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Borrelli S, Martire MS, Stölting A, Vanden Bulcke C, Pedrini E, Guisset F, Bugli C, Yildiz H, Pothen L, Elands S, Martinelli V, Smith B, Jacobson S, Du Pasquier RA, Van Pesch V, Filippi M, Reich DS, Absinta M, Maggi P. Central Vein Sign, Cortical Lesions, and Paramagnetic Rim Lesions for the Diagnostic and Prognostic Workup of Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2024; 11:e200253. [PMID: 38788180 PMCID: PMC11129678 DOI: 10.1212/nxi.0000000000200253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 03/13/2024] [Indexed: 05/26/2024]
Abstract
BACKGROUND AND OBJECTIVES The diagnosis of multiple sclerosis (MS) can be challenging in clinical practice because MS presentation can be atypical and mimicked by other diseases. We evaluated the diagnostic performance, alone or in combination, of the central vein sign (CVS), paramagnetic rim lesion (PRL), and cortical lesion (CL), as well as their association with clinical outcomes. METHODS In this multicenter observational study, we first conducted a cross-sectional analysis of the CVS (proportion of CVS-positive lesions or simplified determination of CVS in 3/6 lesions-Select3*/Select6*), PRL, and CL in MS and non-MS cases on 3T-MRI brain images, including 3D T2-FLAIR, T2*-echo-planar imaging magnitude and phase, double inversion recovery, and magnetization prepared rapid gradient echo image sequences. Then, we longitudinally analyzed the progression independent of relapse and MRI activity (PIRA) in MS cases over the 2 years after study entry. Receiver operating characteristic curves were used to test diagnostic performance and regression models to predict diagnosis and clinical outcomes. RESULTS The presence of ≥41% CVS-positive lesions/≥1 CL/≥1 PRL (optimal cutoffs) had 96%/90%/93% specificity, 97%/84%/60% sensitivity, and 0.99/0.90/0.77 area under the curve (AUC), respectively, to distinguish MS (n = 185) from non-MS (n = 100) cases. The Select3*/Select6* algorithms showed 93%/95% specificity, 97%/89% sensitivity, and 0.95/0.92 AUC. The combination of CVS, CL, and PRL improved the diagnostic performance, especially when Select3*/Select6* were used (93%/94% specificity, 98%/96% sensitivity, 0.99/0.98 AUC; p = 0.002/p < 0.001). In MS cases (n = 185), both CL and PRL were associated with higher MS disability and severity. Longitudinal analysis (n = 61) showed that MS cases with >4 PRL at baseline were more likely to experience PIRA at 2-year follow-up (odds ratio 17.0, 95% confidence interval: 2.1-138.5; p = 0.008), whereas no association was observed between other baseline MRI measures and PIRA, including the number of CL. DISCUSSION The combination of CVS, CL, and PRL can improve MS differential diagnosis. CL and PRL also correlated with clinical measures of poor prognosis, with PRL being a predictor of disability accrual independent of clinical/MRI activity.
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Affiliation(s)
- Serena Borrelli
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Maria Sofia Martire
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Anna Stölting
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Colin Vanden Bulcke
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Edoardo Pedrini
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - François Guisset
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Céline Bugli
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Halil Yildiz
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Lucie Pothen
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Sophie Elands
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Vittorio Martinelli
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Bryan Smith
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Steven Jacobson
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Renaud A Du Pasquier
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Vincent Van Pesch
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Massimo Filippi
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Daniel S Reich
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Martina Absinta
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Pietro Maggi
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
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2
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Miller AE. Dissemination in time as a requirement for diagnosis of multiple sclerosis: Time for a change? Mult Scler 2024; 30:479-482. [PMID: 38411037 DOI: 10.1177/13524585241233999] [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: 02/28/2024]
Abstract
The requirement to demonstrate dissemination in time (DIT) in order to diagnose multiple sclerosis (MS) has been enshrined in the literature since earliest efforts to establish diagnostic critera. However, various diagnostic criteria over the years, including the 2017 McDonald criteria, have inconsistently utilized this concept. This Viewpoint contends that current criteria for DIT are inadequate and sometimes inappropriate. It recommends continuing to consider DIT in the diagnosis of MS, but advocates utilizing all available information with high specificity for the disease, including the presence of large numbers of typical lesions, to make the diagnosis. This approach enables early initiation of disease-modifying treatment in situations with a favorable risk-benefit ratio.
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Affiliation(s)
- Aaron E Miller
- Aaron E Miller Icahn School of Medicine at Mount Sinai, New York, NY, USA
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3
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Pelletier J, Sugar D, Koyfman A, Long B. Multiple Sclerosis: An Emergency Medicine-Focused Narrative Review. J Emerg Med 2024; 66:e441-e456. [PMID: 38472027 DOI: 10.1016/j.jemermed.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 11/15/2023] [Accepted: 12/11/2023] [Indexed: 03/14/2024]
Abstract
BACKGROUND Multiple sclerosis (MS) is a rare but serious condition associated with significant morbidity. OBJECTIVE This review provides a focused assessment of MS for emergency clinicians, including the presentation, evaluation, and emergency department (ED) management based on current evidence. DISCUSSION MS is an autoimmune disorder targeting the central nervous system (CNS), characterized by clinical relapses and radiological lesions disseminated in time and location. Patients with MS most commonly present with long tract signs (e.g., myelopathy, asymmetric spastic paraplegia, urinary dysfunction, Lhermitte's sign), optic neuritis, or brainstem syndromes (bilateral internuclear ophthalmoplegia). Cortical syndromes or multifocal presentations are less common. Radiologically isolated syndrome and clinically isolated syndrome (CIS) may or may not progress to chronic forms of MS, including relapsing remitting MS, primary progressive MS, and secondary progressive MS. The foundation of outpatient management involves disease-modifying therapy, which is typically initiated with the first signs of disease onset. Management of CIS and acute flares of MS in the ED includes corticosteroid therapy, ideally after diagnostic testing with imaging and lumbar puncture for cerebrospinal fluid analysis. Emergency clinicians should evaluate whether patients with MS are presenting with new-onset debilitating neurological symptoms to avoid unnecessary testing and admissions, but failure to appropriately diagnose CIS or MS flare is associated with increased morbidity. CONCLUSIONS An understanding of MS can assist emergency clinicians in better diagnosing and managing this neurologically devastating disease.
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Affiliation(s)
- Jessica Pelletier
- Department of Emergency Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Davis Sugar
- Department of Neurology, Virginia Tech Carilion, Roanoke, Virginia
| | - Alex Koyfman
- Department of Emergency Medicine, University of Texas Southwestern, Dallas, Texas
| | - Brit Long
- SAUSHEC (San Antonio Uniformed Services Health Education Consortium), Department of Emergency Medicine, Brooke Army Medical Center, Fort Sam Houston, Texas
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4
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Adamczyk B, Morawiec N, Boczek S, Dańda K, Herba M, Spyra A, Sowa A, Szczygieł J, Adamczyk-Sowa M. Headache in Multiple Sclerosis: A Narrative Review. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:572. [PMID: 38674218 PMCID: PMC11052044 DOI: 10.3390/medicina60040572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 03/20/2024] [Accepted: 03/27/2024] [Indexed: 04/28/2024]
Abstract
Background: Multiple sclerosis (MS) is a chronic inflammatory demyelinating disorder of the central nervous system characterized by autoimmune-mediated damage to oligodendrocytes and subsequent myelin destruction. Clinical implications: Clinically, the disease presents with many symptoms, often evolving over time. The insidious onset of MS often manifests with non-specific symptoms (prodromal phase), which may precede a clinical diagnosis by several years. Among them, headache is a prominent early indicator, affecting a significant number of MS patients (50-60%). Results: Headache manifests as migraine or tension-type headache with a clear female predilection (female-male ratio 2-3:1). Additionally, some disease-modifying therapies in MS can also induce headache. For instance, teriflunomide, interferons, ponesimod, alemtuzumab and cladribine are associated with an increased incidence of headache. Conclusions: The present review analyzed the literature data on the relationship between headache and MS to provide clinicians with valuable insights for optimized patient management and the therapeutic decision-making process.
