1
|
Omrani M, Chiarelli RR, Acquaviva M, Bassani C, Dalla Costa G, Montini F, Preziosa P, Pagani L, Grassivaro F, Guerrieri S, Romeo M, Sangalli F, Colombo B, Moiola L, Zaffaroni M, Pietroboni A, Protti A, Puthenparampil M, Bergamaschi R, Comi G, Rocca MA, Martinelli V, Filippi M, Farina C. Machine learning-driven diagnosis of multiple sclerosis from whole blood transcriptomics. Brain Behav Immun 2024; 121:269-277. [PMID: 39097200 DOI: 10.1016/j.bbi.2024.07.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 07/23/2024] [Accepted: 07/28/2024] [Indexed: 08/05/2024] Open
Abstract
Multiple sclerosis (MS) is a neurological disorder characterized by immune dysregulation. It begins with a first clinical manifestation, a clinically isolated syndrome (CIS), which evolves to definite MS in case of further clinical and/or neuroradiological episodes. Here we evaluated the diagnostic value of transcriptional alterations in MS and CIS blood by machine learning (ML). Deep sequencing of more than 200 blood RNA samples comprising CIS, MS and healthy subjects, generated transcriptomes that were analyzed by the binary classification workflow to distinguish MS from healthy subjects and the Time-To-Event pipeline to predict CIS conversion to MS along time. To identify optimal classifiers, we performed algorithm benchmarking by nested cross-validation with the train set in both pipelines and then tested models generated with the train set on an independent dataset for final validation. The binary classification model identified a blood transcriptional signature classifying definite MS from healthy subjects with 97% accuracy, indicating that MS is associated with a clear predictive transcriptional signature in blood cells. When analyzing CIS data with ML survival models, prediction power of CIS conversion to MS was about 72% when using paraclinical data and 74.3% when using blood transcriptomes, indicating that blood-based classifiers obtained at the first clinical event can efficiently predict risk of developing MS. Coupling blood transcriptomics with ML approaches enables retrieval of predictive signatures of CIS conversion and MS state, thus introducing early non-invasive approaches to MS diagnosis.
Collapse
Affiliation(s)
- Maryam Omrani
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Rosaria Rita Chiarelli
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Acquaviva
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Claudia Bassani
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Gloria Dalla Costa
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Federico Montini
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Paolo Preziosa
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | | | - Francesca Grassivaro
- Dipartimento di Neuroscienze, Azienda Ospedale - Università di Padova, Padova, Italy
| | - Simone Guerrieri
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marzia Romeo
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesca Sangalli
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Bruno Colombo
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Lucia Moiola
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Mauro Zaffaroni
- Centro Sclerosi Multipla, ASST della Valle Olona, Ospedale di Gallarate, Gallarate, Italy
| | - Anna Pietroboni
- Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Milan, Italy
| | | | - Marco Puthenparampil
- Dipartimento di Neuroscienze, Azienda Ospedale - Università di Padova, Padova, Italy
| | | | - Giancarlo Comi
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Vittorio Martinelli
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Unit of Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Cinthia Farina
- Institute of Experimental Neurology and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
| |
Collapse
|
2
|
Passali M, Galea I, Knudsen MH, Lau LC, Cramer SP, Frederiksen JL. Cerebrospinal fluid neurofilament light chain in acute optic neuritis and its predictive ability of multiple sclerosis. J Neurol 2024; 271:6127-6135. [PMID: 39052040 PMCID: PMC11377639 DOI: 10.1007/s00415-024-12587-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2024] [Revised: 07/15/2024] [Accepted: 07/16/2024] [Indexed: 07/27/2024]
Abstract
BACKGROUND Studies on the capability of cerebrospinal fluid neurofilament light chain (cNfL) to predict multiple sclerosis (MS) conversion in clinically isolated syndromes have yielded varying results. OBJECTIVES To expand our understanding of cNfL in optic neuritis (ON) and investigate whether incorporating cNfL into the 2017 McDonald criteria could accelerate the diagnosis of MS in patients with ON. METHODS cNfL was measured in diagnostic samples from 74 patients with verified ON. MS was diagnosed using the 2017 McDonald criteria with a minimum observation time of two years from ON onset. RESULTS 20.5% of 44 MS-converters did not fulfil the 2017 McDonald criteria at ON onset. A doubling of cNfL was associated with 207% (74%-514%) higher odds of MS (p = 0.00042, adjusted for age). Fulfilment of ≥ 1 MRI criterion for dissemination in space (DIS) and presence of brain contrast-enhancing lesions were associated with higher cNfL. Furthermore, cNfL correlated with inter-eye differences in retinal nerve fiber layer (RNFL) thickness (Spearman's ρ = 0.46, p = 8 × 10-5). Incorporating cNfL ≥ 906 pg/mL as a substitute for either dissemination in time or one MRI criterion for DIS increased the sensitivity (90.9% vs. 79.6%) and accuracy (91.9% vs. 87.8%), but also reduced the specificity (93.3% vs. 100%) of the 2017 McDonald criteria. CONCLUSION cNfL was related to MS diagnostic parameters and the degree of RNFL swelling. Clinical use of cNfL may aid in identification of ON patients with increased risk of MS until larger studies have elaborated on the potential loss of specificity if used diagnostically.
Collapse
Affiliation(s)
- Moschoula Passali
- Optic Neuritis Clinic, Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital Rigshospitalet-Glostrup, Glostrup, Denmark.
- Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark.
| | - Ian Galea
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Maria Højberg Knudsen
- Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
- Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet-Glostrup, Glostrup, Denmark
| | - Laurie Chi Lau
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Stig Præstekjær Cramer
- Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet-Glostrup, Glostrup, Denmark
| | - Jette Lautrup Frederiksen
- Optic Neuritis Clinic, Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital Rigshospitalet-Glostrup, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
3
|
Filippi M, Preziosa P, Margoni M, Rocca MA. Diagnostic Criteria for Multiple Sclerosis, Neuromyelitis Optica Spectrum Disorders, and Myelin Oligodendrocyte Glycoprotein-immunoglobulin G-associated Disease. Neuroimaging Clin N Am 2024; 34:293-316. [PMID: 38942518 DOI: 10.1016/j.nic.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
The diagnostic workup of multiple sclerosis (MS) has evolved considerably. The 2017 revision of the McDonald criteria shows high sensitivity and accuracy in predicting clinically definite MS in patients with a typical clinically isolated syndrome and allows an earlier MS diagnosis. Neuromyelitis optica spectrum disorders (NMOSD) and myelin oligodendrocyte glycoprotein-immunoglobulin G-associated disease (MOGAD) are recognized as separate conditions from MS, with specific diagnostic criteria. New MR imaging markers may improve diagnostic specificity for these conditions, thus reducing the risk of misdiagnosis. This study summarizes the most recent updates regarding the application of MR imaging for the diagnosis of MS, NMOSD, and MOGAD.
Collapse
Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy.
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| |
Collapse
|
4
|
Jakimovski D, Qureshi F, Ramanathan M, Jalaleddini K, Ghoreyshi A, Dwyer MG, Bergsland N, Weinstock-Guttman B, Zivadinov R. Glial cell injury and atrophied lesion volume as measures of chronic multiple sclerosis inflammation. J Neurol Sci 2024; 461:123055. [PMID: 38761669 DOI: 10.1016/j.jns.2024.123055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 04/05/2024] [Accepted: 05/13/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Atrophied lesion volume (aLV), a proposed biomarker of disability progression in multiple sclerosis (MS) and transition into progressive MS (PMS), depicts chronic periventricular white matter (WM) pathology. Meningeal infiltrates, imaged as leptomeningeal contrast enhancement (LMCE), are linked with greater cortical pathology. OBJECTIVES To determine the relationship between serum-derived proteomic data with the development of aLV and LMCE in a heterogeneous group of people with MS (pwMS). METHODS Proteomic and MRI data for 202 pwMS (148 clinically isolated syndrome /relapsing-remitting MS and 54 progressive MS (PMS)) were acquired at baseline and at 5.4-year follow-up. The concentrations of 21 proteins related to multiple MS pathophysiology pathways were derived using a custom-developed Proximity Extension Assay on the Olink™ platform. The accrual of aLV was determined as the volume of baseline T2-weighted lesions that were replaced by cerebrospinal fluid over the follow-up. Regression models and age-adjusted analysis of covariance (ANCOVA) were used. RESULTS Older age (standardized beta = 0.176, p = 0.022), higher glial fibrillary acidic protein (standardized beta = 0.312, p = 0.001), and lower myelin oligodendrocyte glycoprotein levels (standardized beta = -0.271, p = 0.002) were associated with accrual of aLV over follow-up. This relationship was driven by the pwPMS population. The presence of LMCE at the follow-up visit was not predicted by any baseline proteomic biomarker nor cross-sectionally associated with any protein concentration. CONCLUSION Proteomic markers of glial activation are associated with chronic lesional WM pathology (measured as aLV) and may be specific to the progressive MS phenotype. LMCE presence in MS does not appear to relate to proteomic measures.
