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Hosny HS, Shehata HS, Ahmed S, Ramadan I, Abdo SS, Fouad AM. Predictors of severity and outcome of multiple sclerosis relapses. BMC Neurol 2023; 23:67. [PMID: 36782141 PMCID: PMC9926556 DOI: 10.1186/s12883-023-03109-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 02/07/2023] [Indexed: 02/15/2023] Open
Abstract
BACKGROUND Multiple Sclerosis (MS) is a demyelinating disease of the central nervous system (CNS). The most common type of MS is the relapsing-remitting MS (RRMS) where relapses are the main component of the disease course. However, the relationship between the characteristics of the relapses on one hand and their severity and outcome on the other hand has not been fully characterized. OBJECTIVES To explore the characteristics of relapses among a cohort of Egyptian MS patients and their relation to the severity and outcome of the disease. SUBJECTS AND METHODS We analyzed 300 attacks from 223 patients in a retrospective study to identify demographic, clinical and paraclinical (laboratory and radiological) factors affecting: 1- Severity of relapses (the difference between the EDSS at the day of maximum worsening and the EDSS before the onset of the attack). 2- Outcome of relapses (the difference between the EDSS at the day of maximum improvement and the EDSS before the onset of the relapse). RESULTS Severe attacks were most likely to occur in patients who are males, single, presenting with poly-symptomatic presentation, slower tempo of evolution of attack symptoms, longer duration of the attack, absence of DMTs at the time of the attack. The risk of having a severe relapse is more than 3 times when the patient is single. Regarding attack outcome, poorly recovered attacks were more common in patients with older age at disease onset and at attack onset, male sex, higher number of relapses, longer duration of illness prior to the attack, severe relapses, polysymptomatic presentation, associated cognitive symptoms, slower tempo of symptom evolution, longer duration of the attack, patients on OCPs, smoking, and presence of black holes in brain MRI. The risk of having relapses with partial or no recovery is more than five times when the patient has black holes in brain MRI and more than 4 times when the patient is a smoker. CONCLUSION Bearing in mind the demographic characteristics as well as the clinical and paraclinical characteristics of each attack and their relation to attack severity and outcome are a key to understanding the individual disease course of every patient and hence tailoring the best therapeutic plan suitable for his individual needs. In other words, prompt, rapid intervention in male patients, polysymptomatic attacks, slower tempo of evolution of attack symptoms and longer duration of the attack should be adopted since these factors are predictive of severe relapses as well as poor relapse outcome.
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Affiliation(s)
- Hassan Saad Hosny
- grid.7776.10000 0004 0639 9286Neurology Department, Faculty of Medicine, Cairo University, Giza, Egypt
| | - Hatem Samir Shehata
- grid.7776.10000 0004 0639 9286Neurology Department, Faculty of Medicine, Cairo University, Giza, Egypt
| | - Sandra Ahmed
- grid.7776.10000 0004 0639 9286Neurology Department, Faculty of Medicine, Cairo University, Giza, Egypt
| | - Ismail Ramadan
- grid.7155.60000 0001 2260 6941Neurology Department, Faculty of Medicine, Alexandria University, Alexandria, Egypt
| | - Sarah Sherif Abdo
- grid.7776.10000 0004 0639 9286Neurology Department, Faculty of Medicine, Cairo University, Giza, Egypt
| | - Amr Mohamed Fouad
- Neurology Department, Faculty of Medicine, Cairo University, Giza, Egypt.
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2
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Hartmann A, Noro F, Bahia PRV, Fontes-Dantas FL, Andreiuolo RF, Lopes FCR, Pereira VCSR, Coutinho RA, Araujo ADD, Marchiori E, Alves-Leon SV. The clinical-radiological paradox in multiple sclerosis: myth or truth? ARQUIVOS DE NEURO-PSIQUIATRIA 2023; 81:55-61. [PMID: 36918008 PMCID: PMC10014204 DOI: 10.1055/s-0042-1758457] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
BACKGROUND Multiple sclerosis (MS) is an inflammatory, degenerative, demyelinating disease that ranges from benign to rapidly progressive forms. A striking characteristic of the disease is the clinical-radiological paradox. OBJECTIVES The present study was conducted to determine whether, in our cohort, the clinical-radiological paradox exists and whether lesion location is related to clinical disability in patients with MS. METHODS Retrospective data from 95 patients with MS (60 women and 35 men) treated at a single center were examined. One head-and-spine magnetic resonance imaging (MRI) examination from each patient was selected randomly, and two independent observers calculated lesion loads (LLs) on T2/fluid attenuation inversion recovery sequences manually, considering the whole brain and four separate regions (periventricular, juxtacortical, posterior fossa, and spinal cord). The LLs were compared with the degree of disability, measured by the Kurtzke Expanded Disability Status Scale (EDSS), at the time of MRI examination in the whole cohort and in patients with relapsing-remitting (RR), primarily progressive, and secondarily progressive MS. RESULTS High LLs correlated with high EDSS scores in the whole cohort (r = 0.34; p < 0.01) and in the RRMS group (r = 0.27; p = 0.02). The EDSS score correlated with high regional LLs in the posterior fossa (r = 0.31; p = 0.002) and spinal cord (r = 0.35; p = 0.001). CONCLUSIONS Our results indicate that the clinical-radiological paradox is a myth and support the logical connection between lesion location and neurological repercussion.
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Affiliation(s)
- Ana Hartmann
- Universidade Federal do Rio de Janeiro, Departamento de Radiologia, Rio de Janeiro RJ, Brazil
| | - Fabio Noro
- Universidade Federal do Rio de Janeiro, Departamento de Radiologia, Rio de Janeiro RJ, Brazil
| | | | - Fabricia Lima Fontes-Dantas
- Universidade Estadual do Rio de Janeiro, Departamento de Farmacologia e Psicobiologia, Rio de Janeiro RJ, Brazil
| | | | | | | | - Renan Amaral Coutinho
- Universidade Federal do Rio de Janeiro, Departamento de Neurologia, Rio de Janeiro RJ, Brazil
| | - Amanda Dutra de Araujo
- Universidade Federal do Rio de Janeiro, Departamento de Neurologia, Rio de Janeiro RJ, Brazil
| | - Edson Marchiori
- Universidade Federal do Rio de Janeiro, Departamento de Radiologia, Rio de Janeiro RJ, Brazil
| | - Soniza Vieira Alves-Leon
- Universidade Federal do Rio de Janeiro, Departamento de Neurologia, Rio de Janeiro RJ, Brazil.,Universidade Federal do Estado do Rio de Janeiro, Laboratório de Neurociências Translacional. Soniza Vieira Alves-Leon, Rio de Janeiro RJ, Brazil
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3
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Olmez O, Baba C, Abasiyanik Z, Ozakbas S. Epstein-Barr virus antibody in newly diagnosed multiple sclerosis patients and its association with relapse severity and lesion location. Mult Scler Relat Disord 2022; 68:104149. [PMID: 36096010 DOI: 10.1016/j.msard.2022.104149] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Epstein-Barr virus is considered a risk factor for the development of multiple sclerosis, and recent findings reveal infected plasma -cells in meningeal ectopic lymphoid deposits. Activation of the dormant virus could be responsible for the multiple sclerosis exacerbation AIMS: To compare Epstein-Barr nuclear IgG (EBNA IgG) titer in newly diagnosed treatment-naive multiple sclerosis patients regarding the diagnoses date, clinical and radiological activity. METHODS Treatment-naive multiple sclerosis patients were divided into two groups according to Poser (late group) and McDonald2017(early group) diagnostic criteria. EBNA IgG, EDSS, physical (Timed 25 Foot Walk test, Nine-hole Peg test), and cognitive tests (Brief International Cognitive Assessment for Multiple Sclerosis) were done before the methylprednisolone infusion. The lesion location was evaluated by an MRI. Myelitis was considered a severe attack, and optic neuritis a mild relapse. RESULTS In total, 69 patients were enrolled. 44 (63.8%) of them were diagnosed by McDonald2017, and 25 (36.2%) were diagnosed with Poser criteria. There was a significant difference (p = 0.049) between the EBNA IgG titer of the late (median:238 U/ml, IQR: 154-362) and early (median: 154 U/ml, IQR:100.25-293.25). Severe relapse, having a spinal cord lesion, and not being treated with methylprednisolone was associated with higher EBNA IgG titer. CONCLUSION Study results show that EBNA IgG was significantly associated with disease activity regarding relapse severity and lesion location and could be a potential biomarker for predicting disease exacerbation.
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Affiliation(s)
- Onder Olmez
- Department of Neurology, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Cavid Baba
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Zuhal Abasiyanik
- Physical Therapy and Rehabilitation, Graduate School of Health Sciences, Dokuz Eylül University, Inciraltı mah. Mithatpaşa cad., Izmir 35340, Turkey; Department of Physiotherapy and Rehabilitation, Faculty of Health Sciences, Izmir Katip Celebi University, Izmir, Turkey.
| | - Serkan Ozakbas
- Department of Neurology, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
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4
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Meijboom R, Wiseman SJ, York EN, Bastin ME, Valdés Hernández MDC, Thrippleton MJ, Mollison D, White N, Kampaite A, Ng Kee Kwong K, Rodriguez Gonzalez D, Job D, Weaver C, Kearns PKA, Connick P, Chandran S, Waldman AD. Rationale and design of the brain magnetic resonance imaging protocol for FutureMS: a longitudinal multi-centre study of newly diagnosed patients with relapsing-remitting multiple sclerosis in Scotland. Wellcome Open Res 2022; 7:94. [PMID: 36865371 PMCID: PMC9971644 DOI: 10.12688/wellcomeopenres.17731.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/02/2022] [Indexed: 12/22/2022] Open
Abstract
Introduction: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease. MS prevalence varies geographically and is notably high in Scotland. Disease trajectory varies significantly between individuals and the causes for this are largely unclear. Biomarkers predictive of disease course are urgently needed to allow improved stratification for current disease modifying therapies and future targeted treatments aimed at neuroprotection and remyelination. Magnetic resonance imaging (MRI) can detect disease activity and underlying damage non-invasively in vivo at the micro and macrostructural level. FutureMS is a prospective Scottish longitudinal multi-centre cohort study, which focuses on deeply phenotyping patients with recently diagnosed relapsing-remitting MS (RRMS). Neuroimaging is a central component of the study and provides two main primary endpoints for disease activity and neurodegeneration. This paper provides an overview of MRI data acquisition, management and processing in FutureMS. FutureMS is registered with the Integrated Research Application System (IRAS, UK) under reference number 169955. Methods and analysis: MRI is performed at baseline (N=431) and 1-year follow-up, in Dundee, Glasgow and Edinburgh (3T Siemens) and in Aberdeen (3T Philips), and managed and processed in Edinburgh. The core structural MRI protocol comprises T1-weighted, T2-weighted, FLAIR and proton density images. Primary imaging outcome measures are new/enlarging white matter lesions (WML) and reduction in brain volume over one year. Secondary imaging outcome measures comprise WML volume as an additional quantitative structural MRI measure, rim lesions on susceptibility-weighted imaging, and microstructural MRI measures, including diffusion tensor imaging and neurite orientation dispersion and density imaging metrics, relaxometry, magnetisation transfer (MT) ratio, MT saturation and derived g-ratio measures. Conclusions: FutureMS aims to reduce uncertainty around disease course and allow for targeted treatment in RRMS by exploring the role of conventional and advanced MRI measures as biomarkers of disease severity and progression in a large population of RRMS patients in Scotland.
