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Choi S, Lake S, Harrison DM. Evaluation of the Blood-Brain Barrier, Demyelination, and Neurodegeneration in Paramagnetic Rim Lesions in Multiple Sclerosis on 7 Tesla MRI. J Magn Reson Imaging 2024; 59:941-951. [PMID: 37276054 PMCID: PMC10754232 DOI: 10.1002/jmri.28847] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 06/07/2023] Open
Abstract
BACKGROUND Paramagnetic rim lesions (PRLs) are associated with chronic inflammation in multiple sclerosis (MS). 7-Tesla (7T) magnetic resonance imaging (MRI) can evaluate the integrity of the blood-brain barrier (BBB) in addition to the tissue myelination status and cell loss. PURPOSE To use MRI metrics to investigate underlying physiology and clinical importance of PRLs. STUDY TYPE Prospective. SUBJECTS Thirty-six participants (mean-age 47, 23 females, 13 males) of mixed MS subtypes. FIELD STRENGTH/SEQUENCE 7T, MP2RAGE, MULTI-ECHO 3D-GRE, FLAIR. ASSESSMENT Lesion heterogeneity; longitudinal changes in lesion counts; comparison of T1, R2*, and χ; association between baseline lesion types and disease progression (2-3 annual MRI visits with additional years of annual clinical follow-up). STATISTICAL TESTS Two-sample t-test, Wilcoxon Rank-Sum test, Pearson's chi-square test, two-group comparison with linear-mixed-effect model, mixed-effect ANOVA, logistic regression. P-values <0.05 were considered significant. RESULTS A total of 58.3% of participants had at least one PRL at baseline. Higher male proportion in PRL+ group was found. Average change in PRL count was 0.20 (SD = 2.82) for PRLs and 0.00 (SD = 0.82) for mottled lesions. Mean and median pre-/post-contrast T1 were longer in PRL+ than in PRL-. No differences in mean χ were seen for lesions grouped by PRL (P = 0.310, pre-contrast; 0.086, post-contrast) or PRL/M presence (P = 0.234, pre-contrast; 0.163, post-contrast). Median χ were less negative in PRL+ and PRL/M+ than in PRL- and PRL/M-. Mean and median pre-/post-contrast R2* were slower in PRL+ compared to PRL-. Mean and median pre-/post-contrast R2* were slower in PRL/M+ than in PRL/M-. PRL presence at baseline was associated with confirmed EDSS Plus progression (OR 3.75 [1.22-7.59]) and PRL/M+ at baseline with confirmed EDSS Plus progression (OR 3.63 [1.14-7.43]). DATA CONCLUSION Evidence of BBB breakdown in PRLs was not seen. Quantitative metrics confirmed prior results suggesting greater demyelination, cell loss, and possibly disruption of tissue anisotropy in PRLs. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Seongjin Choi
- Department of Neurology, University of Maryland School of Medicine, Baltimore Maryland
| | - Sarah Lake
- Hasbro Children’s Hospital, Brown University
| | - Daniel M. Harrison
- Department of Neurology, University of Maryland School of Medicine, Baltimore Maryland
- Department of Neurology, Baltimore Veterans Affairs Medical Center, Baltimore, Maryland
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Nabizadeh F, Zafari R, Mohamadi M, Maleki T, Fallahi MS, Rafiei N. MRI features and disability in multiple sclerosis: A systematic review and meta-analysis. J Neuroradiol 2024; 51:24-37. [PMID: 38172026 DOI: 10.1016/j.neurad.2023.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 11/28/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND In this systematic review and meta-analysis, we aimed to investigate the correlation between disability in patients with Multiple sclerosis (MS) measured by the Expanded Disability Status Scale (EDSS) and brain Magnetic Resonance Imaging (MRI) features to provide reliable results on which characteristics in the MRI can predict disability and prognosis of the disease. METHODS A systematic literature search was performed using three databases including PubMed, Scopus, and Web of Science. The selected peer-reviewed studies must report a correlation between EDSS scores and MRI features. The correlation coefficients of included studies were converted to the Fisher's z scale, and the results were pooled. RESULTS Overall, 105 studies A total of 16,613 patients with MS entered our study. We found no significant correlation between total brain volume and EDSS assessment (95 % CI: -0.37 to 0.08; z-score: -0.15). We examined the potential correlation between the volume of T1 and T2 lesions and the level of disability. A positive significant correlation was found (95 % CI: 0.19 to 0.43; z-score: 0.31), (95 % CI: 0.17 to 0.33; z-score: 0.25). We observed a significant correlation between white matter volume and EDSS score in patients with MS (95 % CI: -0.37 to -0.03; z-score: -0.21). Moreover, there was a significant negative correlation between gray matter volume and disability (95 % CI: -0.025 to -0.07; z-score: -0.16). CONCLUSION In conclusion, this systematic review and meta-analysis revealed that disability in patients with MS is linked to extensive changes in different brain regions, encompassing gray and white matter, as well as T1 and T2 weighted MRI lesions.