Collapse
Affiliation(s)
- Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
| | | | - Murali Ramanathan
- Department of Pharmaceutical Sciences, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | | | | | - Michael G Dwyer
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Bianca Weinstock-Guttman
- Department of Neurology, Jacobs Comprehensive MS Treatment and Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Center for Biomedical Imaging at the Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
| |
Collapse
|
5
|
Nguyen P, Rempe T, Forghani R. Multiple Sclerosis: Clinical Update and Clinically-Oriented Radiologic Reporting. Magn Reson Imaging Clin N Am 2024; 32:363-374. [PMID: 38555146 DOI: 10.1016/j.mric.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Multiple sclerosis (MS) is a chronic inflammatory disease of the nervous system. MR imaging findings play an integral part in establishing diagnostic hallmarks of the disease during initial diagnosis and evaluating disease status. Multiple iterations of diagnostic criteria and consensus guidelines are put forth by various expert groups incorporating imaging of the brain and spine, and efforts have been made to standardize imaging protocols for MS. Emerging ancillary imaging findings have also attracted increasing interests and should be sought for on radiologic examination. In this paper, the authors review the clinical guidelines and approach to imaging of MS and related disorders, focusing on clinically impactful image interpretation and MR imaging reporting.
Collapse
Affiliation(s)
- Phuong Nguyen
- Department of Radiology, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL 32610-0374, USA
| | - Torge Rempe
- Department of Neurology, University of Florida College of Medicine, Norman Fixel Institute for Neurological Diseases, 3009 SW Williston Road, Gainesville, FL 32608, USA
| | - Reza Forghani
- Department of Radiology, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL 32610-0374, USA; Division of Movement Disorders, Department of Neurology, University of Florida College of Medicine, Norman Fixel Institute for Neurological Diseases, 3009 SW Williston Road, Gainesville, FL 32608, USA; Division of Medical Physics, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL 32610-0374, USA; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Room 221.1, 3011 SW Williston Road, Gainesville, FL 32608, USA.
| |
Collapse
|
6
|
Rasouli S, Dakkali MS, Azarbad R, Ghazvini A, Asani M, Mirzaasgari Z, Arish M. Predicting the conversion from clinically isolated syndrome to multiple sclerosis: An explainable machine learning approach. Mult Scler Relat Disord 2024; 86:105614. [PMID: 38642495 DOI: 10.1016/j.msard.2024.105614] [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: 12/03/2023] [Revised: 04/04/2024] [Accepted: 04/07/2024] [Indexed: 04/22/2024]
Abstract
INTRODUCTION Predicting the conversion of clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS) is critical to personalizing treatment planning and benefits for patients. The aim of this study is to develop an explainable machine learning (ML) model for predicting this conversion based on demographic, clinical, and imaging data. METHOD The ML model, Extreme Gradient Boosting (XGBoost), was employed on the public dataset of 273 Mexican mestizo CIS patients with 10-year follow-up. The data was divided into a training set for cross-validation and feature selection, and a holdout test set for final testing. Feature importance was determined using the SHapley Additive Explanations library (SHAP). Then, two experiments were conducted to optimize the model's performance by selectively adding variables and selecting the most contributive variables for the final model. RESULTS Nine variables including age, gender, schooling, motor symptoms, infratentorial and periventricular lesion at imaging, oligoclonal band in cerebrospinal fluid, lesion and symptoms types were significant. The model achieved an accuracy of 83.6 %, AUC of 91.8 %, sensitivity of 83.9 %, and specificity of 83.4 % in cross-validation. In the final testing, the model achieved an accuracy of 78.3 %, AUC of 85.8 %, sensitivity of 75 %, and specificity of 81.1 %. Finally, a web-based demo of the model was created for testing purposes. CONCLUSION The model, focusing on feature selection and interpretability, effectively stratifies risk for treatment decisions and disability prevention in MS patients. It provides a numerical risk estimate for CDMS conversion, enhancing transparency in clinical decision-making and aiding in patient care.
Collapse
Affiliation(s)
- Saeid Rasouli
- School of Medicine, Five Senses Health Research Institute, Hazrat-e Rasool General Hospital, Iran University of Medical Sciences, Tehran, Iran.
| | - Mohammad Sedigh Dakkali
- Department of Ophthalmology, School of Medicine, Al Zahra Eye Hospital, Zahedan University of Medical Sciences, Zahedan, Iran
| | - Reza Azarbad
- Cellular and Molecular Biology Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Azim Ghazvini
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Mahdi Asani
- Department of Ophthalmology, School of Medicine, Al Zahra Eye Hospital, Zahedan University of Medical Sciences, Zahedan, Iran
| | - Zahra Mirzaasgari
- Department of Neurology, Firoozgar hospital, School of medicine, University of Medical Science, Iran
| | - Mohammed Arish
- Department of Ophthalmology, School of Medicine, Al Zahra Eye Hospital, Zahedan University of Medical Sciences, Zahedan, Iran
| |
Collapse
|
7
|
Snow NJ, Murphy HM, Chaves AR, Moore CS, Ploughman M. Transcranial magnetic stimulation enhances the specificity of multiple sclerosis diagnostic criteria: a critical narrative review. PeerJ 2024; 12:e17155. [PMID: 38563011 PMCID: PMC10984191 DOI: 10.7717/peerj.17155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Background Multiple sclerosis (MS) is an immune-mediated neurodegenerative disease that involves attacks of inflammatory demyelination and axonal damage, with variable but continuous disability accumulation. Transcranial magnetic stimulation (TMS) is a noninvasive method to characterize conduction loss and axonal damage in the corticospinal tract. TMS as a technique provides indices of corticospinal tract function that may serve as putative MS biomarkers. To date, no reviews have directly addressed the diagnostic performance of TMS in MS. The authors aimed to conduct a critical narrative review on the diagnostic performance of TMS in MS. Methods The authors searched the Embase, PubMed, Scopus, and Web of Science databases for studies that reported the sensitivity and/or specificity of any reported TMS technique compared to established clinical MS diagnostic criteria. Studies were summarized and critically appraised for their quality and validity. Results Seventeen of 1,073 records were included for data extraction and critical appraisal. Markers of demyelination and axonal damage-most notably, central motor conduction time (CMCT)-were specific, but not sensitive, for MS. Thirteen (76%), two (12%), and two (12%) studies exhibited high, unclear, and low risk of bias, respectively. No study demonstrated validity for TMS techniques as diagnostic biomarkers in MS. Conclusions CMCT has the potential to: (1) enhance the specificity of clinical MS diagnostic criteria by "ruling in" true-positives, or (2) revise a diagnosis from relapsing to progressive forms of MS. However, there is presently insufficient high-quality evidence to recommend any TMS technique in the diagnostic algorithm for MS.
Collapse
Affiliation(s)
- Nicholas J. Snow
- Faculty of Medicine, Memorial University of Newfoundland, St. John’s, NL, Canada
| | - Hannah M. Murphy
- Faculty of Medicine, Memorial University of Newfoundland, St. John’s, NL, Canada
| | - Arthur R. Chaves
- Faculty of Health Sciences, Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, ON, Canada
- Neuromodulation Research Clinic, The Royal’s Institute of Mental Health Research, Ottawa, ON, Canada
- Département de Psychoéducation et de Psychologie, Université du Québec en Outaouais, Gatineau, QC, Canada
| | - Craig S. Moore
- Faculty of Medicine, Memorial University of Newfoundland, St. John’s, NL, Canada
| | - Michelle Ploughman
- Faculty of Medicine, Memorial University of Newfoundland, St. John’s, NL, Canada
| |
Collapse
|
8
|
Landes-Chateau C, Levraut M, Okuda DT, Themelin A, Cohen M, Kantarci OH, Siva A, Pelletier D, Mondot L, Lebrun-Frenay C. The diagnostic value of the central vein sign in radiologically isolated syndrome. Ann Clin Transl Neurol 2024; 11:662-672. [PMID: 38186317 DOI: 10.1002/acn3.51986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 12/15/2023] [Accepted: 12/16/2023] [Indexed: 01/09/2024] Open
Abstract
OBJECTIVE The radiologically isolated syndrome (RIS) represents the earliest detectable preclinical phase of multiple sclerosis (MS). Increasing evidence suggests that the central vein sign (CVS) enhances lesion specificity, allowing for greater MS diagnostic accuracy. This study evaluated the diagnostic performance of the CVS in RIS. METHODS Patients were prospectively recruited in a single tertiary center for MS care. Participants with RIS were included and compared to a control group of sex and age-matched subjects. All participants underwent 3 Tesla magnetic resonance imaging, including postcontrast susceptibility-based sequences, and the presence of CVS was analyzed. Sensitivity and specificity were assessed for different CVS lesion criteria, defined by proportions of lesions positive for CVS (CVS+) or by the absolute number of CVS+ lesions. RESULTS 180 participants (45 RIS, 45 MS, 90 non-MS) were included, representing 5285 white matter lesions. Among them, 4608 were eligible for the CVS assessment (970 in RIS, 1378 in MS, and 2260 in non-MS). According to independent ROC comparisons, the proportion of CVS+ lesions performed similarly in diagnosing RIS from non-MS than MS from non-MS (p = 0.837). When a 6-lesion CVS+ threshold was applied, RIS lesions could be diagnosed with an accuracy of 87%. MS could be diagnosed with a sensitivity of 98% and a specificity of 83%. Adding OCBs or Kappa index to CVS biomarker increased the specificity to 100% for RIS diagnosis. INTERPRETATION This study shows evidence that CVS is an effective imaging biomarker in differentiating RIS from non-MS, with similar performances to those in MS.