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Affiliation(s)
- Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Stewart J. Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Elizabeth N. York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Mark E. Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Maria del C. Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Daisy Mollison
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Nicole White
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Koy Ng Kee Kwong
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - David Rodriguez Gonzalez
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Dominic Job
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Christine Weaver
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Patrick K. A. Kearns
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
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5
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Mohamed AAB, Algahalan HA, Thabit MN. Correlation between functional MRI techniques and early disability in ambulatory patients with relapsing–remitting MS. THE EGYPTIAN JOURNAL OF NEUROLOGY, PSYCHIATRY AND NEUROSURGERY 2022. [DOI: 10.1186/s41983-022-00457-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
Abstract
Abstract
Background
Multiple sclerosis (MS) is a common neurological disorder which can lead to an occasional damage to the central nervous system. Conventional magnetic resonance imaging (cMRI) is an important modality in the diagnosis of MS; however, correlation between cMRI findings and clinical impairment is weak. Non-conventional MRI techniques including apparent diffusion coefficient (ADC) and magnetic resonance spectroscopy (MRS) investigate the metabolic changes over the course of MS and overcome the limits of cMRI.
A total of 80 patients with MS and 20 age and sex-matched healthy control subjects were enrolled in this cross-sectional study. Ambulatory patients with relapsing–remitting MS (RRMS) were recruited. Expanded Disability Status Scale (EDSS) was used to assess the disability and the patients were categorized into three groups “no disability”, “minimal disability” and “moderate disability”. All patients underwent cMRI techniques. ADC was measured in MS plaques and in normal appearing white matter (NAWM) adjacent and around the plaque. All metabolites concentrations were expressed as ratios including N-acetyl-aspartate/creatine (NAA/Cr), choline/N-acetyl-aspartate (Cho/NAA) and choline/creatine (Cho/Cr). ADC and metabolite concentrations were measured in the normal white matter of 20 healthy control subjects.
Results
The study was carried on 80 MS patients [36 males (45%) and 44 females (55%)] and 20 healthy control [8 males (40%) and 12 females (60%)]. The ADC values and MRS parameters in NAWM of patients with MS were significantly different from those of the control group. The number of the plaques on T2 images and black holes were significantly higher at “Minimal disability” group. Most of the enhanced plaques were at the “Moderate disability” group with P value < 0.001. The mean of ADC in the group 1, 2 and 3 of disability was 1.12 ± 0.19, 1.50 ± 0.35, 1.51 ± 0.36, respectively, with P value < 0. 001. In the group 1, 2 and 3 of disability, the mean of NAA/Cr ratio at the plaque was 1.34 ± 0.44, 1.59 ± 0.51 and 1.11 ± 0.15, respectively, with P value equal 0.001.
Conclusion
The non-conventional quantitative MRI techniques are useful tools for detection of early disability in MS patients.
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Changing Paradigms and Unmet Needs in Multiple Sclerosis: The Role of Clinical Neurophysiology. J Clin Neurophysiol 2021; 38:162-165. [PMID: 33958565 DOI: 10.1097/wnp.0000000000000749] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Abstract
SUMMARY Our increasing understanding of the immunopathogenesis of multiple sclerosis has led to the development of many disease-modifying therapies that have revolutionized the care of patients with relapsing forms of the disease. Our understanding of the pathophysiologic basis of progressive forms of the disease is much more limited but has dramatically changed over the past several decades. We are now on the verge of developing therapies that promote remyelination, reduce axonal loss, and restore axonal function. This progress is challenged by inadequate animal models of progressive disease and incomplete biomarkers of progression. In measuring central nervous system function, evoked potentials may have an advantage over biomarkers, which measure only pathologic change. Monitoring multifocal visual evoked potential amplitude may be one possible means of monitoring disease progression in multiple sclerosis. Additional clinical studies are required to document whether evoked potentials can adequately serve as effective biomarkers of progression.
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7
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Bougnères P, Hacein-Bey-Abina S, Labik I, Adamsbaum C, Castaignède C, Bellesme C, Schmidt M. Long-Term Follow-Up of Hematopoietic Stem-Cell Gene Therapy for Cerebral Adrenoleukodystrophy. Hum Gene Ther 2021; 32:1260-1269. [PMID: 33789438 DOI: 10.1089/hum.2021.053] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
In 2009, cerebral adrenoleukodystrophy (c-ALD) became the first brain disease to be treated with lentiviral (LV)-based hematopoietic stem cell gene therapy with the ABCD1 gene in four boys (P1-P4) who had demyelinating lesions expected to be lethal in the short term and no bone marrow donor. We report the clinical and magnetic resonance imaging (MRI) follow-up over a mean of 8.8 years posttransplant. In parallel, vector genome copies, expression of transgenic ALD protein (ALDP), and viral integration sites were determined in peripheral blood cells. Prior to transplant, the four patients had a normal or near normal neurocognitive status but gadolinium-enhanced demyelination in various brain regions. Gadolinium diffusion disappeared during the first year posttransplant. P3 kept a near normal status until 8.3 years of follow-up, but P1, P2, and P4 showed major cognitive degradation around 9, 28, and 60 months posttransplant. Neurological status and demyelination stabilized until last evaluation in P2, but deteriorated in both P1 at 10 years and P4 at 3 years posttransplant. The proportion of myeloid and lymphoid cells expressing transgenic ALDP decreased by half within 5 years then stabilized around 5% to 10%. Integration site analysis revealed a durable polyclonal distribution of genetically corrected hematopoietic cells. No adverse effects were observed. The long-term arrest of demyelination at MRI and persistence of transduced hematopoietic progenitors support that LV gene therapy may be a safe and durable treatment of c-ALD. However, the neurological degradation observed in three out of four patients mitigates the benefit of this therapy, calling for an earlier intervention, more potent vectors, and additional therapeutic strategies.
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Affiliation(s)
- Pierre Bougnères
- UMR1195 INSERM, Le Kremlin Bicêtre, France.,Université Paris Saclay, MIRCen Institute/Neuratris, Fontenay-aux-Roses, France.,Therapy Design Consulting, Vincennes, France
| | - Salima Hacein-Bey-Abina
- Clinical Immunology Laboratory, Hôpital Kremlin-Bicêtre, Assistance Publique-Hôpitaux de Paris, Université Paris Saclay, Paris, France.,UTCBS, CNRS UMR8258, INSERM U1267, Faculté de Pharmacie de Paris, Université de Paris, Le Kremlin-Bicêtre, France
| | | | | | - Clémence Castaignède
- Pediatric Neurology, Hôpital Kremlin-Bicêtre, Assistance Publique-Hôpitaux de Paris, Université Paris Saclay, Le Kremlin-Bicêtre, France
| | - Céline Bellesme
- Pediatric Neurology, Hôpital Kremlin-Bicêtre, Assistance Publique-Hôpitaux de Paris, Université Paris Saclay, Le Kremlin-Bicêtre, France
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8
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Sucksdorff M, Matilainen M, Tuisku J, Polvinen E, Vuorimaa A, Rokka J, Nylund M, Rissanen E, Airas L. Brain TSPO-PET predicts later disease progression independent of relapses in multiple sclerosis. Brain 2021; 143:3318-3330. [PMID: 33006604 PMCID: PMC7719021 DOI: 10.1093/brain/awaa275] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 07/03/2020] [Accepted: 07/10/2020] [Indexed: 12/28/2022] Open
Abstract
Overactivation of microglia is associated with most neurodegenerative diseases. In this study we examined whether PET-measurable innate immune cell activation predicts multiple sclerosis disease progression. Activation of microglia/macrophages was measured using the 18-kDa translocator protein (TSPO)-binding radioligand 11C-PK11195 and PET imaging in 69 patients with multiple sclerosis and 18 age- and sex-matched healthy controls. Radioligand binding was evaluated as the distribution volume ratio from dynamic PET images. Conventional MRI and disability measurements using the Expanded Disability Status Scale were performed for patients at baseline and 4.1 ± 1.9 (mean ± standard deviation) years later. Fifty-one (74%) of the patients were free of relapses during the follow-up period. Patients had increased activation of innate immune cells in the normal-appearing white matter and in the thalamus compared to the healthy control group (P = 0.033 and P = 0.003, respectively, Wilcoxon). Forward-type stepwise logistic regression was used to assess the best variables predicting disease progression. Baseline innate immune cell activation in the normal-appearing white matter was a significant predictor of later progression when the entire multiple sclerosis cohort was assessed [odds ratio (OR) = 4.26; P = 0.048]. In the patient subgroup free of relapses there was an association between macrophage/microglia activation in the perilesional normal-appearing white matter and disease progression (OR = 4.57; P = 0.013). None of the conventional MRI parameters measured at baseline associated with later progression. Our results strongly suggest that innate immune cell activation contributes to the diffuse neural damage leading to multiple sclerosis disease progression independent of relapses.
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Affiliation(s)
- Marcus Sucksdorff
- 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
| | - Markus Matilainen
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland
| | - Jouni Tuisku
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland
| | - Eero Polvinen
- 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
| | - Anna Vuorimaa
- 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
| | - Johanna Rokka
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland
| | - Marjo Nylund
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland
| | - Eero Rissanen
- 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
| | - 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
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9
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Chard DT, Alahmadi AAS, Audoin B, Charalambous T, Enzinger C, Hulst HE, Rocca MA, Rovira À, Sastre-Garriga J, Schoonheim MM, Tijms B, Tur C, Gandini Wheeler-Kingshott CAM, Wink AM, Ciccarelli O, Barkhof F. Mind the gap: from neurons to networks to outcomes in multiple sclerosis. Nat Rev Neurol 2021; 17:173-184. [PMID: 33437067 DOI: 10.1038/s41582-020-00439-8] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/20/2020] [Indexed: 12/21/2022]
Abstract
MRI studies have provided valuable insights into the structure and function of neural networks, particularly in health and in classical neurodegenerative conditions such as Alzheimer disease. However, such work is also highly relevant in other diseases of the CNS, including multiple sclerosis (MS). In this Review, we consider the effects of MS pathology on brain networks, as assessed using MRI, and how these changes to brain networks translate into clinical impairments. We also discuss how this knowledge can inform the targeting of MS treatments and the potential future directions for research in this area. Studying MS is challenging as its pathology involves neurodegenerative and focal inflammatory elements, both of which could disrupt neural networks. The disruption of white matter tracts in MS is reflected in changes in network efficiency, an increasingly random grey matter network topology, relative cortical disconnection, and both increases and decreases in connectivity centred around hubs such as the thalamus and the default mode network. The results of initial longitudinal studies suggest that these changes evolve rather than simply increase over time and are linked with clinical features. Studies have also identified a potential role for treatments that functionally modify neural networks as opposed to altering their structure.
