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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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2
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Wenger KJ, Hoelter MC, Yalachkov Y, Hendrik Schäfer J, Özkan D, Steffen F, Bittner S, Hattingen E, Foerch C, Schaller-Paule MA. Serum neurofilament light chain is more strongly associated with T2 lesion volume than with number of T2 lesions in patients with multiple sclerosis. Eur J Radiol 2023; 166:111019. [PMID: 37549559 DOI: 10.1016/j.ejrad.2023.111019] [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: 01/11/2023] [Revised: 03/24/2023] [Accepted: 07/28/2023] [Indexed: 08/09/2023]
Abstract
BACKGROUND AND PURPOSE MR imaging provides information on the number and extend of focal lesions in multiple sclerosis (MS) patients. This study explores whether total brain T2 lesion volume or lesion number shows a better correlation with serum and cerebrospinal fluid (CSF) biomarkers of disease activity. MATERIALS AND METHODS In total, 52 patients suffering from clinically isolated syndrome (CIS)/relapsing-remitting multiple sclerosis (RRMS) were assessed including MRI markers (total brain T2 lesion volume semi-automatically outlined on 3D DIR/FLAIR sequences, number of lesions), serum and CSF biomarkers at the time of neuroimaging (neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP)), and clinical parameters. After log-transformation and partial correlations adjusted for the covariates patients' age, BMI, EDSS-score and diagnosis, the Fisher's r-to-Z transformation was used to compare different correlation coefficients. RESULTS The correlation between lesion volume and serum NfL (r = 0.6, p < 0.001) was stronger compared to the association between the number of T2 lesions and serum NfL (r = 0.4, p < 0.01) (z = -2.0, p < 0.05). With regard to CSF NfL, there was a moderate, positive relationship for both number of T2 lesions and lesion volume (r = 0.5 respectively, p < 0.01). We found no significant association between MRI markers and GFAP levels. CONCLUSION Our findings suggest that there is a stronger association between serum NfL and T2 lesion volume, than there is between serum NfL and T2 lesion number. Improving robustness and accuracy of fully-automated lesion volume segmentation tools can expedite implementation into clinical routine and trials.
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Affiliation(s)
- Katharina J Wenger
- Goethe University Frankfurt, University Hospital, Institute of Neuroradiology, Germany.
| | - Maya C Hoelter
- Goethe University Frankfurt, University Hospital, Institute of Neuroradiology, Germany
| | - Yavor Yalachkov
- Goethe University Frankfurt, University Hospital, Department of Neurology, Germany
| | - Jan Hendrik Schäfer
- Goethe University Frankfurt, University Hospital, Department of Neurology, Germany
| | - Dilek Özkan
- Goethe University Frankfurt, University Hospital, Institute of Neuroradiology, Germany
| | - Falk Steffen
- Department of Neurology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Stefan Bittner
- Department of Neurology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Elke Hattingen
- Goethe University Frankfurt, University Hospital, Institute of Neuroradiology, Germany
| | - Christian Foerch
- Goethe University Frankfurt, University Hospital, Department of Neurology, Germany
| | - Martin A Schaller-Paule
- Goethe University Frankfurt, University Hospital, Department of Neurology, Germany; Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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Mainero C, Treaba CA, Barbuti E. Imaging cortical lesions in multiple sclerosis. Curr Opin Neurol 2023; 36:222-228. [PMID: 37078649 DOI: 10.1097/wco.0000000000001152] [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: 04/21/2023]
Abstract
PURPOSE OF REVIEW Cortical lesions are an established pathological feature of multiple sclerosis, develop from the earliest disease stages and contribute to disease progression. Here, we discuss current imaging approaches for detecting cortical lesions in vivo and their contribution for improving our understanding of cortical lesion pathogenesis as well as their clinical significance. RECENT FINDINGS Although a variable portion of cortical lesions goes undetected at clinical field strength and even at ultra-high field MRI, their evaluation is still clinically relevant. Cortical lesions are important for differential multiple sclerosis (MS) diagnosis, have relevant prognostic value and independently predict disease progression. Some studies also show that cortical lesion assessment could be used as a therapeutic outcome target in clinical trials. Advances in ultra-high field MRI not only allow increased cortical lesion detection in vivo but also the disclosing of some interesting features of cortical lesions related to their pattern of development and evolution as well to the nature of associated pathological changes, which might prove relevant for better understanding the pathogenesis of these lesions. SUMMARY Despite some limitations, imaging of cortical lesions is of paramount importance in MS for elucidating disease mechanisms as well as for improving patient management in clinic.
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Affiliation(s)
- Caterina Mainero
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Harvard Medical School, Boston, Massachusetts, USA
| | - Constantina A Treaba
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Harvard Medical School, Boston, Massachusetts, USA
| | - Elena Barbuti
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Ospedale Sant'Andrea, University "La Sapienza", Rome, Italy
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Olatunji SO, Alsheikh N, Alnajrani L, Alanazy A, Almusairii M, Alshammasi S, Alansari A, Zaghdoud R, Alahmadi A, Basheer Ahmed MI, Ahmed MS, Alhiyafi J. Comprehensible Machine-Learning-Based Models for the Pre-Emptive Diagnosis of Multiple Sclerosis Using Clinical Data: A Retrospective Study in the Eastern Province of Saudi Arabia. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4261. [PMID: 36901273 PMCID: PMC10002108 DOI: 10.3390/ijerph20054261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 02/22/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
Multiple Sclerosis (MS) is characterized by chronic deterioration of the nervous system, mainly the brain and the spinal cord. An individual with MS develops the condition when the immune system begins attacking nerve fibers and the myelin sheathing that covers them, affecting the communication between the brain and the rest of the body and eventually causing permanent damage to the nerve. Patients with MS (pwMS) might experience different symptoms depending on which nerve was damaged and how much damage it has sustained. Currently, there is no cure for MS; however, there are clinical guidelines that help control the disease and its accompanying symptoms. Additionally, no specific laboratory biomarker can precisely identify the presence of MS, leaving specialists with a differential diagnosis that relies on ruling out other possible diseases with similar symptoms. Since the emergence of Machine Learning (ML) in the healthcare industry, it has become an effective tool for uncovering hidden patterns that aid in diagnosing several ailments. Several studies have been conducted to diagnose MS using ML and Deep Learning (DL) models trained using MRI images, achieving promising results. However, complex and expensive diagnostic tools are needed to collect and examine imaging data. Thus, the intention of this study is to implement a cost-effective, clinical data-driven model that is capable of diagnosing pwMS. The dataset was obtained from King Fahad Specialty Hospital (KFSH) in Dammam, Saudi Arabia. Several ML algorithms were compared, namely Support Vector Machine (SVM), Decision Tree (DT), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), and Extra Trees (ET). The results indicated that the ET model outpaced the rest with an accuracy of 94.74%, recall of 97.26%, and precision of 94.67%.
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Affiliation(s)
- Sunday O. Olatunji
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Nawal Alsheikh
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Lujain Alnajrani
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Alhatoon Alanazy
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Meshael Almusairii
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Salam Alshammasi
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Aisha Alansari
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Rim Zaghdoud
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Alaa Alahmadi
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Mohammed Imran Basheer Ahmed
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Mohammed Salih Ahmed
- College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
| | - Jamal Alhiyafi
- Department of Computer Science, Kettering University, Flint, MI 48504, USA
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5
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Cappelle S, Pareto D, Sunaert S, Smets I, Laenen A, Dubois B, Demaerel P. T1w/FLAIR ratio standardization as a myelin marker in MS patients. Neuroimage Clin 2022; 36:103248. [PMID: 36451354 PMCID: PMC9668645 DOI: 10.1016/j.nicl.2022.103248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 10/20/2022] [Accepted: 10/23/2022] [Indexed: 11/06/2022]
Abstract
INTRODUCTION Calculation of a T1w/T2w ratio was introduced as a proxy for myelin integrity in the brain of multiple sclerosis (MS) patients. Since nowadays 3D FLAIR is commonly used for lesion detection instead of T2w images, we introduce a T1w/FLAIR ratio as an alternative for the T1w/T2w ratio. OBJECTIVES Bias and intensity variation are widely present between different scanners, between subjects and within subjects over time in T1w, T2w and FLAIR images. We present a standardized method for calculating a histogram calibrated T1w/FLAIR ratio to reduce bias and intensity variation in MR sequences from different scanners and at different time-points. MATERIAL AND METHODS 207 Relapsing Remitting MS patients were scanned on 4 different 3 T scanners with a protocol including 3D T1w, 2D T2w and 3D FLAIR images. After bias correction, T1w/FLAIR ratio maps and T1w/T2w ratio maps were calculated in 4 different ways: without calibration, with linear histogram calibration as described by Ganzetti et al. (2014), and by using 2 methods of non-linear histogram calibration. The first nonlinear calibration uses a template of extra-cerebral tissue and cerebrospinal fluid (CSF) brought from Montreal Neurological Institute (MNI) space to subject space; for the second nonlinear method we used an extra-cerebral tissue and CSF template of our own subjects. Additionally, we segmented several brain structures such as Normal Appearing White Matter (NAWM), Normal Appearing Grey Matter (NAGM), corpus callosum, thalami and MS lesions using Freesurfer and Samseg. RESULTS The coefficient of variation of T1w/FLAIR ratio in NAWM for the no calibrated, linear, and 2 nonlinear calibration methods were respectively 24, 19.1, 9.5, 13.8. The nonlinear methods of calibration showed the best results for calculating the T1w/FLAIR ratio with a smaller dispersion of the data and a smaller overlap of T1w/FLAIR ratio in the different segmented brain structures. T1w/T2w and T1w/FLAIR ratios showed a wider range of values compared to MTR values. CONCLUSIONS Calibration of T1w/T2w and T1w/FLAIR ratio maps is imperative to account for the sources of variation described above. The nonlinear calibration methods showed the best reduction of between-subject and within-subject variability. The T1w/T2w and T1w/FLAIR ratio seem to be more sensitive to smaller changes in tissue integrity than MTR. Future work is needed to determine the exact substrate of T1w/FLAIR ratio and to obtain correlations with clinical outcome.
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Affiliation(s)
- S. Cappelle
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium,Corresponding author
| | - D. Pareto
- Department of Radiology (IDI), Vall d’Hebron University Hospital, Barcelona, Spain
| | - S. Sunaert
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium,Department of Imaging & Pathology, Translational MRI, KU Leuven, Leuven, Belgium
| | - I. Smets
- Laboratory for Neuroimmunology, KU Leuven, Leuven, Belgium,Department of Neurology, Erasmus MC, Rotterdam, The Netherlands
| | - A. Laenen
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics, KU Leuven and Hasselt University, Leuven, Belgium
| | - B. Dubois
- Laboratory for Neuroimmunology, KU Leuven, Leuven, Belgium,Department of Neurology, University Hospitals Leuven, Leuven, Belgium
| | - Ph. Demaerel
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium,Department of Imaging & Pathology, Translational MRI, KU Leuven, Leuven, Belgium
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6
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Brown JWL, Prados F, Altmann DR, Kanber B, Stutters J, Cunniffe NG, Jones JL, Georgieva ZG, Needham EJ, Daruwalla C, Wheeler-Kingshott CG, Connick P, Chandran S, Franklin R, MacManus D, Samson R, Coles A, Chard D. Remyelination varies between and within lesions in multiple sclerosis following bexarotene. Ann Clin Transl Neurol 2022; 9:1626-1642. [PMID: 36116011 PMCID: PMC9539389 DOI: 10.1002/acn3.51662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 08/16/2022] [Accepted: 08/22/2022] [Indexed: 12/01/2022] Open
Abstract
OBJECTIVE In multiple sclerosis chronic demyelination is associated with axonal loss, and ultimately contributes to irreversible progressive disability. Enhancing remyelination may slow, or even reverse, disability. We recently trialled bexarotene versus placebo in 49 people with multiple sclerosis. While the primary MRI outcome was negative, there was converging neurophysiological and MRI evidence of efficacy. Multiple factors influence lesion remyelination. In this study we undertook a systematic exploratory analysis to determine whether treatment response - measured by change in magnetisation transfer ratio - is influenced by location (tissue type and proximity to CSF) or the degree of abnormality (using baseline magnetisation transfer ratio and T1 values). METHODS We examined treatment effects at the whole lesion level, the lesion component level (core, rim and perilesional tissues) and at the individual lesion voxel level. RESULTS At the whole lesion level, significant treatment effects were seen in GM but not WM lesions. Voxel-level analyses detected significant treatment effects in WM lesion voxels with the lowest baseline MTR, and uncovered gradients of treatment effect in both WM and CGM lesional voxels, suggesting that treatment effects were lower near CSF spaces. Finally, larger treatment effects were seen in the outer and surrounding components of GM lesions compared to inner cores. INTERPRETATION Remyelination varies markedly within and between lesions. The greater remyelinating effect in GM lesions is congruent with neuropathological observations. For future remyelination trials, whole GM lesion measures require less complex post-processing compared to WM lesions (which require voxel level analyses) and markedly reduce sample sizes.
