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Shin SH, Moazamian D, Suprana A, Zeng C, Athertya JS, Carl M, Ma Y, Jang H, Du J. Yet more evidence that non-aqueous myelin lipids can be directly imaged with ultrashort echo time (UTE) MRI on a clinical 3T scanner: a lyophilized red blood cell membrane lipid study. Neuroimage 2024; 296:120666. [PMID: 38830440 DOI: 10.1016/j.neuroimage.2024.120666] [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: 08/21/2023] [Revised: 05/16/2024] [Accepted: 05/31/2024] [Indexed: 06/05/2024] Open
Abstract
Direct imaging of semi-solid lipids, such as myelin, is of great interest as a noninvasive biomarker of neurodegenerative diseases. Yet, the short T2 relaxation times of semi-solid lipid protons hamper direct detection through conventional magnetic resonance imaging (MRI) pulse sequences. In this study, we examined whether a three-dimensional ultrashort echo time (3D UTE) sequence can directly acquire signals from membrane lipids. Membrane lipids from red blood cells (RBC) were collected from commercially available blood as a general model of the myelin lipid bilayer and subjected to D2O exchange and freeze-drying for complete water removal. Sufficiently high MR signals were detected with the 3D UTE sequence, which showed an ultrashort T2* of ∼77-271 µs and a short T1 of ∼189 ms for semi-solid RBC membrane lipids. These measurements can guide designing UTE-based sequences for direct in vivo imaging of membrane lipids.
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Affiliation(s)
- Soo Hyun Shin
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Dina Moazamian
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Arya Suprana
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA; Shu Chien-Gene Lay Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Chun Zeng
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Jiyo S Athertya
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | | | - Yajun Ma
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Hyungseok Jang
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Jiang Du
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA; Shu Chien-Gene Lay Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA; Radiology Service, Veterans Affairs San Diego Healthcare System, La Jolla, CA, USA.
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Singh S, Sutkus L, Li Z, Baker S, Bear J, Dilger RN, Miller DJ. Standardization of a silver stain to reveal mesoscale myelin in histological preparations of the mammalian brain. J Neurosci Methods 2024; 407:110139. [PMID: 38626852 DOI: 10.1016/j.jneumeth.2024.110139] [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: 01/18/2024] [Revised: 03/26/2024] [Accepted: 04/12/2024] [Indexed: 04/29/2024]
Abstract
BACKGROUND The brain is built of neurons supported by myelin, a fatty substance that improves cellular communication. Noninvasive magnetic resonance imaging (MRI) is now able to measure brain structure like myelin and requires histological validation. NEW METHOD Here we present work in small and large biomedical model mammals to standardize a silver impregnation method as a high-throughput histological myelin visualization procedure. Specifically, we built a new staining well plate to increase batch size, and then systematically varied the staining and clearing cycles to describe the staining response curve across taxa and conditions. We compared tissues fixed by immersion or perfusion, mounted versus free-floating, and cut as thicker or thinner slices, with two-weeks of post-fixation. RESULTS The staining response curves show optimal staining with a single exposure across taxa when incubation and clearing epochs are held to within 3-9 min. We show that clearing was slower in mounted vs free-floating tissue, and that staining was faster and caused fracturing earlier in thinner sliced and smaller volumes of tissue. COMPARISON WITH EXISTING METHODS We developed a batch processing approach to increase throughput while ensuring reproducibility and demonstrate the optimal conditions for fine myelinated fiber morphology visualization with short cycles (<9 minutes). CONCLUSIONS We present our optimized protocol to reveal mesoscale neuroanatomical myelin content in histology across mammals. This standard staining procedure will facilitate multiscale analyses of myelin content across development as well as in the presence of injury or disease.
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Affiliation(s)
- S Singh
- Department of Evolution, Ecology, and Behavior, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America
| | - L Sutkus
- Neuroscience Program, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America
| | - Z Li
- Neuroscience Program, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America
| | - S Baker
- Machine Shop, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America
| | - J Bear
- Machine Shop, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America
| | - R N Dilger
- Department of Animal Sciences, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America; Neuroscience Program, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America; Beckman Institute for Advanced Science and Technology, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America
| | - D J Miller
- Department of Evolution, Ecology, and Behavior, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America; Neuroscience Program, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America; Beckman Institute for Advanced Science and Technology, at the University of Illinois at Urbana-Champaign, 505 South Goodwin Ave, Urbana, IL 61801, United States of America.
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Lee J, Ji S, Oh SH. So You Want to Image Myelin Using MRI: Magnetic Susceptibility Source Separation for Myelin Imaging. Magn Reson Med Sci 2024; 23:291-306. [PMID: 38644201 DOI: 10.2463/mrms.rev.2024-0001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/23/2024] Open
Abstract
In MRI, researchers have long endeavored to effectively visualize myelin distribution in the brain, a pursuit with significant implications for both scientific research and clinical applications. Over time, various methods such as myelin water imaging, magnetization transfer imaging, and relaxometric imaging have been developed, each carrying distinct advantages and limitations. Recently, an innovative technique named as magnetic susceptibility source separation has emerged, introducing a novel surrogate biomarker for myelin in the form of a diamagnetic susceptibility map. This paper comprehensively reviews this cutting-edge method, providing the fundamental concepts of magnetic susceptibility, susceptibility imaging, and the validation of the diamagnetic susceptibility map as a myelin biomarker that indirectly measures myelin content. Additionally, the paper explores essential aspects of data acquisition and processing, offering practical insights for readers. A comparison with established myelin imaging methods is also presented, and both current and prospective clinical and scientific applications are discussed to provide a holistic understanding of the technique. This work aims to serve as a foundational resource for newcomers entering this dynamic and rapidly expanding field.
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Affiliation(s)
- Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Sooyeon Ji
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Se-Hong Oh
- Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Korea
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Zuroff LR, Green AJ. The Study of Remyelinating Therapies in Multiple Sclerosis: Visual Outcomes as a Window Into Repair. J Neuroophthalmol 2024; 44:143-156. [PMID: 38654413 DOI: 10.1097/wno.0000000000002149] [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: 04/26/2024]
Abstract
INTRODUCTION Amelioration of disability in multiple sclerosis requires the development of complementary therapies that target neurodegeneration and promote repair. Remyelination is a promising neuroprotective strategy that may protect axons from damage and subsequent neurodegeneration. METHODS A review of key literature plus additional targeted search of PubMed and Google Scholar was conducted. RESULTS There has been a rapid expansion of clinical trials studying putative remyelinating candidates, but further growth of the field is limited by the lack of consensus on key aspects of trial design. We have not yet defined the ideal study population, duration of therapy, or the appropriate outcome measures to detect remyelination in humans. The varied natural history of multiple sclerosis, coupled with the short time frame of phase II clinical trials, requires that we develop and validate biomarkers of remyelination that can serve as surrogate endpoints in clinical trials. CONCLUSIONS We propose that the visual system may be the most well-suited and validated model for the study potential remyelinating agents. In this review, we discuss the pathophysiology of demyelination and summarize the current clinical trial landscape of remyelinating agents. We present some of the challenges in the study of remyelinating agents and discuss current potential biomarkers of remyelination and repair, emphasizing both established and emerging visual outcome measures.
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Affiliation(s)
- Leah R Zuroff
- Department of Neurology (LZ), Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; and Department of Neurology (AJG), University of California San Francisco, San Francisco, California
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Guillemin C, Vandeleene N, Charonitis M, Requier F, Delrue G, Lommers E, Maquet P, Phillips C, Collette F. Brain microstructure is linked to cognitive fatigue in early multiple sclerosis. J Neurol 2024; 271:3537-3545. [PMID: 38538776 DOI: 10.1007/s00415-024-12316-1] [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: 12/29/2023] [Revised: 03/08/2024] [Accepted: 03/08/2024] [Indexed: 05/30/2024]
Abstract
Cognitive fatigue is a major symptom of Multiple Sclerosis (MS), from the early stages of the disease. This study aims to detect if brain microstructure is altered early in the disease course and is associated with cognitive fatigue in people with MS (pwMS) compared to matched healthy controls (HC). Recently diagnosed pwMS (N = 18, age < 45 years old) with either a Relapsing-Remitting or a Clinically Isolated Syndrome course of the disease, and HC (N = 19) matched for sex, age and education were analyzed. Quantitative multiparameter maps (MTsat, PD, R1 and R2*) of pwMS and HC were calculated. Parameters were extracted within the normal appearing white matter, cortical grey matter and deep grey matter (NAWM, NACGM and NADGM, respectively). Bayesian T-test for independent samples assessed between-group differences in brain microstructure while associations between score at a cognitive fatigue scale and each parameter in each tissue class were investigated with Generalized Linear Mixed Models. Patients exhibited lower MTsat and R1 values within NAWM and NACGM, and higher R1 values in NADGM compared to HC. Cognitive fatigue was associated with PD measured in every tissue class and to MTsat in NAWM, regardless of group. Disease-specific negative correlations were found in pwMS in NAWM (R1, R2*) and NACGM (R1). These findings suggest that brain microstructure within normal appearing tissues is already altered in the very early stages of the disease. Moreover, additional microstructure alterations (e.g. diffuse and widespread demyelination or axonal degeneration) in pwMS may lead to disease-specific complaint of cognitive fatigue.
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Affiliation(s)
- Camille Guillemin
- GIGA-CRC In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - Nora Vandeleene
- GIGA-CRC In Vivo Imaging, University of Liège, Liège, Belgium
| | - Maëlle Charonitis
- GIGA-CRC In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - Florence Requier
- GIGA-CRC In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - Gaël Delrue
- Department of Neurology, CHU of Liège Sart Tilman, Liège, Belgium
| | - Emilie Lommers
- GIGA-CRC In Vivo Imaging, University of Liège, Liège, Belgium
- Department of Neurology, CHU of Liège Sart Tilman, Liège, Belgium
| | - Pierre Maquet
- GIGA-CRC In Vivo Imaging, University of Liège, Liège, Belgium
- Department of Neurology, CHU of Liège Sart Tilman, Liège, Belgium
| | - Christophe Phillips
- GIGA-CRC In Vivo Imaging, University of Liège, Liège, Belgium
- GIGA In Silico Medicine, University of Liège, Liège, Belgium
| | - Fabienne Collette
- GIGA-CRC In Vivo Imaging, University of Liège, Liège, Belgium.
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium.
