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Thanaraju A, Marzuki AA, Chan JK, Wong KY, Phon-Amnuaisuk P, Vafa S, Chew J, Chia YC, Jenkins M. Structural and functional brain correlates of socioeconomic status across the life span: A systematic review. Neurosci Biobehav Rev 2024; 162:105716. [PMID: 38729281 DOI: 10.1016/j.neubiorev.2024.105716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 04/08/2024] [Accepted: 05/06/2024] [Indexed: 05/12/2024]
Abstract
It is well-established that higher socioeconomic status (SES) is associated with improved brain health. However, the effects of SES across different life stages on brain structure and function is still equivocal. In this systematic review, we aimed to synthesise findings from life course neuroimaging studies that investigated the structural and functional brain correlates of SES across the life span. The results indicated that higher SES across different life stages were independently and cumulatively related to neural outcomes typically reflective of greater brain health (e.g., increased cortical thickness, grey matter volume, fractional anisotropy, and network segregation) in adult individuals. The results also demonstrated that the corticolimbic system was most commonly impacted by socioeconomic disadvantages across the life span. This review highlights the importance of taking into account SES across the life span when studying its effects on brain health. It also provides directions for future research including the need for longitudinal and multimodal research that can inform effective policy interventions tailored to specific life stages.
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Affiliation(s)
- Arjun Thanaraju
- Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Malaysia.
| | - Aleya A Marzuki
- Department for Psychiatry and Psychotherapy, Medical School and University Hospital, Eberhard Karls University of Tübingen, Germany
| | - Jee Kei Chan
- Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Malaysia
| | - Kean Yung Wong
- Sensory Neuroscience and Nutrition Lab, University of Otago, New Zealand
| | - Paveen Phon-Amnuaisuk
- Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Malaysia
| | - Samira Vafa
- Department of Psychology, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Jactty Chew
- Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Yook Chin Chia
- Department of Medical Sciences, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Michael Jenkins
- Department of Psychology, School of Medical and Life Sciences, Sunway University, Malaysia
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Deveshwar N, Yao J, Han M, Dwork N, Shen X, Ljungberg E, Caverzasi E, Cao P, Henry R, Green A, Larson PEZ. Quantification of the in vivo brain ultrashort-T 2* component in healthy volunteers. Magn Reson Med 2024; 91:2417-2430. [PMID: 38291598 DOI: 10.1002/mrm.30013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 12/14/2023] [Accepted: 12/29/2023] [Indexed: 02/01/2024]
Abstract
PURPOSE Recent work has shown MRI is able to measure and quantify signals of phospholipid membrane-bound protons associated with myelin in the human brain. This work seeks to develop an improved technique for characterizing this brain ultrashort-T 2 ∗ $$ {\mathrm{T}}_2\ast $$ component in vivo accounting forT 1 $$ {\mathrm{T}}_1 $$ weighting. METHODS Data from ultrashort echo time scans from 16 healthy volunteers with variable flip angles (VFA) were collected and fitted into an advanced regression model to quantify signal fraction, relaxation time, and frequency shift of the ultrashort-T 2 ∗ $$ {\mathrm{T}}_2\ast $$ component. RESULTS The fitted components show intra-subject differences of different white matter structures and significantly elevated ultrashort-T 2 ∗ $$ {\mathrm{T}}_2\ast $$ signal fraction in the corticospinal tracts measured at 0.09 versus 0.06 in other white matter structures and significantly elevated ultrashort-T 2 ∗ $$ {\mathrm{T}}_2\ast $$ frequency shift in the body of the corpus callosum at- $$ - $$ 1.5 versus- $$ - $$ 2.0 ppm in other white matter structures. CONCLUSION The significantly different measured components and measuredT 1 $$ {\mathrm{T}}_1 $$ relaxation time of the ultrashort-T 2 ∗ $$ {\mathrm{T}}_2\ast $$ component suggest that this method is picking up novel signals from phospholipid membrane-bound protons.
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Affiliation(s)
- Nikhil Deveshwar
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
- UC Berkeley - UCSF Graduate Program in Bioengineering, San Francisco, California, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, California, USA
| | - Jingwen Yao
- UC Berkeley - UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Misung Han
- UC Berkeley - UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Nicholas Dwork
- Departments of Biomedical Informatics and Radiology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Xin Shen
- UC Berkeley - UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Emil Ljungberg
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Eduardo Caverzasi
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Peng Cao
- Department of Diagnostic Radiology, Hong Kong University, Hong Kong, China
| | - Roland Henry
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Ari Green
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
- UC Berkeley - UCSF Graduate Program in Bioengineering, San Francisco, California, USA
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Kohli JS, Linke AC, Martindale IA, Wilkinson M, Kinnear MK, Lincoln AJ, Hau J, Shryock I, Omaleki V, Alemu K, Pedrahita S, Fishman I, Müller R, Carper RA. Associations between atypical intracortical myelin content and neuropsychological functions in middle to older aged adults with ASD. Brain Behav 2024; 14:e3594. [PMID: 38849980 PMCID: PMC11161394 DOI: 10.1002/brb3.3594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 05/06/2024] [Accepted: 05/23/2024] [Indexed: 06/09/2024] Open
Abstract
INTRODUCTION In vivo myeloarchitectonic mapping based on Magnetic Resonance Imaging (MRI) provides a unique view of gray matter myelin content and offers information complementary to other morphological indices commonly employed in studies of autism spectrum disorder (ASD). The current study sought to determine if intracortical myelin content (MC) and its age-related trajectories differ between middle aged to older adults with ASD and age-matched typical comparison participants. METHODS Data from 30 individuals with ASD and 36 age-matched typical comparison participants aged 40-70 years were analyzed. Given substantial heterogeneity in both etiology and outcomes in ASD, we utilized both group-level and subject-level analysis approaches to test for signs of atypical intracortical MC as estimated by T1w/T2w ratio. RESULTS Group-level analyses showed no significant differences in average T1w/T2w ratio or its associations with age between groups, but revealed significant positive main effects of age bilaterally, with T1w/T2w ratio increasing with age across much of the cortex. In subject-level analyses, participants were classified into subgroups based on presence or absence of clusters of aberrant T1w/T2w ratio, and lower neuropsychological function was observed in the ASD subgroup with atypically high T1w/T2w ratio in spatially heterogeneous cortical regions. These differences were observed across several neuropsychological domains, including overall intellectual functioning, processing speed, and aspects of executive function. CONCLUSIONS The group-level and subject-level approaches employed here demonstrate the value of examining inter-individual variability and provide important preliminary insights into relationships between brain structure and cognition in the second half of the lifespan in ASD, suggesting shared factors contributing to atypical intracortical myelin content and poorer cognitive outcomes for a subset of middle aged to older autistic adults. These atypicalities likely reflect diverse histories of neurodevelopmental deficits, and possible compensatory changes, compounded by processes of aging, and may serve as useful markers of vulnerability to further cognitive decline in older adults with ASD.
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Affiliation(s)
- Jiwandeep S. Kohli
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
- San Diego Joint Doctoral Program in Clinical PsychologySan Diego State University/University of CaliforniaSan DiegoCaliforniaUSA
| | - Annika C. Linke
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ian A. Martindale
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Molly Wilkinson
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
- San Diego Joint Doctoral Program in Clinical PsychologySan Diego State University/University of CaliforniaSan DiegoCaliforniaUSA
| | - Mikaela K. Kinnear
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Alan J. Lincoln
- California School of Professional PsychologyAlliant International UniversitySan DiegoCaliforniaUSA
| | - Janice Hau
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ian Shryock
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Vinton Omaleki
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Kalekirstos Alemu
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Stephanie Pedrahita
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Inna Fishman
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ralph‐Axel Müller
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ruth A. Carper
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
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Lazari A, Tachrount M, Valverde JM, Papp D, Beauchamp A, McCarthy P, Ellegood J, Grandjean J, Johansen-Berg H, Zerbi V, Lerch JP, Mars RB. The mouse motor system contains multiple premotor areas and partially follows human organizational principles. Cell Rep 2024; 43:114191. [PMID: 38717901 DOI: 10.1016/j.celrep.2024.114191] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 12/10/2023] [Accepted: 04/17/2024] [Indexed: 06/01/2024] Open
Abstract
While humans are known to have several premotor cortical areas, secondary motor cortex (M2) is often considered to be the only higher-order motor area of the mouse brain and is thought to combine properties of various human premotor cortices. Here, we show that axonal tracer, functional connectivity, myelin mapping, gene expression, and optogenetics data contradict this notion. Our analyses reveal three premotor areas in the mouse, anterior-lateral motor cortex (ALM), anterior-lateral M2 (aM2), and posterior-medial M2 (pM2), with distinct structural, functional, and behavioral properties. By using the same techniques across mice and humans, we show that ALM has strikingly similar functional and microstructural properties to human anterior ventral premotor areas and that aM2 and pM2 amalgamate properties of human pre-SMA and cingulate cortex. These results provide evidence for the existence of multiple premotor areas in the mouse and chart a comparative map between the motor systems of humans and mice.
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Affiliation(s)
- Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Mohamed Tachrount
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Juan Miguel Valverde
- DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark; A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, 70150 Kuopio, Finland
| | - Daniel Papp
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Antoine Beauchamp
- Mouse Imaging Centre, The Hospital for Sick Children, Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Paul McCarthy
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Jacob Ellegood
- Mouse Imaging Centre, The Hospital for Sick Children, Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
| | - Joanes Grandjean
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Heidi Johansen-Berg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFL, 1015 Lausanne, Switzerland; CIBM Center for Biomedical Imaging, 1015 Lausanne, Switzerland
| | - Jason P Lerch
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Mouse Imaging Centre, The Hospital for Sick Children, Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
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Lee CH, Holloman M, Salzer JL, Zhang J. Multi-parametric MRI can detect enhanced myelination in the Gli1 -/- mouse brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.20.567957. [PMID: 38045415 PMCID: PMC10690149 DOI: 10.1101/2023.11.20.567957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
This study investigated the potential of combining multiple MR parameters to enhance the characterization of myelin in the mouse brain. We collected ex vivo multi-parametric MR data at 7 Tesla from control and Gli1 -/- mice; the latter exhibit enhanced myelination at postnatal day 10 (P10) in the corpus callosum and cortex. The MR data included relaxivity, magnetization transfer, and diffusion measurements, each targeting distinct myelin properties. This analysis was followed by and compared to myelin basic protein (MBP) staining of the same samples. Although a majority of the MR parameters included in this study showed significant differences in the corpus callosum between the control and Gli1 -/- mice, only T 2 , T 1 /T 2, and radial diffusivity (RD) demonstrated a significant correlation with MBP values. Based on data from the corpus callosum, partial least square regression suggested that combining T 2 , T 1 /T 2 , and inhomogeneous magnetization transfer ratio could explain approximately 80% of the variance in the MBP values. Myelin predictions based on these three parameters yielded stronger correlations with the MBP values in the P10 mouse brain corpus callosum than any single MR parameter. In the motor cortex, combining T 2 , T 1 /T 2, and radial kurtosis could explain over 90% of the variance in the MBP values at P10. This study demonstrates the utility of multi-parametric MRI in improving the detection of myelin changes in the mouse brain.
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6
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Boudreau M, Karakuzu A, Cohen-Adad J, Bozkurt E, Carr M, Castellaro M, Concha L, Doneva M, Dual SA, Ensworth A, Foias A, Fortier V, Gabr RE, Gilbert G, Glide-Hurst CK, Grech-Sollars M, Hu S, Jalnefjord O, Jovicich J, Keskin K, Koken P, Kolokotronis A, Kukran S, Lee NG, Levesque IR, Li B, Ma D, Mädler B, Maforo NG, Near J, Pasaye E, Ramirez-Manzanares A, Statton B, Stehning C, Tambalo S, Tian Y, Wang C, Weiss K, Zakariaei N, Zhang S, Zhao Z, Stikov N. Repeat it without me: Crowdsourcing the T 1 mapping common ground via the ISMRM reproducibility challenge. Magn Reson Med 2024. [PMID: 38730562 DOI: 10.1002/mrm.30111] [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: 10/17/2023] [Revised: 03/21/2024] [Accepted: 03/23/2024] [Indexed: 05/13/2024]
Abstract
PURPOSE T1 mapping is a widely used quantitative MRI technique, but its tissue-specific values remain inconsistent across protocols, sites, and vendors. The ISMRM Reproducible Research and Quantitative MR study groups jointly launched a challenge to assess the reproducibility of a well-established inversion-recovery T1 mapping technique, using acquisition details from a seminal T1 mapping paper on a standardized phantom and in human brains. METHODS The challenge used the acquisition protocol from Barral et al. (2010). Researchers collected T1 mapping data on the ISMRM/NIST phantom and/or in human brains. Data submission, pipeline development, and analysis were conducted using open-source platforms. Intersubmission and intrasubmission comparisons were performed. RESULTS Eighteen submissions (39 phantom and 56 human datasets) on scanners by three MRI vendors were collected at 3 T (except one, at 0.35 T). The mean coefficient of variation was 6.1% for intersubmission phantom measurements, and 2.9% for intrasubmission measurements. For humans, the intersubmission/intrasubmission coefficient of variation was 5.9/3.2% in the genu and 16/6.9% in the cortex. An interactive dashboard for data visualization was also developed: https://rrsg2020.dashboards.neurolibre.org. CONCLUSION The T1 intersubmission variability was twice as high as the intrasubmission variability in both phantoms and human brains, indicating that the acquisition details in the original paper were insufficient to reproduce a quantitative MRI protocol. This study reports the inherent uncertainty in T1 measures across independent research groups, bringing us one step closer to a practical clinical baseline of T1 variations in vivo.