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Affiliation(s)
- Bożena Adamczyk
- Department of Neurology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, ul. 3 Maja 13-15, 41-800 Zabrze, Poland; (S.B.); (K.D.); (M.H.); (A.S.); (A.S.); (J.S.); (M.A.-S.)
| | - Natalia Morawiec
- Department of Neurology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, ul. 3 Maja 13-15, 41-800 Zabrze, Poland; (S.B.); (K.D.); (M.H.); (A.S.); (A.S.); (J.S.); (M.A.-S.)
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5
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Novakova L, Hedström AK, Axelsson M, Brandt AF, Alfredsson L, Olsson T, Lycke J. Medically unexplained symptoms are common in women in tertiary neurological healthcare center: A survey cohort study of persons investigated for suspected multiple sclerosis. Brain Behav 2024; 14:e3459. [PMID: 38451005 PMCID: PMC10918608 DOI: 10.1002/brb3.3459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 02/06/2024] [Accepted: 02/10/2024] [Indexed: 03/08/2024] Open
Abstract
BACKGROUND A significant proportion of individuals with suspicious onset of multiple sclerosis (MS) does not fulfill the diagnostic criteria. Although some receive other diagnoses, many remain undiagnosed and lack healthcare follow-up. This study aimed to characterize persons with undetermined diagnosis (PwUD) through a questionnaire. METHODS Incident cases with suspected MS were consecutively admitted to a tertiary neurological healthcare center in a prospective cohort study. Those who remained undiagnosed after 40 months (mean, range 31-52) were considered PwUD. They completed a modified questionnaire, previously used in a population-based case-control study of incident MS cases. Their responses were compared with two control cohorts, persons with MS (PwMS) and healthy controls, randomly selected from national registries, matched by age, gender, and area of residence. RESULTS Out of 271 patients with suspected MS onset, 72 (20.3%) were PwUD with a female majority (79%). The response rate was 83% and 39% reported persisting MS-like symptoms. Compared to controls (n = 548) and PwMS (n = 277), fewer PwUD were currently smoking (p = .4 and p = .03), consumed less alcohol (p = .04 and p = .01), and had children (p = .02 and p = .002). PwUD reported occurrence of other autoimmune disease in 29%, higher compared to PwMS and controls (p < .001 and p < .001). CONCLUSIONS UD is common among persons investigated for suspected MS, in particular among female parents. Our data suggest that PwUD can be characterized as nonsmokers with low alcohol consumption and a higher prevalence of autoimmune disease, in particular thyroid disease.
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Affiliation(s)
- Lenka Novakova
- Department of Clinical Neuroscience, Institute of Neuscience and Physiology, Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Department of Neurology, Region Västra GötalandSahlgrenska University HospitalGothenburgSweden
| | - Anna Karin Hedström
- Department of Clinical NeuroscienceKarolinska InstituteStockholmSweden
- Center for Molecular MedicineKarolinska University HospitalStockholmSweden
| | - Markus Axelsson
- Department of Clinical Neuroscience, Institute of Neuscience and Physiology, Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Department of Neurology, Region Västra GötalandSahlgrenska University HospitalGothenburgSweden
| | - Anne Frandsen Brandt
- Department of Clinical Neuroscience, Institute of Neuscience and Physiology, Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Department of Neurology, Region Västra GötalandSahlgrenska University HospitalGothenburgSweden
| | - Lars Alfredsson
- Department of Clinical NeuroscienceKarolinska InstituteStockholmSweden
- Center for Occupational and Environmental Medicine, Region StockholmStockholmSweden
- Institute of Environmental Medicine, Karolinska InstituteStockholmSweden
| | - Tomas Olsson
- Department of Clinical NeuroscienceKarolinska InstituteStockholmSweden
- Center for Molecular MedicineKarolinska University HospitalStockholmSweden
| | - Jan Lycke
- Department of Clinical Neuroscience, Institute of Neuscience and Physiology, Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Department of Neurology, Region Västra GötalandSahlgrenska University HospitalGothenburgSweden
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Wenk J, Voigt I, Inojosa H, Schlieter H, Ziemssen T. Building digital patient pathways for the management and treatment of multiple sclerosis. Front Immunol 2024; 15:1356436. [PMID: 38433832 PMCID: PMC10906094 DOI: 10.3389/fimmu.2024.1356436] [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: 12/15/2023] [Accepted: 01/30/2024] [Indexed: 03/05/2024] Open
Abstract
Recent advances in the field of artificial intelligence (AI) could yield new insights into the potential causes of multiple sclerosis (MS) and factors influencing its course as the use of AI opens new possibilities regarding the interpretation and use of big data from not only a cross-sectional, but also a longitudinal perspective. For each patient with MS, there is a vast amount of multimodal data being accumulated over time. But for the application of AI and related technologies, these data need to be available in a machine-readable format and need to be collected in a standardized and structured manner. Through the use of mobile electronic devices and the internet it has also become possible to provide healthcare services from remote and collect information on a patient's state of health outside of regular check-ups on site. Against this background, we argue that the concept of pathways in healthcare now could be applied to structure the collection of information across multiple devices and stakeholders in the virtual sphere, enabling us to exploit the full potential of AI technology by e.g., building digital twins. By going digital and using pathways, we can virtually link patients and their caregivers. Stakeholders then could rely on digital pathways for evidence-based guidance in the sequence of procedures and selection of therapy options based on advanced analytics supported by AI as well as for communication and education purposes. As far as we aware of, however, pathway modelling with respect to MS management and treatment has not been thoroughly investigated yet and still needs to be discussed. In this paper, we thus present our ideas for a modular-integrative framework for the development of digital patient pathways for MS treatment.
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Affiliation(s)
- Judith Wenk
- Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Isabel Voigt
- Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Hernan Inojosa
- Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Hannes Schlieter
- Research Group Digital Health, Faculty of Business and Economics, Technische Universität Dresden, Dresden, Germany
| | - Tjalf Ziemssen
- Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
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7
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Nabizadeh F, Zafari R, Mohamadi M, Maleki T, Fallahi MS, Rafiei N. MRI features and disability in multiple sclerosis: A systematic review and meta-analysis. J Neuroradiol 2024; 51:24-37. [PMID: 38172026 DOI: 10.1016/j.neurad.2023.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 11/28/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND In this systematic review and meta-analysis, we aimed to investigate the correlation between disability in patients with Multiple sclerosis (MS) measured by the Expanded Disability Status Scale (EDSS) and brain Magnetic Resonance Imaging (MRI) features to provide reliable results on which characteristics in the MRI can predict disability and prognosis of the disease. METHODS A systematic literature search was performed using three databases including PubMed, Scopus, and Web of Science. The selected peer-reviewed studies must report a correlation between EDSS scores and MRI features. The correlation coefficients of included studies were converted to the Fisher's z scale, and the results were pooled. RESULTS Overall, 105 studies A total of 16,613 patients with MS entered our study. We found no significant correlation between total brain volume and EDSS assessment (95 % CI: -0.37 to 0.08; z-score: -0.15). We examined the potential correlation between the volume of T1 and T2 lesions and the level of disability. A positive significant correlation was found (95 % CI: 0.19 to 0.43; z-score: 0.31), (95 % CI: 0.17 to 0.33; z-score: 0.25). We observed a significant correlation between white matter volume and EDSS score in patients with MS (95 % CI: -0.37 to -0.03; z-score: -0.21). Moreover, there was a significant negative correlation between gray matter volume and disability (95 % CI: -0.025 to -0.07; z-score: -0.16). CONCLUSION In conclusion, this systematic review and meta-analysis revealed that disability in patients with MS is linked to extensive changes in different brain regions, encompassing gray and white matter, as well as T1 and T2 weighted MRI lesions.