Collapse
Affiliation(s)
| | - Michael Levraut
- Université Cote d'Azur, UMR2CA (URRIS), Nice, France
- Service de Médecine Interne, Centre Hospitalier Universitaire de Nice, Hôpital l'Archet 1, Nice, France
| | - Darin T Okuda
- The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Albert Themelin
- Service de Radiologie, Centre Hospitalier Universitaire de Nice, Hôpital Pasteur 2, Nice, France
| | - Mikael Cohen
- Université Cote d'Azur, UMR2CA (URRIS), Nice, France
- Service de Neurologie, Centre de Ressource et de Compétence Sclérose en Plaques (CRC-SEP), Centre Hospitalier Universitaire de Nice, Hôpital Pasteur 2, Nice, France
| | | | - Aksel Siva
- Istanbul University, Cerrahpasa School of Medicine, Istanbul, Turkey
| | | | - Lydiane Mondot
- Université Cote d'Azur, UMR2CA (URRIS), Nice, France
- Service de Radiologie, Centre Hospitalier Universitaire de Nice, Hôpital Pasteur 2, Nice, France
| | - Christine Lebrun-Frenay
- Université Cote d'Azur, UMR2CA (URRIS), Nice, France
- Service de Neurologie, Centre de Ressource et de Compétence Sclérose en Plaques (CRC-SEP), Centre Hospitalier Universitaire de Nice, Hôpital Pasteur 2, Nice, France
| |
Collapse
|
9
|
Haki M, AL-Biati HA, Al-Tameemi ZS, Ali IS, Al-hussaniy HA. Review of multiple sclerosis: Epidemiology, etiology, pathophysiology, and treatment. Medicine (Baltimore) 2024; 103:e37297. [PMID: 38394496 PMCID: PMC10883637 DOI: 10.1097/md.0000000000037297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 01/25/2024] [Accepted: 01/26/2024] [Indexed: 02/25/2024] Open
Abstract
Multiple sclerosis (MS) is a chronic autoimmune disease with demyelination, inflammation, neuronal loss, and gliosis (scarring). Our object to review MS pathophysiology causes and treatment. A Narrative Review article was conducted by searching on Google scholar, PubMed, Research Gate about relevant keywords we exclude any unique cases and case reports. The destruction of myelinated axons in the central nervous system reserves this brunt. This destruction is generated by immunogenic T cells that produce cytokines, copying a proinflammatory T helper cells1-mediated response. Autoreactive cluster of differentiation 4 + cells, particularly the T helper cells1 subtype, are activated outside the system after viral infections. T-helper cells (cluster of differentiation 4+) are the leading initiators of MS myelin destruction. The treatment plan for individuals with MS includes managing acute episodes, using disease-modifying agents to decrease MS biological function of MS, and providing symptom relief. Management of spasticity requires physiotherapy, prescription of initial drugs such as baclofen or gabapentin, secondary drug options such as tizanidine or dantrolene, and third-line treatment such as benzodiazepines. To treat urinary incontinence some options include anticholinergic medications such as oxybutynin hydrochloride, tricyclic antidepressants (such as amitriptyline), and intermittent self-catheterization. When it comes to bowel problems, one can try to implement stool softeners and consume a high roughage diet. The review takes about MS causes Pathophysiology and examines current treatment strategies, emphasizing the advancements in disease-modifying therapies and symptomatic treatments. This comprehensive analysis enhances the understanding of MS and underscores the ongoing need for research to develop more effective treatments.
Collapse
Affiliation(s)
- Maha Haki
- Department of Pharmacy, Bilad Alrafidain University College, Diyala, Iraq
| | - Haeder A. AL-Biati
- Department of Pharmacy, Bilad Alrafidain University College, Diyala, Iraq
| | - Zahraa Salam Al-Tameemi
- Department of Pharmacy, Bilad Alrafidain University College, Diyala, Iraq
- Dr. Hany Akeel Institute, Iraqi Medical Research Center, Baghdad, Iraq
| | - Inas Sami Ali
- Department of Pharmacy, Bilad Alrafidain University College, Diyala, Iraq
| | - Hany A. Al-hussaniy
- Department of Pharmacy, Bilad Alrafidain University College, Diyala, Iraq
- Dr. Hany Akeel Institute, Iraqi Medical Research Center, Baghdad, Iraq
- Department of Pharmacology, College of Medicine, University of Baghdad, Baghdad, Iraq
| |
Collapse
|
10
|
Obeidat AZ. Time to involve the multiple sclerosis expert community at large when revising the McDonald diagnostic criteria. Mult Scler Relat Disord 2024; 82:105389. [PMID: 38118288 DOI: 10.1016/j.msard.2023.105389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 12/15/2023] [Indexed: 12/22/2023]
Abstract
Prof. Kurtzke once said, "Multiple sclerosis is what a good clinician would call multiple sclerosis." Recent McDonald's diagnostic criteria revisions have allowed for earlier diagnoses over the past decades. Revisions often allowed increasing sensitivity but at the expense of lowering specificity. In this correspondence, I suggest that the multiple sclerosis expert community worldwide should be given the opportunity to comment and provide feedback on the proposed revisions of the diagnostic criteria before their publication via providing a duration where open commentaries are welcomed to allow for the expert panel to incorporate diverse feedback to improve the final product.
Collapse
Affiliation(s)
- Ahmed Z Obeidat
- Department of Neurology, Division of Neuroimmunology and Multiple Sclerosis, Medical College of Wisconsin, Hub of Collaborative Research, 8701 Watertown Plank Road, Milwaukee, WI 53226, United States.
| |
Collapse
|
11
|
Cagol A, Cortese R, Barakovic M, Schaedelin S, Ruberte E, Absinta M, Barkhof F, Calabrese M, Castellaro M, Ciccarelli O, Cocozza S, De Stefano N, Enzinger C, Filippi M, Jurynczyk M, Maggi P, Mahmoudi N, Messina S, Montalban X, Palace J, Pontillo G, Pröbstel AK, Rocca MA, Ropele S, Rovira À, Schoonheim MM, Sowa P, Strijbis E, Wattjes MP, Sormani MP, Kappos L, Granziera C. Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis. JAMA Neurol 2024; 81:143-153. [PMID: 38079177 PMCID: PMC10714285 DOI: 10.1001/jamaneurol.2023.4737] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 10/06/2023] [Indexed: 02/13/2024]
Abstract
Importance Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. Objective To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). Design, Setting, and Participants This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). Exposures MS/CIS vs non-MS conditions. Main Outcomes and Measures Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. Results The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. Conclusions and Relevance The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis.
Collapse
Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Health Sciences, University of Genova, Genova, Italy
| | - Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Muhamed Barakovic
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Sabine Schaedelin
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Esther Ruberte
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Medical Image Analysis Center, Basel, Switzerland
| | - Martina Absinta
- Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University and Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
| | - Frederik Barkhof
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, United Kingdom
- Multiple Sclerosis Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
| | - Massimiliano Calabrese
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Marco Castellaro
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Olga Ciccarelli
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- National Institute for Health and Care Research (NIHR) University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Sirio Cocozza
- Departments of Advanced Biomedical Sciences and Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Christian Enzinger
- Department of Neurology, Medical University of Graz, Graz, Austria
- Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Maciej Jurynczyk
- Department of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Laboratory of Brain Imaging, Neurobiology Center, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Pietro Maggi
- Department of Neurology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
- Neuroinflammation Imaging Lab, Institute of Neuroscience, Université catholique de Louvain, Brussels, Belgium
| | - Nima Mahmoudi
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Silvia Messina
- Department of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Xavier Montalban
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
- Division of Neurology, St Michael’s Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Jacqueline Palace
- Department of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Giuseppe Pontillo
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- Multiple Sclerosis Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
- Departments of Advanced Biomedical Sciences and Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
| | - Anne-Katrin Pröbstel
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Departments of Biomedicine and Clinical Research, University Hospital of Basel and University of Basel, Basel, Switzerland
| | - Maria A. Rocca
- Neuroimaging Research Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
- Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Menno M. Schoonheim
- Multiple Sclerosis Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
| | - Piotr Sowa
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Eva Strijbis
- Multiple Sclerosis Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
| | - Mike P. Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Maria Pia Sormani
- Department of Health Sciences, University of Genova, Genova, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico, Ospedale Policlinico San Martino, Genova, Italy
| | - Ludwig Kappos
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| |
Collapse
|
12
|
Ferrand M, Epstein J, Soudant M, Guillemin F, Pittion-Vouyovitch S, Debouverie M, Mathey G. Real-life evaluation of the 2017 McDonald criteria for relapsing-remitting multiple sclerosis after a clinically isolated syndrome confirms a gain in time-to-diagnosis. J Neurol 2024; 271:125-133. [PMID: 37650895 DOI: 10.1007/s00415-023-11905-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 07/25/2023] [Accepted: 07/25/2023] [Indexed: 09/01/2023]
Abstract
BACKGROUND Previous cohort studies evaluating the performances of the McDonald criteria suffered from bias regarding real-life conditions. We aimed to evaluate the probability of diagnosing relapsing-remitting multiple sclerosis (MS) at several timepoints from the first medical evaluation and the gain in time-to-diagnosis with the 2017 McDonald criteria compared with the 2001, 2005 and 2010 versions in real life. METHODS Patients with a first demyelinating event suggestive of MS between 2002 and 2020 were included in the ReLSEP, an exhaustive and prospectively incremented registry of MS patients in North-Eastern France. We estimated the probability of being positive at the first medical evaluation and at five timepoints according to the four versions of criteria using Kaplan-Meier estimators and Cox models. RESULTS A total of 2220 patients were followed up for a median of 7.1 years. At baseline, 31.7%, 32.1%, 36.6% and 54.0% of patients, respectively, fulfilled the 2001, 2005, 2010 and 2017 McDonald criteria. Using the 2017 criteria, the gain in time-to-diagnosis was 3.7 months compared with the 2010 criteria. The presence of intrathecal synthesis of immunoglobulin G in the McDonald 2017 criteria led to a 1.8-month reduction in median time-to-diagnosis compared to a version of McDonald 2017 without this criteria. CONCLUSIONS In real-life, the 2017 McDonald criteria revision undoubtedly shortened time-to-diagnosis.