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Affiliation(s)
- J William L Brown
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.,NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of Neurology, London, UK.,Clinical Outcomes Research Unit (CORe), University of Melbourne, Melbourne, Australia
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of Neurology, London, UK.,e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain.,Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing, University College London, London, UK
| | - Daniel R Altmann
- Medical Statistics Department, London School of Hygiene & Tropical Medicine, London, UK
| | - Baris Kanber
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of Neurology, London, UK.,Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing, University College London, London, UK.,National Institute for Health Research Biomedical Research Centre, University College London Hospitals NHS Foundation Trust and University College London, London, UK
| | - Jonathan Stutters
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of Neurology, London, UK
| | - Nick G Cunniffe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Joanne L Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Zoya G Georgieva
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Edward J Needham
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Cyrus Daruwalla
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Claudia Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of Neurology, London, UK.,Brain Connectivity Centre, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Robin Franklin
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.,Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - David MacManus
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of Neurology, London, UK
| | - Rebecca Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of Neurology, London, UK
| | - Alasdair Coles
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Declan Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Queen Square Institute of Neurology, London, UK.,National Institute for Health Research Biomedical Research Centre, University College London Hospitals NHS Foundation Trust and University College London, London, UK
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7
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Upadhayay S, Mehan S, Prajapati A, Sethi P, Suri M, Zawawi A, Almashjary MN, Tabrez S. Nrf2/HO-1 Signaling Stimulation through Acetyl-11-Keto-Beta-Boswellic Acid (AKBA) Provides Neuroprotection in Ethidium Bromide-Induced Experimental Model of Multiple Sclerosis. Genes (Basel) 2022; 13:genes13081324. [PMID: 35893061 PMCID: PMC9331916 DOI: 10.3390/genes13081324] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 12/16/2022] Open
Abstract
Multiple sclerosis (MS) is a severe immune-mediated neurological disease characterized by neuroinflammation, demyelination, and axonal degeneration in the central nervous system (CNS). This is frequently linked to motor abnormalities and cognitive impairments. The pathophysiological hallmarks of MS include inflammatory demyelination, axonal injury, white matter degeneration, and the development of CNS lesions that result in severe neuronal degeneration. Several studies suggested downregulation of nuclear factor erythroid-2-related factor-2 (Nrf2)/Heme oxygenase-1 (HO-1) signaling is a causative factor for MS pathogenesis. Acetyl-11-keto-β-boswellic acid (AKBA) is an active pentacyclictriterpenoid obtained from Boswellia serrata, possessing antioxidant and anti-inflammatory properties. The present study explores the protective potential of AKBA on behavioral, molecular, neurochemical, and gross pathological abnormalitiesandhistopathological alterations by H&E and LFB staining techniques in an experimental model of multiple sclerosis, emphasizing the increase inNrf2/HO-1 levels in the brain. Moreover, we also examine the effect of AKBA on the intensity of myelin basic protein (MBP) in CSF and rat brain homogenate. Specific apoptotic markers (Bcl-2, Bax, andcaspase-3) were also estimated in rat brain homogenate. Neuro behavioralabnormalities in rats were examined using an actophotometer, rotarod test, beam crossing task (BCT),and Morris water maze (MWM). AKBA 50 mg/kg and 100 mg/kg were given orally from day 8 to 35 to alleviate MS symptoms in the EB-injected rats. Furthermore, cellular, molecular, neurotransmitter, neuroinflammatory cytokine, and oxidative stress markers in rat whole brain homogenate, blood plasma, and cerebral spinal fluid were investigated. This study shows that AKBA upregulates the level of antioxidant proteins such as Nrf2 and HO-1 in the rat brain. AKBA restores altered neurochemical levels, potentially preventing gross pathological abnormalities during MS progression.
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Affiliation(s)
- Shubham Upadhayay
- Division of Neuroscience, Department of Pharmacology, ISF College of Pharmacy, Moga 142001, Punjab, India; (S.U.); (A.P.); (P.S.); (M.S.)
| | - Sidharth Mehan
- Division of Neuroscience, Department of Pharmacology, ISF College of Pharmacy, Moga 142001, Punjab, India; (S.U.); (A.P.); (P.S.); (M.S.)
- Correspondence: (S.M.); (S.T.)
| | - Aradhana Prajapati
- Division of Neuroscience, Department of Pharmacology, ISF College of Pharmacy, Moga 142001, Punjab, India; (S.U.); (A.P.); (P.S.); (M.S.)
| | - Pranshul Sethi
- Division of Neuroscience, Department of Pharmacology, ISF College of Pharmacy, Moga 142001, Punjab, India; (S.U.); (A.P.); (P.S.); (M.S.)
| | - Manisha Suri
- Division of Neuroscience, Department of Pharmacology, ISF College of Pharmacy, Moga 142001, Punjab, India; (S.U.); (A.P.); (P.S.); (M.S.)
| | - Ayat Zawawi
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (A.Z.); (M.N.A.)
- Vaccines and Immunotherapy Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Majed N. Almashjary
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (A.Z.); (M.N.A.)
- Hematology Research Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Animal House Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Shams Tabrez
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (A.Z.); (M.N.A.)
- King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Correspondence: (S.M.); (S.T.)
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8
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Periventricular magnetisation transfer abnormalities in early multiple sclerosis. Neuroimage Clin 2022; 34:103012. [PMID: 35487133 PMCID: PMC9125781 DOI: 10.1016/j.nicl.2022.103012] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 04/14/2022] [Accepted: 04/18/2022] [Indexed: 11/30/2022]
Abstract
Periventricular-MTR gradients are present from the earliest stage of MS and become steeper in advanced disease. Lower MTR in periventricular-NAWM was positively associated with reduced cortical-mean-thickness. MTR in periventricular-lesions scaled with cortical-mean-thickness, while non-periventricular lesions were unrelated. These findings suggest a common pathophysiologic mechanism between CSF-adjacent cortical and periventricular areas.
Objective Recent studies suggested that CSF-mediated factors contribute to periventricular (PV) T2-hyperintense lesion formation in multiple sclerosis (MS) and this in turn correlates with cortical damage. We thus investigated if such PV-changes are observable microstructurally in early-MS and if they correlate with cortical damage. Methods We assessed the magnetisation transfer ratio (MTR) in PV normal-appearing white matter (NAWM) and in MS lesions in 44 patients with a clinically isolated syndrome (CIS) suggestive of MS and 73 relapsing-remitting MS (RRMS) patients. Band-wise MTR values were related to cortical mean thickness (CMT) and compared with 49 healthy controls (HCs). For each band, MTR changes were assessed relative to the average MTR values of all HCs. Results Relative to HCs, PV-MTR was significantly reduced up to 2.63% in CIS and 5.37% in RRMS (p < 0.0001). The MTR decreased towards the lateral ventricles with 0.18%/mm in CIS and 0.31%/mm in RRMS patients, relative to HCs. In RRMS, MTR-values adjacent to the ventricle and in PV-lesions correlated positively with CMT and negatively with EDSS. Conclusion PV-MTR gradients are present from the earliest stage of MS, consistent with more pronounced microstructural WM-damage closer to the ventricles. The positive association between reduced CMT and lower MTR in PV-NAWM suggests a common pathophysiologic mechanism. Together, these findings indicate the potential use of multimodal MRI as refined marker for MS-related tissue changes.
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9
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Nakamura K, Zheng Y, Ontaneda D. T1/T2-weighted ratio is a surrogate marker of demyelination in multiple sclerosis-yes. Mult Scler 2022; 28:352-354. [PMID: 35067111 DOI: 10.1177/13524585211066313] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- Kunio Nakamura
- Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Yufan Zheng
- Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
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10
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Baldassari LE, Wattjes MP, Cortese ICM, Gass A, Metz I, Yousry T, Reich DS, Richert N. The neuroradiology of progressive multifocal leukoencephalopathy: a clinical trial perspective. Brain 2021; 145:426-440. [PMID: 34791056 DOI: 10.1093/brain/awab419] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 09/29/2021] [Accepted: 10/22/2021] [Indexed: 11/13/2022] Open
Abstract
Progressive multifocal leukoencephalopathy (PML) is an opportunistic infection of the central nervous system caused by the JC virus, which infects white and grey matter cells and leads to irreversible demyelination and neuroaxonal damage. Brain magnetic resonance imaging (MRI), in addition to the clinical presentation and demonstration of JC virus DNA either in the CSF or by histopathology, is an important tool in the detection of PML. In clinical practice, standard MRI pulse sequences are utilized for screening, diagnosis, and monitoring of PML, but validated imaging-based outcome measures for use in prospective, interventional clinical trials for PML have yet to be established. We review the existing literature regarding the use of MRI and positron emission tomography imaging in PML and discuss the implications of PML histopathology for neuroradiology. MRI not only demonstrates the localization and extent of PML lesions, but also mirrors the tissue destruction, ongoing viral spread, and resulting inflammation. Finally, we explore the potential for imaging measures to serve as an outcome in PML clinical trials and provide recommendations for current and future imaging outcome measure development in this area.
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Affiliation(s)
- Laura E Baldassari
- Division of Neurology 2, Office of Neuroscience, Office of New Drugs, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, Maryland, 20993, USA
| | - Mike P Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, 30625 Hannover, Germany
| | - Irene C M Cortese
- Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, 20892, USA
| | - Achim Gass
- Department of Neurology/Neuroimaging, Mannheim Center of Translational Neuroscience, University Medical Centre Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany
| | - Imke Metz
- Institute of Neuropathology, University Medical Center Göttingen, 37075 Göttingen, Germany
| | - Tarek Yousry
- Neuroradiological Academic Unit, UCL IoN; Lysholm Department of Neuroradiology, UCLH National Hospital for Neurology and Neurosurgery, London, UK
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, 20892, USA
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11
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Madsen MAJ, Wiggermann V, Bramow S, Christensen JR, Sellebjerg F, Siebner HR. Imaging cortical multiple sclerosis lesions with ultra-high field MRI. NEUROIMAGE-CLINICAL 2021; 32:102847. [PMID: 34653837 PMCID: PMC8517925 DOI: 10.1016/j.nicl.2021.102847] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 08/19/2021] [Accepted: 08/25/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Cortical lesions are abundant in multiple sclerosis (MS), yet difficult to visualize in vivo. Ultra-high field (UHF) MRI at 7 T and above provides technological advances suited to optimize the detection of cortical lesions in MS. PURPOSE To provide a narrative and quantitative systematic review of the literature on UHF MRI of cortical lesions in MS. METHODS A systematic search of all literature on UHF MRI of cortical lesions in MS published before September 2020. Quantitative outcome measures included cortical lesion numbers reported using 3 T and 7 T MRI and between 7 T MRI sequences, along with sensitivity of UHF MRI towards cortical lesions verified by histopathology. RESULTS 7 T MRI detected on average 52 ± 26% (mean ± 95% confidence interval) more cortical lesions than the best performing image contrast at 3 T, with the largest increase in type II-IV intracortical lesion detection. Across all studies, the mean cortical lesion number was 17 ± 6 per patient. In progressive MS cohorts, approximately four times more cortical lesions were reported than in CIS/early RRMS, and RRMS. Yet, there was no difference in lesion type ratio between these MS subtypes. Furthermore, superiority of one MRI sequence over another could not be established from available data. Post-mortem lesion detection with UHF MRI agreed only modestly with pathological examinations. Mean pro- and retrospective sensitivity was 33 ± 6% and 71 ± 10%, respectively, with the highest sensitivity towards type I and type IV lesions. CONCLUSION UHF MRI improves cortical lesion detection in MS considerably compared to 3 T MRI, particularly for type II-IV lesions. Despite modest sensitivity, 7 T MRI is still capable of visualizing all aspects of cortical lesion pathology and could potentially aid clinicians in diagnosing and monitoring MS, and progressive MS in particular. However, standardization of acquisition and segmentation protocols is needed.
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Affiliation(s)
- Mads A J Madsen
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark.
| | - Vanessa Wiggermann
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark
| | - Stephan Bramow
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark
| | - Jeppe Romme Christensen
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark
| | - Finn Sellebjerg
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3b, 2200 Copenhagen, Denmark
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital - Bispebjerg, Bispebjerg Bakke 23, 2400 Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3b, 2200 Copenhagen, Denmark
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12
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Brown JWL, Cunniffe NG, Prados F, Kanber B, Jones JL, Needham E, Georgieva Z, Rog D, Pearson OR, Overell J, MacManus D, Samson RS, Stutters J, Ffrench-Constant C, Gandini Wheeler-Kingshott CAM, Moran C, Flynn PD, Michell AW, Franklin RJM, Chandran S, Altmann DR, Chard DT, Connick P, Coles AJ. Safety and efficacy of bexarotene in patients with relapsing-remitting multiple sclerosis (CCMR One): a randomised, double-blind, placebo-controlled, parallel-group, phase 2a study. Lancet Neurol 2021; 20:709-720. [PMID: 34418398 DOI: 10.1016/s1474-4422(21)00179-4] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 05/17/2021] [Accepted: 05/28/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND Progressive disability in multiple sclerosis occurs because CNS axons degenerate as a late consequence of demyelination. In animals, retinoic acid receptor RXR-gamma agonists promote remyelination. We aimed to assess the safety and efficacy of a non-selective retinoid X receptor agonist in promoting remyelination in people with multiple sclerosis. METHODS This randomised, double-blind, placebo-controlled, parallel-group, phase 2a trial (CCMR One) recruited patients with relapsing-remitting multiple sclerosis from two centres in the UK. Eligible participants were aged 18-50 years and had been receiving dimethyl fumarate for at least 6 months. Via a web-based system run by an independent statistician, participants were randomly assigned (1:1), by probability-weighted minimisation using four binary factors, to receive 300 mg/m2 of body surface area per day of oral bexarotene or oral placebo for 6 months. Participants, investigators, and outcome assessors were masked to treatment allocation. MRI scans were done at baseline and at 6 months. The primary safety outcome was the number of adverse events and withdrawals attributable to bexarotene. The primary efficacy outcome was the patient-level change in mean lesional magnetisation transfer ratio between baseline and month 6 for lesions that had a baseline magnetisation transfer ratio less than the within-patient median. We analysed the primary safety outcome in the safety population, which comprised participants who received at least one dose of their allocated treatment. We analysed the primary efficacy outcome in the intention-to-treat population, which comprised all patients who completed the study. This study is registered in the ISRCTN Registry, 14265371, and has been completed. FINDINGS Between Jan 17, 2017, and May 17, 2019, 52 participants were randomly assigned to receive either bexarotene (n=26) or placebo (n=26). Participants who received bexarotene had a higher mean number of adverse events (6·12 [SD 3·09]; 159 events in total) than did participants who received placebo (1·63 [SD 1·50]; 39 events in total). All bexarotene-treated participants had at least one adverse event, which included central hypothyroidism (n=26 vs none on placebo), hypertriglyceridaemia (n=24 vs none on placebo), rash (n=13 vs one on placebo), and neutropenia (n=10 vs none on placebo). Five (19%) participants on bexarotene and two (8%) on placebo discontinued the study drug due to adverse events. One episode of cholecystitis in a placebo-treated participant was the only serious adverse event. The change in mean lesional magnetisation transfer ratio was not different between the bexarotene group (0·25 percentage units [pu; SD 0·98]) and the placebo group (0·09 pu [0·84]; adjusted bexarotene-placebo difference 0·16 pu, 95% CI -0·39 to 0·71; p=0·55). INTERPRETATION We do not recommend the use of bexarotene to treat patients with multiple sclerosis because of its poor tolerability and negative primary efficacy outcome. However, statistically significant effects were seen in some exploratory MRI and electrophysiological analyses, suggesting that other retinoid X receptor agonists might have small biological effects that could be investigated in further studies. FUNDING Multiple Sclerosis Society of the United Kingdom.