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Affiliation(s)
- Declan T Chard
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK. .,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK.
| | - Adnan A S Alahmadi
- Department of Diagnostic Radiology, Faculty of Applied Medical Science, King Abdulaziz University (KAU), Jeddah, Saudi Arabia
| | - Bertrand Audoin
- Aix-Marseille University, CNRS, CRMBM, Marseille, France.,AP-HM, University Hospital Timone, Department of Neurology, Marseille, France
| | - Thalis Charalambous
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Christian Enzinger
- Department of Neurology, Research Unit for Neuronal Repair and Plasticity, Medical University of Graz, Graz, Austria.,Department of Radiology, Division of Neuroradiology, Vascular and Interventional Radiology, Medical University of Graz, Graz, Austria
| | - Hanneke E Hulst
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jaume Sastre-Garriga
- Servei de Neurologia/Neuroimmunologia, Multiple Sclerosis Centre of Catalonia (Cemcat), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Betty Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Carmen Tur
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.,Department of Neurology, Luton and Dunstable University Hospital, Luton, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.,Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.,Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Alle Meije Wink
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK
| | - Frederik Barkhof
- National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK.,Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, University College London, London, UK
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Approved and Emerging Disease Modifying Therapies on Neurodegeneration in Multiple Sclerosis. Int J Mol Sci 2020; 21:ijms21124312. [PMID: 32560364 PMCID: PMC7348940 DOI: 10.3390/ijms21124312] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 06/15/2020] [Accepted: 06/15/2020] [Indexed: 12/16/2022] Open
Abstract
Multiple sclerosis (MS) is an autoimmune, chronic, progressive disease leading to a combination of inflammation, demyelination, and neurodegeneration throughout the central nervous system (CNS). The outcome of these processes can be visualized in magnetic resonance imaging (MRI) scans as brain atrophy, or brain volume loss (BVL), as well as lesions, “black holes” and spinal cord atrophy. MRI outcomes such as BVL have been used as biomarkers of neurodegeneration and other measures of MS disease progression in clinical research settings. Several FDA-approved medications seek to alleviate disease progression by reducing the impact of such factors as demyelination and neurodegeneration, but there are still many shortcomings that current clinical research aims to mitigate. This review attempts to provide an overview of the FDA-approved medications available for treating multiple sclerosis and their effect on neurodegeneration, measured by BVL.
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Smith BC, Sinyuk M, Jenkins JE, Psenicka MW, Williams JL. The impact of regional astrocyte interferon-γ signaling during chronic autoimmunity: a novel role for the immunoproteasome. J Neuroinflammation 2020; 17:184. [PMID: 32532298 PMCID: PMC7291495 DOI: 10.1186/s12974-020-01861-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 05/29/2020] [Indexed: 12/23/2022] Open
Abstract
Background In early autoimmune neuroinflammation, interferon (IFN)γ and its upregulation of the immunoproteasome (iP) is pathologic. However, during chronic multiple sclerosis (MS), IFNγ has protective properties. Although dysregulation of the iP has been implicated in neurodegeneration, its function remains to be fully elucidated. Here, we demonstrate that IFNγ signaling in regional astrocytes induces the iP and promotes protection of the CNS during chronic autoimmunity. Methods In a multiple sclerosis (MS) brain, we evaluated mRNA expression and labeled postmortem MS brainstem and spinal cord for iP subunits and indicators of oxidative stress. Primary regional human astrocytes were analyzed for iP regulation and function by quantitative reverse transcription-polymerase chain reaction (qRT-PCR), Western blot, OxyBlot, and reactive oxygen species and caspase activity detection assays. Following immunization with myelin oligodendrocyte glycoprotein (MOG)35-55, the role of IFNγ signaling and the iP during chronic experimental autoimmune encephalomyelitis (EAE) were assessed using pharmacologic inhibition of the iP and genetic interruption of IFNγ signaling specifically in astrocytes. Central nervous system (CNS) tissues were analyzed by immunohistochemistry (IHC) and immunofluorescence, and cell-specific colocalization was quantified. Results In MS tissue, iP expression was enhanced in the spinal cord compared to brainstem lesions, which correlated with a decrease in oxidative stress. In vitro, IFNγ stimulation enhanced iP expression, reduced reactive oxygen species burden, and decreased oxidatively damaged and poly-ubiquitinated protein accumulation preferentially in human spinal cord astrocytes, which was abrogated with the use of the iP inhibitor, ONX 0914. During the chronic phase of an MS animal model, EAE, ONX 0914 treatment exacerbated the disease and led to increased oxidative stress and poly-ubiquitinated protein buildup. Finally, mice with astrocyte-specific loss of the IFNγ receptor exhibited worsened chronic EAE associated with reduced iP expression, enhanced lesion size and oxidative stress, and poly-ubiquitinated protein accumulation in astrocytes. Conclusions Taken together, our data reveal a protective role for IFNγ in chronic neuroinflammation and identify a novel function of the iP in astrocytes during CNS autoimmunity.
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Affiliation(s)
- Brandon C Smith
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Biological, Geological, and Environmental Sciences, Cleveland State University, Cleveland, OH, USA
| | - Maksim Sinyuk
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Julius E Jenkins
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Morgan W Psenicka
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jessica L Williams
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA. .,Brain Health Research Institute, Kent State University, Kent, OH, USA.
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12
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Huffnagel IC, van Ballegoij WJ, Vos JM, Kemp S, Caan MW, Engelen M. Longitudinal diffusion MRI as surrogate outcome measure for myelopathy in adrenoleukodystrophy. Neurology 2019; 93:e2133-e2143. [DOI: 10.1212/wnl.0000000000008572] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 06/12/2019] [Indexed: 01/05/2023] Open
Abstract
ObjectiveTo prospectively determine the potential of diffusion MRI (dMRI) of the cervical spinal cord and the corticospinal tracts in brain as surrogate outcome measure for progression of myelopathy in men with adrenoleukodystrophy, as better outcome measures to quantify progression of myelopathy would enable clinical trials with fewer patients and shorter follow-up.MethodsClinical assessment of myelopathy included Expanded Disability Status Scale (EDSS), Severity Scoring System for Progressive Myelopathy (SSPROM), Timed Up-and-Go, and 6-Minute Walk Test. Applied dMRI metrics included fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity.ResultsData were available for 33 controls and 52 patients. First, cross-sectionally, differences between groups (controls vs patients; controls vs asymptomatic patients vs symptomatic patients) were statistically significant for fractional anisotropy, mean diffusivity, and radial diffusivity in spinal cord and brain corticospinal tracts (effect size 0.31–0.68). Correlations between dMRI metrics and clinical measures were moderate to strong (correlation coefficient 0.35–0.60). Second, longitudinally (n = 36), change on clinical measures was significant after 2-year follow-up for EDSS, SSPROM, and Timed Up-and-Go (p ≤ 0.021, effect size ≤0.14). Change on brain fractional anisotropy and radial diffusivity was slightly larger (p ≤ 0.002, effect sizes 0.16–0.28). In addition, a statistically significant change was detectable in asymptomatic patients using brain dMRI and not using the clinical measures. Change on clinical measures did not correlate to change on dMRI metrics.ConclusionAlthough effect sizes were small, our prospective data illustrate the potential of dMRI as surrogate outcome measure for progression of myelopathy in men with adrenoleukodystrophy.
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Thomas AM, Xu J, Calabresi PA, van Zijl PCM, Bulte JWM. Monitoring diffuse injury during disease progression in experimental autoimmune encephalomyelitis with on resonance variable delay multiple pulse (onVDMP) CEST MRI. Neuroimage 2019; 204:116245. [PMID: 31605825 DOI: 10.1016/j.neuroimage.2019.116245] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 09/16/2019] [Accepted: 10/03/2019] [Indexed: 12/24/2022] Open
Abstract
Multiple sclerosis (MS) is an autoimmune disorder that targets myelin proteins and results in extensive damage in the central nervous system in the form of focal lesions as well as diffuse molecular changes. Lesions are currently detected using T1-weighted, T2-weighted, and gadolinium-enhanced magnetic resonance imaging (MRI); however, monitoring such lesions has been shown to be a poor predictor of disease progression. Chemical exchange saturation transfer (CEST) MRI is sensitive to many of the biomolecules in the central nervous system altered in MS that cannot be detected using conventional MRI. We monitored disease progression in an experimental autoimmune encephalomyelitis (EAE) model of MS using on resonance variable delay multiple pulse (onVDMP) CEST MRI. Alterations in onVDMP signal were observed in regions responsible for hindlimb function throughout the central nervous system. Histological analysis revealed glial activation in areas highlighted in onVDMP CEST MRI. onVDMP signal changes in the 3rd ventricle preceded paralysis onset that could not be observed with conventional MRI techniques. Hence, the onVDMP CEST MRI signal has potential as a novel imaging biomarker and predictor of disease progression in MS.
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Affiliation(s)
- Aline M Thomas
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jiadi Xu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter A Calabresi
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; The Solomon H. Snyder Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter C M van Zijl
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jeff W M Bulte
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Chemical & Biomolecular Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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14
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Dahan A, Pereira R, Malpas CB, Kalincik T, Gaillard F. PACS Integration of Semiautomated Imaging Software Improves Day-to-Day MS Disease Activity Detection. AJNR Am J Neuroradiol 2019; 40:1624-1629. [PMID: 31515214 DOI: 10.3174/ajnr.a6195] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Accepted: 07/19/2019] [Indexed: 01/06/2023]
Abstract
BACKGROUND AND PURPOSE The standard for evaluating interval radiologic activity in MS, side-by-side MR imaging comparison, is restricted by its time-consuming nature and limited sensitivity. VisTarsier, a semiautomated software for comparing volumetric FLAIR sequences, has shown better disease-activity detection than conventional comparison in retrospective studies. Our objective was to determine whether implementing this software in day-to-day practice would show similar efficacy. MATERIALS AND METHODS VisTarsier created an additional coregistered image series for reporting a color-coded disease-activity change map for every new MS MR imaging brain study that contained volumetric FLAIR sequences. All other MS studies, including those generated during software-maintenance periods, were interpreted with side-by-side comparison only. The number of new lesions reported with software assistance was compared with those observed with traditional assessment in a generalized linear mixed model. Questionnaires were sent to participating radiologists to evaluate the perceived day-to-day impact of the software. RESULTS Nine hundred six study pairs from 538 patients during 2 years were included. The semiautomated software was used in 841 study pairs, while the remaining 65 used conventional comparison only. Twenty percent of software-aided studies reported having new lesions versus 9% with standard comparison only. The use of this software was associated with an odds ratio of 4.15 for detection of new or enlarging lesions (P = .040), and 86.9% of respondents from the survey found that the software saved at least 2-5 minutes per scan report. CONCLUSIONS VisTarsier can be implemented in real-world clinical settings with good acceptance and preservation of accuracy demonstrated in a retrospective environment.
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Affiliation(s)
- A Dahan
- From the Department of Radiology (A.D.), Austin Hospital, Heidelberg, Australia
| | - R Pereira
- Departments of Radiology (R.P., F.G.)
- Department of Radiology (R.P.), University of Queensland, Brisbane, Queensland, Australia
| | - C B Malpas
- Neurology (T.K., C.M.), Royal Melbourne Hospital, Parkville, Victoria, Australia
- Clinical Outcomes Research Unit (CORe) (C.M., T.K.)
| | - T Kalincik
- Neurology (T.K., C.M.), Royal Melbourne Hospital, Parkville, Victoria, Australia
- Clinical Outcomes Research Unit (CORe) (C.M., T.K.)
| | - F Gaillard
- Departments of Radiology (R.P., F.G.)
- Departments of Medicine and Radiology (F.G.), University of Melbourne, Melbourne, Australia
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Hu XY, Rajendran L, Lapointe E, Tam R, Li D, Traboulsee A, Rauscher A. Three-dimensional MRI sequences in MS diagnosis and research. Mult Scler 2019; 25:1700-1709. [DOI: 10.1177/1352458519848100] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The most recent guidelines for magnetic resonance imaging (MRI) in multiple sclerosis (MS) recommend three-dimensional (3D) MRI sequences over their two-dimensional (2D) counterparts. This development has been made possible by advances in MRI scanner hardware and software. In this article, we review the 3D versions of conventional sequences, including T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR), as well as more advanced scans, including double inversion recovery (DIR), FLAIR2, FLAIR*, phase-sensitive inversion recovery, and susceptibility weighted imaging (SWI).