Collapse
Affiliation(s)
- Mickaël Ferrand
- Department of Neurology, Nancy University Hospital, 54035, Nancy, France
| | - Jonathan Epstein
- Université de Lorraine, APEMAC, 54000, Nancy, France
- CHRU-Nancy, INSERM, Université de Lorraine, CIC, Epidémiologie Clinique, 54000, Nancy, France
| | - Marc Soudant
- CHRU-Nancy, INSERM, Université de Lorraine, CIC, Epidémiologie Clinique, 54000, Nancy, France
| | - Francis Guillemin
- Université de Lorraine, APEMAC, 54000, Nancy, France
- CHRU-Nancy, INSERM, Université de Lorraine, CIC, Epidémiologie Clinique, 54000, Nancy, France
| | | | - Marc Debouverie
- Department of Neurology, Nancy University Hospital, 54035, Nancy, France
- Université de Lorraine, APEMAC, 54000, Nancy, France
| | - Guillaume Mathey
- Department of Neurology, Nancy University Hospital, 54035, Nancy, France.
- Université de Lorraine, APEMAC, 54000, Nancy, France.
| |
Collapse
|
13
|
Mizell R. The Impact of Insurance Restrictions in Newly Diagnosed Individuals With Multiple Sclerosis. Int J MS Care 2024; 26:17-21. [PMID: 38213675 PMCID: PMC10779716 DOI: 10.7224/1537-2073.2022-069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
Abstract
BACKGROUND The medical system in the United States has been riddled with insurance restrictions used by insurance companies to limit health care costs. The effects of insurance restrictions on patients receiving disease-modifying therapies for multiple sclerosis (MS) have not been specifically studied. METHODS A retrospective cross-sectional study of 52 individuals recently diagnosed with MS at a tertiary neurology clinic was conducted to measure the association between prior authorization (PA) duration and other variables of interest. The Cox proportional hazards model was used to determine likelihood of approval. Further analysis included multivariable logistic regression to assess the influence of variables of interest on the initial decision from the insurance company and the effect of the PA on disease activity. RESULTS Of 52 PAs, 50% were initially denied. An initial denial decreased the likelihood of approval by 98% (HR, 0.02; 95% CI, <0.01-0.09; P < .001). The odds of denial for oral medications (odds ratio [OR], 4.91; 95% CI, 1.33-21.52; P = .02) and infusions (OR, 8.35; 95% CI, 1.10-88.77; P = .05) were significantly higher than for injections. Medicaid had higher odds of denial compared with commercial insurance (OR, 4.51; 95% CI, 1.13-22.01; P = .04). An initial denial by insurance significantly increased the likelihood of disease activity (OR, 6.18; 95% CI, 1.33-44.86; P = .03). CONCLUSIONS Insurance restrictions delay necessary treatments, increase the likelihood of disease activity, and rarely change the approved disease-modifying therapy. Reducing PAs may lead to improved outcomes for patients with MS.
Collapse
Affiliation(s)
- Ryan Mizell
- From AdventHealth Neurology, Orlando, FL, USA
| |
Collapse
|
14
|
Amezcua L, Robers MV, Soneji D, Manouvakhova O, Martinez A, Islam T. Inclusion of optic neuritis in dissemination in space improves the performance of McDonald 2017 criteria in Hispanic people with suspected multiple sclerosis. Mult Scler 2023; 29:1748-1754. [PMID: 37942880 PMCID: PMC10841903 DOI: 10.1177/13524585231209016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
BACKGROUND Hispanic people compared to White people with multiple sclerosis (MS) are two times more likely to present with optic neuritis (ON). ON in dissemination in space (DIS) after a single attack is not part of the current McDonald 2017 criteria. OBJECTIVE To evaluate if adding ON in DIS (ON-modified criteria) improves the performance of the McDonald 2017 criteria in the diagnosis of MS after a single attack of ON. METHODS Retrospective study of 102 patients of Hispanic background. Cases were reviewed between 2017 and 2021. Clinical ON was reported for 35 cases. ON in DIS was verified for 28 patients via MRI, optical coherence tomography, and/or visual evoked potential. We investigated the performance of the McDonald 2017 criteria and ON-modified criteria and calculated sensitivity, specificity, positive and negative predictive values, and accuracy. RESULTS The ON-modified criteria significantly improved the performance of the McDonald 2017 criteria (p = 0.003) and identified an additional nine patients. Both sensitivity and accuracy increased from 64% to 74% and 62% to 71%, respectively, while specificity remained unchanged (40% (95% confidence interval (CI): 0.10, 0.70)). CONCLUSION This study provides evidence that the inclusion of ON in DIS improved the overall performance of the McDonald 2017 criteria among Hispanic people.
Collapse
Affiliation(s)
- Lilyana Amezcua
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Deepak Soneji
- Neurology and Neuroophthalmology, Sutter East Bay Medical Group, Lafayette, CA, USA
| | - Olga Manouvakhova
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Andrea Martinez
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Talat Islam
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| |
Collapse
|
15
|
Filippi M, Rocca MA. Radiologically isolated syndrome: knowns and unknowns. Lancet Neurol 2023; 22:978-979. [PMID: 37839431 DOI: 10.1016/s1474-4422(23)00362-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 09/13/2023] [Accepted: 09/13/2023] [Indexed: 10/17/2023]
Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy; Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy.
| | - Maria A Rocca
- Neuroimaging Research Unit, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy; Vita-Salute San Raffaele University, Milan, Italy
| |
Collapse
|
16
|
Lipka A, Bogner W, Dal-Bianco A, Hangel GJ, Rommer PS, Strasser B, Motyka S, Hingerl L, Berger T, Leutmezer F, Gruber S, Trattnig S, Niess E. Metabolic Insights into Iron Deposition in Relapsing-Remitting Multiple Sclerosis via 7 T Magnetic Resonance Spectroscopic Imaging. Neuroimage Clin 2023; 40:103524. [PMID: 37839194 PMCID: PMC10590870 DOI: 10.1016/j.nicl.2023.103524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 09/26/2023] [Accepted: 10/07/2023] [Indexed: 10/17/2023]
Abstract
OBJECTIVE To investigate the metabolic pattern of different types of iron accumulation in multiple sclerosis (MS) lesions, and compare metabolic alterations within and at the periphery of lesions and newly emerging lesions in vivo according to iron deposition. METHODS 7 T MR spectroscopic imaging and susceptibility-weighted imaging was performed in 31 patients with relapsing-remitting MS (16 female/15 male; mean age, 36.9 ± 10.3 years). Mean metabolic ratios of four neuro-metabolites were calculated for regions of interest (ROI) of normal appearing white matter (NAWM), "non-iron" (lesion without iron accumulation on SWI), and three distinct types of iron-laden lesions ("rim": distinct rim-shaped iron accumulation; "area": iron deposition across the entire lesions; "transition": transition between "area" and "rim" accumulation shape), and for lesion layers of "non-iron" and "rim" lesions. Furthermore, newly emerging "non-iron" and "iron" lesions were compared longitudinally, as measured before their appearance and one year later. RESULTS Thirty-nine of 75 iron-containing lesions showed no distinct paramagnetic rim. Of these, "area" lesions exhibited a 65% higher mIns/tNAA (p = 0.035) than "rim" lesions. Comparing lesion layers of both "non-iron" and "rim" lesions, a steeper metabolic gradient of mIns/tNAA ("non-iron" +15%, "rim" +40%) and tNAA/tCr ("non-iron" -15%, "rim" -35%) was found in "iron" lesions, with the lesion core showing +22% higher mIns/tNAA (p = 0.005) and -23% lower tNAA/tCr (p = 0.048) in "iron" compared to "non-iron" lesions. In newly emerging lesions, 18 of 39 showed iron accumulation, with the drop in tNAA/tCr after lesion formation remaining significantly lower compared to pre-lesional tissue over time in "iron" lesions (year 0: p = 0.013, year 1: p = 0.041) as opposed to "non-iron" lesions (year 0: p = 0.022, year 1: p = 0.231). CONCLUSION 7 T MRSI allows in vivo characterization of different iron accumulation types each presenting with a distinct metabolic profile. Furthermore, the larger extent of neuronal damage in lesions with a distinct iron rim was reconfirmed via reduced tNAA/tCr concentrations, but with metabolic differences in lesion development between (non)-iron-containing lesions. This highlights the ability of MRSI to further investigate different types of iron accumulation and suggests possible implications for disease monitoring.