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Affiliation(s)
- J William L Brown
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; Clinical Outcomes Research Unit, University of Melbourne, Melbourne, VIC, Australia
| | - Nick G Cunniffe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK; e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Baris Kanber
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK; National Institute for Health Research Biomedical Research Centre, University College London Hospitals NHS Foundation Trust and University College London, London, UK
| | - Joanne L Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Edward Needham
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Zoya Georgieva
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - David Rog
- Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Salford, UK
| | - Owen R Pearson
- Department of Neurology, Swansea Bay University Health Board, Swansea, UK
| | - James Overell
- Product Development Neuroscience, F Hoffmann-La Roche, Basel, Switzerland; Institute of Neurological Sciences, University of Glasgow, Glasgow, UK
| | - David MacManus
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Rebecca S Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jonathan Stutters
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | | | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; Brain Connectivity Centre, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Carla Moran
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Paul D Flynn
- Division of Cardiovascular Medicine, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Andrew W Michell
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Robin J M Franklin
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Daniel R Altmann
- Medical Statistics Department, London School of Hygiene & Tropical Medicine, London, UK
| | - Declan T Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research Biomedical Research Centre, University College London Hospitals NHS Foundation Trust and University College London, London, UK
| | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Alasdair J Coles
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
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13
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Trevarrow MP, Baker SE, Wilson TW, Kurz MJ. Microstructural changes in the spinal cord of adults with cerebral palsy. Dev Med Child Neurol 2021; 63:998-1003. [PMID: 33719037 PMCID: PMC8260437 DOI: 10.1111/dmcn.14860] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/17/2021] [Indexed: 01/01/2023]
Abstract
AIM To quantify the microstructural differences in the cervical-thoracic spinal cord of adults with cerebral palsy (CP). METHOD Magnetic resonance imaging of the proximal spinal cord (C6-T3) was conducted on a cohort of adults with CP (n=13; mean age=31y 11mo, standard deviation [SD] 8y 7mo; range=20y 8mo-47y 6mo; eight females, five males) and population norm adult controls (n=16; mean age=31y 4mo, SD 9y 9mo; range=19y 4mo-49y 5mo; seven females, nine males). The cross-sectional area (CSA) of the spinal cord, gray and white matter, magnetization transfer ratio (MTR), and fractional anisotropy of the cuneatus and corticospinal tracts were calculated. RESULTS The total spinal cord CSA and proportion of the spinal cord gray matter CSA were significantly decreased in the adults with CP. The corticospinal tracts' MTR was lower in the adults with CP. Individuals that had reduced gray matter also tended to have reduced MTR in their corticospinal tracts (r=0.42, p=0.029) and worse hand dexterity clinical scores (r=0.53, p=0.004). INTERPRETATION These results show that there are changes in the spinal cord microstructure of adults with CP. Ultimately, these microstructural changes play a role in the extent of the hand sensorimotor deficits seen in adults with CP. What this paper adds Adults with cerebral palsy (CP) have a reduced spinal cord cross-sectional area (CSA). Spinal cord gray matter is reduced in adults with CP. Spinal cord CSA is associated with hand dexterity. Magnetization transfer ratio of corticospinal tracts was lower in adults with CP.
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Affiliation(s)
- Michael P Trevarrow
- Institute for Human NeuroscienceBoys Town National Research Hospital Boys Town NE USA
| | - Sarah E Baker
- Institute for Human NeuroscienceBoys Town National Research Hospital Boys Town NE USA
| | - Tony W Wilson
- Institute for Human NeuroscienceBoys Town National Research Hospital Boys Town NE USA
| | - Max J Kurz
- Institute for Human NeuroscienceBoys Town National Research Hospital Boys Town NE USA
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14
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Preziosa P, Bouman PM, Kiljan S, Steenwijk MD, Meani A, Pouwels PJ, Rocca MA, Filippi M, Geurts JJG, Jonkman LE. Neurite density explains cortical T1-weighted/T2-weighted ratio in multiple sclerosis. J Neurol Neurosurg Psychiatry 2021; 92:790-792. [PMID: 33436500 DOI: 10.1136/jnnp-2020-324391] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 11/16/2020] [Accepted: 12/16/2020] [Indexed: 11/03/2022]
Affiliation(s)
- Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy .,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Piet M Bouman
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Svenja Kiljan
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Alessandro Meani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Petra J Pouwels
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
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15
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Granziera C, Wuerfel J, Barkhof F, Calabrese M, De Stefano N, Enzinger C, Evangelou N, Filippi M, Geurts JJG, Reich DS, Rocca MA, Ropele S, Rovira À, Sati P, Toosy AT, Vrenken H, Gandini Wheeler-Kingshott CAM, Kappos L. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 2021; 144:1296-1311. [PMID: 33970206 PMCID: PMC8219362 DOI: 10.1093/brain/awab029] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 10/25/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.
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Affiliation(s)
- Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland
- Quantitative Biomedical Imaging Group (qbig), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
- UCL Institutes of Healthcare Engineering and Neurology, London, UK
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Neurology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Christian Enzinger
- Department of Neurology and Division of Neuroradiology, Medical University of Graz, Graz, Austria
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, multiple sclerosis Center Amsterdam, Neuroscience Amsterdam, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Ropele
- Neuroimaging Research Unit, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Vall d'Hebron University Hospital and Research Institute, Barcelona, Spain
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ahmed T Toosy
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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16
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Mizell R, Chen H, Lambe J, Saidha S, Harrison DM. Association of retinal atrophy with cortical lesions and leptomeningeal enhancement in multiple sclerosis on 7T MRI. Mult Scler 2021; 28:393-405. [PMID: 34125629 DOI: 10.1177/13524585211023343] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Retinal atrophy in multiple sclerosis (MS) as measured by optical coherence tomography (OCT) correlates with demyelinating lesions and brain atrophy, but its relationship with cortical lesions (CLs) and meningeal inflammation is not well known. OBJECTIVES To evaluate the relationship of retinal layer atrophy with leptomeningeal enhancement (LME) and CLs in MS as visualized on 7 Tesla (7T) magnetic resonance imaging (MRI). METHODS Forty participants with MS underwent 7T MRI of the brain and OCT. Partial correlation and mixed-effects regression evaluated relationships between MRI and OCT findings. RESULTS All participants had CLs and 32 (80%) participants had LME on post-contrast MRI. Ganglion cell/inner plexiform layer (GCIPL) thickness correlated with total CL volume (r =-0.45, p < 0.01). Participants with LME at baseline had thinner macular retinal nerve fiber layer (mRNFL; p = 0.01) and GCIPL (p < 0.01). Atrophy in various retinal layers was faster in those with certain patterns of LME. For example, mRNFL declined -1.113 (-1.974, -0.252) μm/year faster in those with spread/fill-pattern LME foci at baseline compared with those without (p = 0.01). CONCLUSION This study associates MRI findings of LME and cortical pathology with thinning of retinal layers as measured by OCT, suggesting a common link between meningeal inflammation, CLs, and retinal atrophy in MS.
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Affiliation(s)
- Ryan Mizell
- Baltimore VA Medical Center, Baltimore, MD, USA/University of Maryland Medical Center, Baltimore, MD, USA
| | - Hegang Chen
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jeffrey Lambe
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Shiv Saidha
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel M Harrison
- Baltimore VA Medical Center, Baltimore, MD, USA/University of Maryland Medical Center, Baltimore, MD, USA/Johns Hopkins University School of Medicine, Baltimore, MD, USA/Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
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17
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MR T1 mapping for quantifying brain manganese deposition in type C hepatic encephalopathy rats. Biometals 2021; 34:841-854. [PMID: 33928475 DOI: 10.1007/s10534-021-00311-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Accepted: 04/20/2021] [Indexed: 10/21/2022]
Abstract
To evaluate magnetic resonance (MR) T1 mapping for quantifying brain manganese (Mn) deposition in type C hepatic encephalopathy (CHE) rats and to investigate the mechanism of magnesium sulfate (MgSO4) therapy. Thirty Sprague-Dawley rats were randomly assigned into normal control group (NC, n = 6) and CHE groups (n = 24). Thioacetamide (TAA) was used for modeling CHE rats. CHE groups were further divided into 4 subgroups: TAA group, MgSO4 low dose (Mg-L) group, MgSO4 high dose (Mg-H) group and deionized water (DW) group (n = 6 for each group). TAA, Mg-L, Mg-H and DW groups were received intraperitoneal injections of 250 mg TAA/kg, twice a week for 8 weeks. Mg-L and Mg-H groups were orally received MgSO4 of 124 and 248 mg/kg daily, respectively, for another 8 weeks (without TAA). MR T1 mapping was performed in NC, TAA, Mg-L, Mg-H and DW groups at various time points. T1 value and Mn content in basal ganglia, hippocampus, cerebral cortex and cerebellum were evaluated. Morris water maze (MWM) and narrow beat test (NBT) were utilized to evaluate rats' learning, memory and motor ability. Contents of interleukin-6 (IL-6), tumor necrosis factor-a (TNF-a) and calcium-binding adaptor 1 protein (Iba1) were evaluated. Reduced T1 values in basal ganglia, hippocampus and cerebral cortex (P < 0.01, P < 0.05 and P < 0.05, respectively); increased Mn content in basal ganglia, hippocampus and cerebral cortex (all P < 0.05); reduced times of head contacting with region of interest (ROI), reduced times of entrance into the target quadrant (both P < 0.05); increased NBT total time (P < 0.05); increased brain contents of IL-6 (P < 0.001), TNF-α (P < 0.01) and over-expression of Iba1 were found in TAA group compared to NC group. After treated by MgSO4, increased T1 value and reduced Mn content in basal ganglia, hippocampus and cerebral cortex (all P < 0.01); increased times of head contacting with ROI, increased times of entrance into the target quadrant (both P < 0.05); reduced NBT total time (P < 0.01); reduced brain content of IL-6, TNF-α (both P < 0.05) and reduced expression of Iba1 were found. T1 values were negatively correlated with Mn contents in basal ganglia (r = - 0.834, P < 0.01), hippocampus (r = - 0.739, P < 0.05), cortex (r = - 0.801, P < 0.05) and cerebellum (r = - 0.788, P < 0.05). T1 mapping could quantify brain Mn deposition in CHE rats. MgSO4 could improve cognition and motor ability of CHE rats by reducing brain Mn deposition, alleviating neurological inflammation and achieve the effective therapy for CHE. Mn may participate in the pathogenesis of CHE through neuroinflammation.
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18
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Lazari A, Lipp I. Can MRI measure myelin? Systematic review, qualitative assessment, and meta-analysis of studies validating microstructural imaging with myelin histology. Neuroimage 2021; 230:117744. [PMID: 33524576 PMCID: PMC8063174 DOI: 10.1016/j.neuroimage.2021.117744] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 01/05/2021] [Accepted: 01/09/2021] [Indexed: 12/16/2022] Open
Abstract
Recent years have seen an increased understanding of the importance of myelination in healthy brain function and neuropsychiatric diseases. Non-invasive microstructural magnetic resonance imaging (MRI) holds the potential to expand and translate these insights to basic and clinical human research, but the sensitivity and specificity of different MR markers to myelination is a subject of debate. To consolidate current knowledge on the topic, we perform a systematic review and meta-analysis of studies that validate microstructural imaging by combining it with myelin histology. We find meta-analytic evidence for correlations between various myelin histology metrics and markers from different MRI modalities, including fractional anisotropy, radial diffusivity, macromolecular pool, magnetization transfer ratio, susceptibility and longitudinal relaxation rate, but not mean diffusivity. Meta-analytic correlation effect sizes range widely, between R2 = 0.26 and R2 = 0.82. However, formal comparisons between MRI-based myelin markers are limited by methodological variability, inconsistent reporting and potential for publication bias, thus preventing the establishment of a single most sensitive strategy to measure myelin with MRI. To facilitate further progress, we provide a detailed characterisation of the evaluated studies as an online resource. We also share a set of 12 recommendations for future studies validating putative MR-based myelin markers and deploying them in vivo in humans.