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Affiliation(s)
- Fardin Nabizadeh
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
| | - Rasa Zafari
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mobin Mohamadi
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Tahereh Maleki
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Nazanin Rafiei
- School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
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8
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Kaisey M, Solomon AJ. Multiple Sclerosis Diagnostic Delay and Misdiagnosis. Neurol Clin 2024; 42:1-13. [PMID: 37980109 DOI: 10.1016/j.ncl.2023.07.001] [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: 11/20/2023]
Abstract
Multiple sclerosis (MS) misdiagnosis in the form of an incorrect diagnosis of MS, as well as delayed diagnosis in patients who do have MS, both influence patient clinical outcomes. Contemporary studies have reported data on factors associated with these diagnostic challenges and their frequency. Expediting diagnosis in patients with MS and reducing MS misdiagnosis in patients who do not have MS may be aided by educational efforts surrounding early MS symptoms and proper application of MS diagnostic criteria. Emerging novel MS diagnostic biomarkers may aid early and accurate diagnosis of MS in the future.
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Affiliation(s)
- Marwa Kaisey
- Department of Neurology, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, A6600, Los Angeles, CA 90048, USA.
| | - Andrew J Solomon
- Department of Neurological Sciences, University of Vermont, Larner College of Medicine, University Health Center, Arnold 2, 1 South Prospect Street, Burlington, VT 05401, USA
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Newman-Toker DE, Nassery N, Schaffer AC, Yu-Moe CW, Clemens GD, Wang Z, Zhu Y, Saber Tehrani AS, Fanai M, Hassoon A, Siegal D. Burden of serious harms from diagnostic error in the USA. BMJ Qual Saf 2024; 33:109-120. [PMID: 37460118 PMCID: PMC10792094 DOI: 10.1136/bmjqs-2021-014130] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 06/24/2023] [Indexed: 08/10/2023]
Abstract
BACKGROUND Diagnostic errors cause substantial preventable harms worldwide, but rigorous estimates for total burden are lacking. We previously estimated diagnostic error and serious harm rates for key dangerous diseases in major disease categories and validated plausible ranges using clinical experts. OBJECTIVE We sought to estimate the annual US burden of serious misdiagnosis-related harms (permanent morbidity, mortality) by combining prior results with rigorous estimates of disease incidence. METHODS Cross-sectional analysis of US-based nationally representative observational data. We estimated annual incident vascular events and infections from 21.5 million (M) sampled US hospital discharges (2012-2014). Annual new cancers were taken from US-based registries (2014). Years were selected for coding consistency with prior literature. Disease-specific incidences for 15 major vascular events, infections and cancers ('Big Three' categories) were multiplied by literature-based rates to derive diagnostic errors and serious harms. We calculated uncertainty estimates using Monte Carlo simulations. Validity checks included sensitivity analyses and comparison with prior published estimates. RESULTS Annual US incidence was 6.0 M vascular events, 6.2 M infections and 1.5 M cancers. Per 'Big Three' dangerous disease case, weighted mean error and serious harm rates were 11.1% and 4.4%, respectively. Extrapolating to all diseases (including non-'Big Three' dangerous disease categories), we estimated total serious harms annually in the USA to be 795 000 (plausible range 598 000-1 023 000). Sensitivity analyses using more conservative assumptions estimated 549 000 serious harms. Results were compatible with setting-specific serious harm estimates from inpatient, emergency department and ambulatory care. The 15 dangerous diseases accounted for 50.7% of total serious harms and the top 5 (stroke, sepsis, pneumonia, venous thromboembolism and lung cancer) accounted for 38.7%. CONCLUSION An estimated 795 000 Americans become permanently disabled or die annually across care settings because dangerous diseases are misdiagnosed. Just 15 diseases account for about half of all serious harms, so the problem may be more tractable than previously imagined.
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Affiliation(s)
- David E Newman-Toker
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Najlla Nassery
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Adam C Schaffer
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Department of Patient Safety, The Risk Management Foundation of the Harvard Medical Institutions Inc, Boston, Massachusetts, USA
| | - Chihwen Winnie Yu-Moe
- Department of Patient Safety, The Risk Management Foundation of the Harvard Medical Institutions Inc, Boston, Massachusetts, USA
| | - Gwendolyn D Clemens
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Zheyu Wang
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Yuxin Zhu
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Ali S Saber Tehrani
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Mehdi Fanai
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Ahmed Hassoon
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Dana Siegal
- Candello, The Risk Management Foundation of the Harvard Medical Institutions Inc, Boston, Massachusetts, USA
- Department of Risk Management & Analytics, Coverys, Boston, Massachusetts, USA
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10
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Bellanca CM, Augello E, Mariottini A, Bonaventura G, La Cognata V, Di Benedetto G, Cantone AF, Attaguile G, Di Mauro R, Cantarella G, Massacesi L, Bernardini R. Disease Modifying Strategies in Multiple Sclerosis: New Rays of Hope to Combat Disability? Curr Neuropharmacol 2024; 22:1286-1326. [PMID: 38275058 PMCID: PMC11092922 DOI: 10.2174/1570159x22666240124114126] [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: 05/04/2023] [Revised: 08/21/2023] [Accepted: 09/22/2023] [Indexed: 01/27/2024] Open
Abstract
Multiple sclerosis (MS) is the most prevalent chronic autoimmune inflammatory- demyelinating disorder of the central nervous system (CNS). It usually begins in young adulthood, mainly between the second and fourth decades of life. Usually, the clinical course is characterized by the involvement of multiple CNS functional systems and by different, often overlapping phenotypes. In the last decades, remarkable results have been achieved in the treatment of MS, particularly in the relapsing- remitting (RRMS) form, thus improving the long-term outcome for many patients. As deeper knowledge of MS pathogenesis and respective molecular targets keeps growing, nowadays, several lines of disease-modifying treatments (DMT) are available, an impressive change compared to the relative poverty of options available in the past. Current MS management by DMTs is aimed at reducing relapse frequency, ameliorating symptoms, and preventing clinical disability and progression. Notwithstanding the relevant increase in pharmacological options for the management of RRMS, research is now increasingly pointing to identify new molecules with high efficacy, particularly in progressive forms. Hence, future efforts should be concentrated on achieving a more extensive, if not exhaustive, understanding of the pathogenetic mechanisms underlying this phase of the disease in order to characterize novel molecules for therapeutic intervention. The purpose of this review is to provide a compact overview of the numerous currently approved treatments and future innovative approaches, including neuroprotective treatments as anti-LINGO-1 monoclonal antibody and cell therapies, for effective and safe management of MS, potentially leading to a cure for this disease.