Collapse
Affiliation(s)
- Alexandra Lipka
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna.
| | | | - Gilbert J Hangel
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Paulus S Rommer
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Stanislav Motyka
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Thomas Berger
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Fritz Leutmezer
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Stephan Gruber
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Karl Landsteiner Institute for Clinical Molecular MRI in Musculoskeletal System, Vienna, Austria
| | - Eva Niess
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna
| |
Collapse
|
17
|
Cobo-Calvo A, Tur C, Otero-Romero S, Carbonell-Mirabent P, Ruiz M, Pappolla A, Villacieros Alvarez J, Vidal-Jordana A, Arrambide G, Castilló J, Galan I, Rodríguez Barranco M, Midaglia LS, Nos C, Rodriguez Acevedo B, Zabalza de Torres A, Mongay N, Rio J, Comabella M, Auger C, Sastre-Garriga J, Rovira A, Tintore M, Montalban X. Association of Very Early Treatment Initiation With the Risk of Long-term Disability in Patients With a First Demyelinating Event. Neurology 2023; 101:e1280-e1292. [PMID: 37468284 PMCID: PMC10558169 DOI: 10.1212/wnl.0000000000207664] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 06/02/2023] [Indexed: 07/21/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Early treatment is associated with better long-term outcomes in patients with a first demyelinating event and early multiple sclerosis (MS). However, magnetic resonance (MR) findings are not usually integrated to construct propensity scores (PSs) when evaluating outcomes. We assessed the association of receiving very early treatment with the risk of long-term disability including an MR score (MRS) in patients with a first demyelinating event. METHODS We included 580 patients with a first demyelinating event prospectively collected between 1994 and 2021, who received at least 1 disease-modifying drug (DMD). Patients were classified into tertiles according to the cohort's distribution of the time from the first demyelinating event to the first DMD: first tertile (FT) or very early treatment (6 months; n = 194), second tertile (6.1-16 months, n = 192), and third tertile (TT) (16.1 months, n = 194). A 5-point MRS was built according to the sum of the following indicators: ≥9 brain lesions (1 point); ≥1 infratentorial lesion (1 point); ≥1 spinal cord (SC) lesion (1 point); ≥1 contrast-enhancing (CE) brain lesion (1 point); and ≥1 CE SC lesion (1 point). PS based on covariates and the MRS was computed for each of the outcomes. Inverse PS-weighted Cox and linear regression models assessed the risk of different outcomes between tertile groups. Finally, to confirm the role of MR in treatment decision, we studied the time elapsed from the first demyelinating event to treatment initiation according to the MRS in all patients with radiologic available information, renamed as raw-MRS. RESULTS Very early treatment decreased the risk of reaching Expanded Disability Status Scale 3.0 (hazard ratio [HR] 0.55, 95% CI 0.32-0.97), secondary progressive MS (HR 0.40, 95% CI 0.19-0.85), and sustained disease progression at 12 months after treatment initiation (HR 0.50, 95% CI 0.29-0.84), when compared with patients from the TT group. Patients from the FT group had a lower disability progression rate (β estimate -0.009, 95% CI -0.016 to -0.002) and a lower severe disability measured by the Patient-Determined Disease Step (β estimate -0.52, 95% CI -0.91 to -0.13) than the TT group. Finally, there was a 62.4% reduction in the median time between the first demyelinating event and the first-ever treatment initiation from patients displaying a raw-MRS 1 to patients with a raw-MRS 5. DISCUSSION Using PS models with and without MRS, we showed that treatment initiation at very early stages is associated with a reduction in the risk of long-term disability accrual in patients with a first demyelinating event. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that earlier treatment of patients with MS presenting with a first demyelinating event is associated with improved clinical outcomes.
Collapse
Affiliation(s)
- Alvaro Cobo-Calvo
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain.
| | - Carmen Tur
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Susana Otero-Romero
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Pere Carbonell-Mirabent
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Mariano Ruiz
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Agustin Pappolla
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Javier Villacieros Alvarez
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Angela Vidal-Jordana
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Georgina Arrambide
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Joaquín Castilló
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Ingrid Galan
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Marta Rodríguez Barranco
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Luciana Soledad Midaglia
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Carlos Nos
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Breogan Rodriguez Acevedo
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Ana Zabalza de Torres
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Neus Mongay
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Jordi Rio
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Manuel Comabella
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Cristina Auger
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Jaume Sastre-Garriga
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Alex Rovira
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Mar Tintore
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| | - Xavier Montalban
- From the Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (A.C.-C., C.T., S.O.-R., P.C.-M., A.P., J.V.A., A.V.-J., G.A., J.C., I.G., M.R.B., L.S.M., C.N., B.R.A., A.Z.d.T., N.M., J.R., M.C., J.S.-G., M.T., X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona; Department of Neurology (M.R.), Hospital Universitario Doce de Octubre, Madrid; and Section of Neuroradiology (C.A., A.R.), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain
| |
Collapse
|
18
|
Solomon AJ, Marrie RA, Viswanathan S, Correale J, Magyari M, Robertson NP, Saylor DR, Kaye W, Rechtman L, Bae E, Shinohara R, King R, Laurson-Doube J, Helme A. Global Barriers to the Diagnosis of Multiple Sclerosis: Data From the Multiple Sclerosis International Federation Atlas of MS, Third Edition. Neurology 2023; 101:e624-e635. [PMID: 37321866 PMCID: PMC10424832 DOI: 10.1212/wnl.0000000000207481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 04/18/2023] [Indexed: 06/17/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Recent data suggest increasing global prevalence of multiple sclerosis (MS). Early diagnosis of MS reduces the burden of disability-adjusted life years and associated health care costs. Yet diagnostic delays persist in MS care and even within national health care systems with robust resources, comprehensive registries, and MS subspecialist referral networks. The global prevalence and characteristics of barriers to expedited MS diagnosis, particularly in resource-restricted regions, have not been extensively studied. Recent revisions to MS diagnostic criteria demonstrate potential to facilitate earlier diagnosis, but global implementation remains largely unknown. METHODS The Multiple Sclerosis International Federation third edition of the Atlas of MS was a survey that assessed the current global state of diagnosis including adoption of MS diagnostic criteria; barriers to diagnosis with respect to the patient, health care provider, and health system; and existence of national guidelines or national standards for speed of MS diagnosis. RESULTS Coordinators from 107 countries (representing approximately 82% of the world population), participated. Eighty-three percent reported at least 1 "major barrier" to early MS diagnosis. The most frequently reported barriers included the following: "lack of awareness of MS symptoms among general public" (68%), "lack of awareness of MS symptoms among health care professionals" (59%), and "lack of availability of health care professionals with knowledge to diagnose MS" (44%). One-third reported lack of "specialist medical equipment or diagnostic tests." Thirty-four percent reported the use of only 2017 McDonald criteria (McD-C) for diagnosis, and 79% reported 2017 McD-C as the "most commonly used criteria." Sixty-six percent reported at least 1 barrier to the adoption of 2017 McD-C, including "neurologists lack awareness or training" by 45%. There was no significant association between national guidelines pertaining to MS diagnosis or practice standards addressing the speed of diagnosis and presence of barriers to early MS diagnosis and implementation of 2017 McD-C. DISCUSSION This study finds pervasive consistent global barriers to early diagnosis of MS. While these barriers reflected a lack of resources in many countries, data also suggest that interventions designed to develop and implement accessible education and training can provide cost-effective opportunities to improve access to early MS diagnosis.
Collapse
Affiliation(s)
- Andrew J Solomon
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom.
| | - Ruth Ann Marrie
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Shanthi Viswanathan
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Jorge Correale
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Melinda Magyari
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Neil P Robertson
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Deanna R Saylor
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Wendy Kaye
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Lindsay Rechtman
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Eunchan Bae
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Russell Shinohara
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Rachel King
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Joanna Laurson-Doube
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| | - Anne Helme
- From the Department of Neurological Sciences (A.J.S.), Larner College of Medicine at the University of Vermont, Burlington; Departments of Internal Medicine and Community Health Science (R.A.M.), Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada; Department of Neurology (S.V.), Kuala Lumpur Hospital, Malaysia; Departamento de Neurologia (J.C.), Fleni, Buenos Aires; Institute of Biological Chemistry and Physical Chemistry (IQUIFIB) (J.C.), National Council for Scientific and Technical Research/University of Buenos Aires, Argentina; Department of Neurology (M.M.), Rigshospitalet, Copenhagen University Hospital, Denmark; Division of Psychological Medicine and Clinical Neuroscience (N.P.R.), Department of Neurology, Cardiff University, University Hospital of Wales, United Kingdom; Department of Neurology (D.R.S.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Internal Medicine (D.R.S.), University Teaching Hospital, Lusaka, Zambia; McKing Consulting Corporation (W.K., L.R.), Atlanta, GA; Department of Biostatistics, Epidemiology, and Informatics (E.B., R.S.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; and Multiple Sclerosis International Federation (R.K., J.L.-D., A.H.), London, United Kingdom
| |
Collapse
|
19
|
Chavarria V, Espinosa-Ramírez G, Sotelo J, Flores-Rivera J, Anguiano O, Hernández AC, Guzmán-Ríos ED, Salazar A, Ordoñez G, Pineda B. Conversion Predictors of Clinically Isolated Syndrome to Multiple Sclerosis in Mexican Patients: A Prospective Study. Arch Med Res 2023:102843. [PMID: 37429750 DOI: 10.1016/j.arcmed.2023.102843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 05/13/2023] [Accepted: 06/27/2023] [Indexed: 07/12/2023]
Abstract
BACKGROUND Clinically Isolated Syndrome (CIS) is the first clinical episode suggestive of Clinical Definite Multiple Sclerosis (CDMS). There are no reports on possible predictors of conversion to CDMS in Mexican mestizo patients. AIM OF THE STUDY To investigate immunological markers, clinical and paraclinical findings, and the presence of herpesvirus DNA to predict the transition from CIS to CDMS in Mexican patients. METHODS A single-center prospective cohort study was conducted with newly diagnosed patients with CIS in Mexico between 2006 and 2010. Clinical information, immunophenotype, serum cytokines, anti-myelin protein immunoglobulins, and herpes viral DNA were determined at the time of diagnosis. RESULTS 273 patients diagnosed with CIS met the enrolment criteria; after 10 years of follow-up, 46% met the 2010 McDonald criteria for CDMS. Baseline parameters associated with conversion to CDMS were motor symptoms, multifocal syndromes, and alterations of somatosensory evoked potentials. The presence of at least one lesion on magnetic resonance imaging was the main factor associated with an increased risk of conversion to CDMS (RR 15.52, 95% CI 3.96-60.79, p = 0.000). Patients who converted to CDMS showed a significantly lower percentage of circulating regulatory T cells, cytotoxic T cells, and B cells, and the conversion to CDMS was associated with the presence of varicella-zoster virus and herpes simplex virus 1 DNA in cerebrospinal fluid and blood. CONCLUSION There is scarce evidence in Mexico regarding the demographic and clinical aspects of CIS and CDMS. This study shows several predictors of conversion to CDMS to be considered in Mexican patients with CIS.