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Affiliation(s)
- Mathieu Boudreau
- NeuroPoly Lab, Polytechnique Montréal, Montréal, Quebec, Canada
- Montreal Heart Institute, Montréal, Quebec, Canada
| | - Agah Karakuzu
- NeuroPoly Lab, Polytechnique Montréal, Montréal, Quebec, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Polytechnique Montréal, Montréal, Quebec, Canada
- Montreal Heart Institute, Montréal, Quebec, Canada
- Unité de Neuroimagerie Fonctionnelle, Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, Quebec, Canada
- Mila-Quebec AI Institute, Montréal, Québec, Canada
- Centre de Recherche du CHU Sainte-Justine, Université de Montréal, Montréal, Québec, Canada
| | - Ecem Bozkurt
- Magnetic Resonance Engineering Laboratory, University of Southern California, Los Angeles, California, USA
| | - Madeline Carr
- Medical Physics, Ingham Institute for Applied Medical Research, Liverpool, Australia
- Department of Medical Physics, Liverpool and Macarthur Cancer Therapy Centers, Liverpool, Australia
| | - Marco Castellaro
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | | | - Seraina A Dual
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Alex Ensworth
- Medical Physics Unit, McGill University, Montréal, Québec, Canada
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Alexandru Foias
- NeuroPoly Lab, Polytechnique Montréal, Montréal, Quebec, Canada
| | - Véronique Fortier
- Department of Medical Imaging, McGill University Health Center, Montréal, Québec, Canada
- Department of Radiology, McGill University, Montréal, Québec, Canada
| | - Refaat E Gabr
- Department of Diagnostic and Interventional Imaging, University of Texas Health Science Center at Houston, McGovern Medical School, Houston, Texas, USA
| | | | - Carri K Glide-Hurst
- Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Matthew Grech-Sollars
- Center for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Siyuan Hu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Oscar Jalnefjord
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Kübra Keskin
- Magnetic Resonance Engineering Laboratory, University of Southern California, Los Angeles, California, USA
| | | | - Anastasia Kolokotronis
- Medical Physics Unit, McGill University, Montréal, Québec, Canada
- Hopital Maisonneuve-Rosemont, Montréal, Québec, Canada
| | - Simran Kukran
- Bioengineering, Imperial College London, London, UK
- Radiotherapy and Imaging, Institute of Cancer Research, Imperial College London, London, UK
| | - Nam G Lee
- Magnetic Resonance Engineering Laboratory, University of Southern California, Los Angeles, California, USA
| | - Ives R Levesque
- Medical Physics Unit, McGill University, Montréal, Québec, Canada
- Research Institute of the McGill University Health Center, Montréal, Québec, Canada
| | - Bochao Li
- Magnetic Resonance Engineering Laboratory, University of Southern California, Los Angeles, California, USA
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | | | - Nyasha G Maforo
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA
- Physics and Biology in Medicine IDP, University of California Los Angeles, Los Angeles, California, USA
| | - Jamie Near
- Douglas Brain Imaging Center, Montréal, Québec, Canada
- Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Erick Pasaye
- Institute of Neurobiology, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | | | - Ben Statton
- Medical Research Council, London Institute of Medical Sciences, Imperial College London, London, UK
| | | | - Stefano Tambalo
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Ye Tian
- Magnetic Resonance Engineering Laboratory, University of Southern California, Los Angeles, California, USA
| | - Chenyang Wang
- Department of Radiation Oncology-CNS Service, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Kilian Weiss
- Clinical Science, Philips Healthcare, Hamburg, Germany
| | - Niloufar Zakariaei
- Department of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada
| | - Shuo Zhang
- Clinical Science, Philips Healthcare, Hamburg, Germany
| | - Ziwei Zhao
- Magnetic Resonance Engineering Laboratory, University of Southern California, Los Angeles, California, USA
| | - Nikola Stikov
- NeuroPoly Lab, Polytechnique Montréal, Montréal, Quebec, Canada
- Montreal Heart Institute, Montréal, Quebec, Canada
- Center for Advanced Interdisciplinary Research, Ss. Cyril and Methodius University, Skopje, North Macedonia
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7
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Lazzarotto A, Hamzaoui M, Tonietto M, Dubessy AL, Khalil M, Pirpamer L, Ropele S, Enzinger C, Battaglini M, Stromillo ML, De Stefano N, Filippi M, Rocca MA, Gallo P, Gasperini C, Stankoff B, Bodini B. Time is myelin: early cortical myelin repair prevents atrophy and clinical progression in multiple sclerosis. Brain 2024; 147:1331-1343. [PMID: 38267729 PMCID: PMC10994569 DOI: 10.1093/brain/awae024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 12/15/2023] [Accepted: 01/13/2024] [Indexed: 01/26/2024] Open
Abstract
Cortical myelin loss and repair in multiple sclerosis (MS) have been explored in neuropathological studies, but the impact of these processes on neurodegeneration and the irreversible clinical progression of the disease remains unknown. Here, we evaluated in vivo cortical demyelination and remyelination in a large cohort of people with all clinical phenotypes of MS followed up for 5 years using magnetization transfer imaging (MTI), a technique that has been shown to be sensitive to myelin content changes in the cortex. We investigated 140 people with MS (37 clinically isolated syndrome, 71 relapsing-MS, 32 progressive-MS), who were clinically assessed at baseline and after 5 years and, along with 84 healthy controls, underwent a 3 T-MRI protocol including MTI at baseline and after 1 year. Changes in cortical volume over the radiological follow-up were computed with a Jacobian integration method. Magnetization transfer ratio was employed to calculate for each patient an index of cortical demyelination at baseline and of dynamic cortical demyelination and remyelination over the follow-up period. The three indices of cortical myelin content change were heterogeneous across patients but did not significantly differ across clinical phenotypes or treatment groups. Cortical remyelination, which tended to fail in the regions closer to CSF (-11%, P < 0.001), was extensive in half of the cohort and occurred independently of age, disease duration and clinical phenotype. Higher indices of cortical dynamic demyelination (β = 0.23, P = 0.024) and lower indices of cortical remyelination (β = -0.18, P = 0.03) were significantly associated with greater cortical atrophy after 1 year, independently of age and MS phenotype. While the extent of cortical demyelination predicted a higher probability of clinical progression after 5 years in the entire cohort [odds ratio (OR) = 1.2; P = 0.043], the impact of cortical remyelination in reducing the risk of accumulating clinical disability after 5 years was significant only in the subgroup of patients with shorter disease duration and limited extent of demyelination in cortical regions (OR = 0.86, P = 0.015, area under the curve = 0.93). In this subgroup, a 30% increase in cortical remyelination nearly halved the risk of clinical progression at 5 years, independently of clinical relapses. Overall, our results highlight the critical role of cortical myelin dynamics in the cascade of events leading to neurodegeneration and to the subsequent accumulation of irreversible disability in MS. Our findings suggest that early-stage myelin repair compensating for cortical myelin loss has the potential to prevent neuro-axonal loss and its long-term irreversible clinical consequences in people with MS.
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Affiliation(s)
- Andrea Lazzarotto
- Department of Neuroscience, Sorbonne Université, Paris Brain Institute, CNRS, Inserm, 75013 Paris, France
- AP-HP, Hôpital Universitaire Pitié-Salpêtrière, 75013 Paris, France
- Padova Neuroscience Center, University of Padua, 35122 Padua, Italy
| | - Mariem Hamzaoui
- Department of Neuroscience, Sorbonne Université, Paris Brain Institute, CNRS, Inserm, 75013 Paris, France
| | - Matteo Tonietto
- Université Paris-Saclay, CEA, CNRS, Inserm, BioMaps, Service Hospitalier Frédéric Joliot, 91400 Orsay, France
- Roche Pharma Research & Early Development, F. Hoffmann-La Roche Ltd., CH-4070 Basel, Switzerland
| | | | - Michael Khalil
- Department of Neurology, Medical University of Graz, 8036 Graz, Austria
| | - Lukas Pirpamer
- Department of Neurology, Medical University of Graz, 8036 Graz, Austria
- Medical Image Analysis Center (MIAC) and Department of Biomedical Engineering, University of Basel, CH-4051 Basel, Switzerland
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, 8036 Graz, Austria
| | | | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, 53100 Siena, Italy
| | - Maria Laura Stromillo
- Department of Medicine, Surgery and Neuroscience, University of Siena, 53100 Siena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, 53100 Siena, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
| | - Maria Assunta Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
| | - Paolo Gallo
- Padova Neuroscience Center, University of Padua, 35122 Padua, Italy
- Multiple Sclerosis Centre of Veneto Region, 35128 Padua, Italy
| | | | - Bruno Stankoff
- Department of Neuroscience, Sorbonne Université, Paris Brain Institute, CNRS, Inserm, 75013 Paris, France
- AP-HP, Hôpital Universitaire Pitié-Salpêtrière, 75013 Paris, France
| | - Benedetta Bodini
- Department of Neuroscience, Sorbonne Université, Paris Brain Institute, CNRS, Inserm, 75013 Paris, France
- AP-HP, Hôpital Universitaire Pitié-Salpêtrière, 75013 Paris, France
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8
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Reveley C, Ye FQ, Leopold DA. Diffusion kurtosis MRI tracks gray matter myelin content in the primate cerebral cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.08.584058. [PMID: 38496676 PMCID: PMC10942417 DOI: 10.1101/2024.03.08.584058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Diffusion magnetic resonance imaging (dMRI) has been widely employed to model the trajectory of myelinated fiber bundles in white matter. Increasingly, dMRI is also used to assess local tissue properties throughout the brain. In the cerebral cortex, myelin content is a critical indicator of the maturation, regional variation, and disease related degeneration of gray matter tissue. Gray matter myelination can be measured and mapped using several non-diffusion MRI strategies; however, first order diffusion statistics such as fractional anisotropy (FA) show only weak spatial correlation with cortical myelin content. Here we show that a simple higher order diffusion parameter, the mean diffusion kurtosis (MK), is strongly correlated with the laminar and regional variation of myelin in the primate cerebral cortex. We carried out ultra-high resolution, multi-shelled dMRI in ex vivo marmoset monkey brains and compared dMRI parameters from a number of higher order models (diffusion kurtosis, NODDI and MAP MRI) to the distribution of myelin obtained using histological staining, and via Magnetization Transfer Ratio MRI (MTR), a non-diffusion MRI method. In contrast to FA, MK closely matched the myelin content assessed by histology and by MTR in the same sample. The parameter maps from MAP-MRI and NODDI also showed good correspondence with cortical myelin content. The results demonstrate that dMRI can be used to assess the variation of local myelin content in the primate cortical cortex, which may be of great value for assessing tissue integrity and tracking disease in living human patients.
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Affiliation(s)
- Colin Reveley
- Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU, UK
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD
| | - David A Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD
- Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
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9
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Margolis ET, Gabard-Durnam LJ. Prenatal influences on postnatal neuroplasticity: Integrating DOHaD and sensitive/critical period frameworks to understand biological embedding in early development. INFANCY 2024. [PMID: 38449347 DOI: 10.1111/infa.12588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 01/26/2024] [Accepted: 02/13/2024] [Indexed: 03/08/2024]
Abstract
Early environments can have significant and lasting effects on brain, body, and behavior across the lifecourse. Here, we address current research efforts to understand how experiences impact neurodevelopment with a new perspective integrating two well-known conceptual frameworks - the Developmental Origins of Health and Disease (DOHaD) and sensitive/critical period frameworks. Specifically, we consider how prenatal experiences characterized in the DOHaD model impact two key neurobiological mechanisms of sensitive/critical periods for adapting to and learning from the postnatal environment. We draw from both animal and human research to summarize the current state of knowledge on how particular prenatal substance exposures (psychoactive substances and heavy metals) and nutritional profiles (protein-energy malnutrition and iron deficiency) each differentially impact brain circuits' excitation/GABAergic inhibition balance and myelination. Finally, we highlight new research directions that emerge from this integrated framework, including testing how prenatal environments alter sensitive/critical period timing and learning and identifying potential promotional/buffering prenatal exposures to impact postnatal sensitive/critical periods. We hope this integrative framework considering prenatal influences on postnatal neuroplasticity will stimulate new research to understand how early environments have lasting consequences on our brains, behavior, and health.
