ratio maps is imperative to account for the sources of variation described above. The nonlinear calibration methods showed the best reduction of between-subject and within-subject variability. The T1w/T2w and T1w/FLAIR ratio seem to be more sensitive to smaller changes in tissue integrity than MTR. Future work is needed to determine the exact substrate of T1w/FLAIR ratio and to obtain correlations with clinical outcome.
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Affiliation(s)
- S. Cappelle
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium,Corresponding author
| | - D. Pareto
- Department of Radiology (IDI), Vall d’Hebron University Hospital, Barcelona, Spain
| | - S. Sunaert
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium,Department of Imaging & Pathology, Translational MRI, KU Leuven, Leuven, Belgium
| | - I. Smets
- Laboratory for Neuroimmunology, KU Leuven, Leuven, Belgium,Department of Neurology, Erasmus MC, Rotterdam, The Netherlands
| | - A. Laenen
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics, KU Leuven and Hasselt University, Leuven, Belgium
| | - B. Dubois
- Laboratory for Neuroimmunology, KU Leuven, Leuven, Belgium,Department of Neurology, University Hospitals Leuven, Leuven, Belgium
| | - Ph. Demaerel
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium,Department of Imaging & Pathology, Translational MRI, KU Leuven, Leuven, Belgium
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22
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Glasser MF, Coalson TS, Harms MP, Xu J, Baum GL, Autio JA, Auerbach EJ, Greve DN, Yacoub E, Van Essen DC, Bock NA, Hayashi T. Empirical transmit field bias correction of T1w/T2w myelin maps. Neuroimage 2022; 258:119360. [PMID: 35697132 PMCID: PMC9483036 DOI: 10.1016/j.neuroimage.2022.119360] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 06/01/2022] [Accepted: 06/04/2022] [Indexed: 12/30/2022] Open
Abstract
T1-weighted divided by T2-weighted (T1w/T2w) myelin maps were initially developed for neuroanatomical analyses such as identifying cortical areas, but they are increasingly used in statistical comparisons across individuals and groups with other variables of interest. Existing T1w/T2w myelin maps contain radiofrequency transmit field (B1+) biases, which may be correlated with these variables of interest, leading to potentially spurious results. Here we propose two empirical methods for correcting these transmit field biases using either explicit measures of the transmit field or alternatively a 'pseudo-transmit' approach that is highly correlated with the transmit field at 3T. We find that the resulting corrected T1w/T2w myelin maps are both better neuroanatomical measures (e.g., for use in cross-species comparisons), and more appropriate for statistical comparisons of relative T1w/T2w differences across individuals and groups (e.g., sex, age, or body-mass-index) within a consistently acquired study at 3T. We recommend that investigators who use the T1w/T2w approach for mapping cortical myelin use these B1+ transmit field corrected myelin maps going forward.
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Affiliation(s)
| | | | - Michael P Harms
- Psychiatry, Washington University Medical School, St. Louis, MO, United States
| | - Junqian Xu
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States; Departments of Radiology and Psychiatry, Baylor College of Medicine, Houston, TX, United States
| | - Graham L Baum
- Department of Psychology, Harvard University, Cambridge, MA, United States
| | - Joonas A Autio
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Edward J Auerbach
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Douglas N Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | | | - Nicholas A Bock
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - Takuya Hayashi
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
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23
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Ladopoulos T, Matusche B, Bellenberg B, Heuser F, Gold R, Lukas C, Schneider R. Relaxometry and brain myelin quantification with synthetic MRI in MS subtypes and their associations with spinal cord atrophy. Neuroimage Clin 2022; 36:103166. [PMID: 36081258 PMCID: PMC9463599 DOI: 10.1016/j.nicl.2022.103166] [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: 03/31/2022] [Revised: 07/31/2022] [Accepted: 08/22/2022] [Indexed: 01/18/2023]
Abstract
Immune-mediated demyelination and neurodegeneration are pathophysiological hallmarks of Multiple Sclerosis (MS) and main drivers of disease related disability. The principal method for evaluating qualitatively demyelinating events in the clinical context is contrast-weighted magnetic resonance imaging (MRI). Moreover, advanced MRI sequences provide reliable quantification of brain myelin offering new opportunities to study tissue pathology in vivo. Towards neurodegenerative aspects of the disease, spinal cord atrophy - besides brain atrophy - is a powerful and validated predictor of disease progression. The etiology of spinal cord volume loss is still a matter of research, as it remains unclear whether the impact of local lesion pathology or the interaction with supra- and infratentorial axonal degeneration and demyelination of the long descending and ascending fiber tracts are the determining factors. Quantitative synthetic MR using a multiecho acquisition of saturation recovery pulse sequence provides fast automatic brain tissue and myelin volumetry based on R1 and R2 relaxation rates and proton density quantification, making it a promising modality for application in the clinical routine. In this cross sectional study a total of 91 MS patients and 31 control subjects were included to investigate group differences of global and regional measures of brain myelin and relaxation rates, in different MS subtypes, using QRAPMASTER sequence and SyMRI postprocessing software. Furthermore, we examined associations between these quantitative brain parameters and spinal cord atrophy to draw conclusions about possible pathophysiological relationships. Intracranial myelin volume fraction of the global brain exhibited statistically significant differences between control subjects (10.4%) and MS patients (RRMS 9.4%, PMS 8.1%). In a LASSO regression analysis with total brain lesion load, intracranial myelin volume fraction and brain parenchymal fraction, the intracranial myelin volume fraction was the variable with the highest impact on spinal cord atrophy (standardized coefficient 4.52). Regional supratentorial MRI metrics showed altered average myelin volume fraction, R1, R2 and proton density in MS patients compared to controls most pronounced in PMS. Interestingly, quantitative MRI parameters in supratentorial regions showed strong associations with upper cord atrophy, suggesting an important role of brain diffuse demyelination on spinal cord pathology possibly in the context of global disease activity. R1, R2 or proton density of the thalamus, cerebellum and brainstem correlated with upper cervical cord atrophy, probably reflecting the direct functional connection between these brain structures and the spinal cord as well as the effects of retrograde and anterograde axonal degeneration. By using Synthetic MR-derived myelin volume fraction, we were able to effectively detect significant differences of myelination in relapsing and progressive MS subtypes. Total intracranial brain myelin volume fraction seemed to predict spinal cord volume loss better than brain atrophy or total lesion load. Furthermore, demyelination in highly myelinated supratentorial regions, as an indicator of diffuse disease activity, as well as alterations of relaxation parameters in adjacent infratentorial and midbrain areas were strongly associated with upper cervical cord atrophy.
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Affiliation(s)
- Theodoros Ladopoulos
- Department of Neurology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791 Bochum, Germany,Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791 Bochum, Germany,Corresponding authors at: St. Josef Hospital, Department of Neurology, Gudrunstr. 56, 44791 Bochum, Germany.
| | - Britta Matusche
- Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791 Bochum, Germany
| | - Barbara Bellenberg
- Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791 Bochum, Germany
| | - Florian Heuser
- Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791 Bochum, Germany
| | - Ralf Gold
- Department of Neurology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791 Bochum, Germany
| | - Carsten Lukas
- Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791 Bochum, Germany,Department of Diagnostic and Interventional Radiology and Nuclear Medicine, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791 Bochum, Germany
| | - Ruth Schneider
- Department of Neurology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791 Bochum, Germany,Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Gudrunstr. 56, 44791 Bochum, Germany
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24
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Hansen JY, Shafiei G, Vogel JW, Smart K, Bearden CE, Hoogman M, Franke B, van Rooij D, Buitelaar J, McDonald CR, Sisodiya SM, Schmaal L, Veltman DJ, van den Heuvel OA, Stein DJ, van Erp TGM, Ching CRK, Andreassen OA, Hajek T, Opel N, Modinos G, Aleman A, van der Werf Y, Jahanshad N, Thomopoulos SI, Thompson PM, Carson RE, Dagher A, Misic B. Local molecular and global connectomic contributions to cross-disorder cortical abnormalities. Nat Commun 2022; 13:4682. [PMID: 35948562 PMCID: PMC9365855 DOI: 10.1038/s41467-022-32420-y] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 07/28/2022] [Indexed: 12/21/2022] Open
Abstract
Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21,000 participants and N = 26,000 controls, collected using a harmonised processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find a relationship between molecular vulnerability and white-matter architecture that drives cortical disorder profiles. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, inferior temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local molecular attributes and global connectivity jointly shape cross-disorder cortical abnormalities.
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Affiliation(s)
- Justine Y Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Golia Shafiei
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Jacob W Vogel
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kelly Smart
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Carrie E Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Martine Hoogman
- Departments of Psychiatry and Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Barbara Franke
- Departments of Psychiatry and Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Daan van Rooij
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Jan Buitelaar
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Carrie R McDonald
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Odile A van den Heuvel
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Anatomy & Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, & Center for the Neurobiology of Leaning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, USA
| | - Christopher R K Ching
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Nils Opel
- Institute of Translational Psychiatry, University of Münster, Münster, Germany & Department of Psychiatry, Jena University Hospital/Friedrich-Schiller-University Jena, Jena, Germany
| | - Gemma Modinos
- Department of Psychosis Studies & MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - André Aleman
- Department of Biomedical Sciences of Cells and Systems, University of Groningen, Groningen, The Netherlands
| | - Ysbrand van der Werf
- Department of Anatomy & Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Neda Jahanshad
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Sophia I Thomopoulos
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Paul M Thompson
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Richard E Carson
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada.