Collapse
Affiliation(s)
- Víctor Chavarria
- Neuroimmunology Unit, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | | | - Julio Sotelo
- Neuroimmunology Unit, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | - José Flores-Rivera
- Demyelinating Diseases Clinic, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | - Omar Anguiano
- Neuroimmunology Unit, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | - Ana Campos Hernández
- Neuroimmunology Unit, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | | | - Aleli Salazar
- Neuroimmunology Unit, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | - Graciela Ordoñez
- Neuroimmunology Unit, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | - Benjamin Pineda
- Neuroimmunology Unit, National Institute of Neurology and Neurosurgery, Mexico City, Mexico.
| |
Collapse
|
20
|
Pike SC, Gilli F, Pachner AR. The CXCL13 Index as a Predictive Biomarker for Activity in Clinically Isolated Syndrome. Int J Mol Sci 2023; 24:11050. [PMID: 37446228 DOI: 10.3390/ijms241311050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 06/22/2023] [Accepted: 07/01/2023] [Indexed: 07/15/2023] Open
Abstract
Multiple sclerosis (MS) is a clinically heterogenous disease. Currently, we cannot identify patients with more active disease who may potentially benefit from earlier interventions. Previous data from our lab identified the CXCL13 index (ICXCL13), a measure of intrathecal production of CXCL13, as a potential biomarker to predict future disease activity in MS patients two years after diagnosis. Patients with clinically isolated syndrome (CIS) or radiologically isolated syndrome (RIS) underwent a lumbar puncture and blood draw, and the ICXCL13 was determined. They were then followed for at least 5 years for MS activity. Patients with high ICXCL13 were more likely to convert to clinically definite MS (82.4%) compared to those with low ICXCL13 (10.0%). The data presented below demonstrate that this predictive ability holds true in CIS and RIS patients, and for at least five years compared to our initial two-year follow-up study. These data support the concept that ICXCL13 has the potential to be used to guide immunomodulatory therapy in MS.
Collapse
Affiliation(s)
- Steven C Pike
- Department of Neurology, Geisel School of Medicine at Dartmouth and Dartmouth Hitchcock Medical Center, Lebanon, NH 03756, USA
- Integrative Neuroscience at Dartmouth, Guarini School of Graduate and Advanced Studies, Hanover, NH 03755, USA
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
| | - Francesca Gilli
- Department of Neurology, Geisel School of Medicine at Dartmouth and Dartmouth Hitchcock Medical Center, Lebanon, NH 03756, USA
- Integrative Neuroscience at Dartmouth, Guarini School of Graduate and Advanced Studies, Hanover, NH 03755, USA
| | - Andrew R Pachner
- Department of Neurology, Geisel School of Medicine at Dartmouth and Dartmouth Hitchcock Medical Center, Lebanon, NH 03756, USA
| |
Collapse
|
21
|
Rocca MA, Margoni M, Battaglini M, Eshaghi A, Iliff J, Pagani E, Preziosa P, Storelli L, Taoka T, Valsasina P, Filippi M. Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice. Radiology 2023; 307:e221512. [PMID: 37278626 PMCID: PMC10315528 DOI: 10.1148/radiol.221512] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 11/28/2022] [Accepted: 01/17/2023] [Indexed: 06/07/2023]
Abstract
MRI plays a central role in the diagnosis of multiple sclerosis (MS) and in the monitoring of disease course and treatment response. Advanced MRI techniques have shed light on MS biology and facilitated the search for neuroimaging markers that may be applicable in clinical practice. MRI has led to improvements in the accuracy of MS diagnosis and a deeper understanding of disease progression. This has also resulted in a plethora of potential MRI markers, the importance and validity of which remain to be proven. Here, five recent emerging perspectives arising from the use of MRI in MS, from pathophysiology to clinical application, will be discussed. These are the feasibility of noninvasive MRI-based approaches to measure glymphatic function and its impairment; T1-weighted to T2-weighted intensity ratio to quantify myelin content; classification of MS phenotypes based on their MRI features rather than on their clinical features; clinical relevance of gray matter atrophy versus white matter atrophy; and time-varying versus static resting-state functional connectivity in evaluating brain functional organization. These topics are critically discussed, which may guide future applications in the field.
Collapse
Affiliation(s)
- Maria Assunta Rocca
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Monica Margoni
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Marco Battaglini
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Arman Eshaghi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Jeffrey Iliff
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paolo Preziosa
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Loredana Storelli
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Toshiaki Taoka
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paola Valsasina
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| |
Collapse
|
22
|
Houzen H, Kano T, Kondo K, Takahashi T, Niino M. The prevalence and incidence of multiple sclerosis over the past 20 years in northern Japan. Mult Scler Relat Disord 2023; 73:104696. [PMID: 37028125 DOI: 10.1016/j.msard.2023.104696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 03/27/2023] [Accepted: 04/01/2023] [Indexed: 04/04/2023]
Abstract
OBJECTIVES The prevalence of multiple sclerosis (MS) in East Asia is thought to be lower than in Western countries. Globally, there is a trend of increasing MS prevalence. We investigated the changes in the prevalence and clinical phenotype of MS in the Tokachi province of Hokkaido in northern Japan, from 2001 to 2021. METHODS Data processing sheets were sent to all related institutions inside and outside the Tokachi area of Hokkaido island in Japan and were collected from April to May 2021. The prevalence according to the Poser's diagnostic criteria for MS was determined on March 31, 2021. RESULTS In 2021, the crude MS prevalence in northern Japan was 22.4/100,000 (95% confidence interval, 17.6-28.0). The prevalences of MS standardized by the Japanese national population in 2001, 2006, 2011, 2016, and 2021 were 6.9, 11.5, 15.3, 18.5, and 23.3, respectively. The female/male ratio was 4.0 in 2021, increased from 2.6 in 2001. We checked the prevalence using the 2017 revised McDonald criteria, and found only additional male patient who had not fulfilled Poser's criteria. The age- and sex-adjusted incidence of MS per 100,000 individuals increased from 0.09 in 1980-1984 to 0.99 in 2005-2009; since then, it has remained stable. The proportions of primary-progressive, relapsing-remitting, and secondary-progressive MS types in 2021 were 3%, 82%, and 15%, respectively. CONCLUSION Our results demonstrated a consistent increase in the prevalence of MS among the northern Japanese over 20 years, particularly in females, and consistently lower rates of progressive MS in northern Japan than elsewhere in the world.
Collapse
|
23
|
Marrodan M, Piedrabuena MA, Gaitan MI, Fiol MP, Ysrraelit MC, Carnero Conttenti E, Lopez PA, Peuchot V, Correale J. Performance of McDonald 2017 multiple sclerosis diagnostic criteria and evaluation of genetic ancestry in patients with a first demyelinating event in Argentina. Mult Scler 2023; 29:559-567. [PMID: 36942953 DOI: 10.1177/13524585231157276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
BACKGROUND Information on performance of multiple sclerosis (MS) diagnostic criteria is scarce for populations from Latin America, Asia, or the Caribbean. OBJECTIVE To assess performance of revised 2017 McDonald criteria as well as evaluate genetic ancestry in a group of MS patients from Argentina experiencing a debut demyelinating event. METHODS Demographic and clinical characteristics, cerebrospinal fluid (CSF), and magnetic resonance imaging (MRI) findings and new T2 lesions were recorded at baseline and during relapses. Diagnostic accuracy in predicting conversion to clinically defined MS (CDMS) based on initial imaging applying revised 2017 criteria was evaluated and genetic ancestry-informative markers analyzed. RESULTS Of 201 patients experiencing their first demyelinating event (median follow-up 60 months), CDMS was confirmed in 67. We found 2017 diagnostic criteria were more sensitive (84% vs 67%) and less specific (14% vs 33%) than 2010 criteria, especially in a group of patients revised separately, presenting positive oligoclonal bands (88% vs 8%). Genetic testing performed in 128 cases showed 72% of patients were of European ancestry and 27% presented genetic admixture. CONCLUSION 2017 McDonald criteria showed higher sensitivity and lower specificity compared with 2010 criteria, shortening both time-to-diagnosis and time-to-treatment implementation.