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Affiliation(s)
- Xun Yang Hu
- Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Luckshi Rajendran
- Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Emmanuelle Lapointe
- Department of Medicine, Division of Neurology, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Roger Tam
- Department of Radiology, School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada
| | - David Li
- Department of Radiology, UBC Hospital, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Division of Neurology, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Alexander Rauscher
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada
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16
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Manouchehrinia A, Zhu F, Piani-Meier D, Lange M, Silva DG, Carruthers R, Glaser A, Kingwell E, Tremlett H, Hillert J. Predicting risk of secondary progression in multiple sclerosis: A nomogram. Mult Scler 2018; 25:1102-1112. [PMID: 29911467 DOI: 10.1177/1352458518783667] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
OBJECTIVES We aimed at designing a nomogram, a prediction tool, to predict the individual's risk of conversion to secondary progressive multiple sclerosis (SPMS) at the time of multiple sclerosis (MS) onset. METHODS One derivation and three validation cohorts were established. The derivation cohort included 8825 relapsing-onset MS patients in Sweden. A nomogram was built based on a survival model with the best statistical fit and prediction accuracy. The nomogram was validated using data from 3967 patients in the British Columbia cohort, 176 patients in the ACROSS and 2355 patients in FREEDOMS/FREEDOMS II extension studies. RESULTS Sex, calendar year of birth, first-recorded Expanded Disability Status Scale (EDSS) score, age at the first EDSS and age at disease onset showed significant predictive ability to estimate the risk of SPMS conversion at 10, 15 and 20 years. The nomogram reached 84% (95% confidence intervals (CIs): 83-85) internal and 77% (95% CI: 76-78), 77% (95% CI: 70-85) and 87% (95% CI: 84-89) external accuracy. CONCLUSIONS The SPMS nomogram represents a much-needed complementary tool designed to assist in decision-making and patient counselling in the early phase of MS. The SPMS nomogram may improve outcomes by prompting timely and more efficacious treatment for those with a worse prognosis.
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Affiliation(s)
- Ali Manouchehrinia
- Department of Clinical Neuroscience (CNS), Karolinska Institutet, Stockholm, Sweden
| | - Feng Zhu
- Division of Neurology, UBC Hospital, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | | | | | | | - Robert Carruthers
- Division of Neurology, UBC Hospital, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Anna Glaser
- Department of Clinical Neuroscience (CNS), Karolinska Institutet, Stockholm, Sweden
| | - Elaine Kingwell
- Division of Neurology, UBC Hospital, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Helen Tremlett
- Division of Neurology, UBC Hospital, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Jan Hillert
- Department of Clinical Neuroscience (CNS), Karolinska Institutet, Stockholm, Sweden
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Datta G, Colasanti A, Kalk N, Owen D, Scott G, Rabiner EA, Gunn RN, Lingford-Hughes A, Malik O, Ciccarelli O, Nicholas R, Nei L, Battaglini M, Stefano ND, Matthews PM. 11C-PBR28 and 18F-PBR111 Detect White Matter Inflammatory Heterogeneity in Multiple Sclerosis. J Nucl Med 2017; 58:1477-1482. [DOI: 10.2967/jnumed.116.187161] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Accepted: 02/28/2017] [Indexed: 11/16/2022] Open
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18
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Reich DS. Imag(in)ing multiple sclerosis: Time to take better pictures. J Neuroimmunol 2016; 304:72-80. [PMID: 27742080 DOI: 10.1016/j.jneuroim.2016.09.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 09/28/2016] [Indexed: 01/20/2023]
Abstract
Magnetic resonance imaging (MRI) has led to the identification of widespread brain abnormalities in multiple sclerosis (MS) that extend far beyond the classic white matter lesion. These findings have generated the idea that MS should be understood as a disease of the whole brain, not just the white matter. While it is no doubt the case that many different pathways are ultimately involved in the destruction of brain tissue that occurs in MS, the implications of the accumulated evidence for understanding disease pathophysiology - and hence the overall significance of these imaging findings - are doubtful. Here, I argue that the principled use of imaging can, in fact, address questions about the genesis of these whole-brain abnormalities, rather than simply describe them.
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Affiliation(s)
- Daniel S Reich
- National Institutes of Health, Translational Neuroradiology Section, Building 10, Room 5C103, 20892-4128 Bethesda, MD, USA.
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19
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Lema A, Bishop C, Malik O, Mattoscio M, Ali R, Nicholas R, Muraro PA, Matthews PM, Waldman AD, Newbould RD. A Comparison of Magnetization Transfer Methods to Assess Brain and Cervical Cord Microstructure in Multiple Sclerosis. J Neuroimaging 2016; 27:221-226. [PMID: 27491693 DOI: 10.1111/jon.12377] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Revised: 06/25/2016] [Accepted: 06/26/2016] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Demyelination is a core pathological feature of multiple sclerosis (MS) and spontaneous remyelination appears to be an important mechanism for repair in the disease. Magnetization transfer ratio imaging (MTR) has been used extensively to evaluate demyelination, although limitations to its specificity are recognized. MT saturation imaging (MTsat) removes some of the T1 dependence of MTR. We have performed a comparative evaluation of MTR and MTsat imaging in a mixed group of subjects with active MS, to explore their relative sensitivity to pathology relevant to explaining clinical outcomes. METHODS A total of 134 subjects underwent MRI of their brain and cervical spinal cord. Isotropic 3-dimensional pre- and postcontrast T1-weighted and T2-weighted fluid-attenuated inversion recovery (FLAIR) volumes were segmented into brain normal appearing white matter (NAWM), brain WM lesions (WML), normal appearing spinal cord (NASC), and spinal cord lesions. Volumes and metrics for MTR and MTsat histograms were calculated for each region. RESULTS Significant Spearman correlations were found with the Expanded Disability Status Scale and timed 25-foot walk for the whole brain and WML MTR, but not in that from the NAWM or any cervical spinal cord region. By contrast, the MTsat was correlated with both disability metrics in all these regions in both the brain and spine. CONCLUSIONS This study extends prior work relating atrophy and lesion load with disability, by characterization of MTsat parameters. MTsat is practical in routine clinical applications and may be more sensitive to tissue damage than MTR for both brain and cervical spinal cord.
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Affiliation(s)
- Alfonso Lema
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | | | - Omar Malik
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Miriam Mattoscio
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Rehiana Ali
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Richard Nicholas
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Paolo A Muraro
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Paul M Matthews
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Adam D Waldman
- Department of Imaging, Imperial College Healthcare NHS Trust, London, UK
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Van Steenkiste G, Poot DHJ, Jeurissen B, den Dekker AJ, Vanhevel F, Parizel PM, Sijbers J. Super‐resolution
T
1
estimation: Quantitative high resolution
T
1
mapping from a set of low resolution
T
1
‐weighted images with different slice orientations. Magn Reson Med 2016; 77:1818-1830. [DOI: 10.1002/mrm.26262] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Revised: 04/11/2016] [Accepted: 04/11/2016] [Indexed: 11/06/2022]
Affiliation(s)
| | - Dirk H. J. Poot
- Imaging Science and Technology, Delft University of Technology2628 CJDelft The Netherlands
- BIGR (Department of Medical informatics and Radiology)Erasmus Medical Center RotterdamRotterdam The Netherlands
| | - Ben Jeurissen
- iMinds‐Vision LabDepartment of Physics, University of AntwerpAntwerp Belgium
| | - Arnold J. den Dekker
- iMinds‐Vision LabDepartment of Physics, University of AntwerpAntwerp Belgium
- Delft Center for Systems and Control, Delft University of Technology2628CD Delft The Netherlands
| | - Floris Vanhevel
- Department of RadiologyUniversity of Antwerp, Antwerp University Hospital Belgium
| | - Paul M. Parizel
- Department of RadiologyUniversity of Antwerp, Antwerp University Hospital Belgium
| | - Jan Sijbers
- iMinds‐Vision LabDepartment of Physics, University of AntwerpAntwerp Belgium
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Abstract
Due to its sensitivity to the different multiple sclerosis (MS)-related abnormalities, magnetic resonance imaging (MRI) has become an established tool to diagnose MS and to monitor its evolution. MRI has been included in the diagnostic workup of patients with clinically isolated syndromes suggestive of MS, and ad hoc criteria have been proposed and are regularly updated. In patients with definite MS, the ability of conventional MRI techniques to explain patients' clinical status and progression of disability is still suboptimal. Several advanced MRI-based technologies have been applied to estimate overall MS burden in the different phases of the disease. Their use has allowed the heterogeneity of MS pathology in focal lesions, normal-appearing white matter and gray matter to be graded in vivo. Recently, additional features of MS pathology, including macrophage infiltration and abnormal iron deposition, have become quantifiable. All of this, combined with functional imaging techniques, is improving our understanding of the mechanisms associated with MS evolution. In the near future, the use of ultrahigh-field systems is likely to provide additional insight into disease pathophysiology. However, the utility of advanced MRI techniques in clinical trial monitoring and in assessing individual patients' response to treatment still needs to be assessed.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
| | - Paolo Preziosa
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
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Stone LA, Cutter GR, Fisher E, Richert N, McCartin J, Ohayon J, Bash C, McFarland H. Relapse May Serve as a Mediator Variable in Longitudinal Outcomes in Multiple Sclerosis. J Neuroimaging 2015; 26:296-302. [PMID: 26686343 DOI: 10.1111/jon.12321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2015] [Accepted: 11/02/2015] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND/PURPOSE Contrast-enhancing lesions (CEL) on magnetic resonance imaging (MRI) are believed to represent inflammatory disease activity in multiple sclerosis (MS), but their relationship to subsequent long-term disability and progression is unclear, particularly at longer time periods such as 8-10 years. METHODS Between 1989 and 1994, 111 MS patients were seen at the National Institutes of Health for clinical evaluations and 3 monthly contrast-enhanced MRI scans. Of these, 94 patients were re-evaluated a mean of 8 years later (range 6.1-10.5 years) with a single MRI scan and clinical evaluation. CEL number and volume were determined at baseline and follow-up. The number of relapses was ascertained over the follow-up period and annualized relapse rates were calculated. Other MRI parameters, such as T2 hyperintensity volume, T1 volume, and brain parenchymal fraction, were also calculated. RESULTS While there was no direct correlation between CEL number or volume at baseline and disability status at follow-up, CEL measures at baseline did correlate with number of relapses observed in the subsequent years, and the number of relapses in turn correlated with subsequent disability as well as transition to progressive MS. CONCLUSION While number and volume of CEL at baseline do not directly correlate with disability in the longer term in MS, our data suggest that 1 route to disability involves relapses as a mediator variable in the causal sequence of MS progression from CEL to disability. Further studies using relapse as a mediator variable in a larger data set may be warranted.