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Affiliation(s)
- Emma T Margolis
- Department of Psychology, Northeastern University, Boston, Massachusetts, USA
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10
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Franklin RJM, Bodini B, Goldman SA. Remyelination in the Central Nervous System. Cold Spring Harb Perspect Biol 2024; 16:a041371. [PMID: 38316552 PMCID: PMC10910446 DOI: 10.1101/cshperspect.a041371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
The inability of the mammalian central nervous system (CNS) to undergo spontaneous regeneration has long been regarded as a central tenet of neurobiology. However, while this is largely true of the neuronal elements of the adult mammalian CNS, save for discrete populations of granule neurons, the same is not true of its glial elements. In particular, the loss of oligodendrocytes, which results in demyelination, triggers a spontaneous and often highly efficient regenerative response, remyelination, in which new oligodendrocytes are generated and myelin sheaths are restored to denuded axons. Yet remyelination in humans is not without limitation, and a variety of demyelinating conditions are associated with sustained and disabling myelin loss. In this work, we will (1) review the biology of remyelination, including the cells and signals involved; (2) describe when remyelination occurs and when and why it fails, including the consequences of its failure; and (3) discuss approaches for therapeutically enhancing remyelination in demyelinating diseases of both children and adults, both by stimulating endogenous oligodendrocyte progenitor cells and by transplanting these cells into demyelinated brain.
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Affiliation(s)
- Robin J M Franklin
- Altos Labs Cambridge Institute of Science, Cambridge CB21 6GH, United Kingdom
| | - Benedetta Bodini
- Sorbonne Université, Paris Brain Institute, CNRS, INSERM, Paris 75013, France
- Saint-Antoine Hospital, APHP, Paris 75012, France
| | - Steven A Goldman
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, New York 14642, USA
- University of Copenhagen Faculty of Medicine, Copenhagen 2200, Denmark
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11
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Vasylechko SD, Warfield SK, Kurugol S, Afacan O. Improved myelin water fraction mapping with deep neural networks using synthetically generated 3D data. Med Image Anal 2024; 91:102966. [PMID: 37844473 PMCID: PMC10847969 DOI: 10.1016/j.media.2023.102966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 07/14/2023] [Accepted: 09/11/2023] [Indexed: 10/18/2023]
Abstract
We introduce a generative model for synthesis of large scale 3D datasets for quantitative parameter mapping of myelin water fraction (MWF). Our model combines a MR physics signal decay model with an accurate probabilistic multi-component parametric T2 model. We synthetically generate a wide variety of high quality signals and corresponding parameters from a wide range of naturally occurring prior parameter values. To capture spatial variation, the generative signal decay model is combined with a generative spatial model conditioned on generic tissue segmentations. Synthesized 3D datasets can be used to train any convolutional neural network (CNN) based architecture for MWF estimation. Our source code is available at: https://github.com/quin-med-harvard-edu/synthmap Reduction of acquisition time at the expense of lower SNR, as well as accuracy and repeatability of MWF estimation techniques, are key factors that affect the adoption of MWF mapping in clinical practice. We demonstrate that the synthetically trained CNN provides superior accuracy over the competing methods under the constraints of naturally occurring noise levels as well as on the synthetically generated images at low SNR levels. Normalized root mean squared error (nRMSE) is less than 7% on synthetic data, which is significantly lower than competing methods. Additionally, the proposed method yields a coefficient of variation (CoV) that is at least 4x better than the competing method on intra-session test-retest reference dataset.
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Affiliation(s)
- Serge Didenko Vasylechko
- Computational Radiology Laboratory, Boston Children's Hospital, Boston 02115, MA, USA; Harvard Medical School, Boston 02115, MA, USA.
| | - Simon K Warfield
- Computational Radiology Laboratory, Boston Children's Hospital, Boston 02115, MA, USA; Harvard Medical School, Boston 02115, MA, USA
| | - Sila Kurugol
- Computational Radiology Laboratory, Boston Children's Hospital, Boston 02115, MA, USA; Harvard Medical School, Boston 02115, MA, USA
| | - Onur Afacan
- Computational Radiology Laboratory, Boston Children's Hospital, Boston 02115, MA, USA; Harvard Medical School, Boston 02115, MA, USA
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12
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Nelson MC, Royer J, Lu WD, Leppert IR, Campbell JSW, Schiavi S, Jin H, Tavakol S, Vos de Wael R, Rodriguez-Cruces R, Pike GB, Bernhardt BC, Daducci A, Misic B, Tardif CL. The human brain connectome weighted by the myelin content and total intra-axonal cross-sectional area of white matter tracts. Netw Neurosci 2023; 7:1363-1388. [PMID: 38144691 PMCID: PMC10697181 DOI: 10.1162/netn_a_00330] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 07/19/2023] [Indexed: 12/26/2023] Open
Abstract
A central goal in neuroscience is the development of a comprehensive mapping between structural and functional brain features, which facilitates mechanistic interpretation of brain function. However, the interpretability of structure-function brain models remains limited by a lack of biological detail. Here, we characterize human structural brain networks weighted by multiple white matter microstructural features including total intra-axonal cross-sectional area and myelin content. We report edge-weight-dependent spatial distributions, variance, small-worldness, rich club, hubs, as well as relationships with function, edge length, and myelin. Contrasting networks weighted by the total intra-axonal cross-sectional area and myelin content of white matter tracts, we find opposite relationships with functional connectivity, an edge-length-independent inverse relationship with each other, and the lack of a canonical rich club in myelin-weighted networks. When controlling for edge length, networks weighted by either fractional anisotropy, radial diffusivity, or neurite density show no relationship with whole-brain functional connectivity. We conclude that the co-utilization of structural networks weighted by total intra-axonal cross-sectional area and myelin content could improve our understanding of the mechanisms mediating the structure-function brain relationship.
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Affiliation(s)
- Mark C. Nelson
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
| | - Jessica Royer
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
| | - Wen Da Lu
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Ilana R. Leppert
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
| | - Jennifer S. W. Campbell
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | - Hyerang Jin
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
| | - Shahin Tavakol
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
| | - Reinder Vos de Wael
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
| | - Raul Rodriguez-Cruces
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
| | - G. Bruce Pike
- Hotchkiss Brain Institute and Departments of Radiology and Clinical Neuroscience, University of Calgary, Calgary, Canada
| | - Boris C. Bernhardt
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
| | | | - Bratislav Misic
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
| | - Christine L. Tardif
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
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13
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Dvorak AV, Kumar D, Zhang J, Gilbert G, Balaji S, Wiley N, Laule C, Moore GW, MacKay AL, Kolind SH. The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity. SCIENCE ADVANCES 2023; 9:eadh9853. [PMID: 37910622 PMCID: PMC10619933 DOI: 10.1126/sciadv.adh9853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 09/28/2023] [Indexed: 11/03/2023]
Abstract
Quantitative magnetic resonance imaging (MRI) techniques are powerful tools for the study of human tissue, but, in practice, their utility has been limited by lengthy acquisition times. Here, we introduce the Constrained, Adaptive, Low-dimensional, Intrinsically Precise Reconstruction (CALIPR) framework in the context of myelin water imaging (MWI); a quantitative MRI technique generally regarded as the most rigorous approach for noninvasive, in vivo measurement of myelin content. The CALIPR framework exploits data redundancy to recover high-quality images from a small fraction of an imaging dataset, which allowed MWI to be acquired with a previously unattainable sequence (fully sampled acquisition 2 hours:57 min:20 s) in 7 min:26 s (4.2% of the dataset, acceleration factor 23.9). CALIPR quantitative metrics had excellent precision (myelin water fraction mean coefficient of variation 3.2% for the brain and 3.0% for the spinal cord) and markedly increased sensitivity to demyelinating disease pathology compared to a current, widely used technique. The CALIPR framework facilitates drastically improved MWI and could be similarly transformative for other quantitative MRI applications.
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Affiliation(s)
- Adam V. Dvorak
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
| | - Dushyant Kumar
- Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Jing Zhang
- Global MR Applications & Workflow, GE HealthCare Canada, Mississauga, ON, Canada
| | | | - Sharada Balaji
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
| | - Neale Wiley
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
- Radiology, University of British Columbia, Vancouver, BC, Canada
- Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - G.R. Wayne Moore
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
- Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Alex L. MacKay
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Radiology, University of British Columbia, Vancouver, BC, Canada
- Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Shannon H. Kolind
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
- Radiology, University of British Columbia, Vancouver, BC, Canada
- Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
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14
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Galbusera R, Bahn E, Weigel M, Schaedelin S, Franz J, Lu P, Barakovic M, Melie‐Garcia L, Dechent P, Lutti A, Sati P, Reich DS, Nair G, Brück W, Kappos L, Stadelmann C, Granziera C. Postmortem quantitative MRI disentangles histological lesion types in multiple sclerosis. Brain Pathol 2023; 33:e13136. [PMID: 36480267 PMCID: PMC10580009 DOI: 10.1111/bpa.13136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 11/16/2022] [Indexed: 12/13/2022] Open
Abstract
Quantitative MRI (qMRI) probes the microstructural properties of the central nervous system (CNS) by providing biophysical measures of tissue characteristics. In this work, we aimed to (i) identify qMRI measures that distinguish histological lesion types in postmortem multiple sclerosis (MS) brains, especially the remyelinated ones; and to (ii) investigate the relationship between those measures and quantitative histological markers of myelin, axons, and astrocytes in the same experimental setting. Three fixed MS whole brains were imaged with qMRI at 3T to obtain magnetization transfer ratio (MTR), myelin water fraction (MWF), quantitative T1 (qT1), quantitative susceptibility mapping (QSM), fractional anisotropy (FA) and radial diffusivity (RD) maps. The identification of lesion types (active, inactive, chronic active, or remyelinated) and quantification of tissue components were performed using histological staining methods as well as immunohistochemistry and immunofluorescence. Pairwise logistic and LASSO regression models were used to identify the best qMRI discriminators of lesion types. The association between qMRI and quantitative histological measures was performed using Spearman's correlations and linear mixed-effect models. We identified a total of 65 lesions. MTR and MWF best predicted the chance of a lesion to be remyelinated, whereas RD and QSM were useful in the discrimination of active lesions. The measurement of microstructural properties through qMRI did not show any difference between chronic active and inactive lesions. MWF and RD were associated with myelin content in both lesions and normal-appearing white matter (NAWM), FA was the measure most associated with axon content in both locations, while MWF was associated with astrocyte immunoreactivity only in lesions. Moreover, we provided evidence of extensive astrogliosis in remyelinated lesions. Our study provides new information on the discriminative power of qMRI in differentiating MS lesions -especially remyelinated ones- as well as on the relative association between multiple qMRI measures and myelin, axon and astrocytes.
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Affiliation(s)
- Riccardo Galbusera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Erik Bahn
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
| | - Matthias Weigel
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
- Division of Radiological Physics, Department of RadiologyUniversity Hospital BaselBaselSwitzerland
| | - Sabine Schaedelin
- Clinical Trial Unit, Department of Clinical ResearchUniversity Hospital Basel, University of BaselBaselSwitzerland
| | - Jonas Franz
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
- Campus Institute for Dynamics of Biological NetworksUniversity of GöttingenGöttingenGermany
- Max Planck Institute for Experimental MedicineGöttingenGermany
| | - Po‐Jui Lu
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Lester Melie‐Garcia
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Peter Dechent
- Department of Cognitive NeurologyMR‐Research in Neurosciences, University Medical Center GöttingenGöttingenGermany
| | - Antoine Lutti
- Centre for Research in Neuroscience, Department of Clinical NeurosciencesLaboratoire de Recherche en Neuroimagerie (LREN) University Hospital and University of LausanneLausanneSwitzerland
| | - Pascal Sati
- Department of NeurologyCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Daniel S. Reich
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMarylandUSA
| | - Govind Nair
- National Institute of Neurological Disorders and StrokeBethesdaMarylandUSA
| | - Wolfgang Brück
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Christine Stadelmann
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
- Cluster of Excellence “Multiscale Bioimaging: from Molecular Machines to Network of Excitable Cells (MBExC) ”University of GoettingenGermany
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
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15
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Denis C, Dabbs K, Nair VA, Mathis J, Almane DN, Lakshmanan A, Nencka A, Birn RM, Conant L, Humphries C, Felton E, Raghavan M, DeYoe EA, Binder JR, Hermann B, Prabhakaran V, Bendlin BB, Meyerand ME, Boly M, Struck AF. T1-/T2-weighted ratio reveals no alterations to gray matter myelination in temporal lobe epilepsy. Ann Clin Transl Neurol 2023; 10:2149-2154. [PMID: 37872734 PMCID: PMC10647008 DOI: 10.1002/acn3.51653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 05/29/2022] [Accepted: 06/09/2022] [Indexed: 10/25/2023] Open
Abstract
Short-range functional connectivity in the limbic network is increased in patients with temporal lobe epilepsy (TLE), and recent studies have shown that cortical myelin content correlates with fMRI connectivity. We thus hypothesized that myelin may increase progressively in the epileptic network. We compared T1w/T2w gray matter myelin maps between TLE patients and age-matched controls and assessed relationships between myelin and aging. While both TLE patients and healthy controls exhibited increased T1w/T2w intensity with age, we found no evidence for significant group-level aberrations in overall myelin content or myelin changes through time in TLE.