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25
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Norbom LB, Hanson J, van der Meer D, Ferschmann L, Røysamb E, von Soest T, Andreassen OA, Agartz I, Westlye LT, Tamnes CK. Parental socioeconomic status is linked to cortical microstructure and language abilities in children and adolescents. Dev Cogn Neurosci 2022; 56:101132. [PMID: 35816931 PMCID: PMC9284438 DOI: 10.1016/j.dcn.2022.101132] [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: 01/31/2022] [Revised: 05/11/2022] [Accepted: 06/30/2022] [Indexed: 12/17/2022] Open
Abstract
Gradients in parental socioeconomic status (SES) are closely linked to important life outcomes in children and adolescents, such as cognitive abilities, school achievement, and mental health. Parental SES may also influence brain development, with several magnetic resonance imaging (MRI) studies reporting associations with youth brain morphometry. However, MRI signal intensity metrics have not been assessed, but could offer a microstructural correlate, thereby increasing our understanding of SES influences on neurobiology. We computed a parental SES score from family income, parental education and parental occupation, and assessed relations with cortical microstructure as measured by T1w/T2w ratio (n = 504, age = 3-21 years). We found negative age-stabile relations between parental SES and T1w/T2w ratio, indicating that youths from lower SES families have higher ratio in widespread frontal, temporal, medial parietal and occipital regions, possibly indicating a more developed cortex. Effect sizes were small, but larger than for conventional morphometric properties i.e. cortical surface area and thickness, which were not significantly associated with parental SES. Youths from lower SES families had poorer language related abilities, but microstructural differences did not mediate these relations. T1w/T2w ratio appears to be a sensitive imaging marker for further exploring the association between parental SES and child brain development.
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Affiliation(s)
- Linn B. Norbom
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway,NORMENT, Institute of Clinical Medicine, University of Oslo, Norway,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway,Norwegian Institute of Public Health, Norway,Correspondence to: P.O. box 1094 Blindern, 0317 Oslo, Norway.
| | - Jamie Hanson
- Learning Research and Development Center University of Pittsburgh, USA,Department of Psychology, University of Pittsburgh, USA,Norwegian Institute of Public Health, Norway
| | - Dennis van der Meer
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway,School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands,Norwegian Institute of Public Health, Norway
| | - Lia Ferschmann
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway,Norwegian Institute of Public Health, Norway
| | - Espen Røysamb
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway,Department of Psychology, University of Oslo, Norway,Norwegian Institute of Public Health, Norway
| | - Tilmann von Soest
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway,Norwegian Institute of Public Health, Norway
| | - Ole A. Andreassen
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway,NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway,Norwegian Institute of Public Health, Norway
| | - Ingrid Agartz
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway,K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway,Norwegian Institute of Public Health, Norway,Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Lars T. Westlye
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway,NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway,Department of Psychology, University of Oslo, Norway,Norwegian Institute of Public Health, Norway
| | - Christian K. Tamnes
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway,NORMENT, Institute of Clinical Medicine, University of Oslo, Norway,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway,Norwegian Institute of Public Health, Norway
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26
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Mahoney SO, Chowdhury NF, Ngo V, Imms P, Irimia A. Mild Traumatic Brain Injury Results in Significant and Lasting Cortical Demyelination. Front Neurol 2022; 13:854396. [PMID: 35812106 PMCID: PMC9262516 DOI: 10.3389/fneur.2022.854396] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 05/23/2022] [Indexed: 11/13/2022] Open
Abstract
Despite contributing to neurocognitive deficits, intracortical demyelination after traumatic brain injury (TBI) is understudied. This study uses magnetic resonance imaging (MRI) to map intracortical myelin and its change in healthy controls and after mild TBI (mTBI). Acute mTBI involves reductions in relative myelin content primarily in lateral occipital regions. Demyelination mapped ~6 months post-injury is significantly more severe than that observed in typical aging (p < 0.05), with temporal, cingulate, and insular regions losing more myelin (30%, 20%, and 16%, respectively) than most other areas, although occipital regions experience 22% less demyelination. Thus, occipital regions may be more susceptible to primary injury, whereas temporal, cingulate and insular regions may be more susceptible to later manifestations of injury sequelae. The spatial profiles of aging- and mTBI-related chronic demyelination overlap substantially; exceptions include primary motor and somatosensory cortices, where myelin is relatively spared post-mTBI. These features resemble those of white matter demyelination and cortical thinning during Alzheimer's disease, whose risk increases after mTBI.
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Affiliation(s)
- Sean O. Mahoney
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, United States
| | - Nahian F. Chowdhury
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, United States
| | - Van Ngo
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, United States
| | - Phoebe Imms
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, United States
| | - Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, United States
- Corwin D. Denney Research Center, Department of Biomedical Engineering, Andrew and Edna Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
- *Correspondence: Andrei Irimia
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27
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T1w/T2w Ratio and Cognition in 9-to-11-Year-Old Children. Brain Sci 2022; 12:brainsci12050599. [PMID: 35624986 PMCID: PMC9139105 DOI: 10.3390/brainsci12050599] [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: 03/28/2022] [Revised: 04/28/2022] [Accepted: 05/03/2022] [Indexed: 11/28/2022] Open
Abstract
Childhood is a period of extensive cortical and neural development. Among other things, axons in the brain gradually become more myelinated, promoting the propagation of electrical signals between different parts of the brain, which in turn may facilitate skill development. Myelin is difficult to assess in vivo, and measurement techniques are only just beginning to make their way into standard imaging protocols in human cognitive neuroscience. An approach that has been proposed as an indirect measure of cortical myelin is the T1w/T2w ratio, a contrast that is based on the intensities of two standard structural magnetic resonance images. Although not initially intended as such, researchers have recently started to use the T1w/T2w contrast for between-subject comparisons of cortical data with various behavioral and cognitive indices. As a complement to these earlier findings, we computed individual cortical T1w/T2w maps using data from the Adolescent Brain Cognitive Development study (N = 960; 449 females; aged 8.9 to 11.0 years) and related the T1w/T2w maps to indices of cognitive ability; in contrast to previous work, we did not find significant relationships between T1w/T2w values and cognitive performance after correcting for multiple testing. These findings reinforce existent skepticism about the applicability of T1w/T2w ratio for inter-individual comparisons.
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28
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Koppelmans V, Mulavara AP, Seidler RD, De Dios YE, Bloomberg JJ, Wood SJ. Cortical thickness of primary motor and vestibular brain regions predicts recovery from fall and balance directly after spaceflight. Brain Struct Funct 2022; 227:2073-2086. [PMID: 35469104 DOI: 10.1007/s00429-022-02492-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 03/30/2022] [Indexed: 01/02/2023]
Abstract
Motor adaptations to the microgravity environment during spaceflight allow astronauts to perform adequately in this unique environment. Upon return to Earth, this adaptation is no longer appropriate and can be disruptive for mission critical tasks. Here, we measured if metrics derived from MRI scans collected from astronauts can predict motor performance post-flight. Structural and diffusion MRI scans from 14 astronauts collected before launch, and motor measures (balance performance, speed of recovery from fall, and tandem walk step accuracy) collected pre-flight and post-flight were analyzed. Regional measures of gray matter volume (motor cortex, paracentral lobule, cerebellum), myelin density (motor cortex, paracentral lobule, corticospinal tract), and white matter microstructure (corticospinal tract) were derived as a-priori predictors. Additional whole-brain analyses of cortical thickness, cerebellar gray matter, and cortical myelin were also tested for associations with post-flight and pre-to-post-flight motor performance. The pre-selected regional measures were not significantly associated with motor behavior. However, whole-brain analyses showed that paracentral and precentral gyri thickness significantly predicted recovery from fall post-spaceflight. Thickness of vestibular and sensorimotor regions, including the posterior insula and the superior temporal gyrus, predicted balance performance post-flight and pre-to-post-flight decrements. Greater cortical thickness pre-flight predicted better performance post-flight. Regional thickness of somatosensory, motor, and vestibular brain regions has some predictive value for post-flight motor performance in astronauts, which may be used for the identification of training and countermeasure strategies targeted for maintaining operational task performance.
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Affiliation(s)
| | | | - Rachael D Seidler
- Applied Physiology and Kinesiology, College of Health and Human Performance, University of Florida, Gainesville, FL, USA
| | | | - Jacob J Bloomberg
- National Aeronautics and Space Administration Johnson Space Center, Houston, TX, USA
| | - Scott J Wood
- National Aeronautics and Space Administration Johnson Space Center, Houston, TX, USA
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29
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Diagnostic efficacy of the magnetic resonance T1w/T2w ratio for the middle cerebellar peduncle in multiple system atrophy and spinocerebellar ataxia: A preliminary study. PLoS One 2022; 17:e0267024. [PMID: 35427382 PMCID: PMC9012356 DOI: 10.1371/journal.pone.0267024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 04/01/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND The standardized T1-weighted/T2-weighted (sT1w/T2w) ratio for the middle cerebellar peduncle (MCP) has been reported to be sensitive for detecting degenerative changes in the cerebellar subtype of multiple system atrophy (MSA-C), even in the early stages. We aimed to investigate the diagnostic value of the MCP sT1w/T2w ratio for differentiating between MSA-C and spinocerebellar ataxia (SCA). METHODS We included 32 MSA-C, 8 SCA type 3 (SCA3), 16 SCA type 6 (SCA6) patients, and 17 controls, and the MCP sT1w/T2w ratio was analyzed using a region-of-interest approach. The diagnostic performance of the MCP sT1w/T2w ratio in discriminating among MSA-C, SCA3, and SCA6 was assessed and compared with diagnosis based on visual interpretation of MCP hyperintensities and the "hot cross bun" (HCB) sign. RESULTS MCP sT1w/T2w ratio values were markedly lower in patients with MSA-C than in those with SCA3, those with SCA6, and controls (p < 0.001). The MCP sT1w/T2w ratio showed high diagnostic accuracy for distinguishing MSA-C from SCA3 (area under curve = 0.934), SCA6 (area under curve = 0.965), and controls (area under curve = 0.980). The diagnostic accuracy of the MCP sT1w/T2w ratio for differentiating MSA-C from SCA3 or SCA6 (90.0% for MSA-C vs. SCA3, and 91.7% for MSA-C vs. SCA6) was comparable to or superior than that of visual interpretation of MCP hyperintensities (80.0-87.5% in MSA-C vs. SCA3 and 87.6-97.9% in MSA-C vs. SCA6) or the HCB sign (72.5-80.0% in MSA-C vs. SCA3 and 77.1-93.8% in MSA-C vs. SCA6). CONCLUSIONS The MCP sT1w/T2w ratio might be a sensitive imaging-based marker for detecting MSA-C-related changes and differentiating MSA-C from SCA3 or SCA6.