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Affiliation(s)
- Lael Anne Stone
- Mellen Center for Treatment and Research, Cleveland Clinic Foundation, Cleveland, OH
| | | | | | | | - Jennifer McCartin
- Neuroimmunology Branch of the National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - Joan Ohayon
- Neuroimmunology Branch of the National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - Craig Bash
- Department of Neuroradiology, Uniformed Services School of Medicine, Bethesda, MD
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Oommen VV, Tauhid S, Healy BC, Chua AS, Malik MT, Diaz-Cruz C, Dupuy SL, Weiner HL, Chitnis T, Bakshi R. The Effect of Fingolimod on Conversion of Acute Gadolinium-Enhancing Lesions to Chronic T1 Hypointensities in Multiple Sclerosis. J Neuroimaging 2015; 26:184-7. [PMID: 26445919 PMCID: PMC5057343 DOI: 10.1111/jon.12307] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2015] [Revised: 08/21/2015] [Accepted: 09/01/2015] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Brain lesions converting to chronic T1 hypointensities (“chronic black holes” [CBH]), indicate severe tissue destruction (axonal loss and irreversible demyelination) in multiple sclerosis (MS). Two mechanisms by which fingolimod could limit MS lesion evolution include sequestration of lymphocytes in the periphery or direct neuroprotective effects. We investigated the effect of fingolimod on the evolution of acute gadolinium‐enhancing (Gd+) brain lesions to CBH in patients with MS. METHODS This was a retrospective nonrandomized comparison of patients with Gd+ brain lesions at the time of starting oral fingolimod [.5 mg/day, n = 26, age (mean ± SD) 39.2 ± 10.6 years, Expanded Disability Status Scale (EDSS) score ‐ median (range): 1.75 (0, 6.5)] to those on no therapy [n = 30, age 41.7 ± 9.3 years; EDSS 1.0 (0, 6)]. Each lesion was classified by whether it converted to a CBH in the year following treatment. RESULTS In the fingolimod group, 99 Gd+ baseline lesions (mean ± SD, range: 3.8 ± 5.1; 1, 21 per patient) were identified of which 25 (25%) evolved to CBH (1.0 ± 2.0; 0, 10 per patient). The untreated group had 62 baseline Gd+ lesions (2.1 ± 2.3; 1, 13), 26 (42%) of which evolved to CBH (.9 ± 1.4; 0, 7) (P = .063). Thirteen patients (50%) receiving fingolimod and 17 untreated patients (57%) developed CBH (P = .79). CONCLUSION This pilot study shows a trend of fingolimod on reducing the conversion rate from acute to chronic destructive MS lesions. Such an effect awaits verification in larger randomized prospective studies.
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Affiliation(s)
- Vinit V Oommen
- Department of Neurology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA
| | - Shahamat Tauhid
- Department of Radiology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA
| | - Brian C Healy
- Department of Neurology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA
| | - Alicia S Chua
- Department of Neurology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA
| | - Muhammad T Malik
- Department of Neurology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA
| | - Camilo Diaz-Cruz
- Department of Neurology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA
| | - Sheena L Dupuy
- Department of Neurology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA
| | - Howard L Weiner
- Department of Neurology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA
| | - Tanuja Chitnis
- Department of Neurology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA
| | - Rohit Bakshi
- Department of Neurology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA.,Department of Radiology, Brigham and Women's Hospital, Partners MS Center, Harvard Medical School, Boston, MA
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Goodin DS, Reder AT, Bermel RA, Cutter GR, Fox RJ, John GR, Lublin FD, Lucchinetti CF, Miller AE, Pelletier D, Racke MK, Trapp BD, Vartanian T, Waubant E. Relapses in multiple sclerosis: Relationship to disability. Mult Scler Relat Disord 2015; 6:10-20. [PMID: 27063617 DOI: 10.1016/j.msard.2015.09.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Revised: 08/21/2015] [Accepted: 09/02/2015] [Indexed: 12/21/2022]
Abstract
Multiple sclerosis (MS) is a recurrent inflammatory disease of the central nervous system, which ultimately causes substantial disability in many patients. A key clinical feature of this disease is the occurrence of relapses, consisting of episodes of neurological dysfunction followed by periods of remission. This review considers in detail the importance of the occurrence of relapses to the ultimate course of MS and the impact of relap setreatment (both acutely and prophylactically) on the long-term outcome for individuals. The ultimate goal of therapy in MS is the reduction of long-term disability. Clinical trials in MS, however, typically only extend for a very short time period compared to the time it takes for disability to evolve. Consequently, short-term outcome measures that are associated with, and predict, future disability need to be identified. In this regard, not only are relapses a characteristic feature of MS, they have also been proven to be associated with the occurrence of long-term disability. Moreover, treatments that reduce the number and severity of these attacks improve the long-term prognosis.
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Affiliation(s)
- Douglas S Goodin
- Multiple Sclerosis Center, University of California, San Francisco Medical Center, San Francisco, CA, United States; Department of Neurology, University of California, San Francisco School of Medicine, San Francisco, CA, United States.
| | - Anthony T Reder
- Department of Neurology, The University of Chicago, Chicago, IL, United States
| | - Robert A Bermel
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States
| | - Gary R Cutter
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Robert J Fox
- Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Gareth R John
- Multiple Sclerosis Research Laboratory, Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Friedman Brain Institute, New York, NY, United States; Department of Neurology, Mount Sinai School of Medicine, New York, NY, United States
| | - Fred D Lublin
- Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | | | - Aaron E Miller
- Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Daniel Pelletier
- Neuro-Immunology Division and Yale Multiple Sclerosis Center, Advanced Imaging in Multiple Sclerosis (AIMS) Laboratory, Yale University School of Medicine, New Haven, CT, United States
| | - Michael K Racke
- Department of Neurology, Wexner Medical Center at The Ohio State University, Columbus, OH, United States
| | - Bruce D Trapp
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Timothy Vartanian
- Judith Jaffe Multiple Sclerosis Center, New York-Presbyterian Hospital/Weill Cornell Medical Center, Weill Cornell Medical College, United States
| | - Emmanuelle Waubant
- UCSF Regional Pediatric MS Center, Race to Erase MS, San Francisco, CA, United States
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25
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Pardini M, Yaldizli Ö, Sethi V, Muhlert N, Liu Z, Samson RS, Altmann DR, Ron MA, Wheeler-Kingshott CAM, Miller DH, Chard DT. Motor network efficiency and disability in multiple sclerosis. Neurology 2015; 85:1115-22. [PMID: 26320199 DOI: 10.1212/wnl.0000000000001970] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2015] [Accepted: 04/24/2015] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To develop a composite MRI-based measure of motor network integrity, and determine if it explains disability better than conventional MRI measures in patients with multiple sclerosis (MS). METHODS Tract density imaging and constrained spherical deconvolution tractography were used to identify motor network connections in 22 controls. Fractional anisotropy (FA), magnetization transfer ratio (MTR), and normalized volume were computed in each tract in 71 people with relapse onset MS. Principal component analysis was used to distill the FA, MTR, and tract volume data into a single metric for each tract, which in turn was used to compute a composite measure of motor network efficiency (composite NE) using graph theory. Associations were investigated between the Expanded Disability Status Scale (EDSS) and the following MRI measures: composite motor NE, NE calculated using FA alone, FA averaged in the combined motor network tracts, brain T2 lesion volume, brain parenchymal fraction, normal-appearing white matter MTR, and cervical cord cross-sectional area. RESULTS In univariable analysis, composite motor NE explained 58% of the variation in EDSS in the whole MS group, more than twice that of the other MRI measures investigated. In a multivariable regression model, only composite NE and disease duration were independently associated with EDSS. CONCLUSIONS A composite MRI measure of motor NE was able to predict disability substantially better than conventional non-network-based MRI measures.
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Affiliation(s)
- Matteo Pardini
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK.
| | - Özgür Yaldizli
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Varun Sethi
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Nils Muhlert
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Zheng Liu
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Rebecca S Samson
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Daniel R Altmann
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Maria A Ron
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Claudia A M Wheeler-Kingshott
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - David H Miller
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Declan T Chard
- From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK
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26
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Wu GF, Brier MR, Parks CAL, Ances BM, Van Stavern GP. An Eye on Brain Integrity: Acute Optic Neuritis Affects Resting State Functional Connectivity. Invest Ophthalmol Vis Sci 2015; 56:2541-6. [PMID: 25813992 PMCID: PMC4416526 DOI: 10.1167/iovs.14-16315] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2014] [Accepted: 03/20/2015] [Indexed: 11/24/2022] Open
Abstract
PURPOSE Currently, the ability for imaging to capture brain adaptations to injury that occurs in multiple sclerosis (MS) is limited. In particular, how the brain initially contends with the earliest clinical manifestations of white matter injury has yet to be defined. The purpose of this study was to determine the impact of acute optic neuritis (ON) on resting state functional connectivity magnetic resonance imaging (rs-fcMRI). METHODS Fifteen patients with a clinically isolated syndrome of acute ON were evaluated at an academic center in a prospective study. Subjects were assessed with structural and functional vision measures, including optical coherence tomography (OCT), high- and low-contrast letter acuity testing, and visual fields and quality-of-life measures (VFQ-25). The rs-fcMRI was compared with age- and sex-matched healthy controls. RESULTS We observed reduced functional connectivity within the visual system and a loss of anticorrelations between the visual system and nonvisual networks. Stronger functional connectivity between visual regions correlated with better quality of life, as measured by the VFQ-25, and better acuity scores for both high- and low-contrast testing in the affected eye. CONCLUSIONS The rs-fcMRI functional connectivity changes within (intranetwork) and between (internetwork) resting state networks occur after acute ON, indicating immediate cortical responses to focal inflammatory demyelination. Thus, focal white matter injury in the central nervous system acutely results in widespread network alterations that may lead to functional neurologic changes seen in MS.
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Affiliation(s)
- Gregory F. Wu
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
- Department of Pathology and Immunology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
| | - Matthew R, Brier
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
| | - Cassie A.-L. Parks
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
| | - Beau M. Ances
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
- Department of Radiology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
| | - Gregory P. Van Stavern
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
- Department of Ophthalmology and Visual Sciences, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
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27
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Enzinger C, Fazekas F. Measuring Gray Matter and White Matter Damage in MS: Why This is Not Enough. Front Neurol 2015; 6:56. [PMID: 25852635 PMCID: PMC4362212 DOI: 10.3389/fneur.2015.00056] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Accepted: 02/27/2015] [Indexed: 01/06/2023] Open
Affiliation(s)
- Christian Enzinger
- Department of Neurology, Medical University of Graz , Graz , Austria ; Division of Neuroradiology, Department of Radiology, Medical University of Graz , Graz , Austria
| | - Franz Fazekas
- Department of Neurology, Medical University of Graz , Graz , Austria
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28
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Freedman MS, Abdoli M. Evaluating response to disease-modifying therapy in relapsing multiple sclerosis. Expert Rev Neurother 2015; 15:407-23. [DOI: 10.1586/14737175.2015.1023711] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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29
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Plasticity of the motor system in multiple sclerosis. Neuroscience 2014; 283:222-30. [DOI: 10.1016/j.neuroscience.2014.05.043] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2014] [Revised: 05/20/2014] [Accepted: 05/21/2014] [Indexed: 11/20/2022]
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30
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Goodin DS. The epidemiology of multiple sclerosis: insights to disease pathogenesis. HANDBOOK OF CLINICAL NEUROLOGY 2014; 122:231-66. [PMID: 24507521 DOI: 10.1016/b978-0-444-52001-2.00010-8] [Citation(s) in RCA: 112] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The purpose of studying the epidemiology of multiple sclerosis (MS) is twofold. First, it is important to understand clearly the natural history of the illness in order to assist patients in making decisions about their future with respect to issues such as family planning, the importance of securing lifelong healthcare, their ability to get and maintain employment, and making appropriate choices of therapy for their particular circumstances. This is not to suggest that, even with the best possible information, the ultimate prognosis for any individual can be predicted with absolute accuracy. It cannot. Nevertheless, accurate information can be very helpful both to reassure patients that many individuals with MS do remarkably well in the long term (perhaps, especially, with current and future therapies) and also to empower individuals with respect to their ability to make their own life choices. Second, and arguably the more important purpose for studying the epidemiology of MS, is to gain insights to the underlying causes of the disease. Indeed, if the principal mechanisms of disease pathogenesis were to be understood clearly, then it might be possible to entertain notions of either a cure for existing disease or the primary prevention of future disease. Much of our current understanding of disease pathogenesis, as discussed in other chapters of this volume, has been derived from basic science investigations of animal models of MS such as experimental autoimmune encephalomyelitis (EAE), and these models have provided considerable insight both to the complexity of the mammalian immune system and to the mechanisms underlying its dysfunction in inflammatory autoimmune conditions. Nevertheless, MS is a disease of humans without any known, naturally occurring, counterpart in any nonhuman species. For this reason, the clues to disease pathogenesis provided by a study of basic epidemiologic facts regarding MS (and by a systematic consideration of their implications) are essential to a comprehensive understanding of the human illness we call MS.