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Affiliation(s)
- Carlo Maria Bellanca
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), Section of Pharmacology, University of Catania, 95123 Catania, Italy
- Clinical Toxicology Unit, University Hospital, University of Catania, 95123 Catania, Italy
| | - Egle Augello
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), Section of Pharmacology, University of Catania, 95123 Catania, Italy
- Clinical Toxicology Unit, University Hospital, University of Catania, 95123 Catania, Italy
| | - Alice Mariottini
- Department of Neurosciences Drugs and Child Health, University of Florence, Florence, Italy
| | - Gabriele Bonaventura
- Institute for Biomedical Research and Innovation (IRIB), Italian National Research Council, 95126 Catania, Italy
| | - Valentina La Cognata
- Institute for Biomedical Research and Innovation (IRIB), Italian National Research Council, 95126 Catania, Italy
| | - Giulia Di Benedetto
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), Section of Pharmacology, University of Catania, 95123 Catania, Italy
- Clinical Toxicology Unit, University Hospital, University of Catania, 95123 Catania, Italy
| | - Anna Flavia Cantone
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), Section of Pharmacology, University of Catania, 95123 Catania, Italy
| | - Giuseppe Attaguile
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), Section of Pharmacology, University of Catania, 95123 Catania, Italy
| | - Rosaria Di Mauro
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), Section of Pharmacology, University of Catania, 95123 Catania, Italy
| | - Giuseppina Cantarella
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), Section of Pharmacology, University of Catania, 95123 Catania, Italy
| | - Luca Massacesi
- Department of Neurosciences Drugs and Child Health, University of Florence, Florence, Italy
| | - Renato Bernardini
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), Section of Pharmacology, University of Catania, 95123 Catania, Italy
- Clinical Toxicology Unit, University Hospital, University of Catania, 95123 Catania, Italy
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11
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Daboul L, O’Donnell CM, Amin M, Rodrigues P, Derbyshire J, Azevedo C, Bar-Or A, Caverzasi E, Calabresi PA, Cree BA, Freeman L, Henry RG, Longbrake EE, Oh J, Papinutto N, Pelletier D, Prchkovska V, Raza P, Ramos M, Samudralwar RD, Schindler MK, Sotirchos ES, Sicotte NL, Solomon AJ, Shinohara RT, Reich DS, Sati P, Ontaneda D. A multicenter pilot study evaluating simplified central vein assessment for the diagnosis of multiple sclerosis. Mult Scler 2024; 30:25-34. [PMID: 38088067 PMCID: PMC11037932 DOI: 10.1177/13524585231214360] [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: 12/21/2023]
Abstract
BACKGROUND The central vein sign (CVS) is a proposed magnetic resonance imaging (MRI) biomarker for multiple sclerosis (MS); the optimal method for abbreviated CVS scoring is not yet established. OBJECTIVE The aim of this study was to evaluate the performance of a simplified approach to CVS assessment in a multicenter study of patients being evaluated for suspected MS. METHODS Adults referred for possible MS to 10 sites were recruited. A post-Gd 3D T2*-weighted MRI sequence (FLAIR*) was obtained in each subject. Trained raters at each site identified up to six CVS-positive lesions per FLAIR* scan. Diagnostic performance of CVS was evaluated for a diagnosis of MS which had been confirmed using the 2017 McDonald criteria at thresholds including three positive lesions (Select-3*) and six positive lesions (Select-6*). Inter-rater reliability assessments were performed. RESULTS Overall, 78 participants were analyzed; 37 (47%) were diagnosed with MS, and 41 (53%) were not. The mean age of participants was 45 (range: 19-64) years, and most were female (n = 55, 71%). The area under the receiver operating characteristic curve (AUROC) for the simplified counting method was 0.83 (95% CI: 0.73-0.93). Select-3* and Select-6* had sensitivity of 81% and 65% and specificity of 68% and 98%, respectively. Inter-rater agreement was 78% for Select-3* and 83% for Select-6*. CONCLUSION A simplified method for CVS assessment in patients referred for suspected MS demonstrated good diagnostic performance and inter-rater agreement.
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Affiliation(s)
- Lynn Daboul
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
- Cleveland Clinic Lerner College of Medicine, Cleveland, OH
| | - Carly M. O’Donnell
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Moein Amin
- Neurological Institute, Cleveland Clinic, Cleveland, OH
| | | | - John Derbyshire
- Functional MRI Facility, NIMH, National Institutes of Health, Bethesda, MD
| | - Christina Azevedo
- Department of Neurology, University of Southern California, Los Angeles, CA
| | - Amit Bar-Or
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Eduardo Caverzasi
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | | | - Bruce A.C. Cree
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Leorah Freeman
- Department of Neurology, Dell Medical School, The University of Texas, Austin, TX
| | - Roland G. Henry
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | | | - Jiwon Oh
- Division of Neurology, St. Michael’s Hospital, University of Toronto, Toronto, ON, CANADA
| | - Nico Papinutto
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Daniel Pelletier
- Department of Neurology, University of Southern California, Los Angeles, CA
| | | | - Praneeta Raza
- Cleveland Clinic Lerner College of Medicine, Cleveland, OH
| | - Marc Ramos
- QMENTA Cloud Platform, QMENTA Inc., Boston, MA, USA
| | | | - Matthew K. Schindler
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | | | - Nancy L. Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Andrew J. Solomon
- Department of Neurological Sciences, Larner College of Medicine, The University of Vermont, Burlington, VT
| | - Russell T. Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH
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12
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Tieppo EMDS, Silva GD, Silva TFFD, Araujo RSD, Oliveira MBD, Spricigo MGP, Pimentel GA, Campana IG, Castrillo BB, Mendes NT, Teixeira LS, Nunes DM, Rimkus CDM, Adoni T, Apóstolos Pereira SL, Callegaro D. Misdiagnosis in multiple sclerosis in a Brazilian reference center: Clinical, radiological, laboratory profile and failures in the diagnostic process-Cohort study. Mult Scler 2023; 29:1755-1764. [PMID: 37786965 DOI: 10.1177/13524585231199323] [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: 10/04/2023]
Abstract
BACKGROUND Multiple sclerosis misdiagnosis remains a problem despite the well-validated McDonald 2017. For proper evaluation of errors in the diagnostic process that lead to misdiagnosis, it is adequate to incorporate patients who are already under regular follow-up at reference centers of demyelinating diseases. OBJECTIVES To evaluate multiple sclerosis misdiagnosis in patients who are on follow-up at a reference center of demyelinating diseases in Brazil. METHODS We designed an observational study including patients in regular follow-up, who were diagnosed with multiple sclerosis at our specialized outpatient clinic in the Hospital of Clinics in the University of Sao Paulo, from 1996 to 2021, and were reassessed for misdiagnosis in 2022. We evaluated demographic information, clinical profile, and complementary exams and classified participants as "established multiple sclerosis," "non-multiple sclerosis, diagnosed," and "non-multiple sclerosis, undiagnosed." Failures in the diagnostic process were assessed by the modified Diagnostic Error Evaluation and Research tool. RESULTS A total of 201 patients were included. After analysis, 191/201 (95.02%) participants were confirmed as "established multiple sclerosis," 5/201 (2.49%) were defined as "non-multiple sclerosis, diagnosed," and 5/201 (2.49%) were defined as "non-multiple sclerosis, undiagnosed." CONCLUSIONS Multiple sclerosis misdiagnosis persists in reference centers, emphasizing the need for careful interpretation of clinical findings to prevent errors.