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Affiliation(s)
- Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Ilona Lipp
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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19
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Preziosa P, Storelli L, Meani A, Moiola L, Rodegher M, Filippi M, Rocca MA. Effects of Fingolimod and Natalizumab on Brain T1-/T2-Weighted and Magnetization Transfer Ratios: a 2-Year Study. Neurotherapeutics 2021; 18:878-888. [PMID: 33483938 PMCID: PMC8423925 DOI: 10.1007/s13311-020-00997-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/18/2020] [Indexed: 11/26/2022] Open
Abstract
Fingolimod and natalizumab significantly reduce disease activity in relapsing-remitting multiple sclerosis (RRMS) and could promote tissue repair and neuroprotection. The ratio between conventional T1- and T2-weighted sequences (T1w/T2w-ratio) and magnetization transfer ratio (MTR) allow to quantify brain microstructural tissue abnormalities. Here, we compared fingolimod and natalizumab effects on brain T1w/T2w-ratio and MTR in RRMS over 2 years of treatment. RRMS patients starting fingolimod (n = 25) or natalizumab (n = 30) underwent 3T brain MRI scans at baseline (T0), month 6 (M6), month 12 (M12), and month 24 (M24). White matter (WM) lesions, normal-appearing (NA) WM, and gray matter (GM) T1w/T2w-ratio and MTR were estimated and compared between groups using linear mixed models. No baseline demographic, clinical, and MRI difference was found between groups. In natalizumab patients, lesion T1w/T2w-ratio and MTR significantly increased at M6 vs. T0 (p ≤ 0.035) and decreased at subsequent timepoints (p ≤ 0.037). In fingolimod patients, lesion T1w/T2w-ratio increased at M12 vs. T0 (p = 0.010), while MTR gradually increased at subsequent timepoints vs. T0 (p ≤ 0.027). Natalizumab stabilized NAWM and GM T1w/T2w-ratio and MTR. In fingolimod patients, NAWM T1w/T2w-ratio and MTR significantly increased at M24 vs. M12 (p ≤ 0.001). A significant GM T1w/T2w-ratio decrease at M6 vs. T0 (p = 0.014) and increase at M24 vs. M6 (p = 0.008) occurred, whereas GM MTR was significantly higher at M24 vs. previous timepoints (p ≤ 0.017) with significant between-group differences (p ≤ 0.034). Natalizumab may promote an early recovery of lesional damage and prevent microstructural damage accumulation in NAWM and GM during the first 2 years of treatment. Fingolimod enhances tissue damage recovery being visible after 6 months in lesions and after 2 years in NAWM and GM.
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Affiliation(s)
- Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Loredana Storelli
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Meani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Lucia Moiola
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy.
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20
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Kim JP, Kim J, Jang H, Kim J, Kang SH, Kim JS, Lee J, Na DL, Kim HJ, Seo SW, Park H. Predicting amyloid positivity in patients with mild cognitive impairment using a radiomics approach. Sci Rep 2021; 11:6954. [PMID: 33772041 PMCID: PMC7997887 DOI: 10.1038/s41598-021-86114-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 02/23/2021] [Indexed: 02/01/2023] Open
Abstract
Predicting amyloid positivity in patients with mild cognitive impairment (MCI) is crucial. In the present study, we predicted amyloid positivity with structural MRI using a radiomics approach. From MR images (including T1, T2 FLAIR, and DTI sequences) of 440 MCI patients, we extracted radiomics features composed of histogram and texture features. These features were used alone or in combination with baseline non-imaging predictors such as age, sex, and ApoE genotype to predict amyloid positivity. We used a regularized regression method for feature selection and prediction. The performance of the baseline non-imaging model was at a fair level (AUC = 0.71). Among single MR-sequence models, T1 and T2 FLAIR radiomics models also showed fair performances (AUC for test = 0.71-0.74, AUC for validation = 0.68-0.70) in predicting amyloid positivity. When T1 and T2 FLAIR radiomics features were combined, the AUC for test was 0.75 and AUC for validation was 0.72 (p vs. baseline model < 0.001). The model performed best when baseline features were combined with a T1 and T2 FLAIR radiomics model (AUC for test = 0.79, AUC for validation = 0.76), which was significantly better than those of the baseline model (p < 0.001) and the T1 + T2 FLAIR radiomics model (p < 0.001). In conclusion, radiomics features showed predictive value for amyloid positivity. It can be used in combination with other predictive features and possibly improve the prediction performance.
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Affiliation(s)
- Jun Pyo Kim
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea ,grid.414964.a0000 0001 0640 5613Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea ,grid.414964.a0000 0001 0640 5613Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Jonghoon Kim
- grid.264381.a0000 0001 2181 989XDepartment of Electronic and Computer Engineering, Sungkyunkwan University, Suwon, Korea
| | - Hyemin Jang
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea ,grid.414964.a0000 0001 0640 5613Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea ,grid.414964.a0000 0001 0640 5613Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Jaeho Kim
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea ,grid.414964.a0000 0001 0640 5613Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea ,grid.414964.a0000 0001 0640 5613Neuroscience Center, Samsung Medical Center, Seoul, Korea ,grid.256753.00000 0004 0470 5964Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Korea
| | - Sung Hoon Kang
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea ,grid.414964.a0000 0001 0640 5613Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea ,grid.414964.a0000 0001 0640 5613Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Ji Sun Kim
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea ,grid.414964.a0000 0001 0640 5613Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea ,grid.414964.a0000 0001 0640 5613Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Jongmin Lee
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea ,grid.414964.a0000 0001 0640 5613Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea ,grid.414964.a0000 0001 0640 5613Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Duk L. Na
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea ,grid.414964.a0000 0001 0640 5613Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea ,grid.414964.a0000 0001 0640 5613Neuroscience Center, Samsung Medical Center, Seoul, Korea ,grid.264381.a0000 0001 2181 989XDepartment of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Hee Jin Kim
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea ,grid.414964.a0000 0001 0640 5613Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea ,grid.414964.a0000 0001 0640 5613Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Sang Won Seo
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea ,grid.414964.a0000 0001 0640 5613Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea ,grid.414964.a0000 0001 0640 5613Neuroscience Center, Samsung Medical Center, Seoul, Korea ,grid.264381.a0000 0001 2181 989XDepartment of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, Korea ,grid.414964.a0000 0001 0640 5613Center for Clinical Epidemiology, Samsung Medical Center, Seoul, Korea ,grid.264381.a0000 0001 2181 989XDepartment of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon-si, Korea
| | - Hyunjin Park
- grid.410720.00000 0004 1784 4496Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Korea ,grid.264381.a0000 0001 2181 989XSchool of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon-si, Republic of Korea
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Mancini M, Karakuzu A, Cohen-Adad J, Cercignani M, Nichols TE, Stikov N. An interactive meta-analysis of MRI biomarkers of myelin. eLife 2020; 9:e61523. [PMID: 33084576 PMCID: PMC7647401 DOI: 10.7554/elife.61523] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 10/20/2020] [Indexed: 12/17/2022] Open
Abstract
Several MRI measures have been proposed as in vivo biomarkers of myelin, each with applications ranging from plasticity to pathology. Despite the availability of these myelin-sensitive modalities, specificity and sensitivity have been a matter of discussion. Debate about which MRI measure is the most suitable for quantifying myelin is still ongoing. In this study, we performed a systematic review of published quantitative validation studies to clarify how different these measures are when compared to the underlying histology. We analyzed the results from 43 studies applying meta-analysis tools, controlling for study sample size and using interactive visualization (https://neurolibre.github.io/myelin-meta-analysis). We report the overall estimates and the prediction intervals for the coefficient of determination and find that MT and relaxometry-based measures exhibit the highest correlations with myelin content. We also show which measures are, and which measures are not statistically different regarding their relationship with histology.
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Affiliation(s)
- Matteo Mancini
- Department of Neuroscience, Brighton and Sussex Medical School, University of SussexBrightonUnited Kingdom
- NeuroPoly Lab, Polytechnique MontrealMontrealCanada
- CUBRIC, Cardiff UniversityCardiffUnited Kingdom
| | | | - Julien Cohen-Adad
- NeuroPoly Lab, Polytechnique MontrealMontrealCanada
- Functional Neuroimaging Unit, CRIUGM, Université de MontréalMontrealCanada
| | - Mara Cercignani
- Department of Neuroscience, Brighton and Sussex Medical School, University of SussexBrightonUnited Kingdom
- Neuroimaging Laboratory, Fondazione Santa LuciaRomeItaly
| | - Thomas E Nichols
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of OxfordOxfordUnited Kingdom
- Big Data Institute, University of OxfordOxfordUnited Kingdom
| | - Nikola Stikov
- NeuroPoly Lab, Polytechnique MontrealMontrealCanada
- Montreal Heart Institute, Université de MontréalMontrealCanada
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22
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Moccia M, van de Pavert S, Eshaghi A, Haider L, Pichat J, Yiannakas M, Ourselin S, Wang Y, Wheeler-Kingshott C, Thompson A, Barkhof F, Ciccarelli O. Pathologic correlates of the magnetization transfer ratio in multiple sclerosis. Neurology 2020; 95:e2965-e2976. [PMID: 32938787 DOI: 10.1212/wnl.0000000000010909] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 07/22/2020] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To identify pathologic correlates of magnetization transfer ratio (MTR) in multiple sclerosis (MS) in an MRI-pathology study. METHODS We acquired MTR maps at 3T from 16 fixed MS brains and 4 controls, and immunostained 100 tissue blocks for neuronal neurofilaments, myelin (SMI94), tissue macrophages (CD68), microglia (IBA1), B-lymphocytes, T-lymphocytes, cytotoxic T-lymphocytes, astrocytes (glial fibrillary acidic protein), and mitochondrial damage (COX4, VDAC). We defined regions of interest in lesions, normal-appearing white matter (NAWM), and cortical normal-appearing gray matter (NAGM). Associations between MTR and immunostaining intensities were explored using linear mixed-effects models (with cassettes nested within patients) and interaction terms (for differences between regions of interest and between cases and controls); a multivariate linear mixed-effects model identified the best pathologic correlates of MTR. RESULTS MTR was the lowest in white matter (WM) lesions (23.4 ± 9.4%) and the highest in NAWM (38.1 ± 8.7%). In MS brains, lower MTR was associated with lower immunostaining intensity for myelin (coefficient 0.31; 95% confidence interval [CI] 0.07-0.55), macrophages (coefficient 0.03; 95% CI 0.01-0.07), and astrocytes (coefficient 0.51; 95% CI 0.02-1.00), and with greater mitochondrial damage (coefficient 0.31; 95% CI 0.07-0.55). Based on interaction terms, MTR was more strongly associated with myelin in WM (coefficient 1.58; 95% CI 1.09-2.08) and gray matter (GM) lesions (coefficient 0.66; 95% CI 0.13-1.20), and with macrophages (coefficient 1.40; 95% CI 0.56-2.25), astrocytes (coefficient 2.66; 95% CI 1.31-4.01), and mitochondrial damage (coefficient -12.59; 95% CI -23.16 to -2.02) in MS brains than controls. In the multivariate model, myelin immunostaining intensity was the best correlate of MTR (coefficient 0.31; 95% CI 0.09-0.52; p = 0.004). CONCLUSIONS Myelin was the strongest correlate of MTR, especially in WM and cortical GM lesions, but additional correlates should be kept in mind when designing and interpreting MTR observational and experimental studies in MS.
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Affiliation(s)
- Marcello Moccia
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Steven van de Pavert
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Arman Eshaghi
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Lukas Haider
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Jonas Pichat
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Marios Yiannakas
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Sebastien Ourselin
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Yi Wang
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Claudia Wheeler-Kingshott
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Alan Thompson
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Frederik Barkhof
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Olga Ciccarelli
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK.
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Tsintou M, Dalamagkas K, Makris N. Taking central nervous system regenerative therapies to the clinic: curing rodents versus nonhuman primates versus humans. Neural Regen Res 2020; 15:425-437. [PMID: 31571651 PMCID: PMC6921352 DOI: 10.4103/1673-5374.266048] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 06/04/2019] [Indexed: 12/17/2022] Open
Abstract
The central nervous system is known to have limited regenerative capacity. Not only does this halt the human body's reparative processes after central nervous system lesions, but it also impedes the establishment of effective and safe therapeutic options for such patients. Despite the high prevalence of stroke and spinal cord injury in the general population, these conditions remain incurable and place a heavy burden on patients' families and on society more broadly. Neuroregeneration and neural engineering are diverse biomedical fields that attempt reparative treatments, utilizing stem cells-based strategies, biologically active molecules, nanotechnology, exosomes and highly tunable biodegradable systems (e.g., certain hydrogels). Although there are studies demonstrating promising preclinical results, safe clinical translation has not yet been accomplished. A key gap in clinical translation is the absence of an ideal animal or ex vivo model that can perfectly simulate the human microenvironment, and also correspond to all the complex pathophysiological and neuroanatomical factors that affect functional outcomes in humans after central nervous system injury. Such an ideal model does not currently exist, but it seems that the nonhuman primate model is uniquely qualified for this role, given its close resemblance to humans. This review considers some regenerative therapies for central nervous system repair that hold promise for future clinical translation. In addition, it attempts to uncover some of the main reasons why clinical translation might fail without the implementation of nonhuman primate models in the research pipeline.