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Affiliation(s)
- Douglas S Goodin
- Department of Neurology, University of California, San Francisco, USA.
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31
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Cook SD, Dhib-Jalbut S, Dowling P, Durelli L, Ford C, Giovannoni G, Halper J, Harris C, Herbert J, Li D, Lincoln JA, Lisak R, Lublin FD, Lucchinetti CF, Moore W, Naismith RT, Oehninger C, Simon J, Sormani MP. Use of Magnetic Resonance Imaging as Well as Clinical Disease Activity in the Clinical Classification of Multiple Sclerosis and Assessment of Its Course: A Report from an International CMSC Consensus Conference, March 5-7, 2010. Int J MS Care 2014; 14:105-14. [PMID: 24453741 DOI: 10.7224/1537-2073-14.3.105] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
It has recently been suggested that the Lublin-Reingold clinical classification of multiple sclerosis (MS) be modified to include the use of magnetic resonance imaging (MRI). An international consensus conference sponsored by the Consortium of Multiple Sclerosis Centers (CMSC) was held from March 5 to 7, 2010, to review the available evidence on the need for such modification of the Lublin-Reingold criteria and whether the addition of MRI or other biomarkers might lead to a better understanding of MS pathophysiology and disease course over time. The conference participants concluded that evidence of new MRI gadolinium-enhancing (Gd+) T1-weighted lesions and unequivocally new or enlarging T2-weighted lesions (subclinical activity, subclinical relapses) should be added to the clinical classification of MS in distinguishing relapsing inflammatory from progressive forms of the disease. The consensus was that these changes to the classification system would provide more rigorous definitions and categorization of MS course, leading to better insights as to the evolution and treatment of MS.
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Affiliation(s)
- Stuart D Cook
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Suhayl Dhib-Jalbut
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Peter Dowling
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Luca Durelli
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Corey Ford
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Gavin Giovannoni
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - June Halper
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Colleen Harris
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Joseph Herbert
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - David Li
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - John A Lincoln
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Robert Lisak
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Fred D Lublin
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Claudia F Lucchinetti
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Wayne Moore
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Robert T Naismith
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Carlos Oehninger
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Jack Simon
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
| | - Maria Pia Sormani
- University of Medicine and Dentistry of New Jersey, Newark, NJ, USA (SDC); Department of Neurology, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, New Brunswick, NJ (SDJ); VA Medical Center-East Orange, East Orange, NJ, USA (PD); Department of Clinical and Biological Sciences, San Luigi Gonzaga Medical School, University of Torino, Orbassano, Italy (LD); Multiple Sclerosis Clinic, University of New Mexico Health Sciences Center, Albuquerque, NM, USA (CF); Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, Whitechapel, London, UK (GG); Consortium of Multiple Sclerosis Centers, Hackensack, NJ, USA (J Halper); Multiple Sclerosis Clinic, Foothills Medical Centre, Calgary, Alberta, Canada (CH); MS Comprehensive Care Center, NYU Langone Medical Center, New York, NY, USA (J Herbert); MS Clinic, University of British Columbia Hospital, Vancouver, British Columbia, Canada (DL); MS Research Group, University of Texas Health, Houston, TX, USA (JAL); Comprehensive Clinical and Research MS Center, Wayne State University, Detroit, MI, USA (RL); Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai School of Medicine, New York, NY, USA (FDL); Department of Neurology, Mayo Clinic, Rochester, MN, USA (CFL); Vancouver General Hospital, Vancouver, British Columbia, Canada (WM); Department of Neurology, Washington University, St. Louis, MO, USA (RTN); LACTRIMS and Institute of Neurology, Montevideo, Uruguay (CO); VA Medical Center, Portland, OR, USA (JS); and Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy (MPS)
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Kieseier BC. The challenges of measuring disability accumulation in relapsing–remitting multiple sclerosis: evidence from interferon beta treatments. Expert Rev Neurother 2014; 14:105-20. [DOI: 10.1586/14737175.2014.869478] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Filippi M, Charil A, Rovaris M, Absinta M, Rocca MA. Insights from magnetic resonance imaging. HANDBOOK OF CLINICAL NEUROLOGY 2014; 122:115-149. [PMID: 24507516 DOI: 10.1016/b978-0-444-52001-2.00006-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Recent years have witnessed impressive advancements in the use of magnetic resonance imaging (MRI) for the assessment of patients with multiple sclerosis (MS). Complementary to the clinical evaluation, conventional MRI (cMRI) provides crucial pieces of information for the diagnosis of MS, the understanding of its natural history, and monitoring the efficacy of experimental treatments. Measures derived from cMRI present clear advantages over the clinical assessment, including their more objective nature and an increased sensitivity to MS-related changes. However, the correlation between these measures and the clinical manifestations of the disease remains weak, and this can be explained, at least partially, by the limited ability of cMRI to characterize and quantify the heterogeneous features of MS pathology. Quantitative MR-based techniques have the potential to overcome the limitations of cMRI. Magnetization transfer MRI, diffusion-weighted and diffusion tensor MRI with fiber tractography, proton magnetic resonance spectroscopy, T1 and T2 relaxation time measurement, and functional MRI are contributing to elucidate the mechanisms that underlie injury, repair, and functional adaptation in patients with MS. All conventional and nonconventional MR techniques will benefit from the use of high-field MR systems (3.0T or more).
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
| | - Arnaud Charil
- Neuroimaging Research Unit, Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Marco Rovaris
- Neuroimaging Research Unit, Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Martina Absinta
- Neuroimaging Research Unit, Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Maria Assunta Rocca
- Neuroimaging Research Unit, Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
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Zhang Y, Moore GRW, Laule C, Bjarnason TA, Kozlowski P, Traboulsee A, Li DKB. Pathological correlates of magnetic resonance imaging texture heterogeneity in multiple sclerosis. Ann Neurol 2013; 74:91-9. [PMID: 23939554 DOI: 10.1002/ana.23867] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2011] [Revised: 01/18/2013] [Accepted: 02/01/2013] [Indexed: 11/06/2022]
Abstract
OBJECTIVE To analyze the texture of T2-weighted magnetic resonance imaging (MRI) of postmortem multiple sclerosis (MS) brain, and to determine whether and how MRI texture correlates with tissue pathology. METHODS Ten brain samples from 3 subjects with MS were examined. Areas of complete, partial, or no loss of Luxol fast blue (myelin) and Bielschowsky (axons) staining were marked on histological images, and matched on corresponding MRI as lesions, diffusely abnormal white matter (DAWM), and normal-appearing white matter (NAWM). The number of CD45(+) cells (inflammation) was also counted. MRI texture was computed using polar Stockwell transform and compared to histology. RESULTS Thirty-four lesions, 17 DAWM regions, and 36 NAWM regions were identified. After mixed effects modeling, MRI texture heterogeneity was greater in lesions than in DAWM (p < 0.001) and NAWM (p < 0.001), and was greater in DAWM than in NAWM (p < 0.001); the number of CD45+ cells was greater in both lesions (p < 0.001) and DAWM (p = 0.005) than in NAWM. In MRI, a gradient of texture heterogeneity was detected in lesions, with gradual tapering toward perilesional NAWM. Moreover, besides univariate correlation with histological markers, texture heterogeneity correlated independently with normalized myelin density (p < 0.01) when random effects were considered. Within sample, MRI texture correlated with myelin and axonal density in 7 of 10 samples (p < 0.01). INTERPRETATION Texture analysis performed on routine clinical magnetic resonance images may be a potential measure of tissue integrity. Tissues with more severe myelin and axonal pathology are associated with greater texture heterogeneity.
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Affiliation(s)
- Yunyan Zhang
- Department of Radiology, University of Calgary, Calgary, Alberta; Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta
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Bayesian scalar-on-image regression with application to association between intracranial DTI and cognitive outcomes. Neuroimage 2013; 83:210-23. [PMID: 23792220 DOI: 10.1016/j.neuroimage.2013.06.020] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2012] [Revised: 06/02/2013] [Accepted: 06/03/2013] [Indexed: 11/21/2022] Open
Abstract
Diffusion tensor imaging (DTI) measures water diffusion within white matter, allowing for in vivo quantification of brain pathways. These pathways often subserve specific functions, and impairment of those functions is often associated with imaging abnormalities. As a method for predicting clinical disability from DTI images, we propose a hierarchical Bayesian "scalar-on-image" regression procedure. Our procedure introduces a latent binary map that estimates the locations of predictive voxels and penalizes the magnitude of effect sizes in these voxels, thereby resolving the ill-posed nature of the problem. By inducing a spatial prior structure, the procedure yields a sparse association map that also maintains spatial continuity of predictive regions. The method is demonstrated on a simulation study and on a study of association between fractional anisotropy and cognitive disability in a cross-sectional sample of 135 multiple sclerosis patients.
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Rocca MA, Messina R, Filippi M. Multiple sclerosis imaging: recent advances. J Neurol 2012; 260:929-35. [DOI: 10.1007/s00415-012-6788-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2012] [Revised: 12/04/2012] [Accepted: 12/06/2012] [Indexed: 01/28/2023]
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Chang A, Staugaitis SM, Dutta R, Batt CE, Easley KE, Chomyk AM, Yong VW, Fox RJ, Kidd GJ, Trapp BD. Cortical remyelination: a new target for repair therapies in multiple sclerosis. Ann Neurol 2012; 72:918-26. [PMID: 23076662 DOI: 10.1002/ana.23693] [Citation(s) in RCA: 145] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2012] [Revised: 06/15/2012] [Accepted: 06/26/2012] [Indexed: 12/16/2022]
Abstract
OBJECTIVE Generation and differentiation of new oligodendrocytes in demyelinated white matter is the best described repair process in the adult human brain. However, remyelinating capacity falters with age in patients with multiple sclerosis (MS). Because demyelination of cerebral cortex is extensive in brains from MS patients, we investigated the capacity of cortical lesions to remyelinate and directly compared the extent of remyelination in lesions that involve cerebral cortex and adjacent subcortical white matter. METHODS Postmortem brain tissue from 22 patients with MS (age 27-77 years) and 6 subjects without brain disease were analyzed. Regions of cerebral cortex with reduced myelin were examined for remyelination, oligodendrocyte progenitor cells, reactive astrocytes, and molecules that inhibit remyelination. RESULTS New oligodendrocytes that were actively forming myelin sheaths were identified in 30 of 42 remyelinated subpial cortical lesions, including lesions from 3 patients in their 70s. Oligodendrocyte progenitor cells were not decreased in demyelinated or remyelinated cortices when compared to adjacent normal-appearing cortex or controls. In demyelinated lesions involving cortex and adjacent white matter, the cortex showed greater remyelination, more actively remyelinating oligodendrocytes, and fewer reactive astrocytes. Astrocytes in the white matter, but not in cortical portions of these lesions, significantly upregulate CD44, hyaluronan, and versican, molecules that form complexes that inhibit oligodendrocyte maturation and remyelination. INTERPRETATION Endogenous remyelination of the cerebral cortex occurs in individuals with MS regardless of disease duration or chronological age of the patient. Cortical remyelination should be considered as a primary outcome measure in future clinical trials testing remyelination therapies.