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Affiliation(s)
- Colin Denis
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Kevin Dabbs
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Veena A. Nair
- Department of RadiologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Jedidiah Mathis
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Dace N. Almane
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | | | - Andrew Nencka
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Rasmus M. Birn
- Department of RadiologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of PsychiatryUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Lisa Conant
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Colin Humphries
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Elizabeth Felton
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Manoj Raghavan
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Edgar A. DeYoe
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
- Department of BiophysicsMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Jeffrey R. Binder
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
- Department of BiophysicsMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Bruce Hermann
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Vivek Prabhakaran
- Department of RadiologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Barbara B. Bendlin
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Mary E. Meyerand
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of Biomedical EngineeringUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Mélanie Boly
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of PsychiatryUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Aaron F. Struck
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- William S. Middleton Veterans Administration HospitalMadisonWisconsinUSA
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16
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Lukarski D, Petkoski S, Ji P, Stankovski T. Delta-alpha cross-frequency coupling for different brain regions. CHAOS (WOODBURY, N.Y.) 2023; 33:103126. [PMID: 37844293 DOI: 10.1063/5.0157979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 09/26/2023] [Indexed: 10/18/2023]
Abstract
Neural interactions occur on different levels and scales. It is of particular importance to understand how they are distributed among different neuroanatomical and physiological relevant brain regions. We investigated neural cross-frequency couplings between different brain regions according to the Desikan-Killiany brain parcellation. The adaptive dynamic Bayesian inference method was applied to EEG measurements of healthy resting subjects in order to reconstruct the coupling functions. It was found that even after averaging over all subjects, the mean coupling function showed a characteristic waveform, confirming the direct influence of the delta-phase on the alpha-phase dynamics in certain brain regions and that the shape of the coupling function changes for different regions. While the averaged coupling function within a region was of similar form, the region-averaged coupling function was averaged out, which implies that there is a common dependence within separate regions across the subjects. It was also found that for certain regions the influence of delta on alpha oscillations is more pronounced and that oscillations that influence other are more evenly distributed across brain regions than the influenced oscillations. When presenting the information on brain lobes, it was shown that the influence of delta emanating from the brain as a whole is greatest on the alpha oscillations of the cingulate frontal lobe, and at the same time the influence of delta from the cingulate parietal brain lobe is greatest on the alpha oscillations of the whole brain.
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Affiliation(s)
- Dushko Lukarski
- Faculty of Medicine, Ss. Cyril and Methodius University, 1000 Skopje, Macedonia
- University Clinic for Radiotherapy and Oncology, 1000 Skopje, Macedonia
| | - Spase Petkoski
- Aix Marseille Univ, INSERM, Inst Neurosci Syst (INS), 13005 Marseille, France
| | - Peng Ji
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 200433 Shanghai, China
| | - Tomislav Stankovski
- Faculty of Medicine, Ss. Cyril and Methodius University, 1000 Skopje, Macedonia
- Department of Physics, Lancaster University, LA1 4YB Lancaster, United Kingdom
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17
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Ferrari Bardile C, Radulescu CI, Pouladi MA. Oligodendrocyte pathology in Huntington's disease: from mechanisms to therapeutics. Trends Mol Med 2023; 29:802-816. [PMID: 37591764 DOI: 10.1016/j.molmed.2023.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/18/2023] [Accepted: 07/20/2023] [Indexed: 08/19/2023]
Abstract
Oligodendrocytes (OLGs), highly specialized glial cells that wrap axons with myelin sheaths, are critical for brain development and function. There is new recognition of the role of OLGs in the pathogenesis of neurodegenerative diseases (NDDs), including Huntington's disease (HD), a prototypic NDD caused by a polyglutamine tract expansion in huntingtin (HTT), which results in gain- and loss-of-function effects. Clinically, HD is characterized by a constellation of motor, cognitive, and psychiatric disturbances. White matter (WM) structures, representing myelin-rich regions of the brain, are profoundly affected in HD, and recent findings reveal oligodendroglia dysfunction as an early pathological event. Here, we focus on mechanisms that underlie oligodendroglial deficits and dysmyelination in the progression of the disease, highlighting the pathogenic contributions of mutant HTT (mHTT). We also discuss potential therapeutic implications involving these molecular pathways.
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Affiliation(s)
- Costanza Ferrari Bardile
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, Djavad Mowafaghian Centre for Brain Health, British Columbia Children's Hospital Research Institute, University of British Columbia, Vancouver, BC V5Z 4H4, Canada
| | - Carola I Radulescu
- UK Dementia Research Institute, Imperial College London, London, W12 0NN, UK
| | - Mahmoud A Pouladi
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, Djavad Mowafaghian Centre for Brain Health, British Columbia Children's Hospital Research Institute, University of British Columbia, Vancouver, BC V5Z 4H4, Canada.
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18
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Larsen B, Sydnor VJ, Keller AS, Yeo BTT, Satterthwaite TD. A critical period plasticity framework for the sensorimotor-association axis of cortical neurodevelopment. Trends Neurosci 2023; 46:847-862. [PMID: 37643932 PMCID: PMC10530452 DOI: 10.1016/j.tins.2023.07.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 06/23/2023] [Accepted: 07/25/2023] [Indexed: 08/31/2023]
Abstract
To understand human brain development it is necessary to describe not only the spatiotemporal patterns of neurodevelopment but also the neurobiological mechanisms that underlie them. Human neuroimaging studies have provided evidence for a hierarchical sensorimotor-to-association (S-A) axis of cortical neurodevelopment. Understanding the biological mechanisms that underlie this program of development using traditional neuroimaging approaches has been challenging. Animal models have been used to identify periods of enhanced experience-dependent plasticity - 'critical periods' - that progress along cortical hierarchies and are governed by a conserved set of neurobiological mechanisms that promote and then restrict plasticity. In this review we hypothesize that the S-A axis of cortical development in humans is partly driven by the cascading maturation of critical period plasticity mechanisms. We then describe how recent advances in in vivo neuroimaging approaches provide a promising path toward testing this hypothesis by linking signals derived from non-invasive imaging to critical period mechanisms.
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Affiliation(s)
- Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arielle S Keller
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - B T Thomas Yeo
- Centre for Sleep and Cognition (CSC), and Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Şişman M, Nguyen TD, Roberts AG, Romano DJ, Dimov AV, Kovanlikaya I, Spincemaille P, Wang Y. Microstructure-Informed Myelin Mapping (MIMM) from Gradient Echo MRI using Stochastic Matching Pursuit. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.22.23295993. [PMID: 37808826 PMCID: PMC10557811 DOI: 10.1101/2023.09.22.23295993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Quantification of the myelin content of the white matter is important for studying demyelination in neurodegenerative diseases such as Multiple Sclerosis (MS), particularly for longitudinal monitoring. A novel noninvasive MRI method, called Microstructure-Informed Myelin Mapping (MIMM), is developed to quantify the myelin volume fraction (MVF) by utilizing a multi gradient echo sequence (mGRE) and a detailed biophysical model of tissue microstructure. Myelin is modeled as anisotropic negative susceptibility source based on the Hollow Cylindrical Fiber Model (HCFM), and iron as isotropic positive susceptibility source in the extracellular region. Voxels with a range of biophysical parameters are simulated to create a dictionary of MR echo time magnitude signals and total susceptibility values. MRI signals measured using a mGRE sequence are then matched voxel-by-voxel to the created dictionary to obtain the spatial distributions of myelin and iron. Three different MIMM versions are presented to deal with the fiber orientation dependent susceptibility effects of the myelin sheaths: a basic variation, which assumes fiber orientation is an unknown to fit, two orientation informed variations, which assume the fiber orientation distribution is available either from a separate diffusion tensor imaging (DTI) acquisition or from a DTI atlas based fiber orientation map. While all showed a significant linear correlation with the reference method based on T2-relaxometry (p < 0.0001), DTI orientation informed and atlas orientation informed variations reduced overestimation at white matter tracts compared to the basic variation. Finally, the implications and usefulness of attaining an additional iron susceptibility distribution map are discussed. Highlights novel stochastic matching pursuit algorithm called microstructure-informed myelin mapping (MIMM) is developed to quantify Myelin Volume Fraction (MVF) using Magnetic Resonance Imaging (MRI) and microstructural modeling.utilizes a detailed biophysical model to capture the susceptibility effects on both magnitude and phase to quantify myelin and iron.matter fiber orientation effects are considered for the improved MVF quantification in the major fiber tracts.acquired myelin and iron maps may be utilized to monitor longitudinal disease progress.
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20
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Filo S, Shaharabani R, Bar Hanin D, Adam M, Ben-David E, Schoffman H, Margalit N, Habib N, Shahar T, Mezer AA. Non-invasive assessment of normal and impaired iron homeostasis in the brain. Nat Commun 2023; 14:5467. [PMID: 37699931 PMCID: PMC10497590 DOI: 10.1038/s41467-023-40999-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 08/17/2023] [Indexed: 09/14/2023] Open
Abstract
Strict iron regulation is essential for normal brain function. The iron homeostasis, determined by the milieu of available iron compounds, is impaired in aging, neurodegenerative diseases and cancer. However, non-invasive assessment of different molecular iron environments implicating brain tissue's iron homeostasis remains a challenge. We present a magnetic resonance imaging (MRI) technology sensitive to the iron homeostasis of the living brain (the r1-r2* relaxivity). In vitro, our MRI approach reveals the distinct paramagnetic properties of ferritin, transferrin and ferrous iron ions. In the in vivo human brain, we validate our approach against ex vivo iron compounds quantification and gene expression. Our approach varies with the iron mobilization capacity across brain regions and in aging. It reveals brain tumors' iron homeostasis, and enhances the distinction between tumor tissue and non-pathological tissue without contrast agents. Therefore, our approach may allow for non-invasive research and diagnosis of iron homeostasis in living human brains.
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Affiliation(s)
- Shir Filo
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Rona Shaharabani
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Daniel Bar Hanin
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Miriam Adam
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Eliel Ben-David
- The Department of Radiology, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Hanan Schoffman
- The Laboratory of Molecular Neuro-Oncology, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Nevo Margalit
- The Department of Neurosurgery, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Naomi Habib
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Tal Shahar
- The Laboratory of Molecular Neuro-Oncology, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
- The Department of Neurosurgery, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
- The Department of Neurosurgery, Tel Aviv Sourasky Medical Center, Affiliated with Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Aviv A Mezer
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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Gong Z, Khattar N, Kiely M, Triebswetter C, Bouhrara M. REUSED: A deep neural network method for rapid whole-brain high-resolution myelin water fraction mapping from extremely under-sampled MRI. Comput Med Imaging Graph 2023; 108:102282. [PMID: 37586261 PMCID: PMC10528830 DOI: 10.1016/j.compmedimag.2023.102282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 07/23/2023] [Accepted: 07/24/2023] [Indexed: 08/18/2023]
Abstract
Changes in myelination are a cardinal feature of brain development and the pathophysiology of several central nervous system diseases, including multiple sclerosis and dementias. Advanced magnetic resonance imaging (MRI) methods have been developed to probe myelin content through the measurement of myelin water fraction (MWF). However, the prolonged data acquisition and post-processing times of current MWF mapping methods pose substantial hurdles to their clinical implementation. Recently, fast steady-state MRI sequences have been implemented to produce high-spatial resolution whole-brain MWF mapping within ∼20 min. Despite the subsequent significant advances in the inversion algorithm to derive MWF maps from steady-state MRI, the high-dimensional nature of such inversion does not permit further reduction of the acquisition time by data under-sampling. In this work, we present an unprecedented reduction in the computation (∼30 s) and the acquisition time (∼7 min) required for whole-brain high-resolution MWF mapping through a new Neural Network (NN)-based approach, named NN-Relaxometry of Extremely Under-SamplEd Data (NN-REUSED). Our analyses demonstrate virtually similar accuracy and precision in derived MWF values using NN-REUSED compared to results derived from the fully sampled reference method. The reduction in the acquisition and computation times represents a breakthrough toward clinically practical MWF mapping.
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Affiliation(s)
- Zhaoyuan Gong
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
| | | | - Matthew Kiely
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Curtis Triebswetter
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Mustapha Bouhrara
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
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Cheng GWY, Ma IWT, Huang J, Yeung SHS, Ho P, Chen Z, Mak HKF, Herrup K, Chan KWY, Tse KH. Cuprizone drives divergent neuropathological changes in different mouse models of Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.24.547147. [PMID: 37546935 PMCID: PMC10402084 DOI: 10.1101/2023.07.24.547147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Myelin degradation is a normal feature of brain aging that accelerates in Alzheimer's disease (AD). To date, however, the underlying biological basis of this correlation remains elusive. The amyloid cascade hypothesis predicts that demyelination is caused by increased levels of the β-amyloid (Aβ) peptide. Here we report on work supporting the alternative hypothesis that early demyelination is upstream of amyloid. We challenged two different mouse models of AD (R1.40 and APP/PS1) using cuprizone-induced demyelination and tracked the responses with both neuroimaging and neuropathology. In oppose to amyloid cascade hypothesis, R1.40 mice, carrying only a single human mutant APP (Swedish; APP SWE ) transgene, showed a more abnormal changes of magnetization transfer ratio and diffusivity than in APP/PS1 mice, which carry both APP SWE and a second PSEN1 transgene (delta exon 9; PSEN1 dE9 ). Although cuprizone targets oligodendrocytes (OL), magnetic resonance spectroscopy and targeted RNA-seq data in R1.40 mice suggested a possible metabolic alternation in axons. In support of alternative hypotheses, cuprizone induced significant intraneuronal amyloid deposition in young APP/PS1, but not in R1.40 mice, and it suggested the presence of PSEN deficiencies, may accelerate Aβ deposition upon demyelination. In APP/PS1, mature OL is highly vulnerable to cuprizone with significant DNA double strand breaks (53BP1 + ) formation. Despite these major changes in myelin, OLs, and Aβ immunoreactivity, no cognitive impairment or hippocampal pathology was detected in APP/PS1 mice after cuprizone treatment. Together, our data supports the hypothesis that myelin loss can be the cause, but not the consequence, of AD pathology. SIGNIFICANCE STATEMENT The causal relationship between early myelin loss and the progression of Alzheimer's disease remains unclear. Using two different AD mouse models, R1.40 and APP/PS1, our study supports the hypothesis that myelin abnormalities are upstream of amyloid production and deposition. We find that acute demyelination initiates intraneuronal amyloid deposition in the frontal cortex. Further, the loss of oligodendrocytes, coupled with the accelerated intraneuronal amyloid deposition, interferes with myelin tract diffusivity at a stage before any hippocampus pathology or cognitive impairments occur. We propose that myelin loss could be the cause, not the consequence, of amyloid pathology during the early stages of Alzheimer's disease.