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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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Bianchi A, Cortese R, Prados F, Tur C, Kanber B, Yiannakas MC, Samson R, De Angelis F, Magnollay L, Jacob A, Brownlee W, Trip A, Nicholas R, Hacohen Y, Barkhof F, Ciccarelli O, Toosy AT. Optic chiasm involvement in multiple sclerosis, aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein-associated disease. Mult Scler 2024; 30:674-686. [PMID: 38646958 PMCID: PMC11103893 DOI: 10.1177/13524585241240420] [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: 12/21/2023] [Revised: 02/27/2024] [Accepted: 03/01/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND Optic neuritis (ON) is a common feature of inflammatory demyelinating diseases (IDDs) such as multiple sclerosis (MS), aquaporin 4-antibody neuromyelitis optica spectrum disorder (AQP4 + NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). However, the involvement of the optic chiasm (OC) in IDD has not been fully investigated. AIMS To examine OC differences in non-acute IDD patients with (ON+) and without ON (ON-) using magnetisation transfer ratio (MTR), to compare differences between MS, AQP4 + NMOSD and MOGAD and understand their associations with other neuro-ophthalmological markers. METHODS Twenty-eight relapsing-remitting multiple sclerosis (RRMS), 24 AQP4 + NMOSD, 28 MOGAD patients and 32 healthy controls (HCs) underwent clinical evaluation, MRI and optical coherence tomography (OCT) scan. Multivariable linear regression models were applied. RESULTS ON + IDD patients showed lower OC MTR than HCs (28.87 ± 4.58 vs 31.65 ± 4.93; p = 0.004). When compared with HCs, lower OC MTR was found in ON + AQP4 + NMOSD (28.55 ± 4.18 vs 31.65 ± 4.93; p = 0.020) and MOGAD (28.73 ± 4.99 vs 31.65 ± 4.93; p = 0.007) and in ON- AQP4 + NMOSD (28.37 ± 7.27 vs 31.65 ± 4.93; p = 0.035). ON+ RRMS had lower MTR than ON- RRMS (28.87 ± 4.58 vs 30.99 ± 4.76; p = 0.038). Lower OC MTR was associated with higher number of ON (regression coefficient (RC) = -1.15, 95% confidence interval (CI) = -1.819 to -0.490, p = 0.001), worse visual acuity (RC = -0.026, 95% CI = -0.041 to -0.011, p = 0.001) and lower peripapillary retinal nerve fibre layer (pRNFL) thickness (RC = 1.129, 95% CI = 0.199 to 2.059, p = 0.018) when considering the whole IDD group. CONCLUSION OC microstructural damage indicates prior ON in IDD and is linked to reduced vision and thinner pRNFL.
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Affiliation(s)
- Alessia Bianchi
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Rosa Cortese
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Ferran Prados
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, University College London, London, UK
- eHealth Centre, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Carmen Tur
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- MS Centre of Catalonia (Cemcat), Vall d’Hebron Institute of Research, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Baris Kanber
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Marios C Yiannakas
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Rebecca Samson
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Floriana De Angelis
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Lise Magnollay
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Anu Jacob
- Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, UK
- Department of Neurology, Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Wallace Brownlee
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Biomedical Research Centre, National Institute for Health Research (NIHR), University College London Hospitals (UCLH), London, UK
| | - Anand Trip
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Biomedical Research Centre, National Institute for Health Research (NIHR), University College London Hospitals (UCLH), London, UK
| | - Richard Nicholas
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Yael Hacohen
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Neurology, Great Ormond Street Hospital For Children NHS Foundation Trust, London, UK
| | - Frederik Barkhof
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, University College London, London, UK
- Biomedical Research Centre, National Institute for Health Research (NIHR), University College London Hospitals (UCLH), London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Olga Ciccarelli
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Biomedical Research Centre, National Institute for Health Research (NIHR), University College London Hospitals (UCLH), London, UK
| | - Ahmed T Toosy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
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Mishra S, Bapuraj J, Srinivasan A. Multiple Sclerosis Part 2: Advanced Imaging and Emerging Techniques. Magn Reson Imaging Clin N Am 2024; 32:221-231. [PMID: 38555138 DOI: 10.1016/j.mric.2024.01.002] [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] [Indexed: 04/02/2024]
Abstract
Multiple advanced imaging methods for multiple sclerosis (MS) have been in investigation to identify new imaging biomarkers for early disease detection, predicting disease prognosis, and clinical trial endpoints. Multiple techniques probing different aspects of tissue microstructure (ie, advanced diffusion imaging, magnetization transfer, myelin water imaging, magnetic resonance spectroscopy, glymphatic imaging, and perfusion) support the notion that MS is a global disease with microstructural changes evident in normal-appearing white and gray matter. These global changes are likely better predictors of disability compared with lesion load alone. Emerging techniques in glymphatic and molecular imaging may improve understanding of pathophysiology and emerging treatments.
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Affiliation(s)
- Shruti Mishra
- Department of Radiology, University of Michigan, 1500 East Medical Center Drive, UH B2A209, Ann Arbor, MI 48109-5030, USA.
| | - Jayapalli Bapuraj
- Department of Radiology, University of Michigan, 1500 East Medical Center Drive, UH B2A209, Ann Arbor, MI 48109-5030, USA
| | - Ashok Srinivasan
- Department of Radiology, University of Michigan, 1500 East Medical Center Drive, UH B2A209, Ann Arbor, MI 48109-5030, USA
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Ananthavarathan P, Sahi N, Chard DT. An update on the role of magnetic resonance imaging in predicting and monitoring multiple sclerosis progression. Expert Rev Neurother 2024; 24:201-216. [PMID: 38235594 DOI: 10.1080/14737175.2024.2304116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/08/2024] [Indexed: 01/19/2024]
Abstract
INTRODUCTION While magnetic resonance imaging (MRI) is established in diagnosing and monitoring disease activity in multiple sclerosis (MS), its utility in predicting and monitoring disease progression is less clear. AREAS COVERED The authors consider changing concepts in the phenotypic classification of MS, including progression independent of relapses; pathological processes underpinning progression; advances in MRI measures to assess them; how well MRI features explain and predict clinical outcomes, including models that assess disease effects on neural networks, and the potential role for machine learning. EXPERT OPINION Relapsing-remitting and progressive MS have evolved from being viewed as mutually exclusive to having considerable overlap. Progression is likely the consequence of several pathological elements, each important in building more holistic prognostic models beyond conventional phenotypes. MRI is well placed to assess pathogenic processes underpinning progression, but we need to bridge the gap between MRI measures and clinical outcomes. Mapping pathological effects on specific neural networks may help and machine learning methods may be able to optimize predictive markers while identifying new, or previously overlooked, clinically relevant features. The ever-increasing ability to measure features on MRI raises the dilemma of what to measure and when, and the challenge of translating research methods into clinically useable tools.
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Affiliation(s)
- Piriyankan Ananthavarathan
- Department of Neuroinflammation, University College London Queen Square Multiple Sclerosis Centre, London, UK
| | - Nitin Sahi
- Department of Neuroinflammation, University College London Queen Square Multiple Sclerosis Centre, London, UK
| | - Declan T Chard
- Clinical Research Associate & Consultant Neurologist, Institute of Neurology - Queen Square Multiple Sclerosis Centre, London, UK
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Wu H, Fan S, Yan C, Wang H. Cortical microstructural brain network mediates the association between personality trait of agreeableness and life satisfaction. Cereb Cortex 2024; 34:bhad410. [PMID: 37948663 DOI: 10.1093/cercor/bhad410] [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: 09/12/2022] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 11/12/2023] Open
Abstract
Personality traits are commonly regarded as relatively stable, whereas life satisfaction can fluctuate with time and circumstances, shaped by external influences and personal encounters. The correlation between personality traits and life satisfaction is well-established, yet the underlying neural mechanisms of the myelin-based microstructural brain network connecting them remain unclear. Here, we constructed individual-level whole-brain myelin microstructural networks from the MRI data of 1,043 healthy adults and performed correlation analysis to detect significant personality trait-related and life satisfaction-related subnetworks. A mediation analysis was used to verify whether the shared structural basis of personality traits and life satisfaction significantly mediated their association. The results showed that agreeableness positively correlated with life satisfaction. We identified a shared structural basis of the personality trait of agreeableness and life satisfaction. The regions comprising this overlapping network include the superior parietal lobule, inferior parietal lobule, and temporoparietal junction. Moreover, the shared microstructural connections mediate the association between the personality trait of agreeableness and life satisfaction. This large-scale neuroimaging investigation substantiates a mediation framework for understanding the microstructural connections between personality and life satisfaction, offering potential targets for assessment and interventions to promote human well-being.
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Affiliation(s)
- Huijun Wu
- School of Media & Communication, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Shijia Fan
- School of Psychological and Cognitive Sciences & Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing 100871, China
| | - Chuyao Yan
- School of Psychology, Nanjing Normal University, Nanjing 200097, China
| | - Hao Wang
- School of Physics and Optoelectronic Engineering, Hainan University, Haikou 570228, China
- G. Oppenheimer Center for Neurobiology of Stress & Resilience, UCLA, Los Angeles, CA 90095, United States
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Pokošová P, Kala D, Šanda J, Ježdík P, Prysiazhniuk Y, Faridová A, Jahodová A, Bělohlávková A, Kalina A, Holubová Z, Jurášek B, Kynčl M, Otáhal J. Magnetic resonance imaging techniques for indirect assessment of myelin content in the brain using standard T1w and T2w MRI sequences and postprocessing analysis. Physiol Res 2023; 72:S573-S585. [PMID: 38165761 PMCID: PMC10861246 DOI: 10.33549/physiolres.935250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 10/10/2023] [Indexed: 02/01/2024] Open
Abstract
Magnetic Resonance Imaging (MRI) has revolutionized our ability to non-invasively study the brain's structural and functional properties. However, detecting myelin, a crucial component of white matter, remains challenging due to its indirect visibility on conventional MRI scans. Myelin plays a vital role in neural signal transmission and is associated with various neurological conditions. Understanding myelin distribution and content is crucial for insights into brain development, aging, and neurological disorders. Although specialized MRI sequences can estimate myelin content, these are time-consuming. Also, many patients sent to specialized neurological centers have an MRI of the brain already scanned. In this study, we focused on techniques utilizing standard MRI T1-weighted (T1w) and T2 weighted (T2w) sequences commonly used in brain imaging protocols. We evaluated the applicability of the T1w/T2w ratio in assessing myelin content by comparing it to quantitative T1 mapping (qT1). Our study included 1 healthy adult control and 7 neurologic patients (comprising both pediatric and adult populations) with epilepsy originating from focal epileptogenic lesions visible on MRI structural scans. Following image acquisition on a 3T Siemens Vida scanner, datasets were co registered, and segmented into anatomical regions using the Fastsurfer toolbox, and T1w/T2w ratio maps were calculated in Matlab software. We further assessed interhemispheric differences in volumes of individual structures, their signal intensity, and the correlation of the T1w/T2w ratio to qT1. Our data demonstrate that in situations where a dedicated myelin-sensing sequence such as qT1 is not available, the T1w/T2w ratio provides significantly better information than T1w alone. By providing indirect information about myelin content, this technique offers a valuable tool for understanding the neurobiology of myelin-related conditions using basic brain scans.
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Affiliation(s)
- P Pokošová
- Department of Pathophysiology, Second Faculty of Medicine, Charles University, Praha 5, Czech Republic.