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30
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Andica C, Hagiwara A, Yokoyama K, Kato S, Uchida W, Nishimura Y, Fujita S, Kamagata K, Hori M, Tomizawa Y, Hattori N, Aoki S. Multimodal magnetic resonance imaging quantification of gray matter alterations in relapsing-remitting multiple sclerosis and neuromyelitis optica spectrum disorder. J Neurosci Res 2022; 100:1395-1412. [PMID: 35316545 DOI: 10.1002/jnr.25035] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 02/07/2022] [Accepted: 02/13/2022] [Indexed: 11/08/2022]
Abstract
Herein, we combined neurite orientation dispersion and density imaging (NODDI) and synthetic magnetic resonance imaging (SyMRI) to evaluate the spatial distribution and extent of gray matter (GM) microstructural alterations in patients with relapsing-remitting multiple sclerosis (RRMS) and neuromyelitis optica spectrum disorder (NMOSD). The NODDI (neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISOVF]) and SyMRI (myelin volume fraction [MVF]) measures were compared between age- and sex-matched groups of 30 patients with RRMS (6 males and 24 females; mean age, 51.43 ± 8.02 years), 18 patients with anti-aquaporin-4 antibody-positive NMOSD (2 males and 16 females; mean age, 52.67 ± 16.07 years), and 19 healthy controls (6 males and 13 females; mean age, 51.47 ± 9.25 years) using GM-based spatial statistical analysis. Patients with RRMS showed reduced NDI and MVF and increased ODI and ISOVF, predominantly in the limbic and paralimbic regions, when compared with healthy controls, while only increases in ODI and ISOVF were observed when compared with NMOSD. Compared to NDI and MVF, the changes in ODI and ISOVF were observed more widely, including in the cerebellar cortex. These abnormalities were associated with disease progression and disability. In contrast, patients with NMOSD only showed reduced NDI mainly in the cerebellar, limbic, and paralimbic cortices when compared with healthy controls and patients with RRMS. Taken together, our study supports the notion that GM pathologies in RRMS are distinct from those of NMOSD. However, owing to the limitations of the study, the results should be cautiously interpreted.
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Affiliation(s)
- Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.,Department of Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Kazumasa Yokoyama
- Department of Neurology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shimpei Kato
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.,Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuma Nishimura
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.,Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Shohei Fujita
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.,Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Masaaki Hori
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.,Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - Yuji Tomizawa
- Department of Neurology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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31
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Berg RC, Leutritz T, Weiskopf N, Preibisch C. Multi-parameter quantitative mapping of R1, R2*, PD, and MTsat is reproducible when accelerated with Compressed SENSE. Neuroimage 2022; 253:119092. [PMID: 35288281 DOI: 10.1016/j.neuroimage.2022.119092] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 03/07/2022] [Accepted: 03/08/2022] [Indexed: 10/18/2022] Open
Abstract
Multi-parameter mapping (MPM) magnetic resonance imaging (MRI) provides quantitative estimates of the longitudinal and effective transverse relaxation rates R1 and R2*, proton density (PD), and magnetization transfer saturation (MTsat). Thereby, MPM enables better comparability across sites and time than conventional weighted MRI. However, for MPM, several contrasts must be acquired, resulting in prolonged measurement durations and thus preventing MPM's application in clinical routines. State-of-the-art imaging acceleration techniques such as Compressed SENSE (CS), a combination of compressed sensing and sensitivity encoding, can be used to reduce the scan time of MPM. However, the accuracy and precision of the resulting quantitative parameter maps have not been systematically evaluated. In this study, we therefore investigated the effect of CS acceleration on the fidelity and reproducibility of MPM acquisitions. In five healthy volunteers and in a phantom, we compared MPM metrics acquired without imaging acceleration, with the standard acceleration (SENSE factor 2.5), and with Compressed SENSE with acceleration factors 4 and 6 using a 32-channel head coil. We evaluated the reproducibility and repeatability of accelerated MPM using data from three scan sessions in gray and white matter volumes-of-interest (VOIs). Accelerated MPM provided precise and accurate quantitative parameter maps. For most parameters, the results of the CS-accelerated protocols correlated more strongly with the non-accelerated protocol than the standard SENSE-accelerated protocols. Furthermore, for most VOIs and contrasts, coefficients of variation were lower when calculated from data acquired with different imaging accelerations within a single scan session than from data acquired in different scan sessions. These results suggest that MPM with Compressed SENSE acceleration factors up to at least 6 yields reproducible quantitative parameter maps that are highly comparable to those acquired without imaging acceleration. Compressed SENSE can thus be used to considerably reduce the scan duration of R1, R2*, PD, and MTsat mapping, and is highly promising for clinical applications of MPM.
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Affiliation(s)
- Ronja C Berg
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Neurology, Munich, Germany.
| | - Tobias Leutritz
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurophysics, Leipzig, Germany.
| | - Nikolaus Weiskopf
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurophysics, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany.
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Neurology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Munich, Germany.
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32
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Rahman N, Ramnarine J, Xu K, Brown A, Baron CA. Test-Retest Reproducibility of In Vivo Magnetization Transfer Ratio and Saturation Index in Mice at 9.4 Tesla. J Magn Reson Imaging 2022; 56:893-903. [PMID: 35156740 DOI: 10.1002/jmri.28106] [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: 11/26/2021] [Revised: 01/29/2022] [Accepted: 01/31/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Magnetization transfer saturation (MTsat) imaging was developed to reduce T1 dependence and improve specificity to myelin, compared to the widely used MT ratio (MTR) approach, while maintaining a feasible scan time. As MTsat imaging is an emerging technique, the reproducibility of MTsat compared to MTR must be evaluated. PURPOSE To assess the test-retest reproducibility of MTR and MTsat in the mouse brain at 9.4 T and calculate sample sizes potentially required to detect effect sizes ranging from 6% to 14%. STUDY TYPE Prospective. SUBJECTS Twelve healthy C57Bl/6 mice. FIELD STRENGTH/SEQUENCE 9.4 T; magnetization transfer imaging using FLASH-3D Gradient Echo; T2-weighted TurboRARE spin echo. ASSESSMENT All mice were scanned at two timepoints (5 days apart). MTR and MTsat maps were analyzed using mean region-of-interest (ROIs: corpus callosum [CC], internal capsule [IC], hippocampus [HC], cortex [CX], and thalamus [TH]), and whole brain voxel-wise analysis. STATISTICAL TESTS Bland-Altman plots were used to assess biases between test-retest measurements. Test-retest reproducibility was evaluated via between and within-subject coefficients of variation (bsCV and wsCV, respectively). Sample sizes required were calculated (significance level: 95%; power: 80%), given effect sizes ranging from 6% to 14%, using both between and within-subject approaches. Results were considered statistically significant at P ≤ 0.05. RESULTS Bland-Altman plots showed negligible biases between test-retest sessions (MTR: 0.0009; MTsat: 0). ROI-based and voxel-wise CVs revealed high reproducibility for both MTR (ROI-bsCV/wsCV: CC-4.5/2.8%; IC-6.1/5.2%; HC-5.7/4.6%; CX-5.1/2.3%; TH-7.4/4.9%) and MTsat (ROI-bsCV/wsCV: CC-6.3/4.8%; IC-7.3/5.1%; HC-9.5/6.4%; CX-6.7/6.5%; TH-7.2/5.3%). With a sample size of 6, changes on the order of 15% could be detected in MTR and MTsat, both between and within subjects, while smaller changes (6%-8%) required sample sizes of 10-15 for MTR, and 15-20 for MTsat. DATA CONCLUSION MTsat exhibited comparable reproducibility to MTR, while providing sensitivity to myelin with less T1 dependence than MTR. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Naila Rahman
- Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, University of Western Ontario, London, Ontario, Canada.,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada
| | - Jordan Ramnarine
- Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
| | - Kathy Xu
- Translational Neuroscience Group, Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada
| | - Arthur Brown
- Translational Neuroscience Group, Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada.,Department of Anatomy and Cell Biology, University of Western Ontario, London, Ontario, Canada
| | - Corey A Baron
- Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, University of Western Ontario, London, Ontario, Canada.,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada
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33
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Yoo RE, Choi SH, Youn SW, Hwang M, Kim E, Oh BM, Lee JY, Hwang I, Kang KM, Yun TJ, Kim JH, Sohn CH. Myelin Content in Mild Traumatic Brain Injury Patients with Post-Concussion Syndrome: Quantitative Assessment with a Multidynamic Multiecho Sequence. Korean J Radiol 2022; 23:226-236. [PMID: 35029073 PMCID: PMC8814703 DOI: 10.3348/kjr.2021.0253] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 07/20/2021] [Accepted: 08/28/2021] [Indexed: 11/30/2022] Open
Abstract
Objective This study aimed to explore the myelin volume change in patients with mild traumatic brain injury (mTBI) with post-concussion syndrome (PCS) using a multidynamic multiecho (MDME) sequence and automatic whole-brain segmentation. Materials and Methods Forty-one consecutive mTBI patients with PCS and 29 controls, who had undergone MRI including the MDME sequence between October 2016 and April 2018, were included. Myelin volume fraction (MVF) maps were derived from the MDME sequence. After three dimensional T1-based brain segmentation, the average MVF was analyzed at the bilateral cerebral white matter (WM), bilateral cerebral gray matter (GM), corpus callosum, and brainstem. The Mann–Whitney U-test was performed to compare MVF and myelin volume between patients with mTBI and controls. Myelin volume was correlated with neuropsychological test scores using the Spearman rank correlation test. Results The average MVF at the bilateral cerebral WM was lower in mTBI patients with PCS (median [interquartile range], 25.2% [22.6%–26.4%]) than that in controls (26.8% [25.6%–27.8%]) (p = 0.004). The region-of-interest myelin volume was lower in mTBI patients with PCS than that in controls at the corpus callosum (1.87 cm3 [1.70–2.05 cm3] vs. 2.21 cm3 [1.86–3.46 cm3]; p = 0.003) and brainstem (9.98 cm3 [9.45–11.00 cm3] vs. 11.05 cm3 [10.10–11.53 cm3]; p = 0.015). The total myelin volume was lower in mTBI patients with PCS than that in controls at the corpus callosum (0.45 cm3 [0.39–0.48 cm3] vs. 0.48 cm3 [0.45–0.54 cm3]; p = 0.004) and brainstem (1.45 cm3 [1.28–1.59 cm3] vs. 1.54 cm3 [1.42–1.67 cm3]; p = 0.042). No significant correlation was observed between myelin volume parameters and neuropsychological test scores, except for the total myelin volume at the bilateral cerebral WM and verbal learning test (delayed recall) (r = 0.425; p = 0.048). Conclusion MVF quantified from the MDME sequence was decreased at the bilateral cerebral WM in mTBI patients with PCS. The total myelin volumes at the corpus callosum and brainstem were decreased in mTBI patients with PCS due to atrophic changes.