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Affiliation(s)
- Magdalini Tsintou
- Departments of Psychiatry and Neurology Services, Center for Neural Systems Investigations, Center for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- University College of London Division of Surgery & Interventional Science, Center for Nanotechnology & Regenerative Medicine, University College London, London, UK
| | - Kyriakos Dalamagkas
- University College of London Division of Surgery & Interventional Science, Center for Nanotechnology & Regenerative Medicine, University College London, London, UK
- Department of Physical Medicine and Rehabilitation, The University of Texas Health Science Center at Houston, Houston, TX, USA
- The Institute for Rehabilitation and Research Memorial Hermann Research Center, The Institute for Rehabilitation and Research Memorial Hermann Hospital, Houston, TX, USA
| | - Nikos Makris
- Departments of Psychiatry and Neurology Services, Center for Neural Systems Investigations, Center for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
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24
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Cassiano MT, Lanzillo R, Alfano B, Costabile T, Comerci M, Prinster A, Moccia M, Megna R, Morra VB, Quarantelli M, Brunetti A. Voxel-based analysis of gray matter relaxation rates shows different correlation patterns for cognitive impairment and physical disability in relapsing-remitting multiple sclerosis. NEUROIMAGE-CLINICAL 2020; 26:102201. [PMID: 32062567 PMCID: PMC7025083 DOI: 10.1016/j.nicl.2020.102201] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 01/13/2020] [Accepted: 01/28/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND Regional analyses of markers of microstructural gray matter (GM) changes, including relaxation rates, have shown inconsistent correlations with physical and cognitive impairment in MS. OBJECTIVE To assess voxelwise the correlation of the R1 and R2 relaxation rates with the physical and cognitive impairment in MS. METHODS GM R1 and R2 relaxation rate maps were obtained in 241 relapsing-remitting MS patients by relaxometric segmentation of MRI studies. Correlations with the Expanded Disability Status Scale (EDSS) and the percentage of impaired cognitive test (Brief Repeatable Battery and Stroop Test, available in 186 patients) were assessed voxelwise, including voxel GM content as nuisance covariate to remove the effect of atrophy on the correlations. RESULTS Extensive clusters of inverse correlation between EDSS and R2 were detected throughout the brain, while inverse correlations with R1 were mostly limited to perirolandic and supramarginal cortices. Cognitive impairment correlated negatively with R1, and to a lesser extent with R2, in the middle frontal, mesial temporal, midcingulate and medial parieto-occipital cortices. CONCLUSION In relapsing-remitting MS patients, GM microstructural changes correlate diffusely with physical disability, independent of atrophy, with a preferential role of the sensorimotor cortices. Neuronal damage in the limbic system and dorsolateral prefrontal cortices correlates with cognitive dysfunction.
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Affiliation(s)
- Maria Teresa Cassiano
- Department of Advanced Biomedical Sciences, University "Federico II", Via Pansini, 5, 80131 Naples, Italy
| | - Roberta Lanzillo
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Bruno Alfano
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy
| | - Teresa Costabile
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Marco Comerci
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy
| | - Anna Prinster
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy
| | - Marcello Moccia
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Rosario Megna
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy
| | - Vincenzo Brescia Morra
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Mario Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy.
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University "Federico II", Via Pansini, 5, 80131 Naples, Italy
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25
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Lee S, Lee H, Kim KW. Magnetic resonance imaging texture predicts progression to dementia due to Alzheimer disease earlier than hippocampal volume. J Psychiatry Neurosci 2020; 45:7-14. [PMID: 31228173 PMCID: PMC6919919 DOI: 10.1503/jpn.180171] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Early identification of people at risk of imminent progression to dementia due to Alzheimer disease is crucial for timely intervention and treatment. We investigated whether the texture of MRI brain scans could predict the progression of mild cognitive impairment (MCI) to Alzheimer disease earlier than volume. METHODS We constructed a development data set (121 people who were cognitively normal and 145 who had mild Alzheimer disease) and a validation data set (113 patients with stable MCI who did not progress to Alzheimer disease for 3 years; 40 with early MCI who progressed to Alzheimer disease after 12–36 months; and 41 with late MCI who progressed to Alzheimer disease within 12 months) from the Alzheimer’s Disease Neuroimaging Initiative. We analyzed the texture of the hippocampus, precuneus and posterior cingulate cortex using a grey-level co-occurrence matrix. We constructed texture and volume indices from the development data set using logistic regression. Using area under the curve (AUC) of receiver operator characteristics, we compared the accuracy of hippocampal volume, hippocampal texture and the composite texture of the hippocampus, precuneus and posterior cingulate cortex in predicting conversion from MCI to Alzheimer disease in the validation data set. RESULTS Compared with hippocampal volume, hippocampal texture (0.790 v. 0.739, p = 0.047) and composite texture (0.811 v. 0.739, p = 0.007) showed larger AUCs for conversion to Alzheimer disease from both early and late MCI. Hippocampal texture showed a marginally larger AUC than hippocampal volume in early MCI (0.795 v. 0.726, p = 0.060). Composite texture showed a larger AUC for conversion to Alzheimer disease than hippocampal volume in both early (0.817 v. 0.726, p = 0.027) and late MCI (0.805 v. 0.753, p = 0.019). LIMITATIONS This study was limited by the absence of histological data, and the pathology reflected by the texture measures remains to be validated. CONCLUSION Textures of the hippocampus, precuneus and posterior cingulate cortex predicted conversion from MCI to Alzheimer disease at an earlier time point and with higher accuracy than hippocampal volume.
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Affiliation(s)
- Subin Lee
- From the Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea (S. Lee, Kim); the Health Innovation Big Data Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea (H. Lee); the Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea (Kim); and the Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea (Kim)
| | - Hyunna Lee
- From the Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea (S. Lee, Kim); the Health Innovation Big Data Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea (H. Lee); the Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea (Kim); and the Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea (Kim)
| | - Ki Woong Kim
- From the Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea (S. Lee, Kim); the Health Innovation Big Data Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea (H. Lee); the Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea (Kim); and the Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea (Kim)
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26
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Ighani M, Jonas S, Izbudak I, Choi S, Lema-Dopico A, Hua J, O'Connor EE, Harrison DM. No association between cortical lesions and leptomeningeal enhancement on 7-Tesla MRI in multiple sclerosis. Mult Scler 2019; 26:165-176. [PMID: 31573837 DOI: 10.1177/1352458519876037] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND Autopsy data suggest a causative link between meningeal inflammation and cortical lesions (CLs) in multiple sclerosis (MS). OBJECTIVE To use leptomeningeal enhancement (LME) and CLs on 7-Tesla (7T) magnetic resonance imaging (MRI) to investigate associations between meningeal inflammation and cortical pathology. METHODS Forty-one participants with MS underwent 7T MRI of the brain. CLs and foci of LME were quantified. RESULTS All MS participants had CLs; 27 (65.8%) had >1 focus of LME. Except for hippocampal CL count (ρ = 0.32 with spread/fill-sulcal pattern LME, p = 0.042), no significant correlations were seen between LME and CLs. Mean cortical thickness correlated with the number of LME foci (ρ = -0.43, p = 0.005). Participants with relapsing-remitting multiple sclerosis (RRMS) showed no correlation with neocortical CLs, but significant correlations were seen between LME and hippocampal lesion count (ρ = 0.39, p = 0.030), normalized cortical gray matter (GM) volume (ρ = -0.49, p = 0.005), and mean cortical thickness (ρ = -0.59, p < 0.001). CONCLUSION This study supports a relationship between LME and cortical GM atrophy but does not support an association of LME and neocortical CLs. This may indicate that meningeal inflammation is involved with neurodegenerative inflammatory processes, rather than focal lesion development.
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Affiliation(s)
| | - Samuel Jonas
- Department of Radiology, University of Maryland Medical Center, Baltimore, MD, USA
| | - Izlem Izbudak
- Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Seongjin Choi
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alfonso Lema-Dopico
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jun Hua
- Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA/Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA/F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Erin E O'Connor
- Department of Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Daniel M Harrison
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA/ Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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27
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Magliozzi R, Howell OW, Nicholas R, Cruciani C, Castellaro M, Romualdi C, Rossi S, Pitteri M, Benedetti MD, Gajofatto A, Pizzini FB, Montemezzi S, Rasia S, Capra R, Bertoldo A, Facchiano F, Monaco S, Reynolds R, Calabrese M. Inflammatory intrathecal profiles and cortical damage in multiple sclerosis. Ann Neurol 2019. [PMID: 29518260 DOI: 10.1002/ana.25197] [Citation(s) in RCA: 196] [Impact Index Per Article: 39.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Gray matter (GM) damage and meningeal inflammation have been associated with early disease onset and a more aggressive disease course in multiple sclerosis (MS), but can these changes be identified in the patient early in the disease course? METHODS To identify possible biomarkers linking meningeal inflammation, GM damage, and disease severity, gene and protein expression were analyzed in meninges and cerebrospinal fluid (CSF) from 27 postmortem secondary progressive MS and 14 control cases. Combined cytokine/chemokine CSF profiling and 3T magnetic resonance imaging (MRI) were performed at diagnosis in 2 independent cohorts of MS patients (35 and 38 subjects) and in 26 non-MS patients. RESULTS Increased expression of proinflammatory cytokines (IFNγ, TNF, IL2, and IL22) and molecules related to sustained B-cell activity and lymphoid-neogenesis (CXCL13, CXCL10, LTα, IL6, and IL10) was detected in the meninges and CSF of postmortem MS cases with high levels of meningeal inflammation and GM demyelination. Similar proinflammatory patterns, including increased levels of CXCL13, TNF, IFNγ, CXCL12, IL6, IL8, and IL10, together with high levels of BAFF, APRIL, LIGHT, TWEAK, sTNFR1, sCD163, MMP2, and pentraxin III, were detected in the CSF of MS patients with higher levels of GM damage at diagnosis. INTERPRETATION A common pattern of intrathecal (meninges and CSF) inflammatory profile strongly correlates with increased cortical pathology, both at the time of diagnosis and at death. These results suggest a role for detailed CSF analysis combined with MRI as a prognostic marker for more aggressive MS. Ann Neurol 2018 Ann Neurol 2018;83:739-755.
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Affiliation(s)
- Roberta Magliozzi
- Neurology B, Department of Neurological and Movement Sciences, University of Verona, Verona, Italy.,Division of Brain Sciences, Department of Medicine, Imperial College London, London, United Kingdom
| | - Owain W Howell
- Institute of Life Sciences, Swansea University, Swansea, United Kingdom
| | - Richard Nicholas
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, United Kingdom
| | - Carolina Cruciani
- Neurology B, Department of Neurological and Movement Sciences, University of Verona, Verona, Italy.,Division of Brain Sciences, Department of Medicine, Imperial College London, London, United Kingdom
| | - Marco Castellaro
- Department of Information Engineering, University of Padua, Padua, Italy
| | | | - Stefania Rossi
- Neurology B, Department of Neurological and Movement Sciences, University of Verona, Verona, Italy.,Department of Oncology and Molecular Medicine, Higher Institute of Health Care, Rome, Italy
| | - Marco Pitteri
- Neurology B, Department of Neurological and Movement Sciences, University of Verona, Verona, Italy
| | - Maria Donata Benedetti
- Neurology B, Department of Neurological and Movement Sciences, University of Verona, Verona, Italy
| | - Alberto Gajofatto
- Neurology B, Department of Neurological and Movement Sciences, University of Verona, Verona, Italy
| | - Francesca B Pizzini
- Neuroradiology and Radiology Units, Department of Diagnostic and Pathology, University Hospital of Verona, Verona, Italy
| | - Stefania Montemezzi
- Neuroradiology and Radiology Units, Department of Diagnostic and Pathology, University Hospital of Verona, Verona, Italy
| | | | | | | | - Francesco Facchiano
- Department of Oncology and Molecular Medicine, Higher Institute of Health Care, Rome, Italy
| | - Salvatore Monaco
- Neurology B, Department of Neurological and Movement Sciences, University of Verona, Verona, Italy
| | - Richard Reynolds
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, United Kingdom
| | - Massimiliano Calabrese
- Neurology B, Department of Neurological and Movement Sciences, University of Verona, Verona, Italy
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28
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Brown JWL, Chowdhury A, Kanber B, Prados Carrasco F, Eshaghi A, Sudre CH, Pardini M, Samson RS, van de Pavert SHP, Wheeler-Kingshott CG, Chard DT. Magnetisation transfer ratio abnormalities in primary and secondary progressive multiple sclerosis. Mult Scler 2019; 26:679-687. [DOI: 10.1177/1352458519841810] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Background: In relapse-onset multiple sclerosis (MS), tissue abnormality – as assessed with magnetisation transfer ratio (MTR) imaging – is greater in the outer cortical and inner periventricular layers. The cause of this remains unknown but meningeal inflammation has been implicated, particularly lymphoid follicles, which are seen in secondary progressive (SP) but not primary progressive (PP) MS. Cortical and periventricular MTR gradients might, therefore, differ in PPMS and SPMS if these follicles are responsible. Objective: We assessed cortical and periventricular MTR gradients in PPMS, and compared gradients between people with PPMS and SPMS. Methods: Using an optimised processing pipeline, periventricular normal-appearing white matter and cortical grey-matter MTR gradients were compared between 51 healthy controls and 63 people with progressive MS (28 PPMS, 35 SPMS). Results: The periventricular gradient was significantly shallower in healthy controls (0.122 percentage units (pu)/band) compared to PPMS (0.952 pu/band, p < 0.0001) and SPMS (1.360 pu/band, p < 0.0001). The cortical gradient was also significantly shallower in healthy controls (−2.860 pu/band) compared to PPMS (−3.214 pu/band, p = 0.038) and SPMS (−3.328 pu/band, p = 0.016). Conclusion: Abnormal periventricular and cortical MTR gradients occur in both PPMS and SPMS, suggesting comparable underlying pathological processes.