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Khormi I, Al-Iedani O, Alshehri A, Ramadan S, Lechner-Scott J. MR myelin imaging in multiple sclerosis: A scoping review. J Neurol Sci 2023; 455:122807. [PMID: 38035651 DOI: 10.1016/j.jns.2023.122807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/20/2023] [Accepted: 11/19/2023] [Indexed: 12/02/2023]
Abstract
The inability of disease-modifying therapies to stop the progression of multiple sclerosis (MS), has led to the development of a new therapeutic strategy focussing on myelin repair. While conventional MRI lacks sensitivity for quantifying myelin damage, advanced MRI techniques are proving effective. The development of targeted therapeutics requires histological validation of myelin imaging results, alongside the crucial task of establishing correlations between myelin imaging results and clinical assessments, so that the effectiveness of therapeutic interventions can be evaluated. The aims of this scoping review were to identify myelin imaging methods - some of which have been histologically validated, and to determine how these approaches correlate with clinical assessments of people with MS (pwMS), thus allowing for effective therapeutic evaluation. A search of two databases was undertaken for publications relating to studies on adults MS using either MRI/MR-histology of the MS brain in the range 1990-to-2022. The myelin imaging methods specified were relaxometry, magnetization transfer, and quantitative susceptibility. Relaxometry was used most frequently, with myelin water fraction (MWF) being the primary metric. Studies conducted on tissue from various regions of the brain showed that MWF was significantly lower in pwMS than in healthy controls. Magnetization transfer ratio indicated that the macromolecular content of lesions was lower than that of normal-appearing tissue. Higher magnetic susceptibility of lesions were indicative of myelin breakdown and iron accumulation. Several myelin imaging metrics were correlated with disability, disease severity and duration. Many studies showed a good correlation between myelin measured histologically and by MR myelin imaging techniques.
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Affiliation(s)
- Ibrahim Khormi
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia
| | - Oun Al-Iedani
- Hunter Medical Research Institute, New Lambton Heights, Australia; School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
| | - Abdulaziz Alshehri
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Radiology, King Fahd Hospital of the University, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Saadallah Ramadan
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia.
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Neurology, John Hunter Hospital, New Lambton Heights, Australia; School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
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Lewis L, Corcoran M, Cho KIK, Kwak Y, Hayes RA, Larsen B, Jalbrzikowski M. Age-associated alterations in thalamocortical structural connectivity in youths with a psychosis-spectrum disorder. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:86. [PMID: 38081873 PMCID: PMC10713597 DOI: 10.1038/s41537-023-00411-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 10/30/2023] [Indexed: 12/23/2023]
Abstract
Psychotic symptoms typically emerge in adolescence. Age-associated thalamocortical connectivity differences in psychosis remain unclear. We analyzed diffusion-weighted imaging data from 1254 participants 8-23 years old (typically developing (TD):N = 626, psychosis-spectrum (PS): N = 329, other psychopathology (OP): N = 299) from the Philadelphia Neurodevelopmental Cohort. We modeled thalamocortical tracts using deterministic fiber tractography, extracted Q-Space Diffeomorphic Reconstruction (QSDR) and diffusion tensor imaging (DTI) measures, and then used generalized additive models to determine group and age-associated thalamocortical connectivity differences. Compared to other groups, PS exhibited thalamocortical reductions in QSDR global fractional anisotropy (GFA, p-values range = 3.0 × 10-6-0.05) and DTI fractional anisotropy (FA, p-values range = 4.2 × 10-4-0.03). Compared to TD, PS exhibited shallower thalamus-prefrontal age-associated increases in GFA and FA during mid-childhood, but steeper age-associated increases during adolescence. TD and OP exhibited decreases in thalamus-frontal mean and radial diffusivities during adolescence; PS did not. Altered developmental trajectories of thalamocortical connectivity may contribute to the disruptions observed in adults with psychosis.
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Affiliation(s)
- Lydia Lewis
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Mary Corcoran
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
| | - Kang Ik K Cho
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - YooBin Kwak
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Rebecca A Hayes
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
| | - Bart Larsen
- Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
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Zhang S, She S, Qiu Y, Li Z, Mao D, Zheng W, Wu H, Huang R. Altered cortical myelin in the salience and default mode networks in major depressive disorder patients: A surface-based analysis. J Affect Disord 2023; 340:113-119. [PMID: 37517634 DOI: 10.1016/j.jad.2023.07.068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 05/23/2023] [Accepted: 07/14/2023] [Indexed: 08/01/2023]
Abstract
INTRODUCTION Evidence from previous genetic and post-mortem studies suggested that the myelination abnormality contributed to the pathogenesis of major depressive disorder (MDD). However, image-level alterations in cortical myelin content associated with MDD are still unclear. METHODS The high-resolution T1-weighted (T1w) and T2-weighted (T2w) brain 3D structural images were obtained from 52 MDD patients and 52 healthy controls (HC). We calculated the vertex-based T1w/T2w ratio using the HCP structural pipelines to characterize individual cortical myelin maps at the fs_LR 32 k surface. We attempted to detect the clusters with significant differences in cortical myelin content between MDD and HC groups. We correlated the cluster-wise averaged myelin value and the clinical performances in MDD patients. RESULTS The MDD patients showed significantly lower cortical myelin content in the cluster involving the left insula, orbitofrontal cortex, superior temporal cortex, transverse temporal gyrus, inferior frontal cortex, superior frontal gyrus, anterior cingulate cortex, precentral cortex, and postcentral cortex. The correlation analysis showed a significantly positive correlation between the cluster-wise cortical myelin content and the onset age of MDD patients. CONCLUSION The MDD patients showed lower cortical myelin content in regions of the default mode network regions and salience network than healthy controls.
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Affiliation(s)
- Shufei Zhang
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China
| | - Shenglin She
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China
| | - Yidan Qiu
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China
| | - Zezhi Li
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China; The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China
| | - Deng Mao
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China
| | - Wei Zheng
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China
| | - Huawang Wu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China.
| | - Ruiwang Huang
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China.
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15
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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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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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17
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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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18
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Hejrati N, Wong R, Khazaei M, Fehlings MG. How can clinical safety and efficacy concerns in stem cell therapy for spinal cord injury be overcome? Expert Opin Biol Ther 2023; 23:883-899. [PMID: 37545020 DOI: 10.1080/14712598.2023.2245321] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 08/03/2023] [Indexed: 08/08/2023]
Abstract
INTRODUCTION Spinal cord injury (SCI) can lead to severe neurological dysfunction. Despite scientific and medical advances, clinically effective regenerative therapies including stem cells are lacking for SCI. AREAS COVERED This paper discusses translational challenges related to the safe, effective use of stem cells for SCI, with a focus on mesenchymal stem cells (MSCs), neural stem cells (NSCs), Schwann cells (SCs), olfactory ensheathing cells (OECs), oligodendrocyte precursor cells (OPCs), embryonic stem cells (ESCs), and induced pluripotent stem cells (iPSCs). We discuss approaches to enhance the efficacy of cell-based strategies by i) addressing patient heterogeneity and enhancing patient selection; ii) selecting cell type, cell source, cell developmental stage, and delivery technique; iii) enhancing graft integration and mitigating immune-mediated graft rejection; and iv) ensuring availability of cells. Additionally, we review strategies to optimize outcomes including combinatorial use of rehabilitation and discuss ways to mitigate potential risks of tumor formation associated with stem cell-based strategies. EXPERT OPINION Basic science research will drive translational advances to develop stem cell-based therapies for SCI. Genetic, serological, and imaging biomarkers may enable individualization of cell-based treatments. Moreover, combinatorial strategies will be required to enhance graft survival, migration and functional integration, to enable precision-based intervention.
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Affiliation(s)
- Nader Hejrati
- Division of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, ON, Canada
- Division of Neurosurgery and Spine Program, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Department of Neurosurgery & Spine Center of Eastern Switzerland, Cantonal Hospital St.Gallen, St.Gallen, Switzerland
| | - Raymond Wong
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Mohamad Khazaei
- Division of Neurosurgery and Spine Program, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Michael G Fehlings
- Division of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, ON, Canada
- Division of Neurosurgery and Spine Program, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
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19
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Obrecht M, Zurbruegg S, Accart N, Lambert C, Doelemeyer A, Ledermann B, Beckmann N. Magnetic resonance imaging and ultrasound elastography in the context of preclinical pharmacological research: significance for the 3R principles. Front Pharmacol 2023; 14:1177421. [PMID: 37448960 PMCID: PMC10337591 DOI: 10.3389/fphar.2023.1177421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/16/2023] [Indexed: 07/18/2023] Open
Abstract
The 3Rs principles-reduction, refinement, replacement-are at the core of preclinical research within drug discovery, which still relies to a great extent on the availability of models of disease in animals. Minimizing their distress, reducing their number as well as searching for means to replace them in experimental studies are constant objectives in this area. Due to its non-invasive character in vivo imaging supports these efforts by enabling repeated longitudinal assessments in each animal which serves as its own control, thereby enabling to reduce considerably the animal utilization in the experiments. The repetitive monitoring of pathology progression and the effects of therapy becomes feasible by assessment of quantitative biomarkers. Moreover, imaging has translational prospects by facilitating the comparison of studies performed in small rodents and humans. Also, learnings from the clinic may be potentially back-translated to preclinical settings and therefore contribute to refining animal investigations. By concentrating on activities around the application of magnetic resonance imaging (MRI) and ultrasound elastography to small rodent models of disease, we aim to illustrate how in vivo imaging contributes primarily to reduction and refinement in the context of pharmacological research.
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Affiliation(s)
- Michael Obrecht
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Nathalie Accart
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Christian Lambert
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Arno Doelemeyer
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Birgit Ledermann
- 3Rs Leader, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Nicolau Beckmann
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
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20
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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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21
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Kujawa MJ, Marcinkowska AB, Grzywińska M, Waśkow M, Romanowski A, Szurowska E, Winklewski PJ, Szarmach A. Physical activity and the brain myelin content in humans. Front Cell Neurosci 2023; 17:1198657. [PMID: 37342769 PMCID: PMC10277468 DOI: 10.3389/fncel.2023.1198657] [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: 04/01/2023] [Accepted: 05/19/2023] [Indexed: 06/23/2023] Open
Abstract
New imaging sequences and biophysical models allow adopting magnetic resonance imaging (MRI) for in vivo myelin mapping in humans. Understanding myelination and remyelination processes in the brain is fundamental from the perspective of proper design of physical exercise and rehabilitation schemes that aim to slow down demyelination in the aging population and to induce remyelination in patients with neurodegenerative diseases. Therefore, in this review we strive to provide a state-of-the art summary of the existing MRI studies in humans focused on the effects of physical activity on myelination/remyelination. We present and discuss four cross-sectional and four longitudinal studies and one case report. Physical activity and an active lifestyle have a beneficial effect on the myelin content in humans. Myelin expansion can be induced in humans throughout the entire lifespan by intensive aerobic exercise. Additional research is needed to determine (1) what exercise intensity (and cognitive novelty, which is embedded in the exercise scheme) is the most beneficial for patients with neurodegenerative diseases, (2) the relationship between cardiorespiratory fitness and myelination, and (3) how exercise-induced myelination affect cognitive abilities.