Collapse
Affiliation(s)
| | | | | | - Marcela P Fiol
- Departamento de Neurología, Fleni, Buenos Aires, Argentina
| | | | - Edgar Carnero Conttenti
- Unidad de Neuroinmunología, Departamento de Neurociencias, Hospital Alemán, Buenos Aires, Argentina
| | - Pablo Adrian Lopez
- Unidad de Neuroinmunología, Departamento de Neurociencias, Hospital Alemán, Buenos Aires, Argentina
| | | | - Jorge Correale
- Departamento de Neurología, Fleni, Buenos Aires, Argentina/Instituto de Química y Fisicoquímica Biológicas (IQUIFIB), CONICET/Universidad de Buenos Aires, Buenos Aires, Argentina
| |
Collapse
|
24
|
Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective. J Neurol 2023; 270:1286-1299. [PMID: 36427168 PMCID: PMC9971159 DOI: 10.1007/s00415-022-11488-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 11/09/2022] [Accepted: 11/10/2022] [Indexed: 11/26/2022]
Abstract
In recent years, the use of magnetic resonance imaging (MRI) for the diagnostic work-up of multiple sclerosis (MS) has evolved considerably. The 2017 McDonald criteria show high sensitivity and accuracy in predicting a second clinical attack in patients with a typical clinically isolated syndrome and allow an earlier diagnosis of MS. They have been validated, are evidence-based, simplify the clinical use of MRI criteria and improve MS patients' management. However, to limit the risk of misdiagnosis, they should be applied by expert clinicians only after the careful exclusion of alternative diagnoses. Recently, new MRI markers have been proposed to improve diagnostic specificity for MS and reduce the risk of misdiagnosis. The central vein sign and chronic active lesions (i.e., paramagnetic rim lesions) may increase the specificity of MS diagnostic criteria, but further effort is necessary to validate and standardize their assessment before implementing them in the clinical setting. The feasibility of subpial demyelination assessment and the clinical relevance of leptomeningeal enhancement evaluation in the diagnostic work-up of MS appear more limited. Artificial intelligence tools may capture MRI attributes that are beyond the human perception, and, in the future, artificial intelligence may complement human assessment to further ameliorate the diagnostic work-up and patients' classification. However, guidelines that ensure reliability, interpretability, and validity of findings obtained from artificial intelligence approaches are still needed to implement them in the clinical scenario. This review provides a summary of the most recent updates regarding the application of MRI for the diagnosis of MS.
Collapse
|
25
|
Jakimovski D, Kavak KS, Zakalik K, Coetzee T, Gottesman M, Coyle PK, Zivadinov R, Weinstock-Guttman B. Improvement in time to multiple sclerosis diagnosis: 25-year retrospective analysis from New York State MS Consortium (NYSMSC). Mult Scler 2022; 29:753-756. [PMID: 36545928 DOI: 10.1177/13524585221140271] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Judicious multiple sclerosis (MS) diagnosis and early start of disease modifying therapy significantly improves long-term disability outcomes in persons with MS (pwMS). Retrospective analysis based on 25-year New York State MS Consortium (NYSMSC) data determined the effect of changes in the respective diagnostic criteria in shortening the time between symptom onset to MS diagnosis. Based on 9378 current and historical MS cases, there was a significant decrease in time to diagnosis in pwMS from 1982–2001 to >2017 periods (average 4.2 vs. 1.1 years, p < 0.001). Additional improvements and better implementation of the MS diagnostic criteria can further decrease the diagnosis lag.
Collapse
Affiliation(s)
- Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA/Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Katelyn S Kavak
- Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Karen Zakalik
- Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences University at Buffalo, The State University of New York, Buffalo, NY, USA
| | | | | | - Patricia K Coyle
- State University of New York at Stony Brook, Stony Brook, NY, USA
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA/Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Bianca Weinstock-Guttman
- Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences University at Buffalo, The State University of New York, Buffalo, NY, USA
| |
Collapse
|
26
|
Konen FF, Schwenkenbecher P, Wattjes MP, Skripuletz T. Leistungsfähigkeit der McDonald-Kriterien von 2017. DER NERVENARZT 2022:10.1007/s00115-022-01410-2. [DOI: 10.1007/s00115-022-01410-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/13/2022] [Indexed: 12/04/2022]
Abstract
Zusammenfassung
Hintergrund
Die schnelle und zuverlässige Diagnose einer Multiplen Sklerose (MS) ist entscheidend, um eine angepasste verlaufsmodifizierende Therapie zu beginnen. Die 2017-Revision der McDonald-Kriterien hat das Ziel, eine einfachere und frühzeitigere MS-Diagnose mit hoher diagnostischer Genauigkeit zu ermöglichen.
Ziel der Arbeit/Fragestellung
In der vorliegenden Arbeit wurden die publizierten Arbeiten, die die Anwendung der McDonald-Kriterien von 2017 und 2010 miteinander verglichen haben, ausgewertet und bezüglich der diagnostischen Leistungsfähigkeit analysiert.
Material und Methoden
Mittels Literaturrecherche in der PubMed-Datenbank (Suchbegriff: McDonald criteria 2010 and McDonald criteria 2017) wurden 20 Studien und ein Übersichtsartikel mit insgesamt 3006 auswertbaren Patienten identifiziert.
Ergebnisse
Bei Anwendung der McDonald-Kriterien von 2017 konnte die Diagnose einer MS bei mehr Patienten (2277/3006 Patienten, 76 %) und in einem früheren Stadium (3–10 Monate) verglichen mit der Revision von 2010 (1562/3006 Patienten, 52 %) gestellt werden. Von den zusätzlichen MS-Diagnosen sind 193/715 auf die Anpassung der bildgebenden Kriterien der zeitlichen Dissemination und 536/715 auf die Einführung der oligoklonalen Banden als diagnostisches Kriterium zurückführen.
Diskussion
Die revidierten McDonald-Kriterien von 2017 erlauben die Diagnosestellung einer MS bei einem höheren Anteil an Patienten beim ersten klinischen Ereignis.
Collapse
|
27
|
Martire MS, Moiola L, Rocca MA, Filippi M, Absinta M. What is the potential of paramagnetic rim lesions as diagnostic indicators in multiple sclerosis? Expert Rev Neurother 2022; 22:829-837. [PMID: 36342396 DOI: 10.1080/14737175.2022.2143265] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
INTRODUCTION In multiple sclerosis (MS), paramagnetic rim lesions (PRLs) on MRI identify a subset of chronic active lesions (CALs), which have been linked through clinical and pathological studies to more severe disease course and greater disability accumulation. Beside their prognostic relevance, increasing evidence supports the use of PRL as a diagnostic biomarker. AREAS COVERED This review summarizes the most recent updates regarding the MRI pathophysiology of PRL, their prevalence in MS (by clinical phenotypes) vs mimicking conditions, and their potential role as diagnostic MS biomarkers. We searched PubMed with terms including 'multiple sclerosis' AND 'paramagnetic rim lesions' OR 'iron rim lesions' OR 'rim lesions' for manuscripts published between January 2008 and July 2022. EXPERT OPINION Current research suggests that PRL can improve the diagnostic specificity and the overall accuracy of MS diagnosis when used together with the dissemination in space MRI criteria and the central vein sign. Nevertheless, future prospective multicenter studies should further define the real-world prevalence and specificity of PRL. International guidelines are needed to establish methodological criteria for PRL identification before its implementation into clinical practice.
Collapse
Affiliation(s)
| | - Lucia Moiola
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria Assunta Rocca
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Division of Neuroscience, Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Division of Neuroscience, Vita-Salute San Raffaele University, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Martina Absinta
- Division of Neuroscience, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| |
Collapse
|
28
|
The Brave New World of Early Treatment of Multiple Sclerosis: Using the Molecular Biomarkers CXCL13 and Neurofilament Light to Optimize Immunotherapy. Biomedicines 2022; 10:biomedicines10092099. [PMID: 36140203 PMCID: PMC9495360 DOI: 10.3390/biomedicines10092099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 08/23/2022] [Accepted: 08/24/2022] [Indexed: 11/17/2022] Open
Abstract
Multiple sclerosis (MS) is a highly heterogeneous disease involving a combination of inflammation, demyelination, and CNS injury. It is the leading cause of non-traumatic neurological disability in younger people. There is no cure, but treatments in the form of immunomodulatory drugs (IMDs) are available. Experience over the last 30 years has shown that IMDs, also sometimes called disease-modifying therapies, are effective in downregulating neuroinflammatory activity. However, there are a number of negatives in IMD therapy, including potential for significant side-effects and adverse events, uncertainty about long-term benefits regarding disability outcomes, and very high and increasing financial costs. The two dozen currently available FDA-approved IMDs also are heterogeneous with respect to efficacy and safety, especially long-term safety, and determining an IMD treatment strategy is therefore challenging for the clinician. Decisions about optimal therapy have been particularly difficult in early MS, at the time of the initial clinical demyelinating event (ICDE), at a time when early, aggressive treatment would best be initiated on patients destined to have a highly inflammatory course. However, given the fact that the majority of ICDE patients have a more benign course, aggressive immunosuppression, with its attendant risks, should not be administered to this group, and should only be reserved for patients with a more neuroinflammatory course, a decision that can only be made in retrospect, months to years after the ICDE. This quandary of moderate vs. aggressive therapy facing clinicians would best be resolved by the use of biomarkers that are predictive of future neuroinflammation. Unfortunately, biomarkers, especially molecular biomarkers, have not thus far been particularly useful in assisting clinicians in predicting the likelihood of future neuroinflammation, and thus guiding therapy. However, the last decade has seen the emergence of two highly promising molecular biomarkers to guide therapy in early MS: the CXCL13 index and neurofilament light. This paper will review the immunological and neuroscientific underpinnings of these biomarkers and the data supporting their use in early MS and will propose how they will likely be used to maximize benefit and minimize risk of IMDs in MS patients.