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Affiliation(s)
- James William L Brown
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Azmain Chowdhury
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Baris Kanber
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, UK/National Institute for Health Research (NIHR) Biomedical Research Centre, University College London Hospitals (UCLH), London, UK/Department of Clinical and Experimental Epilepsy, UCL Queen Square
| | - Ferran Prados Carrasco
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, UK/eHealth Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Arman Eshaghi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Carole H Sudre
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, UK/Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK/School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Matteo Pardini
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Rebecca S Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Steven HP van de Pavert
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Claudia Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/Brain MRI 3T Mondino Research Center, IRCCS Mondino Foundation, Pavia, Italy/Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Declan T Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/National Institute for Health Research (NIHR) Biomedical Research Centre, University College London Hospitals (UCLH), London, UK
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29
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Magliozzi R, Reynolds R, Calabrese M. MRI of cortical lesions and its use in studying their role in MS pathogenesis and disease course. Brain Pathol 2019; 28:735-742. [PMID: 30020563 DOI: 10.1111/bpa.12642] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 06/21/2018] [Indexed: 02/01/2023] Open
Abstract
Cortical grey matter (GM) demyelination is present from the earliest stages of multiple sclerosis (MS) and is associated with physical deficits and cognitive impairment. In particular, the rate of disability progression in MS, both in the relapsing and progressive phases, appears to be strictly associated with degenerative GM demyelination and diffuse cortical atrophy. In the last decade, several histopathological studies and advanced radiological methodologies have contributed to better identify the exact involvement/load of cortical pathology in MS, even if the specific inflammatory features and the precise cell and molecular mechanisms of GM demyelination and neurodegeneration in MS remain still not fully understood. It has been proposed that a combined neuropathology, imaging and molecular approach may help to define a more detailed characterization and precise assessment of the heterogeneous features of GM injury and inflammation in MS. This, in turn, will possibly identify specific imaging and biohumoral (cerebrospinal fluid/serum) correlates of cortical pathology that may have an important role in predicting and monitor the disease evolution.
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Affiliation(s)
- R Magliozzi
- Neurology B, Department of Neurological and Movement Sciences, University of Verona, Verona, Italy.,Division of Brain Sciences, Department of Medicine, Imperial College London, London, United Kingdom
| | - R Reynolds
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, United Kingdom
| | - M Calabrese
- Neurology B, Department of Neurological and Movement Sciences, University of Verona, Verona, Italy
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30
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Hametner S, Dal Bianco A, Trattnig S, Lassmann H. Iron related changes in MS lesions and their validity to characterize MS lesion types and dynamics with Ultra-high field magnetic resonance imaging. Brain Pathol 2019; 28:743-749. [PMID: 30020556 PMCID: PMC8028547 DOI: 10.1111/bpa.12643] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 06/12/2018] [Indexed: 12/31/2022] Open
Abstract
Iron accumulates with age in the normal human brain. This process is altered at several levels in the brain of multiple sclerosis (MS) patients. Since iron is mainly stored in oligodendrocytes and myelin in the normal brain, its liberation in demyelinating lesions may amplify tissue damage in demyelinating lesions and its uptake in macrophages and microglia may help to more precisely define activity stages of the lesions. In addition, glia cells change their iron import, export and storage properties in MS lesions, which is reflected by alterations in the expression of iron transport molecules. Changes of iron distribution in the brain can be reliably detected by MRI, particularly upon application of Ultra‐high magnetic field (7 Tesla). Iron‐sensitive MRI allows to more accurately distinguish the lesions in MS from those in other inflammatory brain diseases, to visualize a subset of slowly expanding lesions in the progressive stage of MS and to increase the sensitivity for lesion detection in the gray matter, such as the cerebral cortex or deep gray matter nuclei.
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Affiliation(s)
- Simon Hametner
- Center for Brain Research, Medical University of Vienna, Austria.,Institute of Neuropathology, University of Göttingen, Germany
| | - Assunta Dal Bianco
- Center for Brain Research, Medical University of Vienna, Austria.,Department of Neurology, Medical University of Vienna, Austria
| | - Siegfried Trattnig
- Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Center, Medical University of Vienna, Austria
| | - Hans Lassmann
- Center for Brain Research, Medical University of Vienna, Austria
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31
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Schmierer K, Miquel ME. Magnetic resonance imaging correlates of neuro-axonal pathology in the MS spinal cord. Brain Pathol 2019; 28:765-772. [PMID: 30375114 DOI: 10.1111/bpa.12648] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 07/18/2018] [Indexed: 12/21/2022] Open
Abstract
In people with multiple sclerosis (MS), the spinal cord is the structure most commonly affected by clinically detectable pathology at presentation, and a key part of the central nervous system involved in chronic disease deterioration. Indices, such as the spinal cord cross-sectional area at the level C2 have been developed as tools to predict future disability, and-by inference-axonal loss. However, this and other histo-pathological correlates of spinal cord magnetic resonance imaging (MRI) changes in MS remain incompletely understood. In recent years, there has been a surge of interest in developing quantitative MRI tools to measure specific tissue features, including axonal density, myelin content, neurite density, and orientation, among others, with an emphasis on the spinal cord. Quantitative MRI techniques including T1 and T2 , magnetization transfer and a number of diffusion-derived indices have all been applied to MS spinal cord. Particularly diffusion-based MRI techniques combined with microscopic resolution achievable using high magnetic field scanners enable a new level of anatomical detail and quantification of indices that are clinically meaningful.
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Affiliation(s)
- Klaus Schmierer
- Queen Mary University of London, Barts and The London School of Medicine & Dentistry, Blizard Institute (Neuroscience), London, UK.,Barts Health NHS Trust, Clinical Board Medicine (Neuroscience), The Royal London Hospital, London, UK
| | - Marc E Miquel
- Barts Health NHS Trust, Clinical Physics, London, UK
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32
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Filippi M, Brück W, Chard D, Fazekas F, Geurts JJG, Enzinger C, Hametner S, Kuhlmann T, Preziosa P, Rovira À, Schmierer K, Stadelmann C, Rocca MA. Association between pathological and MRI findings in multiple sclerosis. Lancet Neurol 2019; 18:198-210. [DOI: 10.1016/s1474-4422(18)30451-4] [Citation(s) in RCA: 87] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 10/22/2018] [Accepted: 11/12/2018] [Indexed: 12/12/2022]
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33
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Lassmann H. Pathogenic Mechanisms Associated With Different Clinical Courses of Multiple Sclerosis. Front Immunol 2019; 9:3116. [PMID: 30687321 PMCID: PMC6335289 DOI: 10.3389/fimmu.2018.03116] [Citation(s) in RCA: 364] [Impact Index Per Article: 72.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Accepted: 12/17/2018] [Indexed: 01/02/2023] Open
Abstract
In the majority of patients multiple sclerosis starts with a relapsing remitting course (RRMS), which may at later times transform into secondary progressive disease (SPMS). In a minority of patients the relapsing remitting disease is skipped and the patients show progression from the onset (primary progressive MS, PPMS). Evidence obtained so far indicate major differences between RRMS and progressive MS, but no essential differences between SPMS and PPMS, with the exception of a lower incidence in the global load of focal white matter lesions and in particular in the presence of classical active plaques in PPMS. We suggest that in MS patients two types of inflammation occur, which develop in parallel but partially independent from each other. The first is the focal bulk invasion of T- and B-lymphocytes with profound blood brain barrier leakage, which predominately affects the white matter, and which gives rise to classical active demyelinated plaques. The other type of inflammation is a slow accumulation of T-cells and B-cells in the absence of major blood brain barrier damage in the connective tissue spaces of the brain, such as the meninges and the large perivascular Virchow Robin spaces, where they may form aggregates or in most severe cases structures in part resembling tertiary lymph follicles. This type of inflammation is associated with the formation of subpial demyelinated lesions in the cerebral and cerebellar cortex, with slow expansion of pre-existing lesions in the white matter and with diffuse neurodegeneration in the normal appearing white or gray matter. The first type of inflammation dominates in acute and relapsing MS. The second type of inflammation is already present in early stages of MS, but gradually increases with disease duration and patient age. It is suggested that CD8+ T-lymphocytes remain in the brain and spinal cord as tissue resident cells, which may focally propagate neuroinflammation, when they re-encounter their cognate antigen. B-lymphocytes may propagate demyelination and neurodegeneration, most likely by producing soluble neurotoxic factors. Whether lymphocytes within the brain tissue of MS lesions have also regulatory functions is presently unknown. Key open questions in MS research are the identification of the target antigen recognized by tissue resident CD8+ T-cells and B-cells and the molecular nature of the soluble inflammatory mediators, which may trigger tissue damage.
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Affiliation(s)
- Hans Lassmann
- Center for Brain Research, Medical University of Vienna, Vienna, Austria
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34
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Dusek P, Madai VI, Huelnhagen T, Bahn E, Matej R, Sobesky J, Niendorf T, Acosta-Cabronero J, Wuerfel J. The choice of embedding media affects image quality, tissue R 2 * , and susceptibility behaviors in post-mortem brain MR microscopy at 7.0T. Magn Reson Med 2018; 81:2688-2701. [PMID: 30506939 DOI: 10.1002/mrm.27595] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 09/19/2018] [Accepted: 10/14/2018] [Indexed: 12/22/2022]
Abstract
PURPOSE The quality and precision of post-mortem MRI microscopy may vary depending on the embedding medium used. To investigate this, our study evaluated the impact of 5 widely used media on: (1) image quality, (2) contrast of high spatial resolution gradient-echo (T1 and T2 * -weighted) MR images, (3) effective transverse relaxation rate (R2 * ), and (4) quantitative susceptibility measurements (QSM) of post-mortem brain specimens. METHODS Five formaldehyde-fixed brain slices were scanned using 7.0T MRI in: (1) formaldehyde solution (formalin), (2) phosphate-buffered saline (PBS), (3) deuterium oxide (D2 O), (4) perfluoropolyether (Galden), and (5) agarose gel. SNR and contrast-to-noise ratii (SNR/CNR) were calculated for cortex/white matter (WM) and basal ganglia/WM regions. In addition, median R2 * and QSM values were extracted from caudate nucleus, putamen, globus pallidus, WM, and cortical regions. RESULTS PBS, Galden, and agarose returned higher SNR/CNR compared to formalin and D2 O. Formalin fixation, and its use as embedding medium for scanning, increased tissue R2 * . Imaging with agarose, D2 O, and Galden returned lower R2 * values than PBS (and formalin). No major QSM offsets were observed, although spatial variance was increased (with respect to R2 * behaviors) for formalin and agarose. CONCLUSIONS Embedding media affect gradient-echo image quality, R2 * , and QSM in differing ways. In this study, PBS embedding was identified as the most stable experimental setup, although by a small margin. Agarose and Galden were preferred to formalin or D2 O embedding. Formalin significantly increased R2 * causing noisier data and increased QSM variance.
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Affiliation(s)
- Petr Dusek
- Department of Neurology, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Praha, Czech Republic.,Department of Radiology, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Praha, Czech Republic
| | - Vince Istvan Madai
- Department of Neurology and Center for Stroke Research Berlin (CSB), Charité-Universitaetsmedizin, Berlin, Germany
| | - Till Huelnhagen
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Erik Bahn
- Institute of Neuropathology, University Medicine Göttingen, Göttingen, Germany
| | - Radoslav Matej
- Department of Pathology and Molecular Medicine, Thomayer Hospital, Praha, Czech Republic.,Department of Pathology, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Praha, Czech Republic
| | - Jan Sobesky
- Department of Neurology and Center for Stroke Research Berlin (CSB), Charité-Universitaetsmedizin, Berlin, Germany.,Experimental and Clinical Research Center (ECRC), Charité-Universitaetsmedizin and Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.,Experimental and Clinical Research Center (ECRC), Charité-Universitaetsmedizin and Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, United Kingdom.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Jens Wuerfel
- NeuroCure Clinical Research Center, Charité-Universitaetsmedizin, Berlin, Germany.,Medical Imaging Analysis Center AG, Basel, Switzerland.,Department of Biomedical Engineering, University Basel, Switzerland
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Megna R, Alfano B, Lanzillo R, Costabile T, Comerci M, Vacca G, Carotenuto A, Moccia M, Servillo G, Prinster A, Brescia Morra V, Quarantelli M. Brain tissue volumes and relaxation rates in multiple sclerosis: implications for cognitive impairment. J Neurol 2018; 266:361-368. [PMID: 30498912 DOI: 10.1007/s00415-018-9139-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Revised: 11/07/2018] [Accepted: 11/22/2018] [Indexed: 12/19/2022]
Abstract
OBJECTIVE Both normal gray matter atrophy and brain tissue relaxation rates, in addition to total lesion volume, have shown significant correlations with cognitive test scores in multiple sclerosis (MS). Aim of the study was to assess the relative contributions of macro- and microstructural changes of both normal and abnormal brain tissues, probed, respectively, by their volumes and relaxation rates, to the cognitive status and physical disability of MS patients. METHODS MRI studies from 241 patients with relapsing-remitting MS were retrospectively analyzed by fully automated multiparametric relaxometric segmentation. Ordinal backward regression analysis was applied to the resulting volumes and relaxation rates of both normal (gray matter, normal-appearing white matter and CSF) and abnormal (T2-weighted lesions) brain tissues, controlling for age, sex and disease duration, to identify the main independent contributors to the cognitive status, as measured by the percentage of failed tests at a cognitive test battery (Rao's Brief Repeatable Battery and Stroop test, available in 186 patients), and to the physical disability, as assessed by the Expanded Disability Status Scale (EDSS). RESULTS The R1 relaxation rate (a putative marker of tissue disruption) of the MS lesions appeared the single most significant contributor to cognitive impairment (p < 0.001). On the contrary, the EDSS appeared mainly affected by the decrease in R2 of the gray matter (p < 0.0001), (possibly influenced by cortical plaques, edema and inflammation). CONCLUSIONS In RR-MS the tissue damage in white matter lesions appears the single main determinant of the cognitive status of patients, likely through disconnection phenomena, while the physical disability appears related to the involvement of gray matter.