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Affiliation(s)
- Mariusz J. Kujawa
- 2nd Department of Radiology, Medical University of Gdańsk, Gdańsk, Poland
| | - Anna B. Marcinkowska
- 2nd Department of Radiology, Medical University of Gdańsk, Gdańsk, Poland
- Applied Cognitive Neuroscience Lab, Department of Neurophysiology, Neuropsychology and Neuroinformatics, Medical University of Gdańsk, Gdańsk, Poland
| | - Małgorzata Grzywińska
- Neuroinformatics and Artificial Intelligence Lab, Department of Neurophysiology, Neuropsychology and Neuroinformatics, Medical University of Gdańsk, Gdańsk, Poland
| | - Monika Waśkow
- Institute of Health Sciences, Pomeranian University in Słupsk, Słupsk, Poland
| | | | - Edyta Szurowska
- 2nd Department of Radiology, Medical University of Gdańsk, Gdańsk, Poland
| | - Paweł J. Winklewski
- 2nd Department of Radiology, Medical University of Gdańsk, Gdańsk, Poland
- Department of Neurophysiology, Neuropsychology and Neuroinformatics, Medical University of Gdańsk, Gdańsk, Poland
| | - Arkadiusz Szarmach
- 2nd Department of Radiology, Medical University of Gdańsk, Gdańsk, Poland
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22
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Villaseñor PJ, Cortés-Servín D, Pérez-Moriel A, Aquiles A, Luna-Munguía H, Ramirez-Manzanares A, Coronado-Leija R, Larriva-Sahd J, Concha L. Multi-tensor diffusion abnormalities of gray matter in an animal model of cortical dysplasia. Front Neurol 2023; 14:1124282. [PMID: 37342776 PMCID: PMC10278582 DOI: 10.3389/fneur.2023.1124282] [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: 12/15/2022] [Accepted: 04/18/2023] [Indexed: 06/23/2023] Open
Abstract
Focal cortical dysplasias are a type of malformations of cortical development that are a common cause of drug-resistant focal epilepsy. Surgical treatment is a viable option for some of these patients, with their outcome being highly related to complete surgical resection of lesions visible in magnetic resonance imaging (MRI). However, subtle lesions often go undetected on conventional imaging. Several methods to analyze MRI have been proposed, with the common goal of rendering subtle cortical lesions visible. However, most image-processing methods are targeted to detect the macroscopic characteristics of cortical dysplasias, which do not always correspond to the microstructural disarrangement of these cortical malformations. Quantitative analysis of diffusion-weighted MRI (dMRI) enables the inference of tissue characteristics, and novel methods provide valuable microstructural features of complex tissue, including gray matter. We investigated the ability of advanced dMRI descriptors to detect diffusion abnormalities in an animal model of cortical dysplasia. For this purpose, we induced cortical dysplasia in 18 animals that were scanned at 30 postnatal days (along with 19 control animals). We obtained multi-shell dMRI, to which we fitted single and multi-tensor representations. Quantitative dMRI parameters derived from these methods were queried using a curvilinear coordinate system to sample the cortical mantle, providing inter-subject anatomical correspondence. We found region- and layer-specific diffusion abnormalities in experimental animals. Moreover, we were able to distinguish diffusion abnormalities related to altered intra-cortical tangential fibers from those associated with radial cortical fibers. Histological examinations revealed myelo-architectural abnormalities that explain the alterations observed through dMRI. The methods for dMRI acquisition and analysis used here are available in clinical settings and our work shows their clinical relevance to detect subtle cortical dysplasias through analysis of their microstructural properties.
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Affiliation(s)
- Paulina J. Villaseñor
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | - David Cortés-Servín
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | | | - Ana Aquiles
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | - Hiram Luna-Munguía
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | | | - Ricardo Coronado-Leija
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States
| | - Jorge Larriva-Sahd
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | - Luis Concha
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
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23
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Stellingwerff MD, Pouwels PJW, Roosendaal SD, Barkhof F, van der Knaap MS. Quantitative MRI in leukodystrophies. Neuroimage Clin 2023; 38:103427. [PMID: 37150021 PMCID: PMC10193020 DOI: 10.1016/j.nicl.2023.103427] [Citation(s) in RCA: 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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24
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Kelly KJ, Hutton JS, Parikh NA, Barnes-Davis ME. Neuroimaging of brain connectivity related to reading outcomes in children born preterm: A critical narrative review. Front Pediatr 2023; 11:1083364. [PMID: 36937974 PMCID: PMC10014573 DOI: 10.3389/fped.2023.1083364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 02/06/2023] [Indexed: 03/06/2023] Open
Abstract
Premature children are at high risk for delays in language and reading, which can lead to poor school achievement. Neuroimaging studies have assessed structural and functional connectivity by diffusion MRI, functional MRI, and magnetoencephalography, in order to better define the "reading network" in children born preterm. Findings point to differences in structural and functional connectivity compared to children born at term. It is not entirely clear whether this discrepancy is due to delayed development or alternative mechanisms for reading, which may have developed to compensate for brain injury in the perinatal period. This narrative review critically appraises the existing literature evaluating the neural basis of reading in preterm children, summarizes the current findings, and suggests future directions in the field.
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Affiliation(s)
- Kaitlyn J. Kelly
- Division of Neonatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - John S. Hutton
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
- Division of General & Community Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - Nehal A. Parikh
- Division of Neonatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Maria E. Barnes-Davis
- Division of Neonatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
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25
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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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26
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Piekarski DJ, Colich NL, Ho TC. The effects of puberty and sex on adolescent white matter development: A systematic review. Dev Cogn Neurosci 2023; 60:101214. [PMID: 36913887 PMCID: PMC10010971 DOI: 10.1016/j.dcn.2023.101214] [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: 05/07/2022] [Revised: 12/20/2022] [Accepted: 02/08/2023] [Indexed: 02/12/2023] Open
Abstract
Adolescence, the transition between childhood and adulthood, is characterized by rapid brain development in white matter (WM) that is attributed in part to rising levels in adrenal and gonadal hormones. The extent to which pubertal hormones and related neuroendocrine processes explain sex differences in WM during this period is unclear. In this systematic review, we sought to examine whether there are consistent associations between hormonal changes and morphological and microstructural properties of WM across species and whether these effects are sex-specific. We identified 90 (75 human, 15 non-human) studies that met inclusion criteria for our analyses. While studies in human adolescents show notable heterogeneity, results broadly demonstrate that increases in gonadal hormones across pubertal development are associated with macro- and microstructural changes in WM tracts that are consistent with the sex differences found in non-human animals, particularly in the corpus callosum. We discuss limitations of the current state of the science and recommend important future directions for investigators in the field to consider in order to advance our understanding of the neuroscience of puberty and to promote forward and backward translation across model organisms.
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Affiliation(s)
| | | | - Tiffany C Ho
- Department of Psychology, University of California, Los Angeles, United States.
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27
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Thaler C, Tian Q, Wintermark M, Ghanouni P, Halpern CH, Henderson JM, Airan RD, Zeineh M, Goubran M, Leuze C, Fiehler J, Butts Pauly K, McNab JA. Changes in the Cerebello-Thalamo-Cortical Network After Magnetic Resonance-Guided Focused Ultrasound Thalamotomy. Brain Connect 2023; 13:28-38. [PMID: 35678063 PMCID: PMC9942176 DOI: 10.1089/brain.2021.0157] [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] [Indexed: 11/12/2022] Open
Abstract
Objective: In recent years, transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) has been established as a potential treatment option for movement disorders, including essential tremor (ET). So far, however, little is known about the impact of tcMRgFUS on structural connectivity. The objective of this study was to detect microstructural changes in tremor- and motor-related white matter tracts in ET patients treated with tcMRgFUS thalamotomy. Methods: Eleven patients diagnosed with ET were enrolled in this tcMRgFUS thalamotomy study. For each patient, 3 Tesla magnetic resonance imaging (3T MRI) including structural and diffusion MRI were acquired and the Clinical Rating Scale for Tremor was assessed before the procedure as well as 1 year after the treatment. Diffusion MRI tractography was performed to identify the cerebello-thalamo-cortical tract (CTCT), the medial lemniscus, and the corticospinal tract in both hemispheres on pre-treatment data. Pre-treatment tractography results were co-registered to post-treatment diffusion data. Diffusion tensor imaging (DTI) metrics, including fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD), were averaged across the tracts in the pre- and post-treatment data. Results: The mean value of tract-specific DTI metrics changed significantly within the thalamic lesion and in the CTCT on the treated side (p < 0.05). Changes of DTI-derived indices within the CTCT correlated well with lesion overlap (FA: r = -0.54, p = 0.04; MD: r = 0.57, p = 0.04); RD: r = 0.67, p = 0.036). Further, a trend was seen for the correlation between changes of DTI-derived indices within the CTCT and clinical improvement (FA: r = 0.58; p = 0.062; MD: r = -0.52, p = 0.64; RD: r = -0.61 p = 0.090). Conclusions: Microstructural changes were detected within the CTCT after tcMRgFUS, and these changes correlated well with lesion-tract overlap. Our results show that diffusion MRI is able to detect the microstructural effects of tcMRgFUS, thereby further elucidating the treatment mechanism, and ultimately to improve targeting prospectively. Impact statement The results of this study demonstrate microstructural changes within the cerebello-thalamo-cortical pathways 1 year after MR-guided focused ultrasound thalamotomy. Even more, microstructural changes within the cerebello-thalamo-cortical pathways correlated significantly with clinical outcome. These findings do not only highly emphasize the need of new targeting strategies for MR-guided focused ultrasound thalamotomy but also help to elucidate the treatment mechanism of it.