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Affiliation(s)
- Roh-Eul Yoo
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.,Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, Korea.,School of Chemical and Biological Engineering, Seoul National University, Seoul, Korea.
| | - Sung-Won Youn
- Department of Radiology, Daegu Catholic University Medical Center, Daegu, Korea
| | | | - Eunkyung Kim
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Byung-Mo Oh
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.,National Traffic Injury Rehabilitation Hospital, Yangpyeong, Korea.,Neuroscience Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Ji Ye Lee
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Ji-Hoon Kim
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
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Nerland S, Jørgensen KN, Nordhøy W, Maximov II, Bugge RAB, Westlye LT, Andreassen OA, Geier OM, Agartz I. Multisite reproducibility and test-retest reliability of the T1w/T2w-ratio: A comparison of processing methods. Neuroimage 2021; 245:118709. [PMID: 34848300 DOI: 10.1016/j.neuroimage.2021.118709] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 10/29/2021] [Accepted: 11/02/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The ratio of T1-weighted (T1w) and T2-weighted (T2w) magnetic resonance imaging (MRI) images is often used as a proxy measure of cortical myelin. However, the T1w/T2w-ratio is based on signal intensities that are inherently non-quantitative and known to be affected by extrinsic factors. To account for this a variety of processing methods have been proposed, but a systematic evaluation of their efficacy is lacking. Given the dependence of the T1w/T2w-ratio on scanner hardware and T1w and T2w protocols, it is important to ensure that processing pipelines perform well also across different sites. METHODS We assessed a variety of processing methods for computing cortical T1w/T2w-ratio maps, including correction methods for nonlinear field inhomogeneities, local outliers, and partial volume effects as well as intensity normalisation. These were implemented in 33 processing pipelines which were applied to four test-retest datasets, with a total of 170 pairs of T1w and T2w images acquired on four different MRI scanners. We assessed processing pipelines across datasets in terms of their reproducibility of expected regional distributions of cortical myelin, lateral intensity biases, and test-retest reliability regionally and across the cortex. Regional distributions were compared both qualitatively with histology and quantitatively with two reference datasets, YA-BC and YA-B1+, from the Human Connectome Project. RESULTS Reproducibility of raw T1w/T2w-ratio distributions was overall high with the exception of one dataset. For this dataset, Spearman rank correlations increased from 0.27 to 0.70 after N3 bias correction relative to the YA-BC reference and from -0.04 to 0.66 after N4ITK bias correction relative to the YA-B1+ reference. Partial volume and outlier corrections had only marginal effects on the reproducibility of T1w/T2w-ratio maps and test-retest reliability. Before intensity normalisation, we found large coefficients of variation (CVs) and low intraclass correlation coefficients (ICCs), with total whole-cortex CV of 10.13% and whole-cortex ICC of 0.58 for the raw T1w/T2w-ratio. Intensity normalisation with WhiteStripe, RAVEL, and Z-Score improved total whole-cortex CVs to 5.91%, 5.68%, and 5.19% respectively, whereas Z-Score and Least Squares improved whole-cortex ICCs to 0.96 and 0.97 respectively. CONCLUSIONS In the presence of large intensity nonuniformities, bias field correction is necessary to achieve acceptable correspondence with known distributions of cortical myelin, but it can be detrimental in datasets with less intensity inhomogeneity. Intensity normalisation can improve test-retest reliability and inter-subject comparability. However, both bias field correction and intensity normalisation methods vary greatly in their efficacy and may affect the interpretation of results. The choice of T1w/T2w-ratio processing method must therefore be informed by both scanner and acquisition protocol as well as the given study objective. Our results highlight limitations of the T1w/T2w-ratio, but also suggest concrete ways to enhance its usefulness in future studies.
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Affiliation(s)
- Stener Nerland
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo 0319, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Kjetil N Jørgensen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo 0319, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Wibeke Nordhøy
- Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Ivan I Maximov
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
| | - Robin A B Bugge
- Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Oliver M Geier
- Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo 0319, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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Spindler M, Thiel CM. Quantitative magnetic resonance imaging for segmentation and white matter extraction of the hypothalamus. J Neurosci Res 2021; 100:564-577. [PMID: 34850453 DOI: 10.1002/jnr.24988] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 10/05/2021] [Accepted: 10/12/2021] [Indexed: 11/09/2022]
Abstract
Since the hypothalamus is involved in many neuroendocrine, metabolic, and affective disorders, detailed hypothalamic imaging has become of major interest to better characterize disease-induced tissue damages and abnormalities. Still, image contrast of conventional anatomical magnetic resonance imaging lacks morphological detail, thus complicating complete and precise segmentation of the hypothalamus. The hypothalamus' position lateral to the third ventricle and close proximity to white matter tracts including the optic tract, fornix, and mammillothalamic tract display one of the remaining shortcomings of hypothalamic segmentation, as reliable exclusion of white matter is not yet possible. Recent studies found that quantitative magnetic resonance imaging (qMRI), a method to create maps of different standardized tissue contents, improved segmentation of cortical and subcortical brain regions. So far, this has not been tested for the hypothalamus. Therefore, in this study, we investigated the usability of qMRI and diffusion MRI for the purpose of detailed and reproducible manual segmentation of the hypothalamus and data-driven white matter extraction and compared our results to recent state-of-the-art segmentations. Our results show that qMRI presents good contrast for delineation of the hypothalamus and white matter, and that the properties of these images differ between subunits, such that they can be used to reliably exclude white matter from hypothalamic tissue. We propose that qMRI poses a useful addition to detailed hypothalamic segmentation and volumetry.
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Affiliation(s)
- Melanie Spindler
- Biological Psychology, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
| | - Christiane M Thiel
- Biological Psychology, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.,Cluster of Excellence "Hearing4all", Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.,Research Centre Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
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Hannoun S, Kocevar G, Codjia P, Barile B, Cotton F, Durand-Dubief F, Sappey-Marinier D. T1/T2 ratio: A quantitative sensitive marker of brain tissue integrity in multiple sclerosis. J Neuroimaging 2021; 32:328-336. [PMID: 34752685 DOI: 10.1111/jon.12943] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 09/30/2021] [Accepted: 10/14/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND AND PURPOSE The aim of this study is to determine whether cerebral white matter (WM) microstructural damage, defined by decreased fractional anisotropy (FA) and increased axial (AD) and radial (RD) diffusivities, could be detected as accurately by measuring the T1/T2 ratio, in relapsing-remitting multiple sclerosis (RRMS) patients compared to healthy control (HC) subjects. METHODS Twenty-eight RRMS patients and 24 HC subjects were included in this study. Region-based analysis based on the ICBM-81 diffusion tensor imaging (DTI) atlas WM labels was performed to compare T1/T2 ratio to DTI values in normal-appearing WM (NAWM) regions of interest. Lesions segmentation was also performed and compared to the HC global WM. RESULTS A significant 19.65% decrease of T1/T2 ratio values was observed in NAWM regions of RRMS patients compared to HC. A significant 6.30% decrease of FA, as well as significant 4.76% and 10.27% increases of AD and RD, respectively, were observed in RRMS compared to the HC group in various NAWM regions. Compared to the global WM HC mask, lesions have significantly decreased T1/T2 ratio and FA and increased AD and RD (p < . 001). CONCLUSIONS Results showed significant differences between RRMS and HC in both DTI and T1/T2 ratio measurements. T1/T2 ratio even demonstrated extensive WM abnormalities when compared to DTI, thereby highlighting the ratio's sensitivity to subtle differences in cerebral WM structural integrity using only conventional MRI sequences.