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Affiliation(s)
- Eduardo Macedo de Souza Tieppo
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Guilherme Diogo Silva
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Tomás Fraga Ferreira da Silva
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Roger Santana de Araujo
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Mateus Boaventura de Oliveira
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Mariana Gondim Peixoto Spricigo
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Gabriela Almeida Pimentel
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Igor Gusmão Campana
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Bruno Batitucci Castrillo
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Natalia Trombini Mendes
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Larissa Silva Teixeira
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Douglas Mendes Nunes
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Carolina de Medeiros Rimkus
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Tarso Adoni
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Samira Luisa Apóstolos Pereira
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Dagoberto Callegaro
- Neuroimmunology Division, Department of Neurology, Hospital das Clínicas da Faculdade de Medicina da USP, Sao Paulo, Brazil
- Department of Neurology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil
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13
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Landes-Chateau C, Levraut M, Cohen M, Sicard M, Papeix C, Cotton F, Balcerac A, Themelin A, Mondot L, Lebrun-Frenay C. Identification of demyelinating lesions and application of McDonald criteria when confronted with white matter lesions on brain MRI. Rev Neurol (Paris) 2023; 179:1103-1110. [PMID: 37730469 DOI: 10.1016/j.neurol.2023.04.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 03/14/2023] [Accepted: 04/18/2023] [Indexed: 09/22/2023]
Abstract
INTRODUCTION White matter lesions (WML) on magnetic resonance imaging (MRI) are common in clinical practice. When analyzing WML, radiologists sometimes propose a pathophysiological mechanism to explain the observed MRI abnormalities, which can be a source of anxiety for patients. In some cases, discordance may appear between the patient's clinical symptoms and the identification of the MRI-appearing WML, leading to extensive diagnostic work-up. To avoid misdiagnosis, the analysis of WML should be standardized, and a consensual MRI reading approach is needed. OBJECTIVE To analyze the MRI WML identification process, associated diagnosis approach, and misinterpretations in physicians involved in WML routine practice. METHODS Through a survey distributed online to practitioners involved in WML diagnostic work-up, we described the leading causes of MRI expertise misdiagnosis and associated factors: clinical experience, physicians' subspecialty and location of practice, and type of device used to complete the survey. The survey consisted of sixteen T2-weighted images MRI analysis, from which ten were guided (binary response to lesion location identification), four were not shown (multiple possible answers), and two were associated with dissemination in space (DIS) McDonald criteria application. Two independent, experienced practitioners determined the correct answers before the participants' completion. RESULTS In total, 364 participants from the French Neuro Radiological (SFNR), French Neurological (SFN), and French Multiple Sclerosis (SFSEP) societies completed the survey entirely. According to lesion identification, 34.3% and 16.9% of the participants correctly identified juxtacortical and periventricular lesions, respectively, whereas 56.3% correctly identified non-guided lesions. Application of the 2017 McDonald's DIS criteria was correct for 35.3% of the participants. According to the global survey scoring, factors independently associated with correct answers in multivariate analysis were MS-expert subspecialty (P<0.001), young clinical practitioners (P=0.02), and the use of a computer instead of a smartphone to perform WML analysis (P=0.03). CONCLUSION Our results highlight the difficulties regarding WML analysis in clinical practice and suggest that radiologists and neurologists should rely on each other to ensure the diagnosis of multiple sclerosis and related disorders and limit misdiagnoses.
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Affiliation(s)
- C Landes-Chateau
- UR2CA-URRIS, CRCSEP neurologie, CHU de Nice, université Côte d'Azur, Nice, France.
| | - M Levraut
- UR2CA-URRIS, CRCSEP neurologie, CHU de Nice, université Côte d'Azur, Nice, France
| | - M Cohen
- UR2CA-URRIS, CRCSEP neurologie, CHU de Nice, université Côte d'Azur, Nice, France
| | - M Sicard
- UR2CA-URRIS, CRCSEP neurologie, CHU de Nice, université Côte d'Azur, Nice, France
| | - C Papeix
- Service de neurologie générale, hôpital Fondation Adolphe-de-Rothschild, Paris, France
| | - F Cotton
- U1044 Inserm, CREATIS, UMR 5220 CNRS, service de radiologie, centre hospitalier Lyon-Sud, hospices civils de Lyon, université Claude-Bernard Lyon, Lyon, France
| | - A Balcerac
- Département de neurologie, université la Sorbonne, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
| | - A Themelin
- Service de radiologie, CHU de Nice, université Côte d'Azur, Nice, France
| | - L Mondot
- UR2CA-URRIS, CRCSEP neurologie, CHU de Nice, université Côte d'Azur, Nice, France
| | - C Lebrun-Frenay
- UR2CA-URRIS, CRCSEP neurologie, CHU de Nice, université Côte d'Azur, Nice, France
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14
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Blok KM, Smolders J, van Rosmalen J, Martins Jarnalo CO, Wokke B, de Beukelaar J. Real-world challenges in the diagnosis of primary progressive multiple sclerosis. Eur J Neurol 2023; 30:3799-3808. [PMID: 37578087 DOI: 10.1111/ene.16042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 08/09/2023] [Accepted: 08/09/2023] [Indexed: 08/15/2023]
Abstract
BACKGROUND AND PURPOSE Despite the 2017 revisions to the McDonald criteria, diagnosing primary progressive multiple sclerosis (PPMS) remains challenging. To improve clinical practice, the aim was to identify frequent diagnostic challenges in a real-world setting and associate these with the performance of the 2010 and 2017 PPMS diagnostic McDonald criteria. METHODS Clinical, radiological and laboratory characteristics at the time of diagnosis were retrospectively recorded from designated PPMS patient files. Possible complicating factors were recorded such as confounding comorbidity, signs indicative of alternative diagnoses, possible earlier relapses and/or incomplete diagnostic work-up (no cerebrospinal fluid examination and/or magnetic resonance imaging brain and spinal cord). The percentages of patients fulfilling the 2010 and 2017 McDonald criteria were calculated after censoring patients with these complicating factors. RESULTS A total of 322 designated PPMS patients were included. Of all participants, it was found that n = 28/322 had confounding comorbidity and/or signs indicative of alternative diagnoses, n = 103/294 had possible initial relapsing and/or uncertainly progressive phenotypes and n = 73/191 received an incomplete diagnostic work-up. When applying the 2010 and 2017 diagnostic PPMS McDonald criteria on n = 118 cases with a full diagnostic work-up and a primary progressive disease course without a better alternative explanation, these were met by 104/118 (88.1%) and 98/118 remaining patients (83.1%), respectively (p = 0.15). CONCLUSION Accurate interpretation of the initial clinical course, consideration of alternative diagnoses and a full diagnostic work-up are the cornerstones of a PPMS diagnosis. When these conditions are met, the 2010 and 2017 McDonald criteria for PPMS perform similarly, emphasizing the importance of their appropriate application in clinical practice.
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Affiliation(s)
- Katelijn M Blok
- Department of Neurology, MS Center of the Albert Schweitzer Hospital, Dordrecht, The Netherlands
- Department of Neurology, MS Center ErasMS, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Joost Smolders
- Department of Neurology, MS Center ErasMS, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Immunology, MS Center ErasMS, Erasmus University Medical Center, Rotterdam, The Netherlands
- Neuroimmunology Research Group, Netherlands Institute for Neurosciences, Amsterdam, The Netherlands
| | - Joost van Rosmalen
- Department of Biostatistics, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Carine O Martins Jarnalo
- Department of Radiology, MS Center of the Albert Schweitzer Hospital, Dordrecht, The Netherlands
| | - Beatrijs Wokke
- Department of Neurology, MS Center ErasMS, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Janet de Beukelaar
- Department of Neurology, MS Center of the Albert Schweitzer Hospital, Dordrecht, The Netherlands
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15
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Mustafa R, Flanagan EP, Duffy DJ, Weinshenker BG, Soldán MMP, Kunchok A, Kaisey M, Solomon AJ. Laboratory evaluation for the differential diagnosis of possible multiple sclerosis in the United States: A physician survey. J Neurol Sci 2023; 453:120781. [PMID: 37688999 DOI: 10.1016/j.jns.2023.120781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 08/29/2023] [Accepted: 08/30/2023] [Indexed: 09/11/2023]
Abstract
BACKGROUND There is limited evidence and lack of guidelines for diagnostic laboratory evaluation of patients with possible multiple sclerosis (MS). OBJECTIVE To survey neurologists on their practice of laboratory testing in patients with possible MS. METHODS An online survey was developed to query the frequency of serum and cerebrospinal fluid (CSF) studies ordered in the routine evaluation of patients with possible MS, and in three hypothetical clinical cases. Non-MS specialist neurologists who evaluate patients for MS in their practice were invited to participate by MedSurvey (a medical market research company). RESULTS The survey was completed by 190 neurologists. A mean of 17.2 (SD: 17.0) tests in serum and CSF were reported "always" ordered in the evaluation of patients with possible MS. CSF oligoclonal bands was the most frequently selected ("always" among 73.7% of participants). Antinuclear antibody (43.2%), erythrocyte sedimentation rate (34.2%), and thyroid stimulating hormone (31.6%) were also among the most frequently ordered. DISCUSSION Extensive laboratory evaluations are often completed in the evaluation of possible MS. However, many of these tests have poor specificity and false positive results could yield unnecessary increased costs, diagnostic delay, and potentially misdiagnosis. Further research is needed to identify optimal laboratory approaches for possible MS.