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Affiliation(s)
- Christian Thaler
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Qiyuan Tian
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Max Wintermark
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Pejman Ghanouni
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Casey H. Halpern
- Department of Neurosurgery, Stanford University, Stanford, California, USA
| | | | - Raag D. Airan
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Michael Zeineh
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Maged Goubran
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Christoph Leuze
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kim Butts Pauly
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Jennifer A. McNab
- Department of Radiology, Stanford University, Stanford, California, USA
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28
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Tonietto M, Poirion E, Lazzarotto A, Ricigliano V, Papeix C, Bottlaender M, Bodini B, Stankoff B. Periventricular remyelination failure in multiple sclerosis: a substrate for neurodegeneration. Brain 2023; 146:182-194. [PMID: 36097347 DOI: 10.1093/brain/awac334] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 07/26/2022] [Accepted: 08/18/2022] [Indexed: 01/11/2023] Open
Abstract
In multiple sclerosis, spontaneous remyelination is generally incomplete and heterogeneous across patients. A high heterogeneity in remyelination may also exist across lesions within the same individual, suggesting the presence of local factors interfering with myelin regeneration. In this study we explored in vivo the regional distribution of myelin repair and investigated its relationship with neurodegeneration. We first took advantage of the myelin binding property of the amyloid radiotracer 11C-PiB to conduct a longitudinal 11C-PiB PET study in an original cohort of 19 participants with a relapsing-remitting form of multiple sclerosis, followed-up over a period of 1-4 months. We then replicated our results on an independent cohort of 40 people with multiple sclerosis followed-up over 1 year with magnetization transfer imaging, an MRI metrics sensitive to myelin content. For each imaging method, voxel-wise maps of myelin content changes were generated according to modality-specific thresholds. We demonstrated a selective failure of remyelination in periventricular white matter lesions of people with multiple sclerosis in both cohorts. In both the original and the replication cohort, we estimated that the probability of demyelinated voxels to remyelinate over the follow-up increased significantly as a function of the distance from ventricular CSF. Enlarged choroid plexus, a recently discovered biomarker linked to neuroinflammation, was found to be associated with the periventricular failure of remyelination in the two cohorts (r = -0.79, P = 0.0018; r = -0.40, P = 0.045, respectively), suggesting a role of the brain-CSF barrier in affecting myelin repair in surrounding tissues. In both cohorts, the failure of remyelination in periventricular white matter lesions was associated with lower thalamic volume (r = 0.86, P < 0.0001; r = 0.33; P = 0.069, respectively), an imaging marker of neurodegeneration. Interestingly, we also showed an association between the periventricular failure of remyelination and regional cortical atrophy that was mediated by the number of cortex-derived tracts passing through periventricular white matter lesions, especially in patients at the relapsing-remitting stage. Our findings demonstrate that lesion proximity to ventricles is associated with a failure of myelin repair and support the hypothesis that a selective periventricular remyelination failure in combination with the large number of tracts connecting periventricular lesions with cortical areas is a key mechanism contributing to cortical damage in multiple sclerosis.
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Affiliation(s)
- Matteo Tonietto
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Service Hospitalier Frédéric Joliot, Université Paris-Saclay, CEA, CNRS, Inserm, BioMaps, Orsay, France
| | - Emilie Poirion
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France
| | - Andrea Lazzarotto
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Neurology Department, St Antoine Hospital, APHP, Paris, France
| | - Vito Ricigliano
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Neurology Department, St Antoine Hospital, APHP, Paris, France
| | - Caroline Papeix
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Neurology Department, Pitié-Salpêtrière Hospital, APHP, Paris, France
| | - Michel Bottlaender
- Service Hospitalier Frédéric Joliot, Université Paris-Saclay, CEA, CNRS, Inserm, BioMaps, Orsay, France
| | - Benedetta Bodini
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Neurology Department, St Antoine Hospital, APHP, Paris, France
| | - Bruno Stankoff
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Neurology Department, St Antoine Hospital, APHP, Paris, France
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29
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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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30
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Filimonova E, Amelina E, Sazonova A, Zaitsev B, Rzaev J. Assessment of normal myelination in infants and young children using the T1w/T2w mapping technique. Front Neurosci 2023; 17:1102691. [PMID: 36925743 PMCID: PMC10011126 DOI: 10.3389/fnins.2023.1102691] [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: 11/19/2022] [Accepted: 02/13/2023] [Indexed: 03/04/2023] Open
Abstract
Background White matter myelination is a crucial process of CNS maturation. The purpose of this study was to validate the T1w/T2w mapping technique for brain myelination assessment in infants and young children. Methods Ninety-four patients (0-23 months of age) without structural abnormalities on brain MRI were evaluated by using the T1w/T2w mapping method. The T1w/T2w signal intensity ratio, which reflects white matter integrity and the degree of myelination, was calculated in various brain regions. We performed a Pearson correlation analysis, a LOESS regression analysis, and a 2nd order polynomial regression analysis to describe the relationships between the regional metrics and the age of the patients (in months). Results T1w/T2w ratio values rapidly increased in the first 6-9 months of life and then slowed thereafter. The T1w/T2w mapping technique emphasized the contrast between myelinated and less myelinated structures in all age groups, which resulted in better visualization. There were strong positive correlations between the T1w/T2w ratio values from the majority of white matter ROIs and the subjects' age (R = 0.7-0.9, p < 0.001). Within all of the analyzed regions, there were non-linear relationships between age and T1/T2 ratio values that varied by anatomical and functional location. Regions such as the splenium and the genu of the corpus callosum showed the highest R2 values, thus indicating less scattering of data and a better fit to the model. Conclusion The T1w/T2w mapping technique may enhance our diagnostic ability to assess myelination patterns in the brains of infants and young children.
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Affiliation(s)
- Elena Filimonova
- Federal Center of Neurosurgery, Novosibirsk, Russia.,Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
| | - Evgenia Amelina
- Stream Data Analytics and Machine Learning Laboratory, Novosibirsk State University, Novosibirsk, Russia
| | - Aleksandra Sazonova
- Federal Center of Neurosurgery, Novosibirsk, Russia.,Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia
| | - Boris Zaitsev
- Federal Center of Neurosurgery, Novosibirsk, Russia.,Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia
| | - Jamil Rzaev
- Federal Center of Neurosurgery, Novosibirsk, Russia.,Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia.,Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia
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31
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van der Weijden CWJ, van der Hoorn A, Wang Y, Willemsen ATM, Dierckx RAJO, Lammertsma AA, de Vries EFJ. Investigation of image-derived input functions for non-invasive quantification of myelin density using [ 11C]MeDAS PET. Neuroimage 2022; 264:119772. [PMID: 36436711 DOI: 10.1016/j.neuroimage.2022.119772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/01/2022] [Accepted: 11/23/2022] [Indexed: 11/27/2022] Open
Abstract
Multiple sclerosis (MS) is an inflammatory demyelinating disease. Current treatments are focussed on immune suppression to modulate pathogenic activity that causes myelin damage. New treatment strategies are needed to prevent demyelination and promote remyelination. Development of such myelin repair therapies require a sensitive and specific biomarker for efficacy evaluation. Recently, it has been shown that quantification of myelin density is possible using [11C]MeDAS PET. This method, however, requires arterial blood sampling to generate an arterial input function (AIF). As the invasive nature of arterial sampling will reduce clinical applicability, the purpose of this study was to assess whether an image-derived input function (IDIF) can be used as an alternative way to facilitate its routine clinical use. Six healthy controls and 11 MS patients underwent MRI and [11C]MeDAS PET with arterial blood sampling. The application of both population-based whole blood-to-plasma conversion and metabolite corrections were assessed for the AIF. Next, summed images of the early time frames (0-70 s) and the frame with the highest blood-brain contrast were used to generate IDIFs. IDIFs were created using either the hottest 2, 4, 6 or 12 voxels, or an isocontour of the hottest 10% voxels of the carotid artery. This was followed by blood-to-plasma conversion and metabolite correction of the IDIF. The application of a population-based metabolite correction of the AIF resulted in high correlations of tracer binding (Ki) within subjects, but variable bias across subjects. All IDIFs had a sharper and higher peak in the blood curves than the AIF, most likely due to dispersion during blood sampling. All IDIF methods resulted in similar high correlations within subjects (r = 0.95-0.98), but highly variable bias across subjects (mean slope=0.90-1.09). Therefore, both the use of population based blood-plasma and metabolite corrections and the generation of the image-derived whole-blood curve resulted in substantial bias in [11C]MeDAS PET quantification, due to high inter-subject variability. Consequently, when unbiased quantification of [11C]MeDAS PET data is required, individual AIF needs to be used.
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Affiliation(s)
- Chris W J van der Weijden
- Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen 9713GZ, the Netherlands
| | - Anouk van der Hoorn
- Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen 9713GZ, the Netherlands
| | - Yanming Wang
- Department of Radiology, Case Western Reserve University, Cleveland, OH 44106, United States
| | - Antoon T M Willemsen
- Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen 9713GZ, the Netherlands
| | - Rudi A J O Dierckx
- Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen 9713GZ, the Netherlands
| | - Adriaan A Lammertsma
- Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen 9713GZ, the Netherlands
| | - Erik F J de Vries
- Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen 9713GZ, the Netherlands.
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32
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Fehlings MG, Pedro K, Hejrati N. Management of Acute Spinal Cord Injury: Where Have We Been? Where Are We Now? Where Are We Going? J Neurotrauma 2022; 39:1591-1602. [PMID: 35686453 DOI: 10.1089/neu.2022.0009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Affiliation(s)
- Michael G Fehlings
- Division of Genetics and Development, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.,Division of Neurosurgery and Spine Program, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | - Karlo Pedro
- Division of Neurosurgery and Spine Program, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | - Nader Hejrati
- Division of Genetics and Development, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada.,Division of Neurosurgery and Spine Program, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
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33
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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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34
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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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35
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Baldassarro VA, Stanzani A, Giardino L, Calzà L, Lorenzini L. Neuroprotection and neuroregeneration: roles for the white matter. Neural Regen Res 2022; 17:2376-2380. [PMID: 35535874 PMCID: PMC9120696 DOI: 10.4103/1673-5374.335834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
Efficient strategies for neuroprotection and repair are still an unmet medical need for neurodegenerative diseases and lesions of the central nervous system. Over the last few decades, a great deal of attention has been focused on white matter as a potential therapeutic target, mainly due to the discovery of the oligodendrocyte precursor cells in the adult central nervous system, a cell type able to fully repair myelin damage, and to the development of advanced imaging techniques to visualize and measure white matter lesions. The combination of these two events has greatly increased the body of research into white matter alterations in central nervous system lesions and neurodegenerative diseases and has identified the oligodendrocyte precursor cell as a putative target for white matter lesion repair, thus indirectly contributing to neuroprotection. This review aims to discuss the potential of white matter as a therapeutic target for neuroprotection in lesions and diseases of the central nervous system. Pivot conditions are discussed, specifically multiple sclerosis as a white matter disease; spinal cord injury, the acute lesion of a central nervous system component where white matter prevails over the gray matter, and Alzheimer's disease, where the white matter was considered an ancillary component until recently. We first describe oligodendrocyte precursor cell biology and developmental myelination, and its regulation by thyroid hormones, then briefly describe white matter imaging techniques, which are providing information on white matter involvement in central nervous system lesions and degenerative diseases. Finally, we discuss pathological mechanisms which interfere with myelin repair in adulthood.
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Affiliation(s)
| | - Agnese Stanzani
- Interdepartmental Center for Industrial Research in Life Sciences and Technologies, University of Bologna, Bologna, Italy
| | - Luciana Giardino
- Department of Veterinary Medical Science, University of Bologna, Bologna; Fondazione IRET, Ozzano Emilia, Italy
| | - Laura Calzà
- Fondazione IRET, Ozzano Emilia; Department of Pharmacy and Biotechnology, University of Bologna, Bologna; Montecatone Rehabilitation Institute, Imola, Italy
| | - Luca Lorenzini
- Department of Veterinary Medical Science, University of Bologna, Bologna, Italy
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36
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Combes AJ, Clarke MA, O'Grady KP, Schilling KG, Smith SA. Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions. Neuroimage Clin 2022; 36:103244. [PMID: 36306717 PMCID: PMC9668663 DOI: 10.1016/j.nicl.2022.103244] [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: 04/30/2022] [Revised: 09/02/2022] [Accepted: 10/19/2022] [Indexed: 11/11/2022]
Abstract
Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS. We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field. This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.