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23
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Pérez-Cervera L, De Santis S, Marcos E, Ghorbanzad-Ghaziany Z, Trouvé-Carpena A, Selim MK, Pérez-Ramírez Ú, Pfarr S, Bach P, Halli P, Kiefer F, Moratal D, Kirsch P, Sommer WH, Canals S. Alcohol-induced damage to the fimbria/fornix reduces hippocampal-prefrontal cortex connection during early abstinence. Acta Neuropathol Commun 2023; 11:101. [PMID: 37344865 PMCID: PMC10286362 DOI: 10.1186/s40478-023-01597-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 05/30/2023] [Indexed: 06/23/2023] Open
Abstract
INTRODUCTION Alcohol dependence is characterized by a gradual reduction in cognitive control and inflexibility to contingency changes. The neuroadaptations underlying this aberrant behavior are poorly understood. Using an animal model of alcohol use disorders (AUD) and complementing diffusion-weighted (dw)-MRI with quantitative immunohistochemistry and electrophysiological recordings, we provide causal evidence that chronic intermittent alcohol exposure affects the microstructural integrity of the fimbria/fornix, decreasing myelin basic protein content, and reducing the effective communication from the hippocampus (HC) to the prefrontal cortex (PFC). Using a simple quantitative neural network model, we show how disturbed HC-PFC communication may impede the extinction of maladaptive memories, decreasing flexibility. Finally, combining dw-MRI and psychometric data in AUD patients, we discovered an association between the magnitude of microstructural alteration in the fimbria/fornix and the reduction in cognitive flexibility. Overall, these findings highlight the vulnerability of the fimbria/fornix microstructure in AUD and its potential contribution to alcohol pathophysiology. Fimbria vulnerability to alcohol underlies hippocampal-prefrontal cortex dysfunction and correlates with cognitive impairment.
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Affiliation(s)
- Laura Pérez-Cervera
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
| | - Silvia De Santis
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
| | - Encarni Marcos
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
| | - Zahra Ghorbanzad-Ghaziany
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
- Radiation Science and Biomedical Imaging, University of Sherbrooke, Sherbrooke, Québec, Canada
| | - Alejandro Trouvé-Carpena
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
| | - Mohamed Kotb Selim
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
| | - Úrsula Pérez-Ramírez
- Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain
| | - Simone Pfarr
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Patrick Bach
- Department of Addiction Medicine, Department of Clinical Psychology, Medical Faculty Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Patrick Halli
- Department of Psychology, University of Heidelberg, Heidelberg, Germany
| | - Falk Kiefer
- Department of Addiction Medicine, Department of Clinical Psychology, Medical Faculty Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - David Moratal
- Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain
| | - Peter Kirsch
- Department of Psychology, University of Heidelberg, Heidelberg, Germany
| | - Wolfgang H Sommer
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical faculty Mannheim, University of Heidelberg, Mannheim, Germany.
- Department of Addiction Medicine, Department of Clinical Psychology, Medical Faculty Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany.
| | - Santiago Canals
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain.
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Zhou L, Li Y, Sweeney EM, Wang XH, Kuceyeski A, Chiang GC, Ivanidze J, Wang Y, Gauthier SA, de Leon MJ, Nguyen TD. Association of brain tissue cerebrospinal fluid fraction with age in healthy cognitively normal adults. Front Aging Neurosci 2023; 15:1162001. [PMID: 37396667 PMCID: PMC10312090 DOI: 10.3389/fnagi.2023.1162001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 05/31/2023] [Indexed: 07/04/2023] Open
Abstract
Background and purpose Our objective was to apply multi-compartment T2 relaxometry in cognitively normal individuals aged 20-80 years to study the effect of aging on the parenchymal CSF fraction (CSFF), a potential measure of the subvoxel CSF space. Materials and methods A total of 60 volunteers (age range, 22-80 years) were enrolled. Voxel-wise maps of short-T2 myelin water fraction (MWF), intermediate-T2 intra/extra-cellular water fraction (IEWF), and long-T2 CSFF were obtained using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) sequence and three-pool non-linear least squares fitting. Multiple linear regression analyses were performed to study the association between age and regional MWF, IEWF, and CSFF measurements, adjusting for sex and region of interest (ROI) volume. ROIs include the cerebral white matter (WM), cerebral cortex, and subcortical deep gray matter (GM). In each model, a quadratic term for age was tested using an ANOVA test. A Spearman's correlation between the normalized lateral ventricle volume, a measure of organ-level CSF space, and the regional CSFF, a measure of tissue-level CSF space, was computed. Results Regression analyses showed that there was a statistically significant quadratic relationship with age for CSFF in the cortex (p = 0.018), MWF in the cerebral WM (p = 0.033), deep GM (p = 0.017) and cortex (p = 0.029); and IEWF in the deep GM (p = 0.033). There was a statistically highly significant positive linear relationship between age and regional CSFF in the cerebral WM (p < 0.001) and deep GM (p < 0.001). In addition, there was a statistically significant negative linear association between IEWF and age in the cerebral WM (p = 0.017) and cortex (p < 0.001). In the univariate correlation analysis, the normalized lateral ventricle volume correlated with the regional CSFF measurement in the cerebral WM (ρ = 0.64, p < 0.001), cortex (ρ = 0.62, p < 0.001), and deep GM (ρ = 0.66, p < 0.001). Conclusion Our cross-sectional data demonstrate that brain tissue water in different compartments shows complex age-dependent patterns. Parenchymal CSFF, a measure of subvoxel CSF-like water in the brain tissue, is quadratically associated with age in the cerebral cortex and linearly associated with age in the cerebral deep GM and WM.
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Affiliation(s)
- Liangdong Zhou
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Yi Li
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Elizabeth M. Sweeney
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Xiuyuan H. Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
- Department of Statistics and Data Science, Cornell University, Ithaca, NY, United States
| | - Gloria C. Chiang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Jana Ivanidze
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Susan A. Gauthier
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Mony J. de Leon
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Thanh D. Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
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Guo Y, Dong D, Wu H, Xue Z, Zhou F, Zhao L, Li Z, Feng T. The intracortical myelin content of impulsive choices: results from T1- and T2-weighted MRI myelin mapping. Cereb Cortex 2023; 33:7163-7174. [PMID: 36748995 PMCID: PMC10422924 DOI: 10.1093/cercor/bhad028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 01/18/2023] [Indexed: 02/08/2023] Open
Abstract
Delay discounting (DD) refers to a phenomenon that humans tend to choose small-sooner over large-later rewards during intertemporal choices. Steep discounting of delayed outcome is related to a variety of maladaptive behaviors and is considered as a transdiagnostic process across psychiatric disorders. Previous studies have investigated the association between brain structure (e.g. gray matter volume) and DD; however, it is unclear whether the intracortical myelin (ICM) influences DD. Here, based on a sample of 951 healthy young adults drawn from the Human Connectome Project, we examined the relationship between ICM, which was measured by the contrast of T1w and T2w images, and DD and further tested whether the identified associations were mediated by the regional homogeneity (ReHo) of brain spontaneous activity. Vertex-wise regression analyses revealed that steeper DD was significantly associated with lower ICM in the left temporoparietal junction (TPJ) and right middle-posterior cingulate cortex. Region-of-interest analysis revealed that the ReHo values in the left TPJ partially mediated the association of its myelin content with DD. Our findings provide the first evidence that cortical myelination is linked with individual differences in decision impulsivity and suggest that the myelin content affects cognitive performances partially through altered local brain synchrony.
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Affiliation(s)
- Yiqun Guo
- School of Innovation and Entrepreneurship education, Chongqing University of Posts and Telecommunications, Chongqing, China
- Research Center of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Debo Dong
- Key Laboratory of Cognition and Personality, Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University, Chongqing, China
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Huimin Wu
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Zhiyuan Xue
- School of Humanities and Management, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Feng Zhou
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Le Zhao
- Faculty of Psychology, Beijing Normal University, Zhuhai, China
| | - Zhangyong Li
- Research Center of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Tingyong Feng
- Key Laboratory of Cognition and Personality, Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University, Chongqing, China
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26
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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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27
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Trofimova O, Latypova A, DiDomenicantonio G, Lutti A, de Lange AMG, Kliegel M, Stringhini S, Marques-Vidal P, Vaucher J, Vollenweider P, Strippoli MPF, Preisig M, Kherif F, Draganski B. Topography of associations between cardiovascular risk factors and myelin loss in the ageing human brain. Commun Biol 2023; 6:392. [PMID: 37037939 PMCID: PMC10086032 DOI: 10.1038/s42003-023-04741-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 03/21/2023] [Indexed: 04/12/2023] Open
Abstract
Our knowledge of the mechanisms underlying the vulnerability of the brain's white matter microstructure to cardiovascular risk factors (CVRFs) is still limited. We used a quantitative magnetic resonance imaging (MRI) protocol in a single centre setting to investigate the cross-sectional association between CVRFs and brain tissue properties of white matter tracts in a large community-dwelling cohort (n = 1104, age range 46-87 years). Arterial hypertension was associated with lower myelin and axonal density MRI indices, paralleled by higher extracellular water content. Obesity showed similar associations, though with myelin difference only in male participants. Associations between CVRFs and white matter microstructure were observed predominantly in limbic and prefrontal tracts. Additional genetic, lifestyle and psychiatric factors did not modulate these results, but moderate-to-vigorous physical activity was linked to higher myelin content independently of CVRFs. Our findings complement previously described CVRF-related changes in brain water diffusion properties pointing towards myelin loss and neuroinflammation rather than neurodegeneration.
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Affiliation(s)
- Olga Trofimova
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Adeliya Latypova
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Giulia DiDomenicantonio
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ann-Marie G de Lange
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Matthias Kliegel
- Department of Psychology, University of Geneva, Geneva, Switzerland
| | - Silvia Stringhini
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Julien Vaucher
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Marie-Pierre F Strippoli
- Center for Research in Psychiatric Epidemiology and Psychopathology, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Martin Preisig
- Center for Research in Psychiatric Epidemiology and Psychopathology, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- Neurology Department, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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28
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Huber E, Corrigan NM, Yarnykh VL, Ferjan Ramírez N, Kuhl PK. Language Experience during Infancy Predicts White Matter Myelination at Age 2 Years. J Neurosci 2023; 43:1590-1599. [PMID: 36746626 PMCID: PMC10008053 DOI: 10.1523/jneurosci.1043-22.2023] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 01/06/2023] [Accepted: 01/06/2023] [Indexed: 02/08/2023] Open
Abstract
Parental input is considered a key predictor of language achievement during the first years of life, yet relatively few studies have assessed the effects of parental language input and parent-infant interactions on early brain development. We examined the relationship between measures of parent and child language, obtained from naturalistic home recordings at child ages 6, 10, 14, 18, and 24 months, and estimates of white matter myelination, derived from quantitative MRI at age 2 years (mean = 26.30 months, SD = 1.62, N = 22). Analysis of the white matter focused on dorsal pathways associated with expressive language development and long-term language ability, namely, the left arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF). Frequency of parent-infant conversational turns (CT) uniquely predicted myelin density estimates in both the AF and SLF. Moreover, the effect of CT remained significant while controlling for total adult speech and child speech-related utterances, suggesting a specific role for interactive language experience, rather than simply speech exposure or production. An exploratory analysis of 18 additional tracts, including the right AF and SLF, indicated a high degree of anatomic specificity. Longitudinal analyses of parent and child language variables indicated an effect of CT as early as 6 months of age, as well as an ongoing effect over infancy. Together, these results link parent-infant conversational turns to white matter myelination at age 2 years, and suggest that early, interactive experiences with language uniquely contribute to the development of white matter associated with long-term language ability.SIGNIFICANCE STATEMENT Children's earliest experiences with language are thought to have profound and lasting developmental effects. Recent studies suggest that intervention can increase the quality of parental language input and improve children's learning outcomes. However, important questions remain about the optimal timing of intervention, and the relationship between specific aspects of language experience and brain development. We report that parent-infant turn-taking during home language interactions correlates with myelination of language related white matter pathways through age 2 years. Effects were independent of total speech exposure and infant vocalizations and evident starting at 6 months of age, suggesting that structured language interactions throughout infancy may uniquely support the ongoing development of brain systems critical to long-term language ability.