Collapse
|
29
|
Arrambide G, Espejo C, Carbonell-Mirabent P, Dieli-Crimi R, Rodríguez-Barranco M, Castillo M, Auger C, Cárdenas-Robledo S, Castilló J, Cobo-Calvo Á, Galán I, Midaglia L, Nos C, Otero-Romero S, Río J, Rodríguez-Acevedo B, Ruiz-Ortiz M, Salerno A, Tagliani P, Tur C, Vidal-Jordana A, Zabalza A, Sastre-Garriga J, Rovira A, Comabella M, Hernández-González M, Montalban X, Tintore M. The kappa free light chain index and oligoclonal bands have a similar role in the McDonald criteria. Brain 2022; 145:3931-3942. [PMID: 35727945 DOI: 10.1093/brain/awac220] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 05/10/2022] [Accepted: 05/29/2022] [Indexed: 11/13/2022] Open
Abstract
Intrathecal production of kappa free light chains (KFLC) occurs in multiple sclerosis and can be measured using the KFLC index. KFLC index values can be determined more easily than oligoclonal bands (OB) detection and seem more sensitive than the immunoglobulin (Ig)G index to diagnose multiple sclerosis. We assessed the value of OB, KFLC index cut-offs 5.9, 6.6, and 10.61, and IgG index to diagnose multiple sclerosis with prospectively acquired data from a clinically isolated syndrome (CIS) inception cohort. We selected patients with sufficient data to determine OB positivity, MRI dissemination in space (DIS) and time (DIT), IgG index, and sufficient quantities of paired CSF and blood samples to determine KFLC indexes (n = 214). We used Kendall´s Tau coefficient to estimate concordance; calculated the number of additional diagnoses when adding each positive index to DIS and positive OB; performed survival analyses for OB and each index with the outcomes second attack and 2017 MRI DIS and DIT; and estimated the diagnostic properties of OB and the different indexes for the abovementioned outcomes at five years. OB were positive in 138 patients (64.5%), KFLC-5.9 in 136 (63.6%), KFLC-6.6 in 135 (63.1%), KFLC-10.61 in 126 (58.9%) and IgG index in 101 (47.2%). The highest concordance was between OB and KFLC-6.6 (τ=0.727) followed by OB and KFLC-5.9 (τ=0.716). Combining DIS plus OB or KFLC-5.9 increased the number of diagnosed patients by 11 (5.1%), with KFLC-6.6 by 10 (4.7%), with KFLC-10.61 by 9 (4.2%), and with IgG index by 3 (1.4%). Patients with positive OB or indexes reached second attack and MRI DIS and DIT faster than patients with negative results (P < 0.0001 except IgG index in second attack: P = 0.016). In multivariable Cox models [aHR (95% CI)], the risk for second attack was very similar between KFLC-5.9 [2.0 (0.9-4.3), P = 0.068] and KFLC-6.6 [2.1 (1.1-4.2), P = 0.035]. The highest risk for MRI DIS and DIT was demonstrated with KFLC-5.9 [4.9 (2.5-9.6), P < 0.0001], followed by KFLC-6.6 [3.4 (1.9-6.3), P < 0.0001]. KFLC-5.9 and KFLC-6.6 had a slightly higher diagnostic accuracy than OB for second attack (70.5, 71.1, and 67.8) and MRI DIS and DIT (85.7, 85.1, and 81.0). KFLC indexes 5.9 and 6.6 performed slightly better than OB to assess multiple sclerosis risk and in terms of diagnostic accuracy. Given the concordance between OB and these indexes, we suggest using DIS plus positive OB or positive KFLC index as a modified criterion to diagnose multiple sclerosis.
Collapse
Affiliation(s)
- Georgina Arrambide
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Carmen Espejo
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Pere Carbonell-Mirabent
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Romina Dieli-Crimi
- Immunology Department, Vall d'Hebron Hospital Universitari. 08035 Barcelona, Spain
| | - Marta Rodríguez-Barranco
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Mireia Castillo
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Cristina Auger
- Section of Neuroradiology and Magnetic Resonance Unit. Department of Radiology (IDI). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Simón Cárdenas-Robledo
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain.,Department of Neurology, Multiple Sclerosis Center (CEMHUN), Hospital Universitario Nacional de Colombia. 111321 Bogotá, Colombia
| | - Joaquín Castilló
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Álvaro Cobo-Calvo
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Ingrid Galán
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Luciana Midaglia
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Carlos Nos
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Susana Otero-Romero
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Jordi Río
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Breogán Rodríguez-Acevedo
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Mariano Ruiz-Ortiz
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain.,Department of Neurology, Hospital Universitario Doce de Octubre, 28041 Madrid, Spain
| | - Annalaura Salerno
- Section of Neuroradiology and Magnetic Resonance Unit. Department of Radiology (IDI). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Paula Tagliani
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Carmen Tur
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Angela Vidal-Jordana
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Ana Zabalza
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Jaume Sastre-Garriga
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Alex Rovira
- Section of Neuroradiology and Magnetic Resonance Unit. Department of Radiology (IDI). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Manuel Comabella
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Manuel Hernández-González
- Immunology Department, Vall d'Hebron Hospital Universitari. 08035 Barcelona, Spain.,Diagnostic Immunology Research Group, Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Xavier Montalban
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| | - Mar Tintore
- Servei de Neurologia-Neuroimmunologia. Centre d'Esclerosi Múltiple de Catalunya, (Cemcat). Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari. Universitat Autònoma de Barcelona. 08035 Barcelona, Spain
| |
Collapse
|
30
|
Role of artificial intelligence in MS clinical practice. Neuroimage Clin 2022; 35:103065. [PMID: 35661470 PMCID: PMC9163993 DOI: 10.1016/j.nicl.2022.103065] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 05/04/2022] [Accepted: 05/26/2022] [Indexed: 11/24/2022]
Abstract
For medical applications, machine learning (including deep learning) are the most commonly used artificial intelligence (AI) approaches. It can improve multiple sclerosis (MS) diagnosis, prognostication and treatment monitoring. Thanks to AI, MRI and cognitive phenotypes of MS patients were identified. AI can shorten MRI protocols for MS, allowing the application of advanced techniques. It can reduce the human effort for MRI analysis, especially for lesion segmentation.
Machine learning (ML) and its subset, deep learning (DL), are branches of artificial intelligence (AI) showing promising findings in the medical field, especially when applied to imaging data. Given the substantial role of MRI in the diagnosis and management of patients with multiple sclerosis (MS), this disease is an ideal candidate for the application of AI techniques. In this narrative review, we are going to discuss the potential applications of AI for MS clinical practice, together with their limitations. Among their several advantages, ML algorithms are able to automate repetitive tasks, to analyze more data in less time and to achieve higher accuracy and reproducibility than the human counterpart. To date, these algorithms have been applied to MS diagnosis, prognosis, disease and treatment monitoring. Other fields of application have been improvement of MRI protocols as well as automated lesion and tissue segmentation. However, several challenges remain, including a better understanding of the information selected by AI algorithms, appropriate multicenter and longitudinal validations of results and practical aspects regarding hardware and software integration. Finally, one cannot overemphasize the paramount importance of human supervision, in order to optimize the use and take full advantage of the potential of AI approaches.
Collapse
|
31
|
Cutter GR, Koch MW. Multiple Sclerosis Diagnostic Criteria: Moving Ahead or Walking in Place? Neurology 2022; 98:12-13. [PMID: 34716252 DOI: 10.1212/wnl.0000000000013014] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Affiliation(s)
- Gary R Cutter
- From the Department of Biostatistics (G.R.C.), University of Alabama at Birmingham; and the Departments of Clinical Neurosciences (M.W.K.) and Community Health Sciences (M.W.K.), University of Calgary, Canada.
| | - Marcus W Koch
- From the Department of Biostatistics (G.R.C.), University of Alabama at Birmingham; and the Departments of Clinical Neurosciences (M.W.K.) and Community Health Sciences (M.W.K.), University of Calgary, Canada
| |
Collapse
|
32
|
Diagnosis of multiple sclerosis: Progress or confusion? Mult Scler Relat Disord 2022; 57:103528. [DOI: 10.1016/j.msard.2022.103528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
|