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Affiliation(s)
- Anna J.E. Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Corresponding author at: 1161 21st Ave S, MCN AA1105, Nashville, TN 37232, USA.
| | - Margareta A. Clarke
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States
| | - Kristin P. O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
| | - Kurt G. Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
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37
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Wang Y, Zhan M, Roebroeck A, De Weerd P, Kashyap S, Roberts MJ. Inconsistencies in atlas-based volumetric measures of the human nucleus basalis of Meynert: A need for high-resolution alternatives. Neuroimage 2022; 259:119421. [PMID: 35779763 DOI: 10.1016/j.neuroimage.2022.119421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 06/10/2022] [Accepted: 06/28/2022] [Indexed: 10/17/2022] Open
Abstract
The nucleus basalis of Meynert (nbM) is the major source of cortical acetylcholine (ACh) and has been related to cognitive processes and to neurological disorders. However, spatially delineating the human nbM in MRI studies remains challenging. Due to the absence of a functional localiser for the human nbM, studies to date have localised it using nearby neuroanatomical landmarks or using probabilistic atlases. To understand the feasibility of MRI of the nbM we set our four goals; our first goal was to review current human nbM region-of-interest (ROI) selection protocols used in MRI studies, which we found have reported highly variable nbM volume estimates. Our next goal was to quantify and discuss the limitations of existing atlas-based volumetry of nbM. We found that the identified ROI volume depends heavily on the atlas used and on the probabilistic threshold set. In addition, we found large disparities even for data/studies using the same atlas and threshold. To test whether spatial resolution contributes to volume variability, as our third goal, we developed a novel nbM mask based on the normalized BigBrain dataset. We found that as long as the spatial resolution of the target data was 1.3 mm isotropic or above, our novel nbM mask offered realistic and stable volume estimates. Finally, as our last goal we tried to discern nbM using publicly available and novel high resolution structural MRI ex vivo MRI datasets. We find that, using an optimised 9.4T quantitative T2⁎ ex vivo dataset, the nbM can be visualised using MRI. We conclude caution is needed when applying the current methods of mapping nbM, especially for high resolution MRI data. Direct imaging of the nbM appears feasible and would eliminate the problems we identify, although further development is required to allow such imaging using standard (f)MRI scanning.
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Affiliation(s)
- Yawen Wang
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
| | - Minye Zhan
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; U992 (Cognitive neuroimaging unit), NeuroSpin, INSERM-CEA, Gif sur Yvette, France
| | - Alard Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Peter De Weerd
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Sriranga Kashyap
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; Techna Institute, University Health Network, Toronto, ON, Canada
| | - Mark J Roberts
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
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38
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Rahmanzadeh R, Weigel M, Lu PJ, Melie-Garcia L, Nguyen TD, Cagol A, La Rosa F, Barakovic M, Lutti A, Wang Y, Bach Cuadra M, Radue EW, Gaetano L, Kappos L, Kuhle J, Magon S, Granziera C. A comparative assessment of myelin-sensitive measures in multiple sclerosis patients and healthy subjects. Neuroimage Clin 2022; 36:103177. [PMID: 36067611 PMCID: PMC9468574 DOI: 10.1016/j.nicl.2022.103177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 08/22/2022] [Accepted: 08/27/2022] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Multiple Sclerosis (MS) is a common neurological disease primarily characterized by myelin damage in lesions and in normal - appearing white and gray matter (NAWM, NAGM). Several quantitative MRI (qMRI) methods are sensitive to myelin characteristics by measuring specific tissue biophysical properties. However, there are currently few studies assessing the relative reproducibility and sensitivity of qMRI measures to MS pathology in vivo in patients. METHODS We performed two studies. The first study assessed of the sensitivity of qMRI measures to MS pathology: in this work, we recruited 150 MS and 100 healthy subjects, who underwent brain MRI at 3 T including quantitative T1 mapping (qT1), quantitative susceptibility mapping (QSM), magnetization transfer saturation imaging (MTsat) and myelin water imaging for myelin water fraction (MWF). The sensitivity of qMRIs to MS focal pathology (MS lesions vs peri-plaque white/gray matter (PPWM/PPGM)) was studied lesion-wise; the sensitivity to diffuse normal appearing (NA) pathology was measured using voxel-wise threshold-free cluster enhancement (TFCE) in NAWM and vertex-wise inflated cortex analysis in NAGM. Furthermore, the sensitivity of qMRI to the identification of lesion tissue was investigated using a voxel-wise logistic regression analysis to distinguish MS lesion and PP voxels. The second study assessed the reproducibility of myelin-sensitive qMRI measures in a single scanner. To evaluate the intra-session and inter-session reproducibility of qMRI measures, we have investigated 10 healthy subjects, who underwent two brain 3 T MRIs within the same day (without repositioning), and one after 1-week interval. Five region of interest (ROIs) in white and deep grey matter areas were segmented, and inter- and intra- session reproducibility was studied using the intra-class correlation coefficient (ICC). Further, we also investigated the voxel-wise reproducibility of qMRI measures in NAWM and NAGM. RESULTS qT1 and QSM showed the highest sensitivity to distinguish MS focal WM and cortical pathology from peri-plaque WM (P < 0.0001), although QSM also showed the highest variance when applied to lesions. MWF and MTsat exhibited the highest sensitivity to NAWM pathology (P < 0.01). On the other hand, qT1 appeared to be the most sensitive measure to NAGM pathology (P < 0.01). All myelin-sensitive qMRI measures exhibited high inter/intra sessional ICCs in various WM and deep GM ROIs, in NAWM and in NAGM (ICC 0.82 ± 0.12). CONCLUSION This work shows that the applied qT1, MWF, MTsat and QSM are highly reproducible and exhibit differential sensitivity to focal and diffuse WM and GM pathology in MS patients.
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Affiliation(s)
- Reza Rahmanzadeh
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Po-Jui Lu
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Lester Melie-Garcia
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Thanh D. Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Alessandro Cagol
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,CIBM Center for Biomedical Imaging, Lausanne, Switzerland,Radiology Department, Lausanne University and University Hospital, Lausanne, Switzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Meritxell Bach Cuadra
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,CIBM Center for Biomedical Imaging, Lausanne, Switzerland,Radiology Department, Lausanne University and University Hospital, Lausanne, Switzerland
| | - Ernst-Wilhelm Radue
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | | | - Ludwig Kappos
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Stefano Magon
- Pharmaceutical Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland,Corresponding author.
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Hansen JY, Shafiei G, Vogel JW, Smart K, Bearden CE, Hoogman M, Franke B, van Rooij D, Buitelaar J, McDonald CR, Sisodiya SM, Schmaal L, Veltman DJ, van den Heuvel OA, Stein DJ, van Erp TGM, Ching CRK, Andreassen OA, Hajek T, Opel N, Modinos G, Aleman A, van der Werf Y, Jahanshad N, Thomopoulos SI, Thompson PM, Carson RE, Dagher A, Misic B. Local molecular and global connectomic contributions to cross-disorder cortical abnormalities. Nat Commun 2022; 13:4682. [PMID: 35948562 PMCID: PMC9365855 DOI: 10.1038/s41467-022-32420-y] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 07/28/2022] [Indexed: 12/21/2022] Open
Abstract
Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21,000 participants and N = 26,000 controls, collected using a harmonised processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find a relationship between molecular vulnerability and white-matter architecture that drives cortical disorder profiles. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, inferior temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local molecular attributes and global connectivity jointly shape cross-disorder cortical abnormalities.
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Affiliation(s)
- Justine Y Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Golia Shafiei
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Jacob W Vogel
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kelly Smart
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Carrie E Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Martine Hoogman
- Departments of Psychiatry and Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Barbara Franke
- Departments of Psychiatry and Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Daan van Rooij
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Jan Buitelaar
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Carrie R McDonald
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Odile A van den Heuvel
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Anatomy & Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, & Center for the Neurobiology of Leaning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, USA
| | - Christopher R K Ching
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Nils Opel
- Institute of Translational Psychiatry, University of Münster, Münster, Germany & Department of Psychiatry, Jena University Hospital/Friedrich-Schiller-University Jena, Jena, Germany
| | - Gemma Modinos
- Department of Psychosis Studies & MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - André Aleman
- Department of Biomedical Sciences of Cells and Systems, University of Groningen, Groningen, The Netherlands
| | - Ysbrand van der Werf
- Department of Anatomy & Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Neda Jahanshad
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Sophia I Thomopoulos
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Paul M Thompson
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Richard E Carson
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada.
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Avery SN, Huang AS, Sheffield JM, Rogers BP, Vandekar S, Anticevic A, Woodward ND. Development of Thalamocortical Structural Connectivity in Typically Developing and Psychosis Spectrum Youths. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:782-792. [PMID: 34655804 PMCID: PMC9008075 DOI: 10.1016/j.bpsc.2021.09.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 09/30/2021] [Accepted: 09/30/2021] [Indexed: 12/13/2022]
Abstract
BACKGROUND Thalamocortical white matter connectivity is disrupted in psychosis and is hypothesized to play a role in its etiology and associated cognitive impairment. Attenuated cognitive symptoms often begin in adolescence, during a critical phase of white matter and cognitive development. However, little is known about the development of thalamocortical white matter connectivity and its association with cognition. METHODS This study characterized effects of age, sex, psychosis symptomatology, and cognition in thalamocortical networks in a large sample of youths (N = 1144, ages 8-22 years, 46% male) from the Philadelphia Neurodevelopmental Cohort, which included 316 typically developing youths, 330 youths on the psychosis spectrum, and 498 youths with other psychopathology. Probabilistic tractography was used to quantify percent total connectivity between the thalamus and six cortical regions and assess microstructural properties (i.e., fractional anisotropy) of thalamocortical white matter tracts. RESULTS Overall, percent total connectivity of the thalamus was weakly associated with age and was not associated with psychopathology or cognition. In contrast, fractional anisotropy of all thalamocortical tracts increased significantly with age, was generally higher in males than females, and was lowest in youths on the psychosis spectrum. Fractional anisotropy of tracts linking the thalamus to prefrontal and posterior parietal cortices was related to better cognitive function across subjects. CONCLUSIONS By characterizing the pattern of typical development and alterations in those at risk for psychotic disorders, this study provides a foundation for further conceptualization of thalamocortical white matter microstructure as a marker of neurodevelopment supporting cognition and an important risk marker for psychosis.