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Affiliation(s)
- Rafid Mustafa
- Departments of Neurology, Mayo Clinic College of Medicine & Science, Rochester, MN, USA.
| | - Eoin P Flanagan
- Departments of Neurology, Mayo Clinic College of Medicine & Science, Rochester, MN, USA; Laboratory Medicine and Pathology, Mayo Clinic College of Medicine & Science, Rochester, MN, USA
| | - Dustin J Duffy
- Biostatistics, Mayo Clinic College of Medicine & Science, Rochester, MN, USA
| | - Brian G Weinshenker
- Department of Neurology, University of Virginia Health, Charlottesville, VA, USA
| | - M Mateo Paz Soldán
- Department of Neurology, University of Utah Health, Salt Lake City, UT, USA
| | - Amy Kunchok
- Department of Neurology, Mellen Center for Multiple Sclerosis, Cleveland Clinic and Cleveland Clinic Lerner College of Medicine, Cleveland, OH, USA
| | - Marwa Kaisey
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Andrew J Solomon
- Department of Neurological Sciences, Larner College of Medicine at The University of Vermont Medical Center, Burlington, VT, USA
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16
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Wang Y, Bou Rjeily N, Koshorek J, Grkovski R, Aulakh M, Lin D, Solomon AJ, Mowry EM. Clinical and radiologic characteristics associated with multiple sclerosis misdiagnosis at a tertiary referral center in the United States. Mult Scler 2023; 29:1428-1436. [PMID: 37698023 DOI: 10.1177/13524585231196795] [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: 09/13/2023]
Abstract
BACKGROUND Misdiagnosis of multiple sclerosis (MS) is common and can have harmful effects on patients and healthcare systems. Identification of factors associated with misdiagnosis may aid development of prevention strategies. OBJECTIVE To identify clinical and radiological predictors of MS misdiagnosis. METHODS We retrospectively reviewed medical records of all patients who were referred to Johns Hopkins MS Center from January 2018 to June 2019. Patients who carried a diagnosis of MS were classified as correctly diagnosed or misdiagnosed with MS by the Johns Hopkins clinician. Demographics, clinical, laboratory, and radiologic data were collected. Differences between the two groups were evaluated, and a regression model was constructed to identify predictors of misdiagnosis. RESULTS Out of 338 patients who were previously diagnosed with MS, 41 (12%) had been misdiagnosed. An alternative diagnosis was confirmed in 28 (68%) of the misdiagnosed patients; cerebrovascular disease was the most common alternate diagnosis. Characteristics associated with misdiagnosis were female sex (odds ratio (OR): 5.81 (95% confidence interval (CI): 1.60, 21.05)) and non-specific brain magnetic resonance imaging (MRI) lesions (OR: 7.66 (3.42, 17.16)). CONCLUSION Misdiagnosis is a frequent problem in MS care. Non-specific brain lesions were the most significant predictor of misdiagnosis. Interventions aimed to reduce over-reliance on imaging findings and misapplication of the McDonald criteria may prevent MS misdiagnosis.
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Affiliation(s)
- Yujie Wang
- Department of Neurology, University of Washington School of Medicine, Seattle, WA, USA
| | - Nicole Bou Rjeily
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jacqueline Koshorek
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Risto Grkovski
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Manek Aulakh
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Doris Lin
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Andrew J Solomon
- Department of Neurological Sciences, Larner College of Medicine, The University of Vermont, Burlington, VT, USA
| | - Ellen M Mowry
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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17
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Lebrun-Frénay C, Siva A, Sormani MP, Landes-Chateau C, Mondot L, Bovis F, Vermersch P, Papeix C, Thouvenot E, Labauge P, Durand-Dubief F, Efendi H, Le Page E, Terzi M, Derache N, Bourre B, Hoepner R, Karabudak R, De Seze J, Ciron J, Clavelou P, Wiertlewski S, Turan OF, Yucear N, Cohen M, Azevedo C, Kantarci OH, Okuda DT, Pelletier D. Teriflunomide and Time to Clinical Multiple Sclerosis in Patients With Radiologically Isolated Syndrome: The TERIS Randomized Clinical Trial. JAMA Neurol 2023; 80:1080-1088. [PMID: 37603328 PMCID: PMC10442780 DOI: 10.1001/jamaneurol.2023.2815] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 06/13/2023] [Indexed: 08/22/2023]
Abstract
Importance Radiologically isolated syndrome (RIS) represents the earliest detectable preclinical phase of multiple sclerosis (MS) punctuated by incidental magnetic resonance imaging (MRI) white matter anomalies within the central nervous system. Objective To determine the time to onset of symptoms consistent with MS. Design, Setting, and Participants From September 2017 to October 2022, this multicenter, double-blind, phase 3, randomized clinical trial investigated the efficacy of teriflunomide in delaying MS in individuals with RIS, with a 3-year follow-up. The setting included referral centers in France, Switzerland, and Turkey. Participants older than 18 years meeting 2009 RIS criteria were randomly assigned (1:1) to oral teriflunomide, 14 mg daily, or placebo up to week 96 or, optionally, to week 144. Interventions Clinical, MRI, and patient-reported outcomes (PROs) were collected at baseline and yearly until week 96, with an optional third year in the allocated arm if no symptoms have occurred. Main outcomes Primary analysis was performed in the intention-to-treat population, and safety was assessed accordingly. Secondary end points included MRI outcomes and PROs. Results Among 124 individuals assessed for eligibility, 35 were excluded for declining to participate, not meeting inclusion criteria, or loss of follow-up. Eighty-nine participants (mean [SD] age, 37.8 [12.1] years; 63 female [70.8%]) were enrolled (placebo, 45 [50.6%]; teriflunomide, 44 [49.4%]). Eighteen participants (placebo, 9 [50.0%]; teriflunomide, 9 [50.0%]) discontinued the study, resulting in a dropout rate of 20% for adverse events (3 [16.7%]), consent withdrawal (4 [22.2%]), loss to follow-up (5 [27.8%]), voluntary withdrawal (4 [22.2%]), pregnancy (1 [5.6%]), and study termination (1 [5.6%]). The time to the first clinical event was significantly extended in the teriflunomide arm compared with placebo, in both the unadjusted (hazard ratio [HR], 0.37; 95% CI, 0.16-0.84; P = .02) and adjusted (HR, 0.28; 95% CI, 0.11-0.71; P = .007) analysis. Secondary imaging end point outcomes including the comparison of the cumulative number of new or newly enlarging T2 lesions (rate ratio [RR], 0.57; 95% CI, 0.27-1.20; P = .14), new gadolinium-enhancing lesions (RR, 0.33; 95% CI, 0.09-1.17; P = .09), and the proportion of participants with new lesions (odds ratio, 0.72; 95% CI, 0.25-2.06; P = .54) were not significant. Conclusion and Relevance Treatment with teriflunomide resulted in an unadjusted risk reduction of 63% and an adjusted risk reduction of 72%, relative to placebo, in preventing a first clinical demyelinating event. These data suggest a benefit to early treatment in the MS disease spectrum. Trial Registration ClinicalTrials.gov Identifier: NCT03122652.