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Affiliation(s)
- Ansi Chang
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
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Abstract
Over the past 2 decades, MRI has been integrated into the diagnosis of multiple sclerosis (MS), the study of MS pathobiology, and the development and monitoring of MS treatments. This integration has irrevocably changed the way we think about the disease. New treatments, advanced through early stages of development using MRI outcome measures, have revolutionized the treatment of MS. Although MS remains a clinical diagnosis, conventional MRI is now a requisite adjunct to that diagnosis. Early in the disease, MRI monitoring of a patient on immunomodulatory therapy is helpful in identifying breakthrough disease activity that may predict long-term outcome. Advanced MRI technologies, although currently relegated to the research realm, are improving the detection of previously underappreciated aspects of MS pathology and may help lead to the evaluation of new therapeutic strategies.
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Hasan KM, Walimuni IS, Abid H, Wolinsky JS, Narayana PA. Multi-modal quantitative MRI investigation of brain tissue neurodegeneration in multiple sclerosis. J Magn Reson Imaging 2012; 35:1300-11. [PMID: 22241681 DOI: 10.1002/jmri.23539] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2011] [Accepted: 11/22/2011] [Indexed: 12/22/2022] Open
Abstract
PURPOSE To investigate the utility of multimodal quantitative MRI (qMRI) and atlas-based methods to identify characteristics of lesion-driven injury and neurodegeneration in relapsing remitting multiple sclerosis (RRMS). MATERIALS AND METHODS This work is health insurance portability and accountability act compliant. High resolution T1-weighted, dual echo, and fluid-attenuated inversion recovery and diffusion tensor MRI images were prospectively acquired on 68 RRMS patients (range, 25-58 years) and 68 age-matched controls. The data were analyzed using standardized human brain atlas-based tissue segmentation procedures to obtain regional volumes and their corresponding T2 relaxation times and DTI maps. RESULTS Group-averaged brain atlas-based qMRI maps of T2, fractional anisotropy and diffusivities are visually presented and compared between controls and RRMS. The analysis shows a widespread injury in RRMS. Atrophy of the corpus callosum (CC) was substantial in RRMS. The qMRI attributes of the neocortex in combination with the CC such as T2 and diffusivities were elevated and correlated with disability. CONCLUSION Using a standardized multimodal qMRI acquisition and analyses that accounted for lesion distribution we demonstrate that cerebral pathology is widespread in RRMS. Our analysis of CC and neocortex qMRI metrics in relation to disability points to a neurodegenerative injury component that is independent from lesions.
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Affiliation(s)
- Khader M Hasan
- Department of Diagnostic and Interventional Imaging, University of Texas Health Science Center at Houston, Houston, Texas, USA.
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Hasan KM, Walimuni IS, Abid H, Datta S, Wolinsky JS, Narayana PA. Human brain atlas-based multimodal MRI analysis of volumetry, diffusimetry, relaxometry and lesion distribution in multiple sclerosis patients and healthy adult controls: implications for understanding the pathogenesis of multiple sclerosis and consolidation of quantitative MRI results in MS. J Neurol Sci 2011; 313:99-109. [PMID: 21978603 DOI: 10.1016/j.jns.2011.09.015] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2011] [Revised: 08/31/2011] [Accepted: 09/13/2011] [Indexed: 01/18/2023]
Abstract
Multiple sclerosis (MS) is the most common immune-mediated disabling neurological disease of the central nervous system. The pathogenesis of MS is not fully understood. Histopathology implicates both demyelination and axonal degeneration as the major contributors to the accumulation of disability. The application of several in vivo quantitative magnetic resonance imaging (MRI) methods to both lesioned and normal-appearing brain tissue has not yet provided a solid conclusive support of the hypothesis that MS might be a diffuse disease. In this work, we adopted FreeSurfer to provide standardized macrostructure or volumetry of lesion free normal-appearing brain tissue in combination with multiple quantitative MRI metrics (T(2) relaxation time, diffusion tensor anisotropy and diffusivities) that characterize tissue microstructural integrity. By incorporating a large number of healthy controls, we have attempted to separate the natural age-related change from the disease-induced effects. Our work shows elevation in diffusivity and relaxation times and reduction in volume in a number of normal-appearing white matter and gray matter structures in relapsing-remitting multiple sclerosis patients. These changes were related in part with the spatial distribution of lesions. The whole brain lesion load and age-adjusted expanded disability status score showed strongest correlations in regions such as corpus callosum with qMRI metrics that are believed to be specific markers of axonal dysfunction, consistent with histologic data of others indicating axonal loss that is independent of focal lesions. Our results support that MS at least in part has a neurodegenerative component.
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Affiliation(s)
- Khader M Hasan
- The University of Texas Health Science Center at Houston, Department of Diagnostic & Interventional Imaging, 6431 Fannin Street, MSB 2.100, Houston, Texas 77030, USA.
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Goodin DS, Hartung HP, O'Connor P, Filippi M, Arnason B, Comi G, Cook S, Jeffery D, Kappos L, Bogumil T, Knappertz V, Sandbrink R, Beckmann K, White R, Petkau J, Pohl C. Neutralizing antibodies to interferon beta-1b multiple sclerosis: a clinico-radiographic paradox in the BEYOND trial. Mult Scler 2011; 18:181-95. [PMID: 21952094 DOI: 10.1177/1352458511418629] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The frequency and impact of neutralizing antibodies (NAbs) to interferon beta-1b (IFNβ-1b) on clinical and radiographic outcomes is controversial. OBJECTIVE To assess NAb impact in the BEYOND study. METHODS 2244 patients were randomized (2:2:1) to receive IFNβ-1b, either 250 or 500 µg, or glatiramer acetate, 20 mg, and observed for 2-3.5 years. NAb titers were determined every 6 months. A titer ≥20 NU/ml was considered NAb positive. Efficacy was compared between NAb-positive and NAb-negative patients, using comprehensive statistical analyses, taking into account the delayed appearance of NAbs, the time-dependent changes in the relapse rate, spontaneous reversions to NAb-negative status, NAb-titer level, and also adjusting for baseline factors. RESULTS In the IFNβ-1b 250 µg group, NAb-positive titers were detected (≥ once) in 319 patients (37.0%); of these, 112 (35.1%) reverted to NAb-negative status. In the IFNβ-1b 500 µg group, 340 patients (40.7%) became NAb-positive and 119 (35.0%) reverted to NAb-negative status. In both IFNβ groups, especially the 250 µg arm, NAb-positive status was not associated with a convincing impact on any clinical outcome measure by any statistical analysis. By contrast, in both IFNβ groups, NAbs were associated with a very consistent deleterious impact on most MRI outcomes. CONCLUSION There was a notable dissociation between the impact of NAbs on MRI and clinical outcomes. On MRI measures, the impact was consistent and convincing, whereas on clinical measures a negative impact of NAbs was not found. The basis for this clinico-radiographic paradox is unknown but it suggests that the relationship between NAbs and the therapeutic effects of IFNβ-1b is complex.
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Abstract
Owing to its ability to depict the pathologic features of multiple sclerosis (MS) in exquisite detail, conventional magnetic resonance (MR) imaging has become an established tool in the diagnosis of this disease and in monitoring its evolution. MR imaging has been formally included in the diagnostic work-up of patients who present with a clinically isolated syndrome suggestive of MS, and ad hoc diagnostic criteria have been proposed and are updated on a regular basis. In patients with established MS and in those participating in treatment trials, examinations performed with conventional MR pulse sequences provide objective measures to monitor disease activity and progression; however, they have a limited prognostic role. This has driven the application of newer MR imaging technologies, including higher-field-strength MR units, to estimate overall MS burden and mechanisms of recovery in patients at different stages of the disease. These techniques have allowed in vivo assessment of the heterogeneity of MS pathologic features in focal lesions and in normal-appearing tissues. More recently, some of the finer details of MS, including macrophage infiltration and abnormal iron deposition, have become quantifiable with MR imaging. The utility of these modern MR techniques in clinical trial monitoring and in the assessment of the individual patient's response to treatment still need to be evaluated.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, Scientific Institute and University Hospital San Raffaele, Via Olgettina 60, 20132 Milan, Italy.
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Goldsmith J, Crainiceanu CM, Caffo BS, Reich DS. Penalized functional regression analysis of white-matter tract profiles in multiple sclerosis. Neuroimage 2011; 57:431-9. [PMID: 21554962 PMCID: PMC3114268 DOI: 10.1016/j.neuroimage.2011.04.044] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2011] [Revised: 03/23/2011] [Accepted: 04/20/2011] [Indexed: 10/18/2022] Open
Abstract
Diffusion tensor imaging (DTI) enables noninvasive parcellation of cerebral white matter into its component fiber bundles or tracts. These tracts often subserve specific functions, and damage to the tracts can therefore result in characteristic forms of disability. Attempts to quantify the extent of tract-specific damage have been limited in part by substantial spatial variation of imaging properties from one end of a tract to the other, variation that can be compounded by the effects of disease. Here, we develop a "penalized functional regression" procedure to analyze spatially normalized tract profiles, which powerfully characterize such spatial variation. The central idea is to identify and emphasize portions of a tract that are more relevant to a clinical outcome score, such as case status or degree of disability. The procedure also yields a "tract abnormality score" for each tract and MRI index studied. Importantly, the weighting function used in this procedure is constrained to be smooth, and the statistical associations are estimated using generalized linear models. We test the method on data from a cross-sectional MRI and functional study of 115 multiple-sclerosis cases and 42 healthy volunteers, considering a range of quantitative MRI indices, white-matter tracts, and clinical outcome scores, and using training and testing sets to validate the results. We show that attention to spatial variation yields up to 15% (mean across all tracts and MRI indices: 6.4%) improvement in the ability to discriminate multiple sclerosis cases from healthy volunteers. Our results confirm that comprehensive analysis of white-matter tract-specific imaging data improves with knowledge and characterization of the normal spatial variation.
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Affiliation(s)
- Jeff Goldsmith
- Department of Biostatistics, Johns Hopkins School of Public Health, 615 N Wolfe St, Baltimore, MD 21205
| | - Ciprian M. Crainiceanu
- Department of Biostatistics, Johns Hopkins School of Public Health, 615 N Wolfe St, Baltimore, MD 21205
| | - Brian S. Caffo
- Department of Biostatistics, Johns Hopkins School of Public Health, 615 N Wolfe St, Baltimore, MD 21205
| | - Daniel S. Reich
- Departments of Radiology and Neurology, Johns Hopkins School of Medicine, 600 N Wolfe St, Baltimore, MD 20892
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Cadavid D, Kim S, Peng B, Skurnick J, Younes M, Hill J, Wolansky LJ, Cook SD. Clinical consequences of MRI activity in treated multiple sclerosis. Mult Scler 2011; 17:1113-21. [DOI: 10.1177/1352458511405375] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: Inflammation on brain MRI is the most sensitive marker of disease activity in multiple sclerosis (MS) but its clinical consequences remain controversial. Objective: Here we investigated the clinical consequences of MRI activity in MS subjects treated with two different first line disease modifying agents. Methods: Seventy-five treatment-naïve subjects with relapsing–remitting MS ( N = 61) or clinically isolated syndromes at risk of MS ( N = 14) from the BECOME study that had been randomized to interferon beta-1b ( N = 39) or glatiramer acetate ( N = 36) and followed for up to two years by monthly brain MRI optimized to detect inflammatory activity were studied for the clinical consequences of lack of MRI remission. Results: MRI remission occurred in 46.4% of participants transiently and in 23.2% completely while it was never achieved in 30.4%. There was no difference by treatment in MRI remission, progression of physical disability, or cognitive function. The percentage of relapse-free subjects was 87.5% for the group in complete MRI remission, 47.6% in the group never in remission and 59.4% in the group in transient remission ( p = 0.017). Similar differences were observed for six-month-confirmed worsening of ambulatory function as measured by the timed 25 foot walk ( p = 0.026) and by Expanded Disability Status Scale (EDSS) ( p = 0.10). Cognitive function was lowest at baseline for the group that never reached MRI remission on treatment; this group improved the least upon repeated cognitive testing during the two years of treatment ( p < 0.001). Conclusions: Lack of MRI remission during treatment with interferon beta-1b or glatiramer acetate is associated with higher relapse rate and worsening of physical and cognitive function.