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Affiliation(s)
- Salem Hannoun
- Medical Imaging Sciences Program, Division of Health Professions, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Gabriel Kocevar
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France.,Seenovate, Datascience pole, Lyon, France
| | - Pekes Codjia
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France.,Service de Radiologie, Centre Hospitalier Lyon-Sud, Hospices Civils de Lyon, Pierre Bénite, France
| | - Berardino Barile
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France
| | - Francois Cotton
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France.,Service de Radiologie, Centre Hospitalier Lyon-Sud, Hospices Civils de Lyon, Pierre Bénite, France
| | - Francoise Durand-Dubief
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France.,Service de Neurologie A, Hôpital Neurologique Pierre Wertheimer, Groupement Hospitalier Est, Hospices Civils de Lyon, Bron, France
| | - Dominique Sappey-Marinier
- CREATIS, UMR 5220 CNRS & U1294 INSERM, Université Claude Bernard - Lyon1, Université de Lyon, Villeurbanne, France.,Département IRM, CERMEP-Imagerie du Vivant, Université de Lyon, Bron, France
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Sommer RC, Hata J, Rimkus CDM, Klein da Costa B, Nakahara J, Sato DK. Mechanisms of myelin repair, MRI techniques and therapeutic opportunities in multiple sclerosis. Mult Scler Relat Disord 2021; 58:103407. [DOI: 10.1016/j.msard.2021.103407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 10/29/2021] [Accepted: 11/13/2021] [Indexed: 11/16/2022]
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Ogawa T, Hatano T, Kamagata K, Andica C, Takeshige-Amano H, Uchida W, Kamiyama D, Shimo Y, Oyama G, Umemura A, Iwamuro H, Ito M, Hori M, Aoki S, Hattori N. White matter and nigral alterations in multiple system atrophy-parkinsonian type. NPJ PARKINSONS DISEASE 2021; 7:96. [PMID: 34716335 PMCID: PMC8556415 DOI: 10.1038/s41531-021-00236-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 09/15/2021] [Indexed: 12/20/2022]
Abstract
Multiple system atrophy (MSA) is classified into two main types: parkinsonian and cerebellar ataxia with oligodendrogliopathy. We examined microstructural alterations in the white matter and the substantia nigra pars compacta (SNc) of patients with MSA of parkinsonian type (MSA-P) using multishell diffusion magnetic resonance imaging (dMRI) and myelin sensitive imaging techniques. Age- and sex-matched patients with MSA-P (n = 21, n = 10 first and second cohorts, respectively), Parkinson’s disease patients (n = 19, 17), and healthy controls (n = 20, 24) were enrolled. Magnetization transfer saturation imaging (MT-sat) and dMRI were obtained using 3-T MRI. Measurements obtained from diffusion tensor imaging (DTI), free-water elimination DTI, neurite orientation dispersion and density imaging (NODDI), and MT-sat were compared between groups. Tract-based spatial statistics analysis revealed differences in diffuse white matter alterations in the free-water fractional volume, myelin volume fraction, and intracellular volume fraction between the patients with MSA-P and healthy controls, whereas free-water and MT-sat differences were limited to the middle cerebellar peduncle in comparison with those with Parkinson’s disease. Region-of-interest analysis of white matter and SNc revealed significant differences in the middle and inferior cerebellar peduncle, pontine crossing tract, corticospinal tract, and SNc between the MSA-P and healthy controls and/or Parkinson’s disease patients. Our results shed light on alterations to brain microstructure in MSA.
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Affiliation(s)
- Takashi Ogawa
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Taku Hatano
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan.
| | - Koji Kamagata
- Department of Radiology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Christina Andica
- Department of Radiology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | | | - Wataru Uchida
- Department of Radiology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Daiki Kamiyama
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Yasushi Shimo
- Department of Neurology, Juntendo University Nerima Hospital, Tokyo, Japan
| | - Genko Oyama
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Atsushi Umemura
- Department of Neurosurgery, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Hirokazu Iwamuro
- Department of Neurosurgery, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Masanobu Ito
- Department of Psychiatry, Faculty of Medicine Juntendo University, Tokyo, Japan
| | - Masaaki Hori
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Nobutaka Hattori
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan.
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Martin E, Aigrot MS, Lamari F, Bachelin C, Lubetzki C, Nait Oumesmar B, Zalc B, Stankoff B. Teriflunomide Promotes Oligodendroglial 8,9-Unsaturated Sterol Accumulation and CNS Remyelination. NEUROLOGY-NEUROIMMUNOLOGY & NEUROINFLAMMATION 2021; 8:8/6/e1091. [PMID: 34642237 PMCID: PMC8515201 DOI: 10.1212/nxi.0000000000001091] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 08/23/2021] [Indexed: 11/29/2022]
Abstract
Background and Objectives To test whether low concentrations of teriflunomide (TF) could promote remyelination, we investigate the effect of TF on oligodendrocyte in culture and on remyelination in vivo in 2 demyelinating models. Methods The effect of TF on oligodendrocyte precursor cell (OPC) proliferation and differentiation was assessed in vitro in glial cultures derived from neonatal mice and confirmed on fluorescence-activated cell sorting–sorted adult OPCs. The levels of the 8,9-unsaturated sterols lanosterol and zymosterol were quantified in TF- and sham-treated cultures. In vivo, TF was administered orally, and remyelination was assessed both in myelin basic protein–GFP-nitroreductase (Mbp:GFP-NTR) transgenic Xenopus laevis demyelinated by metronidazole and in adult mice demyelinated by lysolecithin. Results In cultures, low concentrations of TF down to 10 nM decreased OPC proliferation and increased their differentiation, an effect that was also detected on adult OPCs. Oligodendrocyte differentiation induced by TF was abrogated by the oxidosqualene cyclase inhibitor Ro 48-8071 and was mediated by the accumulation of zymosterol. In the demyelinated tadpole, TF enhanced the regeneration of mature oligodendrocytes up to 2.5-fold. In the mouse demyelinated spinal cord, TF promoted the differentiation of newly generated oligodendrocytes by a factor of 1.7-fold and significantly increased remyelination. Discussion TF enhances zymosterol accumulation in oligodendrocytes and CNS myelin repair, a beneficial off-target effect that should be investigated in patients with multiple sclerosis.
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Affiliation(s)
- Elodie Martin
- From the Sorbonne Université, Paris Brain Institute, CNRS, Inserm (E.M., M.-S.A., C.B., C.L., B.N.O., B.Z., B.S.); Pitié-Salpêtrière Hospital, APHP (F.L., C.L.); and Saint Antoine Hospital, APHP (B.S.), Paris, France
| | - Marie-Stephane Aigrot
- From the Sorbonne Université, Paris Brain Institute, CNRS, Inserm (E.M., M.-S.A., C.B., C.L., B.N.O., B.Z., B.S.); Pitié-Salpêtrière Hospital, APHP (F.L., C.L.); and Saint Antoine Hospital, APHP (B.S.), Paris, France
| | - Foudil Lamari
- From the Sorbonne Université, Paris Brain Institute, CNRS, Inserm (E.M., M.-S.A., C.B., C.L., B.N.O., B.Z., B.S.); Pitié-Salpêtrière Hospital, APHP (F.L., C.L.); and Saint Antoine Hospital, APHP (B.S.), Paris, France
| | - Corinne Bachelin
- From the Sorbonne Université, Paris Brain Institute, CNRS, Inserm (E.M., M.-S.A., C.B., C.L., B.N.O., B.Z., B.S.); Pitié-Salpêtrière Hospital, APHP (F.L., C.L.); and Saint Antoine Hospital, APHP (B.S.), Paris, France
| | - Catherine Lubetzki
- From the Sorbonne Université, Paris Brain Institute, CNRS, Inserm (E.M., M.-S.A., C.B., C.L., B.N.O., B.Z., B.S.); Pitié-Salpêtrière Hospital, APHP (F.L., C.L.); and Saint Antoine Hospital, APHP (B.S.), Paris, France
| | - Brahim Nait Oumesmar
- From the Sorbonne Université, Paris Brain Institute, CNRS, Inserm (E.M., M.-S.A., C.B., C.L., B.N.O., B.Z., B.S.); Pitié-Salpêtrière Hospital, APHP (F.L., C.L.); and Saint Antoine Hospital, APHP (B.S.), Paris, France
| | - Bernard Zalc
- From the Sorbonne Université, Paris Brain Institute, CNRS, Inserm (E.M., M.-S.A., C.B., C.L., B.N.O., B.Z., B.S.); Pitié-Salpêtrière Hospital, APHP (F.L., C.L.); and Saint Antoine Hospital, APHP (B.S.), Paris, France
| | - Bruno Stankoff
- From the Sorbonne Université, Paris Brain Institute, CNRS, Inserm (E.M., M.-S.A., C.B., C.L., B.N.O., B.Z., B.S.); Pitié-Salpêtrière Hospital, APHP (F.L., C.L.); and Saint Antoine Hospital, APHP (B.S.), Paris, France.