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Affiliation(s)
- Christine Lebrun-Frénay
- Centre de Ressources et de Compétences Sclerose En Plaques, Neurologie Pasteur 2, CHU de Nice, Université Cote d’Azur, UMR2CA-URRIS, Nice, France
| | - Aksel Siva
- Cerrahpasa School of Medicine, Istanbul University, Istanbul, Turkiye
| | - Maria Pia Sormani
- University of Genoa, Genoa, Italy
- Ospedale Policlinico San Martino Instituti di Ricovero e Cura a Carattere Scientifico, Genoa, Italy
| | - Cassandre Landes-Chateau
- Centre de Ressources et de Compétences Sclerose En Plaques, Neurologie Pasteur 2, CHU de Nice, Université Cote d’Azur, UMR2CA-URRIS, Nice, France
| | - Lydiane Mondot
- Centre de Ressources et de Compétences Sclerose En Plaques, Neurologie Pasteur 2, CHU de Nice, Université Cote d’Azur, UMR2CA-URRIS, Nice, France
| | | | - Patrick Vermersch
- Université de Lille, Inserm, Unit 1172, LilNCog, Centre Hospitalier Universitaire de Lille, Fédération Hospitalo-Universitaire Precise, Lille, France
| | - Caroline Papeix
- Assistance Publique des Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Thouvenot
- Multiple Sclerosis Clinic, Nîmes University Hospital, Nîmes, France
| | - Pierre Labauge
- Multiple Sclerosis Clinic, Montpellier University Hospital, Montpellier, France
| | | | - Husnu Efendi
- Neurology, Kocaeli University Faculty of Medicine, Kocaeli, Turkiye
| | - Emmanuelle Le Page
- Multiple Sclerosis Clinic, Rennes University Hospital, Inserm, CIC1414, Rennes, France
| | - Murat Terzi
- School of Medicine, Neurology, Ondokuz Mayis University, Samsun, Turkiye
| | - Nathalie Derache
- Multiple Sclerosis Clinic, Caen University Hospital, Caen, France
| | - Bertrand Bourre
- Multiple Sclerosis Clinic, Rouen University Hospital, Rouen, France
| | - Robert Hoepner
- Department of Neurology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Rana Karabudak
- Hacettepe University Medical Faculty, School of Medicine, Ankara, Turkiye
| | - Jérôme De Seze
- Strasbourg University Hospital, Clinical Investigation Center, INBSRM 1434, Strasbourg, France
| | - Jonathan Ciron
- Toulouse University Hospital, Centre de Ressources et de Compétences Sclérose en Plaques, Department of Neurology, Université Toulouse III, Infinity, Inserm UMR1291, CNRS UMR5051, Toulouse, France
| | - Pierre Clavelou
- Multiple Sclerosis Clinic, Clermont-Ferrand University Hospital, Clermont-Ferrand, France
| | - Sandrine Wiertlewski
- Centre de Ressources et de Compétences Sclérose en Plaques and Clinical Investigation Center, Inserm, Nantes University Hospital, France
- Transplantation and Immunology Transplantation Center, Inserm, Nantes, France
| | | | - Nur Yucear
- Ege University Medical Faculty, Bornova, Izmir, Turkiye
| | - Mikael Cohen
- Centre de Ressources et de Compétences Sclerose En Plaques, Neurologie Pasteur 2, CHU de Nice, Université Cote d’Azur, UMR2CA-URRIS, Nice, France
| | | | | | - Darin T. Okuda
- The University of Texas Southwestern Medical Center, Dallas
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18
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Kunst MM, Gautam A, Pisa M, Wald C, Broder JC. Get With the Guidelines on MS Imaging by Leveraging Peer Learning. Curr Probl Diagn Radiol 2023; 52:322-326. [PMID: 37069020 DOI: 10.1067/j.cpradiol.2023.03.011] [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: 03/08/2023] [Accepted: 03/16/2023] [Indexed: 04/03/2023]
Abstract
OBJECTIVES To achieve consensus on the performance, interpretation and reporting of MS imaging according to up-to-date guidelines using the Peer Learning Methodology. MATERIALS AND METHODS We utilized the Peer Learning Methodology to engage our clinical and radiology colleagues, review the current guidelines, acheive consensus on imaging techniques and reporting standards. After implementing changes, we collected radiologist feedback on the impact of the optimized images on their interpretation. RESULTS Survey responders indicated a strong preference for the new protocol in terms of overall image quality, individual lesions conspicuity and confidence in the ability to detect an MS lesion. The new protocol was preferred for both MS diagnosis and MS surveillance in 25 of 28 responses. CONCLUSION The Peer Learning Methodology is an effective tool to standardize and improve MR imaging quality, interpretation and reporting for Multiple Sclerosis in accordance with current guidelines.
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Affiliation(s)
- Mara M Kunst
- Deptartment of Radiology, Lahey Hospital and Medical Center, Burlington, MA.
| | - Anirudh Gautam
- Deptartment of Radiology, Lahey Hospital and Medical Center, Burlington, MA
| | - Michelle Pisa
- Deptartment of Radiology, Lahey Hospital and Medical Center, Burlington, MA
| | - Christoph Wald
- Deptartment of Radiology, Lahey Hospital and Medical Center, Burlington, MA
| | - Jennifer C Broder
- Deptartment of Radiology, Lahey Hospital and Medical Center, Burlington, MA
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19
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Carnero Contentti E, Okuda DT, Rojas JI, Chien C, Paul F, Alonso R. MRI to differentiate multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. J Neuroimaging 2023; 33:688-702. [PMID: 37322542 DOI: 10.1111/jon.13137] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 06/17/2023] Open
Abstract
Differentiating multiple sclerosis (MS) from other relapsing inflammatory autoimmune diseases of the central nervous system such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is crucial in clinical practice. The differential diagnosis may be challenging but making the correct ultimate diagnosis is critical, since prognosis and treatments differ, and inappropriate therapy may promote disability. In the last two decades, significant advances have been made in MS, NMOSD, and MOGAD including new diagnostic criteria with better characterization of typical clinical symptoms and suggestive imaging (magnetic resonance imaging [MRI]) lesions. MRI is invaluable in making the ultimate diagnosis. An increasing amount of new evidence with respect to the specificity of observed lesions as well as the associated dynamic changes in the acute and follow-up phase in each condition has been reported in distinct studies recently published. Additionally, differences in brain (including the optic nerve) and spinal cord lesion patterns between MS, aquaporin4-antibody-positive NMOSD, and MOGAD have been described. We therefore present a narrative review on the most relevant findings in brain, spinal cord, and optic nerve lesions on conventional MRI for distinguishing adult patients with MS from NMOSD and MOGAD in clinical practice. In this context, cortical and central vein sign lesions, brain and spinal cord lesions characteristic of MS, NMOSD, and MOGAD, optic nerve involvement, role of MRI at follow-up, and new proposed diagnostic criteria to differentiate MS from NMOSD and MOGAD were discussed.