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Affiliation(s)
- Elizabeth Huber
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Speech & Hearing Sciences, University of Washington, Seattle, Washington 98195
| | - Neva M Corrigan
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Speech & Hearing Sciences, University of Washington, Seattle, Washington 98195
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle, Washington 98195
| | - Naja Ferjan Ramírez
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Linguistics, University of Washington, Seattle, Washington 98195
| | - Patricia K Kuhl
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Speech & Hearing Sciences, University of Washington, Seattle, Washington 98195
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29
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Ziminski JJ, Frangou P, Karlaftis VM, Emir U, Kourtzi Z. Microstructural and neurochemical plasticity mechanisms interact to enhance human perceptual decision-making. PLoS Biol 2023; 21:e3002029. [PMID: 36897881 PMCID: PMC10032544 DOI: 10.1371/journal.pbio.3002029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 03/22/2023] [Accepted: 02/08/2023] [Indexed: 03/11/2023] Open
Abstract
Experience and training are known to boost our skills and mold the brain's organization and function. Yet, structural plasticity and functional neurotransmission are typically studied at different scales (large-scale networks, local circuits), limiting our understanding of the adaptive interactions that support learning of complex cognitive skills in the adult brain. Here, we employ multimodal brain imaging to investigate the link between microstructural (myelination) and neurochemical (GABAergic) plasticity for decision-making. We test (in males, due to potential confounding menstrual cycle effects on GABA measurements in females) for changes in MRI-measured myelin, GABA, and functional connectivity before versus after training on a perceptual decision task that involves identifying targets in clutter. We demonstrate that training alters subcortical (pulvinar, hippocampus) myelination and its functional connectivity to visual cortex and relates to decreased visual cortex GABAergic inhibition. Modeling interactions between MRI measures of myelin, GABA, and functional connectivity indicates that pulvinar myelin plasticity interacts-through thalamocortical connectivity-with GABAergic inhibition in visual cortex to support learning. Our findings propose a dynamic interplay of adaptive microstructural and neurochemical plasticity in subcortico-cortical circuits that supports learning for optimized decision-making in the adult human brain.
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Affiliation(s)
- Joseph J Ziminski
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Polytimi Frangou
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Vasilis M Karlaftis
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Uzay Emir
- Purdue University School of Health Sciences, West Lafayette, Indiana, United States of America
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
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30
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Advanced methods and implementations for the meta-analyses of animal models: Current practices and future recommendations. Neurosci Biobehav Rev 2023; 146:105016. [PMID: 36566804 DOI: 10.1016/j.neubiorev.2022.105016] [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: 06/21/2022] [Revised: 12/19/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022]
Abstract
Meta-analytic techniques have been widely used to synthesize data from animal models of human diseases and conditions, but these analyses often face two statistical challenges due to complex nature of animal data (e.g., multiple effect sizes and multiple species): statistical dependency and confounding heterogeneity. These challenges can lead to unreliable and less informative evidence, which hinders the translation of findings from animal to human studies. We present a literature survey of meta-analysis using animal models (animal meta-analysis), showing that these issues are not adequately addressed in current practice. To address these challenges, we propose a meta-analytic framework based on multilevel (linear mixed-effects) models. Through conceptualization, formulations, and worked examples, we illustrate how this framework can appropriately address these issues while allowing for testing new questions. Additionally, we introduce other advanced techniques such as multivariate models, robust variance estimation, and meta-analysis of emergent effect sizes, which can deliver robust inferences and novel biological insights. We also provide a tutorial with annotated R code to demonstrate the implementation of these techniques.
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31
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Paquola C, Hong SJ. The Potential of Myelin-Sensitive Imaging: Redefining Spatiotemporal Patterns of Myeloarchitecture. Biol Psychiatry 2023; 93:442-454. [PMID: 36481065 DOI: 10.1016/j.biopsych.2022.08.031] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/12/2022] [Accepted: 08/30/2022] [Indexed: 02/07/2023]
Abstract
Recent advances in magnetic resonance imaging (MRI) have paved the way for approximation of myelin content in vivo. In this review, our main goal was to determine how to best capitalize on myelin-sensitive imaging. First, we briefly overview the theoretical and empirical basis for the myelin sensitivity of different MRI markers and, in doing so, highlight how multimodal imaging approaches are important for enhancing specificity to myelin. Then, we discuss recent studies that have probed the nonuniform distribution of myelin across cortical layers and along white matter tracts. These approaches, collectively known as myelin profiling, have provided detailed depictions of myeloarchitecture in both the postmortem and living human brain. Notably, MRI-based profiling studies have recently focused on investigating whether it can capture interindividual variability in myelin characteristics as well as trajectories across the lifespan. Finally, another line of recent evidence emphasizes the contribution of region-specific myelination to large-scale organization, demonstrating the impact of myelination on global brain networks. In conclusion, we suggest that combining well-validated MRI markers with profiling techniques holds strong potential to elucidate individual differences in myeloarchitecture, which has important implications for understanding brain function and disease.
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Affiliation(s)
- Casey Paquola
- Institute of Neuroscience and Medicine, Forschungszentrum Jülich, Jülich, Germany.
| | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Suwon, South Korea; Center for the Developing Brain, Child Mind Institute, New York, New York; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
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32
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Chary K, Manninen E, Claessens J, Ramirez-Manzanares A, Gröhn O, Sierra A. Diffusion MRI approaches for investigating microstructural complexity in a rat model of traumatic brain injury. Sci Rep 2023; 13:2219. [PMID: 36755032 PMCID: PMC9908904 DOI: 10.1038/s41598-023-29010-3] [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: 06/17/2022] [Accepted: 01/30/2023] [Indexed: 02/10/2023] Open
Abstract
Our study explores the potential of conventional and advanced diffusion MRI techniques including diffusion tensor imaging (DTI), and single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD) to investigate complex microstructural changes following severe traumatic brain injury in rats at a chronic phase. Rat brains after sham-operation or lateral fluid percussion (LFP) injury were scanned ex vivo in a 9.4 T scanner. Our region-of-interest-based approach of tensor-, and SS3T-CSD derived fixel-, 3-tissue signal fraction maps were sensitive to changes in both white matter (WM) and grey matter (GM) areas. Tensor-based measures, such as fractional anisotropy (FA) and radial diffusivity (RD), detected more changes in WM and GM areas as compared to fixel-based measures including apparent fiber density (AFD), peak FOD amplitude and primary fiber bundle density, while 3-tissue signal fraction maps revealed distinct changes in WM, GM, and phosphate-buffered saline (PBS) fractions highlighting the complex tissue microstructural alterations post-trauma. Track-weighted imaging demonstrated changes in track morphology including reduced curvature and average pathlength distal from the primary lesion in severe TBI rats. In histological analysis, changes in the diffusion MRI measures could be associated to decreased myelin density, loss of myelinated axons, and increased cellularity, revealing progressive microstructural alterations in these brain areas five months after injury. Overall, this study highlights the use of combined conventional and advanced diffusion MRI measures to obtain more precise insights into the complex tissue microstructural alterations in chronic phase of severe brain injury.
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Affiliation(s)
- Karthik Chary
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland.,Department of Radiology, University of Cambridge, Cambridge, UK
| | - Eppu Manninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
| | - Jade Claessens
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
| | | | - Olli Gröhn
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
| | - Alejandra Sierra
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland.
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33
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Robles I, Eidsness MA, Travis KE, Feldman HM, Dubner SE. Effects of postnatal glucocorticoids on brain structure in preterm infants, a scoping review. Neurosci Biobehav Rev 2023; 145:105034. [PMID: 36608916 PMCID: PMC9898165 DOI: 10.1016/j.neubiorev.2023.105034] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 12/11/2022] [Accepted: 01/02/2023] [Indexed: 01/07/2023]
Abstract
Glucocorticoids (GC) are used in neonatal intensive care units to prevent or reduce the severity of chronic lung disease in preterm infants and have been implicated in impaired neurodevelopment. Our objective was to identify what is known about the effects of postnatal GC treatment in human preterm infants on structural brain development and to identify gaps in the literature. Following Arksey and O'Malley's scoping review methodological framework, we searched scientific literature databases for original research on human preterm infants, postnatal GCs, and brain structure. 11 studies assessed the effects of GCs on structural brain outcomes. 56 studies reported brain injury, but not structure. Dexamethasone was consistently associated with decreased total and regional brain volumes, including cerebellar volumes. Hydrocortisone was often, but not always associated with absence of brain volume differences. No studies examined the impact of inhaled GC on brain structure. Additional research on the effects of neonatal GCs after preterm birth on a variety of structural brain measures is required for understanding contributions to neurodevelopment and informing practice guidelines.
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Affiliation(s)
- Isabella Robles
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, United States
| | - Margarita Alethea Eidsness
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, United States
| | - Katherine E Travis
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, United States
| | - Heidi M Feldman
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, United States
| | - Sarah E Dubner
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, United States.
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34
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Genc S, Raven EP, Drakesmith M, Blakemore SJ, Jones DK. Novel insights into axon diameter and myelin content in late childhood and adolescence. Cereb Cortex 2023; 33:6435-6448. [PMID: 36610731 PMCID: PMC10183755 DOI: 10.1093/cercor/bhac515] [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: 11/16/2022] [Revised: 12/05/2022] [Accepted: 12/07/2022] [Indexed: 01/09/2023] Open
Abstract
White matter microstructural development in late childhood and adolescence is driven predominantly by increasing axon density and myelin thickness. Ex vivo studies suggest that the increase in axon diameter drives developmental increases in axon density observed with pubertal onset. In this cross-sectional study, 50 typically developing participants aged 8-18 years were scanned using an ultra-strong gradient magnetic resonance imaging scanner. Microstructural properties, including apparent axon diameter $({d}_a)$, myelin content, and g-ratio, were estimated in regions of the corpus callosum. We observed age-related differences in ${d}_a$, myelin content, and g-ratio. In early puberty, males had larger ${d}_a$ in the splenium and lower myelin content in the genu and body of the corpus callosum, compared with females. Overall, this work provides novel insights into developmental, pubertal, and cognitive correlates of individual differences in apparent axon diameter and myelin content in the developing human brain.
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Affiliation(s)
- Sila Genc
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Erika P Raven
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom.,Department of Radiology, New York University School of Medicine, 550 1st Ave., New York, NY 10016, United States
| | - Mark Drakesmith
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Sarah-Jayne Blakemore
- Department of Psychology, University of Cambridge, Downing Pl, Cambridge CB2 3EB, United Kingdom
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
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35
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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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36
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Leo H, Kipp M. Remyelination in Multiple Sclerosis: Findings in the Cuprizone Model. Int J Mol Sci 2022; 23:ijms232416093. [PMID: 36555733 PMCID: PMC9783537 DOI: 10.3390/ijms232416093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/14/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022] Open
Abstract
Remyelination therapies, which are currently under development, have a great potential to delay, prevent or even reverse disability in multiple sclerosis patients. Several models are available to study the effectiveness of novel compounds in vivo, among which is the cuprizone model. This model is characterized by toxin-induced demyelination, followed by endogenous remyelination after cessation of the intoxication. Due to its high reproducibility and ease of use, this model enjoys high popularity among various research and industrial groups. In this review article, we will summarize recent findings using this model and discuss the potential of some of the identified compounds to promote remyelination in multiple sclerosis patients.
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Affiliation(s)
| | - Markus Kipp
- Correspondence: ; Tel.: +49-(0)-381-494-8400
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37
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Edwards LJ, McColgan P, Helbling S, Zarkali A, Vaculčiaková L, Pine KJ, Dick F, Weiskopf N. Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis. Cereb Cortex 2022; 33:5704-5716. [PMID: 36520483 PMCID: PMC10152104 DOI: 10.1093/cercor/bhac453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 10/20/2022] [Accepted: 10/21/2022] [Indexed: 12/23/2022] Open
Abstract
Abstract
Quantitative magnetic resonance imaging (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (${R_{1}}$), effective transverse relaxation rate (${R_{2}}^{\ast }$), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (${R_{2}}^{\ast }$ at 3T, ${R_{1}}$ at 7T), endothelial cells (${R_{1}}$ and MTsat at 3T), microglia (${R_{1}}$ and MTsat at 3T, ${R_{1}}$ at 7T), and oligodendrocytes and oligodendrocyte precursor cells (${R_{1}}$ at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.