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Parlak S, Coban G, Gumeler E, Karakaya J, Soylemezoglu F, Tezer I, Bilginer B, Saygi S, Oguz KK. Reduced myelin in patients with isolated hippocampal sclerosis as assessed by SyMRI. Neuroradiology 2021; 64:99-107. [PMID: 34611716 PMCID: PMC8492040 DOI: 10.1007/s00234-021-02824-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 09/25/2021] [Indexed: 02/05/2023]
Abstract
Purpose Synthetic MRI (SyMRI) enables to quantify brain tissue and morphometry. We aimed to investigate the WM and myelin alterations in patients with unilateral hippocampal sclerosis (HS) with SyMRI. Methods Adult patients with isolated unilateral HS and age-matched control subjects (CSs) were included in this study. The SyMRI sequence QRAPMASTER in the coronal plane perpendicular to the hippocampi was obtained from the whole brain. Automatic segmentation of the whole brain was processed by SyMRI Diagnostic software (Version 11.2). Two neuroradiologists also performed quantitative analyses independently from symmetrical 14 ROIs placed in temporal and extratemporal WM, hippocampi, and amygdalae in both hemispheres. Results Sixteen patients (F/M = 6/10, mean age = 32.5 ± 11.3 years; right/left HS: 8/8) and 10 CSs (F/M = 5/5, mean age = 30.7 ± 7 years) were included. Left HS patients had significantly lower myelin and WM volumes than CSs (p < .05). Myelin was reduced significantly in the ipsilateral temporal lobe of patients than CSs, greater in left HS (p < .05). Histopathological examination including luxol fast blue stain also revealed myelin pallor in all of 6 patients who were operated. Ipsilateral temporal pole and sub-insular WM had significantly reduced myelin than the corresponding contralateral regions in patients (p < .05). No significant difference was found in WM values. GM values were significantly lower in hippocampi in patients than CSs (p < .05). Conclusion SyMRI revealed myelin reduction in the ipsilateral temporal lobe and sub-insular WM of patients with HS. Whether this finding correlates with electrophysiological features and SyMRI could serve as lateralization of temporal lobe epilepsy need to be investigated. Supplementary Information The online version contains supplementary material available at 10.1007/s00234-021-02824-6.
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Affiliation(s)
- Safak Parlak
- Department of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey.
| | - Gokcen Coban
- Department of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Ekim Gumeler
- Department of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Jale Karakaya
- Department of Biostatistics, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Figen Soylemezoglu
- Department of Pathology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Irsel Tezer
- Department of Neurology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Burcak Bilginer
- Department of Neurosurgery, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Serap Saygi
- Department of Neurology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Kader K Oguz
- Department of Radiology, Hacettepe University Faculty of Medicine, Ankara, Turkey
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Assessing the differential sensitivities of wave-CAIPI ViSTa myelin water fraction and magnetization transfer saturation for efficiently quantifying tissue damage in MS. Mult Scler Relat Disord 2021; 56:103309. [PMID: 34688179 DOI: 10.1016/j.msard.2021.103309] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 09/21/2021] [Accepted: 10/02/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND Wave-CAIPI Visualization of Short Transverse relaxation time component (ViSTa) is a recently developed, short-T1-sensitized MRI method for fast quantification of myelin water fraction (MWF) in the human brain. It represents a promising technique for the evaluation of subtle, early signals of demyelination in the cerebral white matter of multiple sclerosis (MS) patients. Currently however, few studies exist that robustly assess the utility of ViSTa MWF measures of myelin compared to more conventional MRI measures of myelin in the brain of MS patients. Moreover, there are no previous studies evaluating the sensitivity of ViSTa MWF for the non-invasive detection of subtle tissue damage in both normal-appearing white matter (NAWM) and white matter lesions of MS patients. As a result, a central purpose of this study was to systematically evaluate the relationship between myelin sensitivity of T1-based ViSTa MWF mapping and a more generally recognized metric, Magnetization Transfer Saturation (MTsat), in healthy control and MS brain white matter. METHODS ViSTa MWF and MTsat values were evaluated in automatically-classified normal appearing white matter (NAWM), white matter (WM) lesion tissue, cortical gray matter, and deep gray matter of 29 MS patients and 10 healthy controls using 3T MRI. MWF and MT sat were also assessed in a tract-specific manner using the Johns Hopkins University WM atlas. MRI-derived measures of cerebral myelin content were uniquely compared by employing non-normal distribution-specific measures of median, interquartile range and skewness. Separate analyses of variance were applied to test tissue-specific differences in MTsat and ViSTa MWF distribution metrics. Non-parametric tests were utilized when appropriate. All tests were corrected for multiple comparisons using the False Discovery Rate method at the level, α=0.05. RESULTS Differences in whole NAWM MS tissue damage were detected with a higher effect size when using ViSTa MWF (q = 0.0008; ƞ2 = 0.34) compared to MTsat (q = 0.02; ƞ2= 0.24). We also observed that, as a possible measure of WM pathology, ViSTa-derived NAWM MWF voxel distributions of MS subjects were consistently skewed towards lower MWF values, while MTsat voxel distributions showed reduced skewness values. We further identified tract-specific reductions in mean ViSTa MWF of MS patients compared to controls that were not observed with MTsat. However, MTsat (q = 1.4 × 10-21; ƞ2 = 0.88) displayed higher effect sizes when differentiating NAWM and MS lesion tissue. Using regression analysis at the group level, we identified a linear relationship between MTsat and ViSTa MWF in NAWM (R2 = 0.46; p = 7.8 × 10-4) lesions (R2 = 0.30; p = 0.004), and with all tissue types combined (R2 = 0.71; p = 8.4 × 10-45). The linear relationship was also observed in most of the WM tracts we investigated. ViSTa MWF in NAWM of MS patients correlated with both disease duration (p = 0.02; R2 = 0.27) and WM lesion volume (p = 0.002; R2 = 0.34). CONCLUSION Because ViSTa MWF and MTsat metrics exhibit differential sensitivities to tissue damage in MS white matter, they can be collected in combination to provide an efficient, comprehensive measure of myelin water and macromolecular pool proton signals. These complementary measures may offer a more sensitive, non-invasive biopsy of early precursor signals in NAWM that occur prior to lesion formation. They may also aid in monitoring the efficacy of remyelination therapies.
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Wei W, Yin Y, Zhang Y, Li X, Li M, Guo W, Wang Q, Deng W, Ma X, Zhao L, Palaniyappan L, Li T. Structural Covariance of Depth-Dependent Intracortical Myelination in the Human Brain and Its Application to Drug-Naïve Schizophrenia: A T1w/T2w MRI Study. Cereb Cortex 2021; 32:2373-2384. [PMID: 34581399 DOI: 10.1093/cercor/bhab337] [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: 06/02/2021] [Revised: 08/16/2021] [Accepted: 08/17/2021] [Indexed: 02/05/2023] Open
Abstract
Aberrations in intracortical myelination are increasingly being considered as a cardinal feature in the pathophysiology of schizophrenia. We investigated the network-level distribution of intracortical myelination across various cortex depths. We enrolled 126 healthy subjects and 106 first-episode drug-naïve schizophrenia patients. We used T1w/T2w ratio as a proxy of intracortical myelination, parcellated cortex into several equivolumetric surfaces based on cortical depths and mapped T1w/T2w ratios to each surface. Non-negative matrix factorization was used to generate depth-dependent structural covariance networks (dSCNs) of intracortical myelination from 2 healthy controls datasets-one from our study and another from 100-unrelated dataset of the Human Connectome Project. For patient versus control comparisons, partial least squares approach was used; we also related myelination to clinical features of schizophrenia. We found that dSCNs were highly reproducible in 2 independent samples. Network-level myelination was reduced in prefrontal and cingulate cortex and increased in perisylvian cortex in schizophrenia. The abnormal network-level myelination had a canonical correlation with symptom burden in schizophrenia. Moreover, myelination of prefrontal cortex correlated with duration of untreated psychosis. In conclusion, we offer a feasible and sensitive framework to study depth-dependent myelination and its relationship with clinical features.
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Affiliation(s)
- Wei Wei
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China
| | - Yubing Yin
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China
| | - Yamin Zhang
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China
| | - Xiaojing Li
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China
| | - Mingli Li
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China
| | - Wanjun Guo
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China
| | - Qiang Wang
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China
| | - Wei Deng
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China
| | - Xiaohong Ma
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China
| | - Liansheng Zhao
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China
| | - Lena Palaniyappan
- Department of Psychiatry, University of Western Ontario, London, Ontario N6A 3K7, Canada.,Robarts Research Institute, University of Western Ontario, London, Ontario N6A 3K7, Canada.,Lawson Health Research Institute, London, Ontario N6C 2R5, Canada
| | - Tao Li
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan 610000, China.,Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310013, China
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Ptito M, Paré S, Dricot L, Cavaliere C, Tomaiuolo F, Kupers R. A quantitative analysis of the retinofugal projections in congenital and late-onset blindness. NEUROIMAGE-CLINICAL 2021; 32:102809. [PMID: 34509923 PMCID: PMC8435915 DOI: 10.1016/j.nicl.2021.102809] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 07/14/2021] [Accepted: 08/24/2021] [Indexed: 01/22/2023]
Abstract
Congenital (CB) and late blind (LB) affects the integrity brain visual structures. We measured the integrity of the retino-fugal system using structural MRI images. Optic nerve, optic tract, optic chiasm and LGN were reduced by 50 to 60% in CB and LB. There were no differences between CB and LB. In LB, optic nerve volume correlated negatively with blindness duration.