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Affiliation(s)
- Diego Cadavid
- Department of Neurology and Neuroscience, University of Medicine and Dentistry of New Jersey (UMDNJ)-New Jersey Medical School, USA
| | - Soyeon Kim
- Department of Preventive Medicine and Community Health, University of Medicine and Dentistry of New Jersey (UMDNJ)-New Jersey Medical School, USA
| | - Bo Peng
- Department of Preventive Medicine and Community Health, University of Medicine and Dentistry of New Jersey (UMDNJ)-New Jersey Medical School, USA
| | - Joan Skurnick
- Department of Preventive Medicine and Community Health, University of Medicine and Dentistry of New Jersey (UMDNJ)-New Jersey Medical School, USA
| | - Maha Younes
- Department of Neurology and Neuroscience, University of Medicine and Dentistry of New Jersey (UMDNJ)-New Jersey Medical School, USA
- Department of Psychiatry, University of Medicine and Dentistry of New Jersey (UMDNJ)-New Jersey Medical School, USA
| | - James Hill
- Department of Psychiatry, University of Medicine and Dentistry of New Jersey (UMDNJ)-New Jersey Medical School, USA
| | - Leo J Wolansky
- Department of Radiology, University of Medicine and Dentistry of New Jersey (UMDNJ)-New Jersey Medical School, USA
| | - Stuart D Cook
- Department of Neurology and Neuroscience, University of Medicine and Dentistry of New Jersey (UMDNJ)-New Jersey Medical School, USA
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Poonawalla AH, Datta S, Juneja V, Nelson F, Wolinsky JS, Cutter G, Narayana PA. Composite MRI scores improve correlation with EDSS in multiple sclerosis. Mult Scler 2010; 16:1117-25. [PMID: 20813778 DOI: 10.1177/1352458510374892] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Quantitative measures derived from magnetic resonance imaging (MRI) have been widely investigated as non-invasive biomarkers in multiple sclerosis (MS). However, the correlation of single measures with Expanded Disability Status Scale (EDSS) is poor, especially for studies with large population samples. OBJECTIVE To explore the correlation of MRI-derived measures with EDSS through composite MRI scores. METHODS Magnetic resonance images of 126 patients with relapsing-remitting MS were segmented into white and gray matter, cerebrospinal fluid, T2-hyperintense lesions, gadolinium contrast-enhancing lesions, T1-hypointense lesions ('black holes': BH). The volumes and average T2 values for each of these tissues and lesions were calculated and converted to a z-score (in units of standard deviation from the mean). These z-scores were combined to construct composite z-scores, and evaluated against individual z-scores for correlation with EDSS. RESULTS Composite scores including relaxation times of different tissues and/or volumetric measures generally correlated more strongly with EDSS than individual measures. The maximum observed correlation of a composite with EDSS was r = 0.344 (p < 0.0001), which is an improvement over the highest-performing single MRI measure (BH; r = 0.298, p < 0.001). CONCLUSION Z-transformation permits construction of composite scores including volumetric and T2-relaxation measures. Inclusion of multiple MRI measures in the composite can provide a broader characterization of the disease process, resulting in more robust correlations with EDSS.
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Affiliation(s)
- A H Poonawalla
- Department of Diagnostic and Interventional Imaging, University of Texas Medical School at Houston, Houston TX, USA
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46
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Kincses ZT, Ropele S, Jenkinson M, Khalil M, Petrovic K, Loitfelder M, Langkammer C, Aspeck E, Wallner-Blazek M, Fuchs S, Jehna M, Schmidt R, Vécsei L, Fazekas F, Enzinger C. Lesion probability mapping to explain clinical deficits and cognitive performance in multiple sclerosis. Mult Scler 2010; 17:681-9. [PMID: 21177325 DOI: 10.1177/1352458510391342] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Lesion dissemination in time and space represents a key feature and diagnostic marker of multiple sclerosis (MS). The correlation between magnetic resonance imaging (MRI) lesion load and disability is only modest, however. Strategic lesion location might at least partially account for this 'clinico-radiologic paradox'. OBJECTIVES Here we used a non-parametric permutation-based approach to map lesion location probability based on MS lesions identified on T2-weighted MRI. We studied 121 patients with clinically isolated syndrome, relapsing-remitting or secondary progressive MS and correlated these maps to assessments of neurologic and cognitive functions. RESULTS The Expanded Disability Status Scale correlated with bilateral periventricular lesion location (LL), and sensory and coordination functional system deficits correlated with lesion accumulation in distinct anatomically plausible regions, i.e. thalamus and middle cerebellar peduncule. Regarding cognitive performance, decreased verbal fluency correlated with left parietal LL comprising the putative superior longitudinal fascicle. Delayed spatial recall correlated with _amygdalar, _left frontal and parietal LL. Delayed selective reminding correlated with bilateral frontal and temporal LL. However, only part of the spectrum of cognitive and neurological problems encountered in our cohort could be explained by specific lesion location. CONCLUSIONS Lesion probability mapping supports the association of specific lesion locations with symptom development in MS, but only to limited extent.
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Affiliation(s)
- Z T Kincses
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Hungary
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Sahraian MA, Eshaghi A. Role of MRI in diagnosis and treatment of multiple sclerosis. Clin Neurol Neurosurg 2010; 112:609-15. [DOI: 10.1016/j.clineuro.2010.03.022] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2010] [Revised: 03/03/2010] [Accepted: 03/23/2010] [Indexed: 11/25/2022]
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Sahraian MA, Radue EW, Haller S, Kappos L. Black holes in multiple sclerosis: definition, evolution, and clinical correlations. Acta Neurol Scand 2010; 122:1-8. [PMID: 20003089 DOI: 10.1111/j.1600-0404.2009.01221.x] [Citation(s) in RCA: 95] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Magnetic resonance imaging (MRI) is a sensitive paraclinical test for diagnosis and assessment of disease progression in multiple sclerosis (MS) and is often used to evaluate therapeutic efficacy. The formation of new T2-hyperintense MRI lesions is commonly used to measure disease activity, but lacks specificity because edema, inflammation, gliosis, and axonal loss all contribute to T2 lesion formation. As the role of neurodegeneration in the pathophysiology of MS has become more prominent, the formation and evolution of chronic or persistent Tl-hypointense lesions (black holes) have been used as markers of axonal loss and neuronal destruction to measure disease activity. Despite the use of various detection methods, including advanced imaging techniques such as magnetization transfer imaging and magnetic resonance spectroscopy, correlation of persistent black holes with clinical outcomes in patients with MS remains uncertain. Furthermore, although axonal loss and neuronal tissue destruction are known to contribute to irreversible disability in patients with MS, there are limited data on the effect of therapy on longitudinal change in Tl-hypointense lesion volume. Measurement of black holes in clinical studies may elucidate the underlying pathophysiology of MS and may be an additional method of evaluating therapeutic efficacy.
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49
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Siepman TAM, Bettink-Remeijer MW, Hintzen RQ. Retinal nerve fiber layer thickness in subgroups of multiple sclerosis, measured by optical coherence tomography and scanning laser polarimetry. J Neurol 2010; 257:1654-60. [PMID: 20461397 PMCID: PMC2951505 DOI: 10.1007/s00415-010-5589-1] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2010] [Revised: 04/28/2010] [Accepted: 04/30/2010] [Indexed: 12/02/2022]
Abstract
Optical coherence tomography (OCT) and scanning laser polarimetry (GDx ECC) are non-invasive methods used to assess retinal nerve fiber layer (RNFL) thickness, which may be a reliable tool used to monitor axonal loss in multiple sclerosis (MS). The objectives of this study are (1) to compare OCT with the GDx ECC; (2) to assess and compare the RNFL thickness in subgroups of MS. Ophthalmologic examination and RNFL assessment by OCT and GDx were performed in 65 MS patients (26 relapsing-remitting (RRMS), ten secondary-progressive (SPMS), 29 primary-progressive (PPMS)). Twenty-eight patients (43%) had a history of optic neuritis (ON). Adjustments were made for age and disease duration. RNFL thickness was reduced in eyes with previous ON (p < 0.01). No differences were found between PPMS and relapse-onset MS. OCT and GDx ECC measurements were moderately correlated (rho = 0.73, p < 0.01). Visual field-mean deviation (MD) values correlated with OCT means (r = 0.44, p < 0.01) and GDx ECC TSNIT average (r = 0.41, p < 0.01). In patients without previous ON, EDSS correlated with MD (r = −0.36, p < 0.01), visual field-pattern standard deviation (PSD) (r = 0.30, p < 0.05), OCT means (r = −0.31–0.30, p < 0.05) and macular volume (r = −0.37, p < 0.01). For MSIS-29 physical impact score, significant correlations were found with MD (r = −0.48, p < 0.01) and PSD (r = 0.48, p < 0.01). Conclusions: No differences between PPMS and relapse-onset MS subgroups were found. RNFL thickness was reduced in eyes with previous ON. Although OCT and GDx ECC findings were moderately correlated and showed significant correlations with measures of visual function in patients without previous ON, EDSS correlated significantly with visual and OCT measures, but not with GDx ECC.
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Affiliation(s)
- Theodora A M Siepman
- Department of Neurology, MS Centre ErasMS, Erasmus MC, 's Gravendijkwal 230, 3015 CE, Rotterdam, The Netherlands
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50
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Tomassini V, Palace J. Multiple sclerosis lesions: insights from imaging techniques. Expert Rev Neurother 2009; 9:1341-59. [PMID: 19769449 DOI: 10.1586/ern.09.83] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The hallmark of multiple sclerosis (MS) pathology is the presence of inflammatory demyelinated lesions distributed throughout the CNS. Along with more diffuse tissue abnormalities, it is considered one of the major determinants of neurological deficit in MS. Conventional MRI has contributed to improve our understanding of MS pathology and has provided objective and reliable measures to monitor the effect of treatments. Advanced MRI techniques have offered the opportunity to quantify pathological changes in lesions, as well as in normal-appearing brain tissue and to characterize their dynamics. This review will discuss the characteristics and development of MS lesions and the contribution of conventional and quantitative MRI techniques to understanding pathological changes associated with them.
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Affiliation(s)
- Valentina Tomassini
- Oxford Centre for Functional MRI of the Brain (FMRIB), The University of Oxford, Department of Clinical Neurology, John Radcliffe Hospital, Headley Way, Headigton, Oxford OX39DU, UK.
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