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Affiliation(s)
- Suzanne N Avery
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee.
| | - Anna S Huang
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Julia M Sheffield
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Baxter P Rogers
- Vanderbilt University Institute of Imaging Sciences, Nashville, Tennessee
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Neil D Woodward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
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Silva NCBS, Dao E, Hsu CL, Tam RC, Stein R, Alkeridy W, Laule C, Vavasour IM, Liu-Ambrose T. Myelin Content and Gait Impairment in Older Adults with Cerebral Small Vessel Disease and Mild Cognitive Impairment. Neurobiol Aging 2022; 119:56-66. [DOI: 10.1016/j.neurobiolaging.2022.03.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 02/19/2022] [Accepted: 03/15/2022] [Indexed: 11/25/2022]
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42
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Staging of Alzheimer's disease: past, present, and future perspectives. Trends Mol Med 2022; 28:726-741. [PMID: 35717526 DOI: 10.1016/j.molmed.2022.05.008] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/15/2022] [Accepted: 05/16/2022] [Indexed: 01/01/2023]
Abstract
For many years Alzheimer's disease (AD) was associated with the dementia stage of the disease, the tail end of a pathophysiological process that lasts approximately two decades. Whereas early disease staging assessments focused on progressive deterioration of clinical functioning, brain imaging with positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarker studies highlighted the long preclinical phase of AD in which a cascade of detectable biological abnormalities precede cognitive decline. The recent proliferation of imaging and fluid biomarkers of AD pathophysiology provide an opportunity for the identification of several biological stages in the preclinical phase of AD. We discuss the use of clinical and biomarker information in past, present, and future staging of AD. We highlight potential applications of PET, CSF, and plasma biomarkers for staging AD severity in vivo.
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York EN, Thrippleton MJ, Meijboom R, Hunt DPJ, Waldman AD. Quantitative magnetization transfer imaging in relapsing-remitting multiple sclerosis: a systematic review and meta-analysis. Brain Commun 2022; 4:fcac088. [PMID: 35652121 PMCID: PMC9149789 DOI: 10.1093/braincomms/fcac088] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/17/2021] [Accepted: 03/31/2022] [Indexed: 11/28/2022] Open
Abstract
Myelin-sensitive MRI such as magnetization transfer imaging has been widely used in multiple sclerosis. The influence of methodology and differences in disease subtype on imaging findings is, however, not well established. Here, we systematically review magnetization transfer brain imaging findings in relapsing-remitting multiple sclerosis. We examine how methodological differences, disease effects and their interaction influence magnetization transfer imaging measures. Articles published before 06/01/2021 were retrieved from online databases (PubMed, EMBASE and Web of Science) with search terms including 'magnetization transfer' and 'brain' for systematic review, according to a pre-defined protocol. Only studies that used human in vivo quantitative magnetization transfer imaging in adults with relapsing-remitting multiple sclerosis (with or without healthy controls) were included. Additional data from relapsing-remitting multiple sclerosis subjects acquired in other studies comprising mixed disease subtypes were included in meta-analyses. Data including sample size, MRI acquisition protocol parameters, treatments and clinical findings were extracted and qualitatively synthesized. Where possible, effect sizes were calculated for meta-analyses to determine magnetization transfer (i) differences between patients and healthy controls; (ii) longitudinal change and (iii) relationships with clinical disability in relapsing-remitting multiple sclerosis. Eighty-six studies met inclusion criteria. MRI acquisition parameters varied widely, and were also underreported. The majority of studies examined the magnetization transfer ratio in white matter, but magnetization transfer metrics, brain regions examined and results were heterogeneous. The analysis demonstrated a risk of bias due to selective reporting and small sample sizes. The pooled random-effects meta-analysis across all brain compartments revealed magnetization transfer ratio was 1.17 per cent units (95% CI -1.42 to -0.91) lower in relapsing-remitting multiple sclerosis than healthy controls (z-value: -8.99, P < 0.001, 46 studies). Linear mixed-model analysis did not show a significant longitudinal change in magnetization transfer ratio across all brain regions [β = 0.12 (-0.56 to 0.80), t-value = 0.35, P = 0.724, 14 studies] or normal-appearing white matter alone [β = 0.037 (-0.14 to 0.22), t-value = 0.41, P = 0.68, eight studies]. There was a significant negative association between the magnetization transfer ratio and clinical disability, as assessed by the Expanded Disability Status Scale [r = -0.32 (95% CI -0.46 to -0.17); z-value = -4.33, P < 0.001, 13 studies]. Evidence suggests that magnetization transfer imaging metrics are sensitive to pathological brain changes in relapsing-remitting multiple sclerosis, although effect sizes were small in comparison to inter-study variability. Recommendations include: better harmonized magnetization transfer acquisition protocols with detailed methodological reporting standards; larger, well-phenotyped cohorts, including healthy controls; and, further exploration of techniques such as magnetization transfer saturation or inhomogeneous magnetization transfer ratio.
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Affiliation(s)
- Elizabeth N. York
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
| | | | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
| | - David P. J. Hunt
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of
Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic,
University of Edinburgh, Edinburgh, UK
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of
Edinburgh, Edinburgh, UK
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van der Weijden CWJ, Meilof JF, van der Hoorn A, Zhu J, Wu C, Wang Y, Willemsen ATM, Dierckx RAJO, Lammertsma AA, de Vries EFJ. Quantitative assessment of myelin density using [ 11C]MeDAS PET in patients with multiple sclerosis: a first-in-human study. Eur J Nucl Med Mol Imaging 2022; 49:3492-3507. [PMID: 35366079 PMCID: PMC9308583 DOI: 10.1007/s00259-022-05770-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 03/19/2022] [Indexed: 12/21/2022]
Abstract
Purpose Multiple sclerosis (MS) is a disease characterized by inflammatory demyelinated lesions. New treatment strategies are being developed to stimulate myelin repair. Quantitative myelin imaging could facilitate these developments. This first-in-man study aimed to evaluate [11C]MeDAS as a PET tracer for myelin imaging in humans. Methods Six healthy controls and 11 MS patients underwent MRI and dynamic [11C]MeDAS PET scanning with arterial sampling. Lesion detection and classification were performed on MRI. [11C]MeDAS time-activity curves of brain regions and MS lesions were fitted with various compartment models for the identification of the best model to describe [11C]MeDAS kinetics. Several simplified methods were compared to the optimal compartment model. Results Visual analysis of the fits of [11C]MeDAS time-activity curves showed no preference for irreversible (2T3k) or reversible (2T4k) two-tissue compartment model. Both volume of distribution and binding potential estimates showed a high degree of variability. As this was not the case for 2T3k-derived net influx rate (Ki), the 2T3k model was selected as the model of choice. Simplified methods, such as SUV and MLAIR2 correlated well with 2T3k-derived Ki, but SUV showed subject-dependent bias when compared to 2T3k. Both the 2T3k model and the simplified methods were able to differentiate not only between gray and white matter, but also between lesions with different myelin densities. Conclusion [11C]MeDAS PET can be used for quantification of myelin density in MS patients and is able to distinguish differences in myelin density within MS lesions. The 2T3k model is the optimal compartment model and MLAIR2 is the best simplified method for quantification. Trial registration. NL7262. Registered 18 September 2018. Supplementary information The online version contains supplementary material available at 10.1007/s00259-022-05770-4.
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Affiliation(s)
- Chris W J van der Weijden
- Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen, The Netherlands
| | - Jan F Meilof
- Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
- Department of Neurology, Martini Ziekenhuis, Groningen, The Netherlands
| | - Anouk van der Hoorn
- Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Junqing Zhu
- Department of Radiology, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Chunying Wu
- Department of Radiology, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Yanming Wang
- Department of Radiology, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Antoon T M Willemsen
- Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen, The Netherlands
| | - Rudi A J O Dierckx
- Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen, The Netherlands
| | - Adriaan A Lammertsma
- Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen, The Netherlands
| | - Erik F J de Vries
- Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen, The Netherlands.
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Sisco NJ, Wang P, Stokes AM, Dortch RD. Rapid parameter estimation for selective inversion recovery myelin imaging using an open-source Julia toolkit. PeerJ 2022; 10:e13043. [PMID: 35368333 PMCID: PMC8973461 DOI: 10.7717/peerj.13043] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/10/2022] [Indexed: 01/11/2023] Open
Abstract
Background Magnetic resonance imaging (MRI) is used extensively to quantify myelin content, however computational bottlenecks remain challenging for advanced imaging techniques in clinical settings. We present a fast, open-source toolkit for processing quantitative magnetization transfer derived from selective inversion recovery (SIR) acquisitions that allows parameter map estimation, including the myelin-sensitive macromolecular pool size ratio (PSR). Significant progress has been made in reducing SIR acquisition times to improve clinically feasibility. However, parameter map estimation from the resulting data remains computationally expensive. To overcome this computational limitation, we developed a computationally efficient, open-source toolkit implemented in the Julia language. Methods To test the accuracy of this toolkit, we simulated SIR images with varying PSR and spin-lattice relaxation time of the free water pool (R 1f) over a physiologically meaningful scale from 5% to 20% and 0.5 to 1.5 s-1, respectively. Rician noise was then added, and the parameter maps were estimated using our Julia toolkit. Probability density histogram plots and Lin's concordance correlation coefficients (LCCC) were used to assess accuracy and precision of the fits to our known simulation data. To further mimic biological tissue, we generated five cross-linked bovine serum albumin (BSA) phantoms with concentrations that ranged from 1.25% to 20%. The phantoms were imaged at 3T using SIR, and data were fit to estimate PSR and R 1f. Similarly, a healthy volunteer was imaged at 3T, and SIR parameter maps were estimated to demonstrate the reduced computational time for a real-world clinical example. Results Estimated SIR parameter maps from our Julia toolkit agreed with simulated values (LCCC > 0.98). This toolkit was further validated using BSA phantoms and a whole brain scan at 3T. In both cases, SIR parameter estimates were consistent with published values using MATLAB. However, compared to earlier work using MATLAB, our Julia toolkit provided an approximate 20-fold reduction in computational time. Conclusions Presented here, we developed a fast, open-source, toolkit for rapid and accurate SIR MRI using Julia. The reduction in computational cost should allow SIR parameters to be accessible in clinical settings.