Vision loss early in life has dramatic consequences on the organization of the visual system and hence on structural plasticity of its remnant components. Most of the studies on the anatomical changes in the brain following visual deprivation have focused on the re-organization of the visual cortex and its afferent and efferent projections. In this study, we performed a quantitative analysis of the volume and size of the optic chiasm, optic nerve, optic tract and the lateral geniculate nucleus (LGN), the retino recipient thalamic nucleus. Analysis was carried out on structural T1-weighted MRIs from 22 congenitally blind (CB), 14 late blind (LB) and 29 age -and sex-matched sighted control (SC) subjects. We manually segmented the optic nerve, optic chiasm and optic tract, while LGN volumes were extracted using in-house software. We also measured voxel intensity of optic nerve, optic chiasm and optic tract. Mean volumes of the optic nerve, optic tract and optic chiasm were reduced by 50 to 60% in both CB and LB participants. No significant differences were found between the congenitally and late-onset blind participants for any of the measures. Our data further revealed reduced white matter voxel intensities in optic nerve, optic chiasm and optic tract in blind compared to sighted participants, suggesting decreased myelin content in the atrophied white matter. The LGN was reduced by 50% and 44% in CB and LB, respectively. In LB, optic nerve volume correlated negatively with the blindness duration index; no such correlation was found for optic chiasm, optic tract and LGN. The observation that despite the absence of visual input about half of the subcortical retinofugal projections are structurally preserved raises the question of their functional role. One possibility is that the surviving fibers play a role in the maintenance of circadian rhythms in the blind through the intrinsically photosensitive melanopsin-containing retinal ganglion cells.
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Affiliation(s)
- Maurice Ptito
- School of Optometry, University of Montreal, Montreal, QC, Canada; BRAINlab, University of Copenhagen, Copenhagen, Denmark; Danish Research Center for Magnetic Resonance (DRCMR), Copenhagen University Hospital, Hvidovre, Denmark
| | - Samuel Paré
- School of Optometry, University of Montreal, Montreal, QC, Canada
| | - Laurence Dricot
- Institute of NeuroScience (IoNS), Université catholique de Louvain (UCLouvain), Belgium
| | - Carlo Cavaliere
- IRCCS SDN, Naples, Italy; Coma Science Group, Cyclotron Research Center and Neurology Department, University and University Hospital of Liège, Liège, Belgium
| | - Francesco Tomaiuolo
- Univesità degli Studi di Messina, Dipartimento di Medicina Clinica e Sperimentale
| | - Ron Kupers
- School of Optometry, University of Montreal, Montreal, QC, Canada; BRAINlab, University of Copenhagen, Copenhagen, Denmark; Institute of NeuroScience (IoNS), Université catholique de Louvain (UCLouvain), Belgium.
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Li CMF, Chu PPW, Hung PSP, Mikulis D, Hodaie M. Standardizing T1-w/T2-w ratio images in trigeminal neuralgia to estimate the degree of demyelination in vivo. NEUROIMAGE-CLINICAL 2021; 32:102798. [PMID: 34450507 PMCID: PMC8391058 DOI: 10.1016/j.nicl.2021.102798] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 07/04/2021] [Accepted: 08/17/2021] [Indexed: 11/17/2022]
Abstract
The T1-w/T2-w ratio image or “myelin-sensitive map (MM)” is a non-invasive tool that can estimate myelin content in different regions of the brain and between different patients in vivo. T1-w and T2-w images are standardized post-hoc using histogram matching algorithms to provide tissue-specific intensity information and facilitate MM analysis. Analysis of MM intensities demonstrate reduced myelin content in MS plaques compared to its corresponding pontine regions in CTN patients and its surrounding NAWM in MSTN patients. MM has the potential to distinguish changes in myelin of NAWM before MS plaques are detectable on conventional MR images.
Background Novel magnetic resonance (MR) imaging techniques have led to the development of T1-w/T2-w ratio images or “myelin-sensitive maps (MMs)” to estimate and compare myelin content in vivo. Currently, raw image intensities in conventional MR images are unstandardized, preventing meaningful quantitative comparisons. We propose an improved workflow to standardize the MMs, which was applied to patients with classic trigeminal neuralgia (CTN) and trigeminal neuralgia secondary to multiple sclerosis (MSTN), to assess the validity and feasibility of this clinical tool. Methods T1-w and T2-w images were obtained for 17 CTN patients and 17 MSTN patients using a 3 T scanner. Template images were obtained from ICBM152. Multiple sclerosis (MS) plaques in the pons were labelled in MSTN patients. For each patient image, a Gaussian curve was fitted to the histogram of its intensity distribution, and transformed to match the Gaussian curve of its template image. Results After standardization, the structural contrast of the patient image and its histogram more closely resembled the ICBM152 template. Moreover, there was reduced variability in the histogram peaks of the gray and white matter between patients after standardization (p < 0.001). MM intensities were decreased within MS plaques, compared to normal-appearing white matter (NAWM) in MSTN patients (p < 0.001) and its corresponding regions in CTN patients (p < 0.001). Conclusions Images intensities are calibrated according to a mathematic relationship between the intensities of the patient image and its template. Reduced variability among histogram peaks allows for interpretation of tissue-specific intensity and facilitates quantitative analysis. The resultant MMs facilitate comparisons of myelin content between different regions of the brain and between different patients in vivo. MM analysis revealed reduced myelin content in MS plaques compared to its corresponding regions in CTN patients and its surrounding NAWM in MSTN patients. Thus, the standardized MM serves as a non-invasive, easily-automated tool that can be feasibly applied to clinical populations for quantitative analyses of myelin content.
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Affiliation(s)
- Cathy Meng Fei Li
- Department of Clinical Neurological Sciences, University of Western Ontario, Ontario, Canada; Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada; Division of Brain, Imaging, and Behavior - Systems Neuroscience, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Powell P W Chu
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Peter Shih-Ping Hung
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada; Division of Brain, Imaging, and Behavior - Systems Neuroscience, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - David Mikulis
- Division of Brain, Imaging, and Behavior - Systems Neuroscience, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Mojgan Hodaie
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada; Division of Brain, Imaging, and Behavior - Systems Neuroscience, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.
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Warling A, McDermott CL, Liu S, Seidlitz J, Rodrigue AL, Nadig A, Gur RC, Gur RE, Roalf D, Moore TM, Glahn D, Satterthwaite TD, Bullmore ET, Raznahan A. Regional White Matter Scaling in the Human Brain. J Neurosci 2021; 41:7015-7028. [PMID: 34244364 PMCID: PMC8372020 DOI: 10.1523/jneurosci.1193-21.2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 06/12/2021] [Indexed: 11/21/2022] Open
Abstract
Anatomical organization of the primate cortex varies as a function of total brain size, where possession of a larger brain is accompanied by disproportionate expansion of associative cortices alongside a relative contraction of sensorimotor systems. However, equivalent scaling maps are not yet available for regional white matter anatomy. Here, we use three large-scale neuroimaging datasets to examine how regional white matter volume (WMV) scales with interindividual variation in brain volume among typically developing humans (combined N = 2391: 1247 females, 1144 males). We show that WMV scaling is regionally heterogeneous: larger brains have relatively greater WMV in anterior and posterior regions of cortical white matter, as well as the genu and splenium of the corpus callosum, but relatively less WMV in most subcortical regions. Furthermore, regions of positive WMV scaling tend to connect previously-defined regions of positive gray matter scaling in the cortex, revealing a coordinated coupling of regional gray and white matter organization with naturally occurring variations in human brain size. However, we also show that two commonly studied measures of white matter microstructure, fractional anisotropy (FA) and magnetization transfer (MT), scale negatively with brain size, and do so in a manner that is spatially unlike WMV scaling. Collectively, these findings provide a more complete view of anatomic scaling in the human brain, and offer new contexts for the interpretation of regional white matter variation in health and disease.SIGNIFICANCE STATEMENT Recent work has shown that, in humans, regional cortical and subcortical anatomy show systematic changes as a function of brain size variation. Here, we show that regional white matter structures also show brain-size related changes in humans. Specifically, white matter regions connecting higher-order cortical systems are relatively expanded in larger human brains, while subcortical and cerebellar white matter tracts responsible for unimodal sensory or motor functions are relatively contracted. This regional scaling of white matter volume (WMV) is coordinated with regional scaling of cortical anatomy, but is distinct from scaling of white matter microstructure. These findings provide a more complete view of anatomic scaling of the human brain, with relevance for evolutionary, basic, and clinical neuroscience.
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Affiliation(s)
- Allysa Warling
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, Maryland 20892
| | - Cassidy L McDermott
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, Maryland 20892
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Siyuan Liu
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, Maryland 20892
| | - Jakob Seidlitz
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, Maryland 20892
| | - Amanda L Rodrigue
- Tommy Fuss Center for Neuropsychiatric Disease Research, Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Ajay Nadig
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, Maryland 20892
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania 19104
- Lifespan Brain Institute of the Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, Pennsylvania 19104
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania 19104
- Lifespan Brain Institute of the Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, Pennsylvania 19104
| | - David Roalf
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania 19104
| | - Tyler M Moore
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania 19104
- Lifespan Brain Institute of the Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, Pennsylvania 19104
| | - David Glahn
- Tommy Fuss Center for Neuropsychiatric Disease Research, Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Theodore D Satterthwaite
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania 19104
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, United Kingdom
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, Maryland 20892
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Maekawa T, Hagiwara A, Yokoyama K, Hori M, Andica C, Fujita S, Kamagata K, Wada A, Abe O, Tomizawa Y, Hattori N, Aoki S. Multiple sclerosis plaques may undergo continuous myelin degradation: a cross-sectional study with myelin and axon-related quantitative magnetic resonance imaging metrics. Neuroradiology 2021; 64:465-471. [PMID: 34383123 DOI: 10.1007/s00234-021-02781-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 07/30/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE We hypothesize that myelin is more susceptible to damage over time than axons. We investigated the association between the estimated duration from the onset of multiple sclerosis (MS) plaques and myelin- and axon-related quantitative synthetic magnetic resonance imaging (SyMRI) and neurite orientation dispersion and density imaging (NODDI) metrics. METHODS We analyzed 31 patients with MS with 73 newly appeared plaques. Simple linear regression analysis was performed to assess the association between the estimated duration from the onset of plaques and quantitative MRI metrics. These metrics included the myelin volume fraction (MVF), axon volume fraction, and g-ratio in plaque and normal-appearing white matter. RESULTS MS plaques with a longer estimated duration from onset were significantly correlated with a lower MVF (slope = - 0.0070, R2 = 0.0970), higher g-ratio (slope = 0.0078, R2 = 0.0842) (all P values < 0.05). CONCLUSION These results suggested that myelin in plaques undergoes continuous damage, more so than axons. Myelin imaging with SyMRI and NODDI may be useful for the quantitative assessment of temporal changes in MS plaques.