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Affiliation(s)
- Fardin Nabizadeh
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
| | - Rasa Zafari
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mobin Mohamadi
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Tahereh Maleki
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Nazanin Rafiei
- School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
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Oh J, Airas L, Harrison D, Järvinen E, Livingston T, Lanker S, Malik RA, Okuda DT, Villoslada P, de Vries HE. Neuroimaging to monitor worsening of multiple sclerosis: advances supported by the grant for multiple sclerosis innovation. Front Neurol 2023; 14:1319869. [PMID: 38107636 PMCID: PMC10722910 DOI: 10.3389/fneur.2023.1319869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 11/13/2023] [Indexed: 12/19/2023] Open
Abstract
Key unmet needs in multiple sclerosis (MS) include detection of early pathology, disability worsening independent of relapses, and accurate monitoring of treatment response. Collaborative approaches to address these unmet needs have been driven in part by industry-academic networks and initiatives such as the Grant for Multiple Sclerosis Innovation (GMSI) and Multiple Sclerosis Leadership and Innovation Network (MS-LINK™) programs. We review the application of recent advances, supported by the GMSI and MS-LINK™ programs, in neuroimaging technology to quantify pathology related to central pathology and disease worsening, and potential for their translation into clinical practice/trials. GMSI-supported advances in neuroimaging methods and biomarkers include developments in magnetic resonance imaging, positron emission tomography, ocular imaging, and machine learning. However, longitudinal studies are required to facilitate translation of these measures to the clinic and to justify their inclusion as endpoints in clinical trials of new therapeutics for MS. Novel neuroimaging measures and other biomarkers, combined with artificial intelligence, may enable accurate prediction and monitoring of MS worsening in the clinic, and may also be used as endpoints in clinical trials of new therapies for MS targeting relapse-independent disease pathology.
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Affiliation(s)
- Jiwon Oh
- Division of Neurology, St. Michael’s Hospital, Department of Medicine, University of Toronto, Toronto, ON, Canada
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Laura Airas
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland
- Division of Clinical Neurosciences, Turku University Hospital and University of Turku, Turku, Finland
| | - Daniel Harrison
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States
- Baltimore VA Medical Center, VA Maryland Healthcare System, Baltimore, MD, United States
| | - Elina Järvinen
- Neurology and Immunology, Medical Unit N&I, Merck OY (an affiliate of Merck KGaA), Espoo, Finland
| | - Terrie Livingston
- Patient Solutions and Center of Excellence Strategic Engagement, EMD Serono, Inc., Rockland, MA, United States
| | - Stefan Lanker
- Neurology & Immunology, US Medical Affairs, EMD Serono Research & Development Institute, Inc., (an affiliate of Merck KGaA), Billerica, MA, United States
| | - Rayaz A. Malik
- Weill Cornell Medicine-Qatar, Research Division, Doha, Qatar
- Institute of Cardiovascular Sciences, University of Manchester, Manchester, United Kingdom
| | - Darin T. Okuda
- Department of Neurology, Neuroinnovation Program, Multiple Sclerosis and Neuroimmunology Imaging Program, Clinical Center for Multiple Sclerosis, UT Southwestern Medical Center, Dallas, TX, United States
| | - Pablo Villoslada
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Helga E. de Vries
- MS Center Amsterdam, Department of Molecular Cell Biology and Immunology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical Centers (Amsterdam UMC), Location VUmc, Amsterdam, Netherlands
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Donatelli G, Cecchi P, Migaleddu G, Cencini M, Frumento P, D'Amelio C, Peretti L, Buonincontri G, Pasquali L, Tosetti M, Cosottini M, Costagli M. Quantitative T1 mapping detects blood-brain barrier breakdown in apparently non-enhancing multiple sclerosis lesions. Neuroimage Clin 2023; 40:103509. [PMID: 37717382 PMCID: PMC10514220 DOI: 10.1016/j.nicl.2023.103509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 08/09/2023] [Accepted: 09/10/2023] [Indexed: 09/19/2023]
Abstract
OBJECTIVES The disruption of the blood-brain barrier (BBB) is a key and early feature in the pathogenesis of demyelinating multiple sclerosis (MS) lesions and has been neuropathologically demonstrated in both active and chronic plaques. The local overt BBB disruption in acute demyelinating lesions is captured as signal hyperintensity in post-contrast T1-weighted images because of the contrast-related shortening of the T1 relaxation time. On the contrary, the subtle BBB disruption in chronic lesions is not visible at conventional radiological evaluation but it might be of clinical relevance. Indeed, persistent, subtle BBB leakage might be linked to low-grade inflammation and plaque evolution. Here we hypothesised that 3D Quantitative Transient-state Imaging (QTI) was able to reveal and measure T1 shortening (ΔT1) reflecting small amounts of contrast media leakage in apparently non-enhancing lesions (ANELs). MATERIALS AND METHODS Thirty-four patients with relapsing remitting MS were included in the study. All patients underwent a 3 T MRI exam of the brain including conventional sequences and QTI acquisitions (1.1 mm isotropic voxel) performed both before and after contrast media administration. For each patient, a ΔT1 map was obtained via voxel-wise subtraction of pre- and post- contrast QTI-derived T1 maps. ΔT1 values measured in ANELs were compared with those recorded in enhancing lesions and in the normal appearing white matter. A reference distribution of ΔT1 in the white matter was obtained from datasets acquired in 10 non-MS patients with unrevealing MR imaging. RESULTS Mean ΔT1 in ANELs (57.45 ± 48.27 ms) was significantly lower than in enhancing lesions (297.71 ± 177.52 ms; p < 0. 0001) and higher than in the normal appearing white matter (36.57 ± 10.53 ms; p < 0.005). Fifty-two percent of ANELs exhibited ΔT1 higher than those observed in the white matter of non-MS patients. CONCLUSIONS QTI-derived quantitative ΔT1 mapping enabled to measure contrast-related T1 shortening in ANELs. ANELs exhibiting ΔT1 values that deviate from the reference distribution in non-MS patients may indicate persistent, subtle, BBB disruption. Access to this information may be proved useful to better characterise pathology and objectively monitor disease activity and response to therapy.