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Affiliation(s)
- Nicholas J. Sisco
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, AZ, United States
- Barrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, AZ, United States
- St. Joseph’s Hospital and Medical Center, Phoenix, Arizona, United States of America
| | - Ping Wang
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, AZ, United States
- Barrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, AZ, United States
- St. Joseph’s Hospital and Medical Center, Phoenix, Arizona, United States of America
| | - Ashley M. Stokes
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, AZ, United States
- Barrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, AZ, United States
- St. Joseph’s Hospital and Medical Center, Phoenix, Arizona, United States of America
| | - Richard D. Dortch
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, AZ, United States
- Barrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, AZ, United States
- St. Joseph’s Hospital and Medical Center, Phoenix, Arizona, United States of America
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46
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Cho H, Lee H, Gong Y, Kim YR, Cho J, Cho HJ. Quantitative susceptibility mapping and R1 measurement: Determination of the myelin volume fraction in the aging ex vivo rat corpus callosum. NMR IN BIOMEDICINE 2022; 35:e4645. [PMID: 34739153 DOI: 10.1002/nbm.4645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 10/03/2021] [Accepted: 10/16/2021] [Indexed: 06/13/2023]
Abstract
In studies of the white matter (WM) in aging brains, both quantitative susceptibility mapping (QSM) and direct R1 measurement offer potentially useful ex vivo MRI tools that allow volumetric characterization of myelin content changes. Despite the technical importance of such MRI methods in numerous age-related diseases, the supposed linear relationship between the estimates of either the QSM or R1 method and age-affected myelin contents has not been validated. In this study, the absolute myelin volume fraction (MVF) was determined by transmission electron microscopy (TEM) as a gold standard measure for comparison with the values obtained by the aforementioned MR methods. To theoretically evaluate and understand the MR signal characteristics, QSM simulations were performed using the finite perturber method (FPM). Specifically, the simulation geometry modeling was based on TEM-derived structures aligned orthogonally to the main magnetic field, the construct of which was used to estimate the magnetic field shift (ΔB) changes arising from the conjectured myelin structures. Experimentally, ex vivo corpus callosum (CC) samples from rat brains obtained at 6 weeks (n = 3), 4 months (n = 3), and 20 months (n = 3) after birth were used to establish the relationship between changes quantified by either QSM or R1 with the absolute MVF by TEM. From the ex vivo brain samples, the scatterplot of mean MVF versus R1 was fitted to a linear equation, where R1mean = 0.7948 × MVFmean + 0.8118 (Pearson's correlation coefficient r = 0.9138; p < 0.01), while the scatterplot of mean MVF versus MRI-derived magnetic susceptibility (χ) was also fitted to a line where χmeasured,mean = -0.1218 × MVFmean - 0.006345 (r = -0.8435; p < 0.01). As a result of the FPM-based QSM simulations, a linearly proportional relationship between the simulated magnetic susceptibility, χsimulated,mean , and MVF (r = -0.9648; p < 0.01) was established. Such a statistically significant linear correlation between MRI-derived values by the QSM (or R1 ) method and MVF demonstrated that variable myelin contents in the WM (i.e., CC) can be quantified across multiple stages of aging. These findings further support that both techniques based on QSM and R1 provide an efficient means of studying the brain-aging process with accurate volumetric quantification of the myelin content in WM.
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Affiliation(s)
- Hwapyeong Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Hansol Lee
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Yelim Gong
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Young Ro Kim
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Hyung Joon Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
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47
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Hori M, Maekawa T, Kamiya K, Hagiwara A, Goto M, Takemura MY, Fujita S, Andica C, Kamagata K, Cohen-Adad J, Aoki S. Advanced Diffusion MR Imaging for Multiple Sclerosis in the Brain and Spinal Cord. Magn Reson Med Sci 2022; 21:58-70. [PMID: 35173096 PMCID: PMC9199983 DOI: 10.2463/mrms.rev.2021-0091] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Diffusion tensor imaging (DTI) has been established its usefulness in evaluating normal-appearing white matter (NAWM) and other lesions that are difficult to evaluate with routine clinical MRI in the evaluation of the brain and spinal cord lesions in multiple sclerosis (MS), a demyelinating disease. With the recent advances in the software and hardware of MRI systems, increasingly complex and sophisticated MRI and analysis methods, such as q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, white matter tract integrity, and multiple diffusion encoding, referred to as advanced diffusion MRI, have been proposed. These are capable of capturing in vivo microstructural changes in the brain and spinal cord in normal and pathological states in greater detail than DTI. This paper reviews the current status of recent advanced diffusion MRI for assessing MS in vivo as part of an issue celebrating two decades of magnetic resonance in medical sciences (MRMS), an official journal of the Japanese Society of Magnetic Resonance in Medicine.
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Affiliation(s)
- Masaaki Hori
- Department of Radiology, Toho University Omori Medical Center.,Department of Radiology, Juntendo University School of Medicine
| | - Tomoko Maekawa
- Department of Radiology, Juntendo University School of Medicine
| | - Kouhei Kamiya
- Department of Radiology, Toho University Omori Medical Center.,Department of Radiology, Juntendo University School of Medicine
| | | | - Masami Goto
- Department of Radiological Technology, Faculty of Health Science, Juntendo University
| | | | - Shohei Fujita
- Department of Radiology, Juntendo University School of Medicine
| | | | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine
| | | | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine
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48
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Kisel AA, Naumova AV, Yarnykh VL. Macromolecular Proton Fraction as a Myelin Biomarker: Principles, Validation, and Applications. Front Neurosci 2022; 16:819912. [PMID: 35221905 PMCID: PMC8863973 DOI: 10.3389/fnins.2022.819912] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 01/17/2022] [Indexed: 12/16/2022] Open
Abstract
Macromolecular proton fraction (MPF) is a quantitative MRI parameter describing the magnetization transfer (MT) effect and defined as a relative amount of protons bound to biological macromolecules with restricted molecular motion, which participate in magnetic cross-relaxation with water protons. MPF attracted significant interest during past decade as a biomarker of myelin. The purpose of this mini review is to provide a brief but comprehensive summary of MPF mapping methods, histological validation studies, and MPF applications in neuroscience. Technically, MPF maps can be obtained using a variety of quantitative MT methods. Some of them enable clinically reasonable scan time and resolution. Recent studies demonstrated the feasibility of MPF mapping using standard clinical MRI pulse sequences, thus substantially enhancing the method availability. A number of studies in animal models demonstrated strong correlations between MPF and histological markers of myelin with a minor influence of potential confounders. Histological studies validated the capability of MPF to monitor both demyelination and re-myelination. Clinical applications of MPF have been mainly focused on multiple sclerosis where this method provided new insights into both white and gray matter pathology. Besides, several studies used MPF to investigate myelin role in other neurological and psychiatric conditions. Another promising area of MPF applications is the brain development studies. MPF demonstrated the capabilities to quantitatively characterize the earliest stage of myelination during prenatal brain maturation and protracted myelin development in adolescence. In summary, MPF mapping provides a technically mature and comprehensively validated myelin imaging technology for various preclinical and clinical neuroscience applications.
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Affiliation(s)
- Alena A. Kisel
- Department of Radiology, University of Washington, Seattle, WA, United States
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russia
| | - Anna V. Naumova
- Department of Radiology, University of Washington, Seattle, WA, United States
| | - Vasily L. Yarnykh
- Department of Radiology, University of Washington, Seattle, WA, United States
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russia
- *Correspondence: Vasily L. Yarnykh,
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49
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Hertanu A, Soustelle L, Buron J, Le Priellec J, Cayre M, Le Troter A, Varma G, Alsop DC, Durbec P, Girard OM, Duhamel G. T 1D -weighted ihMT imaging - Part II. Investigating the long- and short-T 1D components correlation with myelin content. Comparison with R 1 and the macromolecular proton fraction. Magn Reson Med 2022; 87:2329-2346. [PMID: 35001427 DOI: 10.1002/mrm.29140] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 10/29/2021] [Accepted: 12/12/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE To investigate the long- and short-T1D components correlation with myelin content using inhomogeneous magnetization transfer (ihMT) high-pass and band-pass T1D -filters and to compare ihMT, R1 , and the macromolecular proton fraction (MPF) for myelin specific imaging. METHODS The 3D ihMT rapid gradient echo (ihMTRAGE) sequences with increasing switching times (Δt) were used to derive ihMT high-pass T1D -filters with increasing T1D cutoff values and an ihMT band-pass T1D -filter for components in the 100 µs to 1 ms range. 3D spoiled gradient echo quantitative MT (SPGR-qMT) protocols were used to derive R1 and MPF maps. The specificity of R1 , MPF, and ihMT T1D -filters was evaluated by comparison with two histological reference techniques for myelin imaging. RESULTS The higher contribution of long-T1D s as compared to the short components as Δt got longer led to an increase in the specificity to myelination. In contrast, focusing on the signal originating from a narrow range of short-T1D s (< 1 ms) as isolated by the band-pass T1D -filter led to lower specificity. In addition, the significantly lower r2 correlation coefficient of the band-pass T1D -filter suggests that the origin of short-T1D components is mostly associated with non-myelin protons. Also, the important contribution of short-T1D s to the estimated MPF, explains its low specificity to myelination as compared to the ihMT high-pass T1D -filters. CONCLUSION Long-T1D components imaging by means of ihMT high-pass T1D -filters is proposed as an MRI biomarker for myelin content. Future studies should enable the investigation of the sensitivity of ihMT T1D -filters for demyelinating processes.
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Affiliation(s)
- Andreea Hertanu
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Lucas Soustelle
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Julie Buron
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France.,Aix Marseille Univ, CNRS, IBDM, Marseille, France
| | | | - Myriam Cayre
- Aix Marseille Univ, CNRS, IBDM, Marseille, France
| | - Arnaud Le Troter
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Gopal Varma
- Division of MR Research, Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - David C Alsop
- Division of MR Research, Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Olivier M Girard
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Guillaume Duhamel
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
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50
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Groppa S, Gonzalez-Escamilla G, Eshaghi A, Meuth SG, Ciccarelli O. Linking immune-mediated damage to neurodegeneration in multiple sclerosis: could network-based MRI help? Brain Commun 2021; 3:fcab237. [PMID: 34729480 PMCID: PMC8557667 DOI: 10.1093/braincomms/fcab237] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/21/2021] [Indexed: 01/04/2023] Open
Abstract
Inflammatory demyelination characterizes the initial stages of multiple sclerosis, while progressive axonal and neuronal loss are coexisting and significantly contribute to the long-term physical and cognitive impairment. There is an unmet need for a conceptual shift from a dualistic view of multiple sclerosis pathology, involving either inflammatory demyelination or neurodegeneration, to integrative dynamic models of brain reorganization, where, glia-neuron interactions, synaptic alterations and grey matter pathology are longitudinally envisaged at the whole-brain level. Functional and structural MRI can delineate network hallmarks for relapses, remissions or disease progression, which can be linked to the pathophysiology behind inflammatory attacks, repair and neurodegeneration. Here, we aim to unify recent findings of grey matter circuits dynamics in multiple sclerosis within the framework of molecular and pathophysiological hallmarks combined with disease-related network reorganization, while highlighting advances from animal models (in vivo and ex vivo) and human clinical data (imaging and histological). We propose that MRI-based brain networks characterization is essential for better delineating ongoing pathology and elaboration of particular mechanisms that may serve for accurate modelling and prediction of disease courses throughout disease stages.
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Affiliation(s)
- Sergiu Groppa
- Imaging and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Gabriel Gonzalez-Escamilla
- Imaging and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Arman Eshaghi
- Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London WC1E 6BT, UK.,Department of Computer Science, Centre for Medical Image Computing (CMIC), University College London, London WC1E 6BT, UK
| | - Sven G Meuth
- Department of Neurology, Medical Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Olga Ciccarelli
- Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London WC1E 6BT, UK
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