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Affiliation(s)
- Tomoko Maekawa
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Kazumasa Yokoyama
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
- Department of Diagnostic Radiology, Toho University Omori Medical Center, 6-11-1, Omori-Nishi, Ota-Ku, Tokyo, Japan
| | - Christina Andica
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Shohei Fujita
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
- Departmen of Radiology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Akihiko Wada
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Osamu Abe
- Departmen of Radiology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Yuji Tomizawa
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
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Sugiyama A, Cooper G, Hirano S, Yokota H, Mori M, Shimizu K, Yakiyama M, Finke C, Brandt AU, Paul F, Kuwabara S. Cognitive Impairment in Multiple System Atrophy Is Related to White Matter Damage Detected by the T1-Weighted/T2-Weighted Ratio. Eur Neurol 2021; 84:435-443. [PMID: 34284398 DOI: 10.1159/000517360] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 05/15/2021] [Indexed: 11/19/2022]
Abstract
INTRODUCTION This study aimed to use a novel MRI contrast, the standardized T1-weighted/T2-weighted (sT1w/T2w) ratio, to assess damage of the white matter and gray matter in multiple system atrophy (MSA). Furthermore, this study investigated whether the sT1w/T2w ratio was associated with cognitive impairment in MSA. METHODS The white matter and gray matter sT1w/T2w ratio of 37 MSA patients and 19 healthy controls were measured. Correlation analyses were used to evaluate the relationship between sT1w/T2w ratio values and clinical variables, and a multivariate analysis was used to identify independent factors associated with cognitive impairment in MSA. RESULTS MSA patients showed a higher white matter sT1w/T2w ratio value than controls (p < 0.001), and the white matter sT1w/T2w ratio value was significantly correlated with the International Cooperative Ataxia Rating Scale score (r = 0.377, p = 0.021) and the Addenbrooke's cognitive examination III score (r = -0.438, p = 0.007). Cognitively impaired MSA patients had a significantly higher white matter sT1w/T2w ratio value than cognitively preserved MSA patients (p = 0.010), and the multiple logistic regression analysis revealed that the median white matter sT1w/T2w ratio value was independently associated with cognitive impairment in MSA. CONCLUSION The sT1w/T2w ratio is sensitive to degenerative changes in the white matter that is associated with cognitive ability in MSA patients.
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Affiliation(s)
- Atsuhiko Sugiyama
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Graham Cooper
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,Department of Experimental Neurology and Center for Stroke Research, Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Shigeki Hirano
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba, Japan.,Medical Center for Dementia, Chiba University Hospital, Chiba, Japan
| | - Hajime Yokota
- Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Masahiro Mori
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Keisuke Shimizu
- Medical Center for Dementia, Chiba University Hospital, Chiba, Japan
| | | | - Carsten Finke
- Einstein Center for Neurosciences, Berlin, Germany.,Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Department of Neurology, University of California, Irvine, California, USA
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Satoshi Kuwabara
- Department of Neurology, Graduate School of Medicine, Chiba University, Chiba, Japan.,Medical Center for Dementia, Chiba University Hospital, Chiba, Japan
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Granziera C, Wuerfel J, Barkhof F, Calabrese M, De Stefano N, Enzinger C, Evangelou N, Filippi M, Geurts JJG, Reich DS, Rocca MA, Ropele S, Rovira À, Sati P, Toosy AT, Vrenken H, Gandini Wheeler-Kingshott CAM, Kappos L. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 2021; 144:1296-1311. [PMID: 33970206 PMCID: PMC8219362 DOI: 10.1093/brain/awab029] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 10/25/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.
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Affiliation(s)
- Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland
- Quantitative Biomedical Imaging Group (qbig), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
- UCL Institutes of Healthcare Engineering and Neurology, London, UK
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Neurology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Christian Enzinger
- Department of Neurology and Division of Neuroradiology, Medical University of Graz, Graz, Austria
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, multiple sclerosis Center Amsterdam, Neuroscience Amsterdam, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Ropele
- Neuroimaging Research Unit, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Vall d'Hebron University Hospital and Research Institute, Barcelona, Spain
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ahmed T Toosy
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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49
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Norbom LB, Ferschmann L, Parker N, Agartz I, Andreassen OA, Paus T, Westlye LT, Tamnes CK. New insights into the dynamic development of the cerebral cortex in childhood and adolescence: Integrating macro- and microstructural MRI findings. Prog Neurobiol 2021; 204:102109. [PMID: 34147583 DOI: 10.1016/j.pneurobio.2021.102109] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 04/26/2021] [Accepted: 06/15/2021] [Indexed: 12/11/2022]
Abstract
Through dynamic transactional processes between genetic and environmental factors, childhood and adolescence involve reorganization and optimization of the cerebral cortex. The cortex and its development plays a crucial role for prototypical human cognitive abilities. At the same time, many common mental disorders appear during these critical phases of neurodevelopment. Magnetic resonance imaging (MRI) can indirectly capture several multifaceted changes of cortical macro- and microstructure, of high relevance to further our understanding of the neural foundation of cognition and mental health. Great progress has been made recently in mapping the typical development of cortical morphology. Moreover, newer less explored MRI signal intensity and specialized quantitative T2 measures have been applied to assess microstructural cortical development. We review recent findings of typical postnatal macro- and microstructural development of the cerebral cortex from early childhood to young adulthood. We cover studies of cortical volume, thickness, area, gyrification, T1-weighted (T1w) tissue contrasts such a grey/white matter contrast, T1w/T2w ratio, magnetization transfer and myelin water fraction. Finally, we integrate imaging studies with cortical gene expression findings to further our understanding of the underlying neurobiology of the developmental changes, bridging the gap between ex vivo histological- and in vivo MRI studies.
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Affiliation(s)
- Linn B Norbom
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
| | - Lia Ferschmann
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway
| | - Nadine Parker
- Institute of Medical Science, University of Toronto, Ontario, Canada
| | - Ingrid Agartz
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway
| | - Ole A Andreassen
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Tomáš Paus
- ECOGENE-21, Chicoutimi, Quebec, Canada; Department of Psychology and Psychiatry, University of Toronto, Ontario, Canada; Department of Psychiatry and Centre hospitalier universitaire Sainte-Justine, University of Montreal, Canada
| | - Lars T Westlye
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway
| | - Christian K Tamnes
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
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50
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Rowley CD, Campbell JSW, Wu Z, Leppert IR, Rudko DA, Pike GB, Tardif CL. A model-based framework for correcting B 1 + inhomogeneity effects in magnetization transfer saturation and inhomogeneous magnetization transfer saturation maps. Magn Reson Med 2021; 86:2192-2207. [PMID: 33956348 DOI: 10.1002/mrm.28831] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 03/08/2021] [Accepted: 04/16/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE In this work, we propose that Δ B 1 + -induced errors in magnetization transfer (MT) saturation (MTsat ) maps can be corrected with use of an R1 and B 1 + map and through numerical simulations of the sequence. THEORY AND METHODS One healthy subject was scanned at 3.0T using a partial quantitative MT protocol to estimate the relationship between observed R1 (R1,obs ) and apparent bound pool size ( M 0 , a p p B ) in the brain. MTsat values were simulated for a range of B 1 + , R1,obs , and M 0 , a p p B . An equation was fit to the simulated MTsat , then a linear relationship between R1,obs and M 0 , a p p B was generated. These results were used to generate correction factor maps for the MTsat acquired from single-point data. The proposed correction was compared to an empirical correction factor with different MT-preparation schemes. RESULTS M 0 , a p p B was highly correlated with R1,obs (r > 0.96), permitting the use of R1,obs to estimate M 0 , a p p B for B 1 + correction. All B 1 + corrected MTsat maps displayed a decreased correlation with B 1 + compared to uncorrected MTsat and MTsat corrected with an empirical factor in the corpus callosum. There was good agreement between the proposed approach and the empirical correction with radiofrequency saturation at 2 kHz, with larger deviations seen when using saturation pulses further off-resonance and in inhomogeneous (ih) MTsat maps. CONCLUSION The proposed correction decreases the dependence of MTsat on B 1 + inhomogeneities. Furthermore, this flexible framework permits the use of different saturation protocols, making it useful for correcting B 1 + inhomogeneities in ihMT.
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Affiliation(s)
- Christopher D Rowley
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Jennifer S W Campbell
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Zhe Wu
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.,Techna Institute, University Health Network, Toronto, Ontario, Canada
| | - Ilana R Leppert
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - David A Rudko
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.,Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Gilbert Bruce Pike
- Hotchkiss Brain Institute and Departments of Radiology and Clinical Neuroscience, University of Calgary, Calgary, Canada
| | - Christine L Tardif
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.,Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
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