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Affiliation(s)
- Rosario Megna
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy
| | - Bruno Alfano
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy
| | - Roberta Lanzillo
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Teresa Costabile
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Marco Comerci
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy
| | - Giovanni Vacca
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Antonio Carotenuto
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Marcello Moccia
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Giuseppe Servillo
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Anna Prinster
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy
| | - Vincenzo Brescia Morra
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Mario Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy.
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Abstract
This chapter provides a brief overview of studies that combine postmortem magnetic resonance imaging (MRI) and histopathology. We touch upon the logistics of setting up a protocol that limits unwanted postmortem delays and explain how combining postmortem MRI and histopathology can elucidate the histologic substrate of signal changes that appear on MRI. This is demonstrated by exemplary studies in multiple sclerosis, and includes various histopathologic techniques and a wide range of conventional and advanced MRI sequences at various field strengths. We cover topics such as how to visualize white-matter pathology and repair with conventional and advanced MRI sequences, describe the history of visualizing pathology of the gray matter (with newly developed MRI and immunohistopathology techniques), and how advanced methods have aided research in other neurologic diseases. We conclude with several suggestions for future development, such as bridging the gap between postmortem and in vivo research and the importance of collecting non-neurological control tissue.
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Affiliation(s)
- Laura E Jonkman
- Department of Anatomy and Neurosciences, VU Medical Center, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, VU Medical Center, Amsterdam, The Netherlands.
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37
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Heath F, Hurley SA, Johansen-Berg H, Sampaio-Baptista C. Advances in noninvasive myelin imaging. Dev Neurobiol 2017; 78:136-151. [PMID: 29082667 PMCID: PMC5813152 DOI: 10.1002/dneu.22552] [Citation(s) in RCA: 88] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Revised: 09/18/2017] [Accepted: 10/24/2017] [Indexed: 12/11/2022]
Abstract
Myelin is important for the normal development and healthy function of the nervous system. Recent developments in MRI acquisition and tissue modeling aim to provide a better characterization and more specific markers for myelin. This allows for specific monitoring of myelination longitudinally and noninvasively in the healthy brain as well as assessment of treatment and intervention efficacy. Here, we offer a nontechnical review of MRI techniques developed to specifically monitor myelin such as magnetization transfer (MT) and myelin water imaging (MWI). We further summarize recent studies that employ these methods to measure myelin in relation to development and aging, learning and experience, and neuropathology and psychiatric disorders. © 2017 The Authors. Developmental Neurobiology Published by Wiley Periodicals, Inc. Develop Neurobiol 78: 136–151, 2018
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Affiliation(s)
- Florence Heath
- Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Samuel A Hurley
- Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, United Kingdom.,Departments of Neuroscience and Radiology, 1111 Highland Ave, University of Wisconsin - Madison, Madison, Wisconsin, 53705
| | - Heidi Johansen-Berg
- Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Cassandra Sampaio-Baptista
- Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, United Kingdom
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38
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Nakamura K, Chen JT, Ontaneda D, Fox RJ, Trapp BD. T1-/T2-weighted ratio differs in demyelinated cortex in multiple sclerosis. Ann Neurol 2017; 82:635-639. [PMID: 28833377 DOI: 10.1002/ana.25019] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Revised: 08/02/2017] [Accepted: 08/02/2017] [Indexed: 01/04/2023]
Abstract
Detecting cortical demyelination in patients with multiple sclerosis (MS) is difficult. Using magnetic resonance imaging (MRI), ratio maps of T1-weighted (T1w) and T2-weighted (T2w) images may be sensitive to cortical myelin levels. In this MRI-histological study, postmortem in situ scans were acquired from 6 cadavers with MS on a 3T MRI machine. Immunocytochemistry was used to correlate myelin status and cortical T1w/T2w measures. The results showed that the T1w/T2w values significantly differed between demyelinated and myelinated cortex (p < 0.001). The T1w/T2w ratio maps may be a relatively simple, clinically feasible method to assess cortical demyelination. Ann Neurol 2017;82:635-639.
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Affiliation(s)
- Kunio Nakamura
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic
| | - Jacqueline T Chen
- Department of Neuroscience, Lerner Research Institute, Cleveland Clinic
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis Treatment and Research, Cleveland Clinic, Cleveland, OH
| | - Robert J Fox
- Mellen Center for Multiple Sclerosis Treatment and Research, Cleveland Clinic, Cleveland, OH
| | - Bruce D Trapp
- Department of Neuroscience, Lerner Research Institute, Cleveland Clinic
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39
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Nantes JC, Proulx S, Zhong J, Holmes SA, Narayanan S, Brown RA, Hoge RD, Koski L. GABA and glutamate levels correlate with MTR and clinical disability: Insights from multiple sclerosis. Neuroimage 2017; 157:705-715. [DOI: 10.1016/j.neuroimage.2017.01.033] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 01/12/2017] [Accepted: 01/15/2017] [Indexed: 01/04/2023] Open
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40
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Carassiti D, Altmann DR, Petrova N, Pakkenberg B, Scaravilli F, Schmierer K. Neuronal loss, demyelination and volume change in the multiple sclerosis neocortex. Neuropathol Appl Neurobiol 2017; 44:377-390. [DOI: 10.1111/nan.12405] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Revised: 04/11/2017] [Accepted: 04/18/2017] [Indexed: 12/20/2022]
Affiliation(s)
- D. Carassiti
- Blizard Institute (Neuroscience); Queen Mary University of London; London UK
| | - D. R. Altmann
- Department of Medical Statistics; London School of Hygiene and Tropical Medicine; London UK
| | - N. Petrova
- Blizard Institute (Neuroscience); Queen Mary University of London; London UK
| | - B. Pakkenberg
- Research Laboratory for Stereology and Neuroscience; Bispebjerg University Hospital; Copenhagen Denmark
| | - F. Scaravilli
- Blizard Institute (Neuroscience); Queen Mary University of London; London UK
| | - K. Schmierer
- Blizard Institute (Neuroscience); Queen Mary University of London; London UK
- Neurosciences Clinical Academic Group; The Royal London Hospital; Barts Health NHS Trust; London UK
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42
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Schindler MK, Sati P, Reich DS. Insights from Ultrahigh Field Imaging in Multiple Sclerosis. Neuroimaging Clin N Am 2017; 27:357-366. [PMID: 28391792 DOI: 10.1016/j.nic.2016.12.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Ultrahigh-field (≥7 T) magnetic resonance (MR) imaging is being used at many leading academic medical centers to study neurologic disorders. The improved spatial resolution and anatomic detail are due to the increase in signal-to-noise and contrast-to-noise ratio at higher magnetic field strengths. Ultrahigh-field MR imaging improves multiple sclerosis (MS) lesion detection, with particular sensitivity to detect cortical lesions. The increase in magnetic susceptibility effects inherent to ultrahigh field can be used to detect pathologic features of MS lesions, including a central vein, potentially useful for diagnostic considerations, and heterogeneity among MS lesions, potentially useful in determining lesion outcomes.
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Affiliation(s)
- Matthew K Schindler
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Medical Center Boulevard, 10 Center Drive, MSC 1400, Bethesda, MD 20892, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Medical Center Boulevard, 10 Center Drive, MSC 1400, Bethesda, MD 20892, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Medical Center Boulevard, 10 Center Drive, MSC 1400, Bethesda, MD 20892, USA.
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43
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Retooling Laser Speckle Contrast Analysis Algorithm to Enhance Non-Invasive High Resolution Laser Speckle Functional Imaging of Cutaneous Microcirculation. Sci Rep 2017; 7:41048. [PMID: 28106129 PMCID: PMC5247692 DOI: 10.1038/srep41048] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Accepted: 12/15/2016] [Indexed: 12/30/2022] Open
Abstract
Cutaneous microvasculopathy complicates wound healing. Functional assessment of gated individual dermal microvessels is therefore of outstanding interest. Functional performance of laser speckle contrast imaging (LSCI) systems is compromised by motion artefacts. To address such weakness, post-processing of stacked images is reported. We report the first post-processing of binary raw data from a high-resolution LSCI camera. Sharp images of low-flowing microvessels were enabled by introducing inverse variance in conjunction with speckle contrast in Matlab-based program code. Extended moving window averaging enhanced signal-to-noise ratio. Functional quantitative study of blood flow kinetics was performed on single gated microvessels using a free hand tool. Based on detection of flow in low-flow microvessels, a new sharp contrast image was derived. Thus, this work presents the first distinct image with quantitative microperfusion data from gated human foot microvasculature. This versatile platform is applicable to study a wide range of tissue systems including fine vascular network in murine brain without craniotomy as well as that in the murine dorsal skin. Importantly, the algorithm reported herein is hardware agnostic and is capable of post-processing binary raw data from any camera source to improve the sensitivity of functional flow data above and beyond standard limits of the optical system.
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44
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Caporale A, Palombo M, Macaluso E, Guerreri M, Bozzali M, Capuani S. The γ-parameter of anomalous diffusion quantified in human brain by MRI depends on local magnetic susceptibility differences. Neuroimage 2016; 147:619-631. [PMID: 28011255 DOI: 10.1016/j.neuroimage.2016.12.051] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2016] [Revised: 11/22/2016] [Accepted: 12/19/2016] [Indexed: 12/15/2022] Open
Abstract
Motivated by previous results obtained in vitro, we investigated the dependence of the anomalous diffusion (AD) MRI technique on local magnetic susceptibility differences (Δχ) driven by magnetic field inhomogeneity in human brains. The AD-imaging contrast investigated here is quantified by the stretched-exponential parameter γ, extracted from diffusion weighted (DW) data collected by varying diffusion gradient strengths. We performed T2* and DW experiments in eight healthy subjects at 3.0T. T2*-weighted images at different TEs=(10,20,35,55)ms and DW-EPI images with fourteen b-values from 0 to 5000s/mm2 were acquired. AD-metrics and Diffusion Tensor Imaging (DTI) parameters were compared and correlated to R2* and to Δχ values taken from literature for the gray (GM) and the white (WM) matter. Pearson's correlation test and Analysis of Variance with Bonferroni post-hoc test were used. Significant strong linear correlations were found between AD γ-metrics and R2* in both GM and WM of the human brain, but not between DTI-metrics and R2*. Depending on Δχ driven magnetic field inhomogeneity, the new contrast provided by AD-γ imaging reflects Δχ due to differences in myelin orientation and iron content within selected regions in the WM and GM, respectively. This feature of the AD-γ imaging due to the fact that γ is quantified by using MRI, may be an alternative strategy to investigate, at high magnetic fields, microstructural changes in myelin, and alterations due to iron accumulation. Possible clinical applications might be in the field of neurodegenerative diseases.
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Affiliation(s)
- A Caporale
- Morpho-functional Sciences, Department of Anatomical, Histological, Forensic and of the Locomotor System Science, Sapienza University of Rome, Italy; CNR ISC UOS Roma Sapienza, Physics Department Sapienza University of Rome, Rome, Italy.
| | - M Palombo
- CNR ISC UOS Roma Sapienza, Physics Department Sapienza University of Rome, Rome, Italy; MIRCen, CEA/DSV/I(2)BM, Fontenay-aux-Roses, France
| | - E Macaluso
- ImpAct Team, Lyon Neuroscience Research Center, Lyon, France
| | - M Guerreri
- CNR ISC UOS Roma Sapienza, Physics Department Sapienza University of Rome, Rome, Italy; Morphogenesis & Tissue Engineering, Department of Anatomical, Histological, Forensic and of the Locomotor System Science, Sapienza University of Rome, Italy
| | - M Bozzali
- Neuroimaging Laboratory Santa Lucia Foundation, Rome, Italy
| | - S Capuani
- CNR ISC UOS Roma Sapienza, Physics Department Sapienza University of Rome, Rome, Italy
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45
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Tsintou M, Dalamagkas K, Makris N. Advancing research in regeneration and repair of the motor circuitry: non-human primate models and imaging scales as the missing links for successfully translating injectable therapeutics to the clinic. ACTA ACUST UNITED AC 2016; 3. [PMID: 29600289 DOI: 10.23937/2469-570x/1410042] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Regeneration and repair is the ultimate goal of therapeutics in trauma of the central nervous system (CNS). Stroke and spinal cord injury (SCI) are two highly prevalent CNS disorders that remain incurable, despite numerous research studies and the clinical need for effective treatments. Neural engineering is a diverse biomedical field, that addresses these diseases using new approaches. Research in the field involves principally rodent models and biologically active, biodegradable hydrogels. Promising results have been reported in preclinical studies of CNS repair, demonstrating the great potential for the development of new treatments for the brain, spinal cord and peripheral nerve injury. Several obstacles stand in the way of clinical translation of neuroregeneration research. There seems to be a key gap in the translation of research from rodent models to human applications, namely non-human primate models, which constitute a critical bridging step. Applying injectable therapeutics and multimodal neuroimaging in stroke lesions using experimental rhesus monkey models is an avenue that a few research groups have begun to embark on. Understanding and assessing the changes that the injured brain or spinal cord undergoes after an intervention with biodegradable hydrogels in non-human primates seem to represent critical preclinical research steps. Existing innovative models in non-human primates allow us to evaluate the potential of neural engineering and injectable hydrogels. The results of these preliminary studies will pave the way for translating this research into much needed clinical therapeutic approaches. Cutting edge imaging technology using Connectome scanners represents a tremendous advancement, enabling the in vivo, detailed, high-resolution evaluation of these therapeutic interventions in experimental animals. Most importantly, they also allow quantifiable and clinically meaningful correlations with humans, increasing the translatability of these innovations to the bedside.