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Affiliation(s)
- Graziella Donatelli
- Neuroradiology Unit, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy; Imago7 Research Foundation, Pisa, Italy
| | - Paolo Cecchi
- Neuroradiology Unit, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy; Imago7 Research Foundation, Pisa, Italy
| | | | - Matteo Cencini
- National Institute for Nuclear Physics (INFN), Pisa Division, Pisa, Italy
| | - Paolo Frumento
- Department of Political Sciences, University of Pisa, Pisa, Italy
| | - Claudio D'Amelio
- Neuroradiology Unit, Department of Translational Research on New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Luca Peretti
- Imago7 Research Foundation, Pisa, Italy; Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Guido Buonincontri
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Livia Pasquali
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Michela Tosetti
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Mirco Cosottini
- Neuroradiology Unit, Department of Translational Research on New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.
| | - Mauro Costagli
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy
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Moyaert P, Padrela BE, Morgan CA, Petr J, Versijpt J, Barkhof F, Jurkiewicz MT, Shao X, Oyeniran O, Manson T, Wang DJJ, Günther M, Achten E, Mutsaerts HJMM, Anazodo UC. Imaging blood-brain barrier dysfunction: A state-of-the-art review from a clinical perspective. Front Aging Neurosci 2023; 15:1132077. [PMID: 37139088 PMCID: PMC10150073 DOI: 10.3389/fnagi.2023.1132077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 03/15/2023] [Indexed: 05/05/2023] Open
Abstract
The blood-brain barrier (BBB) consists of specialized cells that tightly regulate the in- and outflow of molecules from the blood to brain parenchyma, protecting the brain's microenvironment. If one of the BBB components starts to fail, its dysfunction can lead to a cascade of neuroinflammatory events leading to neuronal dysfunction and degeneration. Preliminary imaging findings suggest that BBB dysfunction could serve as an early diagnostic and prognostic biomarker for a number of neurological diseases. This review aims to provide clinicians with an overview of the emerging field of BBB imaging in humans by answering three key questions: (1. Disease) In which diseases could BBB imaging be useful? (2. Device) What are currently available imaging methods for evaluating BBB integrity? And (3. Distribution) what is the potential of BBB imaging in different environments, particularly in resource limited settings? We conclude that further advances are needed, such as the validation, standardization and implementation of readily available, low-cost and non-contrast BBB imaging techniques, for BBB imaging to be a useful clinical biomarker in both resource-limited and well-resourced settings.
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Affiliation(s)
- Paulien Moyaert
- Department of Medical Imaging, Ghent University Hospital, Ghent, Belgium
- Lawson Health Research Institute, London, ON, Canada
- Department of Neurology, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
- *Correspondence: Paulien Moyaert,
| | - Beatriz E. Padrela
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Catherine A. Morgan
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand
- Centre for Advanced MRI, Auckland UniServices Limited, Auckland, New Zealand
| | - Jan Petr
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Jan Versijpt
- Department of Neurology, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, United Kingdom
| | | | - Xingfeng Shao
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Olujide Oyeniran
- Lawson Health Research Institute, London, ON, Canada
- Department of Medical Biophysics, Western University, London, ON, Canada
| | - Tabitha Manson
- Centre for Advanced MRI, Auckland UniServices Limited, Auckland, New Zealand
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Danny J. J. Wang
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Matthias Günther
- Fraunhofer Institute for Digital Medicine, University of Bremen, Bremen, Germany
| | - Eric Achten
- Department of Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Henk J. M. M. Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Udunna C. Anazodo
- Lawson Health Research Institute, London, ON, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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Choi S, Spini M, Hua J, Harrison DM. Correction: Blood-brain barrier breakdown in non-enhancing multiple sclerosis lesions detected by 7-Tesla MP2RAGE ΔT1 mapping. PLoS One 2022; 17:e0264452. [PMID: 35192677 PMCID: PMC8863243 DOI: 10.1371/journal.pone.0264452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
[This corrects the article DOI: 10.1371/journal.pone.0249973.].
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