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Affiliation(s)
- Luke J Edwards
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Peter McColgan
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Huntington’s Disease Centre, University College London , London, UK
| | - Saskia Helbling
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Poeppel Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society , Frankfurt am Main, DE, Germany
| | - Angeliki Zarkali
- Dementia Research Centre, University College London , London, UK
| | - Lenka Vaculčiaková
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Kerrin J Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Fred Dick
- Birkbeck/UCL Centre for Neuroimaging (BUCNI) , London, UK
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University , Leipzig, DE, Germany
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38
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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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39
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A macroscopic link between interhemispheric tract myelination and cortico-cortical interactions during action reprogramming. Nat Commun 2022; 13:4253. [PMID: 35869067 PMCID: PMC9307658 DOI: 10.1038/s41467-022-31687-5] [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: 03/15/2021] [Accepted: 06/16/2022] [Indexed: 11/15/2022] Open
Abstract
Myelination has been increasingly implicated in the function and dysfunction of the adult human brain. Although it is known that axon myelination shapes axon physiology in animal models, it is unclear whether a similar principle applies in the living human brain, and at the level of whole axon bundles in white matter tracts. Here, we hypothesised that in humans, cortico-cortical interactions between two brain areas may be shaped by the amount of myelin in the white matter tract connecting them. As a test bed for this hypothesis, we use a well-defined interhemispheric premotor-to-motor circuit. We combined TMS-derived physiological measures of cortico-cortical interactions during action reprogramming with multimodal myelin markers (MT, R1, R2* and FA), in a large cohort of healthy subjects. We found that physiological metrics of premotor-to-motor interaction are broadly associated with multiple myelin markers, suggesting interindividual differences in tract myelination may play a role in motor network physiology. Moreover, we also demonstrate that myelination metrics link indirectly to action switching by influencing local primary motor cortex dynamics. These findings suggest that myelination levels in white matter tracts may influence millisecond-level cortico-cortical interactions during tasks. They also unveil a link between the physiology of the motor network and the myelination of tracts connecting its components, and provide a putative mechanism mediating the relationship between brain myelination and human behaviour. Myelination is a key regulator of brain function. Here the authors use MR-based myelin measures to examine if cortico-cortical interactions, as assessed by paired pulse transcranial magnetic stimulation, are affected by variations in myelin in the human brain.
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40
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Mesoscopic in vivo human T 2* dataset acquired using quantitative MRI at 7 Tesla. Neuroimage 2022; 264:119733. [PMID: 36375782 DOI: 10.1016/j.neuroimage.2022.119733] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 10/15/2022] [Accepted: 11/03/2022] [Indexed: 11/13/2022] Open
Abstract
Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for advancing neuroscience and bridging the resolution gap with animal models. Despite the variety of MRI contrasts measured in recent years at the mesoscopic scale, in vivo quantitative imaging of T2* has not been performed. Here we provide a dataset containing empirical T2* measurements acquired at 0.35 × 0.35 × 0.35 mm3 voxel resolution using 7 Tesla MRI. To demonstrate unique features and high quality of this dataset, we generate flat map visualizations that reveal fine-scale cortical substructures such as layers and vessels, and we report quantitative depth-dependent T2* (as well as R2*) values in primary visual cortex and auditory cortex that are highly consistent across subjects. This dataset is freely available at https://doi.org/10.17605/OSF.IO/N5BJ7, and may prove useful for anatomical investigations of the human brain, as well as for improving our understanding of the basis of the T2*-weighted (f)MRI signal.
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Kor DZL, Jbabdi S, Huszar IN, Mollink J, Tendler BC, Foxley S, Wang C, Scott C, Smart A, Ansorge O, Pallebage-Gamarallage M, Miller KL, Howard AFD. An automated pipeline for extracting histological stain area fraction for voxelwise quantitative MRI-histology comparisons. Neuroimage 2022; 264:119726. [PMID: 36368503 PMCID: PMC10933753 DOI: 10.1016/j.neuroimage.2022.119726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/27/2022] [Accepted: 10/31/2022] [Indexed: 11/11/2022] Open
Abstract
The acquisition of MRI and histology in the same post-mortem tissue sample enables direct correlation between MRI and histologically-derived parameters. However, there still lacks a standardised automated pipeline to process histology data, with most studies relying on manual intervention. Here, we introduce an automated pipeline to extract a quantitative histological measure for staining density (stain area fraction, SAF) from multiple immunohistochemical (IHC) stains. The pipeline is designed to directly address key IHC artefacts related to tissue staining and slide digitisation. Here, the pipeline was applied to post-mortem human brain data from multiple subjects, relating MRI parameters (FA, MD, RD, AD, R2*, R1) to IHC slides stained for myelin, neurofilaments, microglia and activated microglia. Utilising high-quality MRI-histology co-registrations, we then performed whole-slide voxelwise comparisons (simple correlations, partial correlations and multiple regression analyses) between multimodal MRI- and IHC-derived parameters. The pipeline was found to be reproducible, robust to artefacts and generalisable across multiple IHC stains. Our partial correlation results suggest that some simple MRI-SAF correlations should be interpreted with caution, due to the co-localisation of other tissue features (e.g., myelin and neurofilaments). Further, we find activated microglia-a generic biomarker of inflammation-to consistently be the strongest predictor of high DTI FA and low RD, which may suggest sensitivity of diffusion MRI to aspects of neuroinflammation related to microglial activation, even after accounting for other microstructural changes (demyelination, axonal loss and general microglia infiltration). Together, these results show the utility of this approach in carefully curating IHC data and performing multimodal analyses to better understand microstructural relationships with MRI.
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Affiliation(s)
- Daniel Z L Kor
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom.
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Sean Foxley
- Department of Radiology, University of Chicago, Chicago, IL, United States of America
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Connor Scott
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom; Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Olaf Ansorge
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Menuka Pallebage-Gamarallage
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Amy F D Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
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Reveley C, Ye FQ, Mars RB, Matrov D, Chudasama Y, Leopold DA. Diffusion MRI anisotropy in the cerebral cortex is determined by unmyelinated tissue features. Nat Commun 2022; 13:6702. [PMID: 36335105 PMCID: PMC9637141 DOI: 10.1038/s41467-022-34328-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 10/19/2022] [Indexed: 11/07/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) is commonly used to assess the tissue and cellular substructure of the human brain. In the white matter, myelinated axons are the principal neural elements that shape dMRI through the restriction of water diffusion; however, in the gray matter the relative contributions of myelinated axons and other tissue features to dMRI are poorly understood. Here we investigate the determinants of diffusion in the cerebral cortex. Specifically, we ask whether myelinated axons significantly shape dMRI fractional anisotropy (dMRI-FA), a measure commonly used to characterize tissue properties in humans. We compared ultra-high resolution ex vivo dMRI data from the brain of a marmoset monkey with both myelin- and Nissl-stained histological sections obtained from the same brain after scanning. We found that the dMRI-FA did not match the spatial distribution of myelin in the gray matter. Instead dMRI-FA was more closely related to the anisotropy of stained tissue features, most prominently those revealed by Nissl staining and to a lesser extent those revealed by myelin staining. Our results suggest that unmyelinated neurites such as large caliber apical dendrites are the primary features shaping dMRI measures in the cerebral cortex.
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Affiliation(s)
- Colin Reveley
- grid.4991.50000 0004 1936 8948Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU UK ,grid.12082.390000 0004 1936 7590Department of Informatics, University of Sussex, Falmer, Brighton, BN1 9QJ UK
| | - Frank Q. Ye
- grid.94365.3d0000 0001 2297 5165Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD USA
| | - Rogier B. Mars
- grid.4991.50000 0004 1936 8948Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU UK ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Denis Matrov
- grid.94365.3d0000 0001 2297 5165Section on Behavioral Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA
| | - Yogita Chudasama
- grid.94365.3d0000 0001 2297 5165Section on Behavioral Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA
| | - David A. Leopold
- grid.94365.3d0000 0001 2297 5165Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD USA ,grid.94365.3d0000 0001 2297 5165Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA
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Kiely M, Triebswetter C, Gong Z, Laporte JP, Faulkner ME, Akhonda MABS, Alsameen MH, Spencer RG, Bouhrara M. Evidence of An Association Between Cerebral Blood Flow and Microstructural Integrity in Normative Aging Using a Holistic
MRI
Approach. J Magn Reson Imaging 2022. [PMID: 36326302 PMCID: PMC10154435 DOI: 10.1002/jmri.28508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Cerebral tissue integrity decline and cerebral blood flow (CBF) alteration are major aspects of motor and cognitive dysfunctions and neurodegeneration. However, little is known about the association between blood flow and brain microstructural integrity, especially in normal aging. PURPOSE To assess the association between CBF and cerebral microstructural integrity. STUDY TYPE Cross sectional. POPULATION A total of 94 cognitively unimpaired adults (mean age 50.7 years, age range between 22 and 88 years, 56 Men). FIELD STRENGTH/SEQUENCE A 3 T; pseudo-continuous arterial spin labeling (pCASL), diffusion tensor imaging (DTI), Bayesian Monte Carlo analysis of multicomponent driven equilibrium steady-state observation of T1 and T2 (BMC-mcDESPOT). ASSESSMENT Lobar associations between CBF derived from pCASL, and longitudinal relaxation rate (R1 ), transverse relaxation rate (R2 ) and myelin water fraction (MWF) derived from BMC-mcDESPOT, or radial diffusivity (RD), axial diffusivity (AxD), mean diffusivity (MD) and fractional anisotropy (FA) derived from DTI were assessed. STATISTICAL TESTS Multiple linear regression models were used using the mean region of interest (ROI) values for MWF, R1 , R2 , FA, MD, RD, or AxD as the dependent variable and CBF, age, age2 , and sex as the independent variables. A two-sided P value of <0.05 defined statistical significance. RESULTS R1 , R2 , MWF, FA, MD, RD, and AxD parameters were associated with CBF in most of the cerebral regions evaluated. Specifically, higher CBF values were significantly associated with higher FA, MWF, R1 and R2 , or lower MD, RD and AxD values. DATA CONCLUSION These findings suggest that cerebral tissue microstructure may be impacted by global brain perfusion, adding further evidence to the intimate relationship between cerebral blood supply and cerebral tissue integrity. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 4.
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Affiliation(s)
- Matthew Kiely
- Laboratory of Clinical Investigation National Institute on Aging, NIH Baltimore Maryland USA
| | - Curtis Triebswetter
- Laboratory of Clinical Investigation National Institute on Aging, NIH Baltimore Maryland USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation National Institute on Aging, NIH Baltimore Maryland USA
| | - John P. Laporte
- Laboratory of Clinical Investigation National Institute on Aging, NIH Baltimore Maryland USA
| | - Mary E. Faulkner
- Laboratory of Clinical Investigation National Institute on Aging, NIH Baltimore Maryland USA
| | | | - Maryam H. Alsameen
- Laboratory of Clinical Investigation National Institute on Aging, NIH Baltimore Maryland USA
| | - Richard G. Spencer
- Laboratory of Clinical Investigation National Institute on Aging, NIH Baltimore Maryland USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation National Institute on Aging, NIH Baltimore Maryland USA
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Corrigan NM, Yarnykh VL, Huber E, Zhao TC, Kuhl PK. Brain myelination at 7 months of age predicts later language development. Neuroimage 2022; 263:119641. [PMID: 36170763 PMCID: PMC10038938 DOI: 10.1016/j.neuroimage.2022.119641] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 08/24/2022] [Accepted: 09/19/2022] [Indexed: 11/17/2022] Open
Abstract
Between 6 and 12 months of age there are dramatic changes in infants' processing of language. The neurostructural underpinnings of these changes are virtually unknown. The objectives of this study were to (1) examine changes in brain myelination during this developmental period and (2) examine the relationship between myelination during this period and later language development. Macromolecular proton fraction (MPF) was used as a marker of myelination. Whole-brain MPF maps were obtained with 1.25 mm3 isotropic spatial resolution from typically developing children at 7 and 11 months of age. Effective myelin density was calculated from MPF based on a linear relationship known from the literature. Voxel-based analyses were used to identify longitudinal changes in myelin density and to calculate correlations between myelin density at these ages and later language development. Increases in myelin density were more predominant in white matter than in gray matter. A strong predictive relationship was found between myelin density at 7 months of age, language production at 24 and 30 months of age, and rate of language growth. No relationships were found between myelin density at 11 months, or change in myelin density between 7 and 11 months of age, and later language measures. Our findings suggest that critical changes in brain structure may precede periods of pronounced change in early language skills.
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Affiliation(s)
- Neva M Corrigan
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA.
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle, WA 98195, USA
| | - Elizabeth Huber
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
| | - T Christina Zhao
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
| | - Patricia K Kuhl
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
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45
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Rubinski A, Franzmeier N, Dewenter A, Luan Y, Smith R, Strandberg O, Ossenkoppele R, Dichgans M, Hansson O, Ewers M. Higher levels of myelin are associated with higher resistance against tau pathology in Alzheimer’s disease. Alzheimers Res Ther 2022; 14:139. [PMID: 36153607 PMCID: PMC9508747 DOI: 10.1186/s13195-022-01074-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 08/28/2022] [Indexed: 11/10/2022]
Abstract
Background In Alzheimer’s disease (AD), fibrillar tau initially occurs locally and progresses preferentially between closely connected regions. However, the underlying sources of regional vulnerability to tau pathology remain unclear. Previous brain-autopsy findings suggest that the myelin levels—which differ substantially between white matter tracts in the brain—are a key modulating factor of region-specific susceptibility to tau deposition. Here, we investigated whether myelination differences between fiber tracts of the human connectome are predictive of the interregional spreading of tau pathology in AD. Methods We included two independently recruited samples consisting of amyloid-PET-positive asymptomatic and symptomatic elderly individuals, in whom tau-PET was obtained at baseline (ADNI: n = 275; BioFINDER-1: n = 102) and longitudinally in a subset (ADNI: n = 123, mean FU = 1.53 [0.69–3.95] years; BioFINDER-1: n = 39, mean FU = 1.87 [1.21–2.78] years). We constructed MRI templates of the myelin water fraction (MWF) in 200 gray matter ROIs and connecting fiber tracts obtained from adult cognitively normal participants. Using the same 200 ROI brain-parcellation atlas, we obtained tau-PET ROI values from each individual in ADNI and BioFINDER-1. In a spatial regression analysis, we first tested the association between cortical myelin and group-average tau-PET signal in the amyloid-positive and control groups. Secondly, employing a previously established approach of modeling tau-PET spreading based on functional connectivity between ROIs, we estimated in a linear regression analysis, whether the level of fiber-tract myelin modulates the association between functional connectivity and longitudinal tau-PET spreading (i.e., covariance) between ROIs. Results We found that higher myelinated cortical regions show lower tau-PET uptake (ADNI: rho = − 0.267, p < 0.001; BioFINDER-1: rho = − 0.175, p = 0.013). Fiber-tract myelin levels modulated the association between functional connectivity and tau-PET spreading, such that at higher levels of fiber-tract myelin, the association between stronger connectivity and higher covariance of tau-PET between the connected ROIs was attenuated (interaction fiber-tract myelin × functional connectivity: ADNI: β = − 0.185, p < 0.001; BioFINDER-1: β = − 0.166, p < 0.001). Conclusion Higher levels of myelin are associated with lower susceptibility of the connected regions to accumulate fibrillar tau. These results enhance our understanding of brain substrates that explain regional variation in tau accumulation and encourage future studies to investigate potential underlying mechanisms. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-022-01074-9.