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Affiliation(s)
- Magdalini Tsintou
- Psychiatry Neuroimaging Laboratory, Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115.,Center for Neural Systems Investigations, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129
| | - Kyriakos Dalamagkas
- Psychiatry Neuroimaging Laboratory, Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115
| | - Nikos Makris
- Psychiatry Neuroimaging Laboratory, Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115.,Center for Neural Systems Investigations, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129.,Center for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129
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46
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Lee JH, Baek SY, Song Y, Lim S, Lee H, Nguyen MP, Kim EJ, Huh GY, Chun SY, Cho H. The Neuromelanin-related T2* Contrast in Postmortem Human Substantia Nigra with 7T MRI. Sci Rep 2016; 6:32647. [PMID: 27596274 PMCID: PMC5011647 DOI: 10.1038/srep32647] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2016] [Accepted: 08/12/2016] [Indexed: 11/11/2022] Open
Abstract
High field magnetic resonance imaging (MRI)-based delineation of the substantia nigra (SN) and visualization of its inner cellular organization are promising methods for the evaluation of morphological changes associated with neurodegenerative diseases; however, corresponding MR contrasts must be matched and validated with quantitative histological information. Slices from two postmortem SN samples were imaged with a 7 Tesla (7T) MRI with T1 and T2* imaging protocols and then stained with Perl’s Prussian blue, Kluver-Barrera, tyrosine hydroxylase, and calbindin immunohistochemistry in a serial manner. The association between T2* values and quantitative histology was investigated with a co-registration method that accounts for histology slice preparation. The ventral T2* hypointense layers between the SNr and the crus cerebri extended anteriorly to the posterior part of the crus cerebri, which demonstrates the difficulty with an MRI-based delineation of the SN. We found that the paramagnetic hypointense areas within the dorsolateral SN corresponded to clusters of neuromelanin (NM). These NM-rich zones were distinct from the hypointense ventromedial regions with high iron pigments. Nigral T2* imaging at 7T can reflect the density of NM-containing neurons as the metal-bound NM macromolecules may decrease T2* values and cause hypointense signalling in T2* imaging at 7T.
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Affiliation(s)
- Jae-Hyeok Lee
- Department of Neurology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, South Korea
| | - Sun-Yong Baek
- Department of Anatomy, Pusan National University School of Medicine, Yangsan, South Korea
| | - YoungKyu Song
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Sujeong Lim
- 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
| | - Minh Phuong Nguyen
- School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Eun-Joo Kim
- Department of Neurology, Pusan National University Hospital, Busan, South Korea
| | - Gi Yeong Huh
- Department of Forensic Medicine, Pusan National University School of Medicine, Yangsan, South Korea
| | - Se Young Chun
- School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - HyungJoon Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
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47
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Steenwijk MD, Vrenken H, Jonkman LE, Daams M, Geurts JJG, Barkhof F, Pouwels PJW. High-resolution T1-relaxation time mapping displays subtle, clinically relevant, gray matter damage in long-standing multiple sclerosis. Mult Scler 2016; 22:1279-88. [DOI: 10.1177/1352458515615953] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Accepted: 10/14/2015] [Indexed: 01/02/2023]
Abstract
Background: Gray matter (GM) pathology has high clinical relevance in multiple sclerosis (MS), but conventional magnetic resonance imaging (MRI) is insufficiently sensitive to visualize the rather subtle damage. Objective: To investigate whether high spatial resolution T1-relaxation time (T1-RT) measurements can detect changes in the normal-appearing GM of patients with long-standing MS and whether these changes are associated with physical and cognitive impairment. Methods: High spatial resolution (1.05 × 1.05 × 1.2 mm3) T1-RT measurements were performed at 3 T in 156 long-standing MS patients and 54 healthy controls. T1-RT histogram parameters in several regions were analyzed to investigate group differences. Stepwise linear regression analyses were used to assess the relation of T1-RT with physical and cognitive impairment. Results: In both thalamus and cortex, T1-RT histogram skewness was higher in patients than controls. In the cortex, this was driven by the frontal and temporal lobes. No differences were found in other GM histogram parameters. Cortical skewness, thalamus volume, and average white matter (WM) lesion T1-RT emerged as the strongest predictors for cognitive performance (adjusted R2 = 0.39). Conclusion: Subtle GM damage was present in the cortex and thalamus of MS patients, as indicated by increased T1-RT skewness. Increased cortical skewness emerged as an independent predictor of cognitive dysfunction.
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Affiliation(s)
- Martijn D Steenwijk
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands/Department of Physics and Medical Technology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands/Department of Physics and Medical Technology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Marita Daams
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands/Department of Anatomy and Neurosciences, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Jeroen JG Geurts
- Department of Anatomy and Neurosciences, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Petra JW Pouwels
- Department of Physics and Medical Technology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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48
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Zhong J, Nantes JC, Holmes SA, Gallant S, Narayanan S, Koski L. Abnormal functional connectivity and cortical integrity influence dominant hand motor disability in multiple sclerosis: a multimodal analysis. Hum Brain Mapp 2016; 37:4262-4275. [PMID: 27381089 DOI: 10.1002/hbm.23307] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Revised: 05/23/2016] [Accepted: 06/22/2016] [Indexed: 01/04/2023] Open
Abstract
Functional reorganization and structural damage occur in the brains of people with multiple sclerosis (MS) throughout the disease course. However, the relationship between resting-state functional connectivity (FC) reorganization in the sensorimotor network and motor disability in MS is not well understood. This study used resting-state fMRI, T1-weighted and T2-weighted, and magnetization transfer (MT) imaging to investigate the relationship between abnormal FC in the sensorimotor network and upper limb motor disability in people with MS, as well as the impact of disease-related structural abnormalities within this network. Specifically, the differences in FC of the left hemisphere hand motor region between MS participants with preserved (n = 17) and impaired (n = 26) right hand function, compared with healthy controls (n = 20) was investigated. Differences in brain atrophy and MT ratio measured at the global and regional levels were also investigated between the three groups. Motor preserved MS participants had stronger FC in structurally intact visual information processing regions relative to motor impaired MS participants. Motor impaired MS participants showed weaker FC in the sensorimotor and somatosensory association cortices and more severe structural damage throughout the brain compared with the other groups. Logistic regression analysis showed that regional MTR predicted motor disability beyond the impact of global atrophy whereas regional grey matter volume did not. More importantly, as the first multimodal analysis combining resting-state fMRI, T1-weighted, T2-weighted and MTR images in MS, we demonstrate how a combination of structural and functional changes may contribute to motor impairment or preservation in MS. Hum Brain Mapp 37:4262-4275, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Jidan Zhong
- Research Institute of the McGill University Health Centre, 2155 Guy Street, 5th Floor, Montreal, Quebec, H3H 2R9, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, H3H 2R9, Canada
| | - Julia C Nantes
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, H3H 2R9, Canada.,Integrated Program in Neuroscience, McGill University, 3801 University Street, Room 141, Montreal, Quebec, H3A 2B4, Canada
| | - Scott A Holmes
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, H3H 2R9, Canada.,Integrated Program in Neuroscience, McGill University, 3801 University Street, Room 141, Montreal, Quebec, H3A 2B4, Canada
| | - Serge Gallant
- Research Institute of the McGill University Health Centre, 2155 Guy Street, 5th Floor, Montreal, Quebec, H3H 2R9, Canada
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3H 2R9, Canada
| | - Lisa Koski
- Research Institute of the McGill University Health Centre, 2155 Guy Street, 5th Floor, Montreal, Quebec, H3H 2R9, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, H3H 2R9, Canada.,Department of Psychology, McGill University, Montreal, Quebec, H3H 2R9, Canada
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49
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Reeves C, Tachrount M, Thomas D, Michalak Z, Liu J, Ellis M, Diehl B, Miserocchi A, McEvoy AW, Eriksson S, Yousry T, Thom M. Combined Ex Vivo 9.4T MRI and Quantitative Histopathological Study in Normal and Pathological Neocortical Resections in Focal Epilepsy. Brain Pathol 2016; 26:319-33. [PMID: 26268959 PMCID: PMC4950048 DOI: 10.1111/bpa.12298] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2015] [Accepted: 08/07/2015] [Indexed: 01/04/2023] Open
Abstract
High-resolution magnetic resonance imaging (MRI) may improve the preoperative diagnosis of focal cortical dysplasia (FCD) in epilepsy. Quantitative 9.4T MRI was carried out (T1, T2, T2* and magnetization transfer ratio) on 13 cortical resections, representing pathologically confirmed FCD (five cases) and normal cortex. Quantitative immunohistochemistry for myelination (myelin basic protein/SMI94), neuronal populations [microtubule-associated protein 2 (MAP2), neurofilament (SMI31, SMI32), synaptophysin, NeuN, calbindin], reactive glia (GFAP), microglia (CD68) and blood-brain barrier permeability (albumin) was carried out in 43 regions of interest (ROI) from normal and abnormal white matter and cortex. MRI was spatially aligned and quantitative analysis carried out on corresponding ROI. Line profile analysis (LPA) of intensity gradients through the cortex was carried out on MRI and immunostained sections. An inverse correlation was noted between myelin/SMI94 and T1, T2 (P < 0.005) and T2* (P < 0.05; Spearman's correlation) and a positive correlation between neuronal MAP2 and T1 (P < 0.005) and T2* (P < 0.05) over all ROI. Similar pathology-MRI correlations were observed for histologically unremarkable white matter ROI only. LPA showed altered gradient contours in regions of FCD, reflecting abnormal cortical lamination and myelo-architecture, including a preoperatively undetected FCD case. This study demonstrates the ability of quantitative 9.4T MRI to detect subtle differences in neuronal numbers and myelination in histologically normal appearing white matter and LPA in the evaluation of cortical dyslamination. These methods may be translatable to the in vivo detection of mild cortical malformations.
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Affiliation(s)
- Cheryl Reeves
- Department of NeuropathologyUCL, Institute of NeurologyLondonUK
- Department of Clinical and Experimental EpilepsyUCL, Institute of NeurologyLondonUK
| | - Mohamed Tachrount
- Department of NeuroradiologyUCL, Institute of NeurologyLondonUK
- Department of Brain Repair and RehabilitationUCL, Institute of NeurologyLondonUK
| | - David Thomas
- Department of Brain Repair and RehabilitationUCL, Institute of NeurologyLondonUK
| | - Zuzanna Michalak
- Department of NeuropathologyUCL, Institute of NeurologyLondonUK
- Department of Clinical and Experimental EpilepsyUCL, Institute of NeurologyLondonUK
| | - Joan Liu
- Department of NeuropathologyUCL, Institute of NeurologyLondonUK
- Department of Clinical and Experimental EpilepsyUCL, Institute of NeurologyLondonUK
| | - Matthew Ellis
- Department of NeuropathologyUCL, Institute of NeurologyLondonUK
| | - Beate Diehl
- Department of Clinical and Experimental EpilepsyUCL, Institute of NeurologyLondonUK
| | - Anna Miserocchi
- Department of NeurosurgeryUCL, Institute of NeurologyLondonUK
| | - Andrew W. McEvoy
- Department of Clinical and Experimental EpilepsyUCL, Institute of NeurologyLondonUK
- Department of NeurosurgeryUCL, Institute of NeurologyLondonUK
| | - Sofia Eriksson
- Department of Clinical and Experimental EpilepsyUCL, Institute of NeurologyLondonUK
| | - Tarek Yousry
- Department of NeuroradiologyUCL, Institute of NeurologyLondonUK
- Department of Brain Repair and RehabilitationUCL, Institute of NeurologyLondonUK
| | - Maria Thom
- Department of NeuropathologyUCL, Institute of NeurologyLondonUK
- Department of Clinical and Experimental EpilepsyUCL, Institute of NeurologyLondonUK
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50
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Abstract
Over the past few decades, MRI-based visualization of demyelinated CNS lesions has become pivotal to the diagnosis and monitoring of multiple sclerosis (MS). In this Review, we outline current efforts to correlate imaging findings with the pathology of lesion development in MS, and the pitfalls that are being encountered in this research. Multimodal imaging at high and ultra-high magnetic field strengths is yielding biologically relevant insights into the pathophysiology of blood-brain barrier dynamics and both active and chronic inflammation, as well as mechanisms of lesion healing and remyelination. Here, we parallel the results in humans with advances in imaging of a primate model of MS - experimental autoimmune encephalomyelitis (EAE) in the common marmoset - in which demyelinated lesions resemble their human counterparts far more closely than do EAE lesions in the rodent. This approach holds promise for the identification of innovative biological markers, and for next-generation clinical trials that will focus more on tissue protection and repair.
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