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Foit NA, Yung S, Lee HM, Bernasconi A, Bernasconi N, Hong SJ. A whole-brain 3D myeloarchitectonic atlas: Mapping the Vogt-Vogt legacy to the cortical surface. Neuroimage 2022; 263:119617. [PMID: 36084859 DOI: 10.1016/j.neuroimage.2022.119617] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 09/03/2022] [Accepted: 09/05/2022] [Indexed: 11/18/2022] Open
Abstract
Building precise and detailed parcellations of anatomically and functionally distinct brain areas has been a major focus in Neuroscience. Pioneer anatomists parcellated the cortical manifold based on extensive histological studies of post-mortem brain, harnessing local variations in cortical cyto- and myeloarchitecture to define areal boundaries. Compared to the cytoarchitectonic field, where multiple neuroimaging studies have recently translated this old legacy data into useful analytical resources, myeloarchitectonics, which parcellate the cortex based on the organization of myelinated fibers, has received less attention. Here, we present the neocortical surface-based myeloarchitectonic atlas based on the histology-derived maps of the Vogt-Vogt school and its 2D translation by Nieuwenhuys. In addition to a myeloarchitectonic parcellation, our package includes intracortical laminar profiles of myelin content based on Vogt-Vogt-Hopf original publications. Histology-derived myelin density mapped on our atlas demonstrated a close overlap with in vivo quantitative MRI markers for myelin and relates to cytoarchitectural features. Complementing the existing battery of approaches for digital cartography, the whole-brain myeloarchitectonic atlas offers an opportunity to validate imaging surrogate markers of myelin in both health and disease.
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Affiliation(s)
- Niels A Foit
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Seles Yung
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
| | - Hyo Min Lee
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
| | - Seok-Jun Hong
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada; Center for the Developing Brain, Child Mind Institute, NY, USA; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea.
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Gudberg C, Stevelink R, Douaud G, Wulff K, Lazari A, Fleming MK, Johansen-Berg H. Individual differences in slow wave sleep architecture relate to variation in white matter microstructure across adulthood. Front Aging Neurosci 2022; 14:745014. [PMID: 36092806 PMCID: PMC9453235 DOI: 10.3389/fnagi.2022.745014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 08/08/2022] [Indexed: 11/18/2022] Open
Abstract
Sleep plays a key role in supporting brain function and resilience to brain decline. It is well known that sleep changes substantially with aging and that aging is associated with deterioration of brain structure. In this study, we sought to characterize the relationship between slow wave slope (SWslope)—a key marker of sleep architecture and an indirect proxy of sleep quality—and microstructure of white matter pathways in healthy adults with no sleep complaints. Participants were 12 young (24–27 years) and 12 older (50–79 years) adults. Sleep was assessed with nocturnal electroencephalography (EEG) and the Pittsburgh Sleep Quality Index (PSQI). White matter integrity was assessed using tract-based spatial statistics (TBSS) on tensor-based metrics such as Fractional Anisotropy (FA) and Mean Diffusivity (MD). Global PSQI score did not differ between younger (n = 11) and older (n = 11) adults (U = 50, p = 0.505), but EEG revealed that younger adults had a steeper SWslope at both frontal electrode sites (F3: U = 2, p < 0.001, F4: U = 4, p < 0.001, n = 12 younger, 10 older). There were widespread correlations between various diffusion tensor-based metrics of white matter integrity and sleep SWslope, over and above effects of age (n = 11 younger, 9 older). This was particularly evident for the corpus callosum, corona radiata, superior longitudinal fasciculus, internal and external capsule. This indicates that reduced sleep slow waves may be associated with widespread white matter deterioration. Future studies should investigate whether interventions targeted at improving sleep architecture also impact on decline in white matter microstructure in older adults.
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Affiliation(s)
- Christel Gudberg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Remi Stevelink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Gwenaëlle Douaud
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Katharina Wulff
- Nuffield Laboratory of Ophthalmology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Department of Radiation Sciences and Molecular Biology, Umeå University, Umeå, Sweden
- Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Melanie K. Fleming
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- *Correspondence: Melanie K. Fleming,
| | - Heidi Johansen-Berg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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48
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Karakuzu A, Appelhoff S, Auer T, Boudreau M, Feingold F, Khan AR, Lazari A, Markiewicz C, Mulder M, Phillips C, Salo T, Stikov N, Whitaker K, de Hollander G. qMRI-BIDS: An extension to the brain imaging data structure for quantitative magnetic resonance imaging data. Sci Data 2022; 9:517. [PMID: 36002444 PMCID: PMC9402561 DOI: 10.1038/s41597-022-01571-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 07/19/2022] [Indexed: 11/16/2022] Open
Abstract
The Brain Imaging Data Structure (BIDS) established community consensus on the organization of data and metadata for several neuroimaging modalities. Traditionally, BIDS had a strong focus on functional magnetic resonance imaging (MRI) datasets and lacked guidance on how to store multimodal structural MRI datasets. Here, we present and describe the BIDS Extension Proposal 001 (BEP001), which adds a range of quantitative MRI (qMRI) applications to the BIDS. In general, the aim of qMRI is to characterize brain microstructure by quantifying the physical MR parameters of the tissue via computational, biophysical models. By proposing this new standard, we envision standardization of qMRI through multicenter dissemination of interoperable datasets. This way, BIDS can act as a catalyst of convergence between qMRI methods development and application-driven neuroimaging studies that can help develop quantitative biomarkers for neural tissue characterization. In conclusion, this BIDS extension offers a common ground for developers to exchange novel imaging data and tools, reducing the entrance barrier for qMRI in the field of neuroimaging.
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Affiliation(s)
- Agah Karakuzu
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montréal, QC, Canada. .,Montreal Heart Institute, Montreal, QC, Canada.
| | - Stefan Appelhoff
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
| | - Tibor Auer
- NeuroModulation Lab, School of Psychology, University of Surrey, Guildford, UK
| | - Mathieu Boudreau
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montréal, QC, Canada.,Montreal Heart Institute, Montreal, QC, Canada
| | | | - Ali R Khan
- Department of Medical Biophysics, Robarts Research Institute, University of Western Ontario, London, Canada
| | - Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Martijn Mulder
- Department of Experimental Psychology, Utrecht University, Utrecht, the Netherlands
| | - Christophe Phillips
- GIGA Cyclotron Research Centre in vivo imaging, GIGA Institute, University of Liège, Liège, Belgium
| | - Taylor Salo
- Florida International University, Miami, FL, USA
| | - Nikola Stikov
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montréal, QC, Canada.,Montreal Heart Institute, Montreal, QC, Canada.,Center for Advanced Interdisciplinary Research, Ss. Cyril and Methodius University, Skopje, North Macedonia
| | | | - Gilles de Hollander
- Zurich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, Zurich, Switzerland. .,Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands.
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49
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Casella C, Chamberland M, Laguna PL, Parker GD, Rosser AE, Coulthard E, Rickards H, Berry SC, Jones DK, Metzler‐Baddeley C. Mutation-related magnetization-transfer, not axon density, drives white matter differences in premanifest Huntington disease: Evidence from in vivo ultra-strong gradient MRI. Hum Brain Mapp 2022; 43:3439-3460. [PMID: 35396899 PMCID: PMC9248323 DOI: 10.1002/hbm.25859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 03/07/2022] [Accepted: 03/27/2022] [Indexed: 11/10/2022] Open
Abstract
White matter (WM) alterations have been observed in Huntington disease (HD) but their role in the disease-pathophysiology remains unknown. We assessed WM changes in premanifest HD by exploiting ultra-strong-gradient magnetic resonance imaging (MRI). This allowed to separately quantify magnetization transfer ratio (MTR) and hindered and restricted diffusion-weighted signal fractions, and assess how they drove WM microstructure differences between patients and controls. We used tractometry to investigate region-specific alterations across callosal segments with well-characterized early- and late-myelinating axon populations, while brain-wise differences were explored with tract-based cluster analysis (TBCA). Behavioral measures were included to explore disease-associated brain-function relationships. We detected lower MTR in patients' callosal rostrum (tractometry: p = .03; TBCA: p = .03), but higher MTR in their splenium (tractometry: p = .02). Importantly, patients' mutation-size and MTR were positively correlated (all p-values < .01), indicating that MTR alterations may directly result from the mutation. Further, MTR was higher in younger, but lower in older patients relative to controls (p = .003), suggesting that MTR increases are detrimental later in the disease. Finally, patients showed higher restricted diffusion signal fraction (FR) from the composite hindered and restricted model of diffusion (CHARMED) in the cortico-spinal tract (p = .03), which correlated positively with MTR in the posterior callosum (p = .033), potentially reflecting compensatory mechanisms. In summary, this first comprehensive, ultra-strong gradient MRI study in HD provides novel evidence of mutation-driven MTR alterations at the premanifest disease stage which may reflect neurodevelopmental changes in iron, myelin, or a combination of these.
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Affiliation(s)
- Chiara Casella
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
- Department of Perinatal Imaging and Health, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUK
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenThe Netherlands
| | - Pedro L. Laguna
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Greg D. Parker
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Anne E. Rosser
- Department of Neurology and Psychological MedicineHayden Ellis BuildingCardiffUK
- School of BiosciencesCardiff UniversityCardiffUK
| | | | - Hugh Rickards
- Birmingham and Solihull Mental Health NHS Foundation TrustBirminghamUK
- Institute of Clinical Sciences, College of Medical and Dental SciencesUniversity of BirminghamBirminghamUK
| | - Samuel C. Berry
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Claudia Metzler‐Baddeley
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
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50
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Jelescu IO, de Skowronski A, Geffroy F, Palombo M, Novikov DS. Neurite Exchange Imaging (NEXI): A minimal model of diffusion in gray matter with inter-compartment water exchange. Neuroimage 2022; 256:119277. [PMID: 35523369 PMCID: PMC10363376 DOI: 10.1016/j.neuroimage.2022.119277] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 04/26/2022] [Accepted: 05/01/2022] [Indexed: 01/18/2023] Open
Abstract
Biophysical models of diffusion in white matter have been center-stage over the past two decades and are essentially based on what is now commonly referred to as the "Standard Model" (SM) of non-exchanging anisotropic compartments with Gaussian diffusion. In this work, we focus on diffusion MRI in gray matter, which requires rethinking basic microstructure modeling blocks. In particular, at least three contributions beyond the SM need to be considered for gray matter: water exchange across the cell membrane - between neurites and the extracellular space; non-Gaussian diffusion along neuronal and glial processes - resulting from structural disorder; and signal contribution from soma. For the first contribution, we propose Neurite Exchange Imaging (NEXI) as an extension of the SM of diffusion, which builds on the anisotropic Kärger model of two exchanging compartments. Using datasets acquired at multiple diffusion weightings (b) and diffusion times (t) in the rat brain in vivo, we investigate the suitability of NEXI to describe the diffusion signal in the gray matter, compared to the other two possible contributions. Our results for the diffusion time window 20-45 ms show minimal diffusivity time-dependence and more pronounced kurtosis decay with time, which is well fit by the exchange model. Moreover, we observe lower signal for longer diffusion times at high b. In light of these observations, we identify exchange as the mechanism that best explains these signal signatures in both low-b and high-b regime, and thereby propose NEXI as the minimal model for gray matter microstructure mapping. We finally highlight multi-b multi-t acquisition protocols as being best suited to estimate NEXI model parameters reliably. Using this approach, we estimate the inter-compartment water exchange time to be 15 - 60 ms in the rat cortex and hippocampus in vivo, which is of the same order or shorter than the diffusion time in typical diffusion MRI acquisitions. This suggests water exchange as an essential component for interpreting diffusion MRI measurements in gray matter.
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Affiliation(s)
- Ileana O Jelescu
- CIBM Center for Biomedical Imaging, Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland; School of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland.
| | - Alexandre de Skowronski
- CIBM Center for Biomedical Imaging, Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | | | - Marco Palombo
- School of Psychology, Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK; School of Computer Science and Informatics, Cardiff University, Cardiff, UK; Department of Computer Science, Centre for Medical Image Computing, University College London, London, UK
| | - Dmitry S Novikov
- Department of Radiology, Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA
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