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Affiliation(s)
| | - Darin T Okuda
- Department of Neurology, Neuroinnovation Program, Multiple Sclerosis & Neuroimmunology Imaging Program, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Juan I Rojas
- Centro de esclerosis múltiple de Buenos Aires, Buenos Aires, Argentina
| | - Claudia Chien
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Friedemman Paul
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ricardo Alonso
- Centro Universitario de Esclerosis Múltiple (CUEM), Hospital Ramos Mejía, Buenos Aires, Argentina
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20
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Thomas C, Schneider BT, Verza CS, Fassina G, Weber LR, Moreira M, Fusinato PT, Forcelini CM. Prevalence of fibromyalgia in a Brazilian series of patients with multiple sclerosis. ARQUIVOS DE NEURO-PSIQUIATRIA 2023; 81:803-808. [PMID: 37793402 PMCID: PMC10550347 DOI: 10.1055/s-0043-1772673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 06/05/2023] [Indexed: 10/06/2023]
Abstract
BACKGROUND The prevalence of pain in patients with multiple sclerosis is remarkable. Fibromyalgia has been considered as one of the forms of chronic pain encompassed in multiple sclerosis, but data are restricted to studies from Europe and North America. OBJECTIVE To assess the prevalence of fibromyalgia in a series of Brazilian patients with multiple sclerosis and the characteristics of this comorbidity. METHODS The present cross-sectional study included 60 consecutive adult patients with multiple sclerosis. Upon consent, participants underwent a thorough evaluation for disability, fatigue, quality of life, presence of fibromyalgia, depression, and anxiety. RESULTS The prevalence of fibromyalgia was 11.7%, a figure similar to that observed in previous studies. Patients with the comorbidity exhibited worse scores on fatigue (median and interquartile range [IQR]: 68 [48-70] versus 39 [16.5-49]; p < 0.001), quality of life (mean ± standard deviation [SD]: 96.5 ± 35.9 versus 124.8 ± 28.8; p = 0.021), anxiety (mean ± SD: 22.7 ± 15.1 versus 13.8 ± 8.4; p = 0.021), and depression (median and IQR: 23 [6-28] versus 6 [3-12.5]; p = 0.034) indices than patients without fibromyalgia. There was a strong positive correlation between depression and anxiety scores with fatigue (r = 0.773 and r = 0.773, respectively; p < 0.001). Conversely, a moderate negative correlation appeared between the Expanded Disability Status Scale (EDSS), fatigue, and depression scores with quality of life (r= -0.587, r= -0.551, r= -0.502, respectively; p < 0.001). CONCLUSION Fibromyalgia is a comorbidity of multiple sclerosis that can enhance fatigue and decrease quality of life, although depression, anxiety, and disability are factors that can potentiate the impact of the comorbidity.
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Affiliation(s)
| | | | | | - Gabriel Fassina
- Universidade de Passo Fundo, Faculdade de Medicina, Passo Fundo RS, Brazil.
| | - Laís Restel Weber
- Universidade de Passo Fundo, Faculdade de Medicina, Passo Fundo RS, Brazil.
| | - Marlinton Moreira
- Universidade de Passo Fundo, Faculdade de Medicina, Passo Fundo RS, Brazil.
| | | | - Cassiano Mateus Forcelini
- Hospital São Vicente de Paulo, Passo Fundo RS, Brazil.
- Universidade de Passo Fundo, Faculdade de Medicina, Passo Fundo RS, Brazil.
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21
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Lebrun-Frénay C, Okuda DT, Siva A, Landes-Chateau C, Azevedo CJ, Mondot L, Carra-Dallière C, Zephir H, Louapre C, Durand-Dubief F, Le Page E, Bensa C, Ruet A, Ciron J, Laplaud DA, Casez O, Mathey G, de Seze J, Zeydan B, Makhani N, Tutuncu M, Levraut M, Cohen M, Thouvenot E, Pelletier D, Kantarci OH. The radiologically isolated syndrome: revised diagnostic criteria. Brain 2023; 146:3431-3443. [PMID: 36864688 PMCID: PMC11004931 DOI: 10.1093/brain/awad073] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/26/2023] [Accepted: 02/05/2023] [Indexed: 03/04/2023] Open
Abstract
The radiologically isolated syndrome (RIS) was defined in 2009 as the presence of asymptomatic, incidentally identified demyelinating-appearing white matter lesions in the CNS within individuals lacking symptoms typical of multiple sclerosis (MS). The RIS criteria have been validated and predict the transition to symptomatic MS reliably. The performance of RIS criteria that require fewer MRI lesions is unknown. 2009-RIS subjects, by definition, fulfil three to four of four criteria for 2005 dissemination in space (DIS) and subjects fulfilling only one or two lesions in at least one 2017 DIS location were identified within 37 prospective databases. Univariate and multivariate Cox regression models were used to identify predictors of a first clinical event. Performances of different groups were calculated. Seven hundred and forty-seven subjects (72.2% female, mean age 37.7 ± 12.3 years at the index MRI) were included. The mean clinical follow-up time was 46.8 ± 45.4 months. All subjects had focal T2 hyperintensities suggestive of inflammatory demyelination on MRI; 251 (33.6%) fulfilled one or two 2017 DIS criteria (designated as Groups 1 and 2, respectively), and 496 (66.4%) fulfilled three or four 2005 DIS criteria representing 2009-RIS subjects. Group 1 and 2 subjects were younger than the 2009-RIS group and were more likely to develop new T2 lesions over time (P < 0.001). Groups 1 and 2 were similar regarding survival distribution and risk factors for transition to MS. At 5 years, the cumulative probability for a clinical event was 29.0% for Groups 1 and 2 compared to 38.7% for 2009-RIS (P = 0.0241). The presence of spinal cord lesions on the index scan and CSF-restricted oligoclonal bands in Groups 1-2 increased the risk of symptomatic MS evolution at 5 years to 38%, comparable to the risk of development in the 2009-RIS group. The presence of new T2 or gadolinium-enhancing lesions on follow-up scans independently increased the risk of presenting with a clinical event (P < 0.001). The 2009-RIS subjects or Groups 1 and 2 with at least two of the risk factors for a clinical event demonstrated better sensitivity (86.0%), negative predictive value (73.1%), accuracy (59.8%) and area under the curve (60.7%) compared to other criteria studied. This large prospective cohort brings Class I evidence that subjects with fewer lesions than required in the 2009 RIS criteria evolve directly to a first clinical event at a similar rate when additional risk factors are present. Our results provide a rationale for revisions to existing RIS diagnostic criteria.
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Affiliation(s)
- Christine Lebrun-Frénay
- Neurology MS Clinic Nice, Pasteur 2 University Hospital, UR2CA-URRIS, Côte d’Azur University, Nice 06002, France
| | - Darin T Okuda
- Neuroinnovation Program, Multiple Sclerosis, and Neuroimmunology Imaging Program, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Aksel Siva
- Department of Neurology, Istanbul University Cerrahpasa School of Medicine, 34098 Istanbul, Turkey
| | - Cassandre Landes-Chateau
- Neurology MS Clinic Nice, Pasteur 2 University Hospital, UR2CA-URRIS, Côte d’Azur University, Nice 06002, France
| | - Christina J Azevedo
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Lydiane Mondot
- Neurology MS Clinic Nice, Pasteur 2 University Hospital, UR2CA-URRIS, Côte d’Azur University, Nice 06002, France
| | - Clarisse Carra-Dallière
- Neurology MS Clinic, Montpellier University Hospital, 34295 Montpellier, France
- University of Montpellier (MUSE), 34295 Montpellier, France
| | - Helene Zephir
- Inserm UMR-S 1172 LilNcog, Lille University, Lille University Hospital Precise, 59000 Lille, France
| | - Celine Louapre
- Department of Neurology, Sorbonne University, AP-HP, Pitié-Salpêtrière Hospital, 75013 Paris, France
| | - Françoise Durand-Dubief
- Neurology MS Clinic, Neurological Hospital Pierre Wertheimer, Lyon University Hospital, 69500 Lyon/Bron, France
| | - Emmanuelle Le Page
- Neurology MS Clinic Rennes, Clinical Investigation Centre CIC-P 1414, Rennes University Hospital, 35000 Rennes, France
| | | | - Aurélie Ruet
- Neurology MS Clinic Bordeaux, University Hospital, 33000 Bordeaux, France
- Neurocentre Magendie, Bordeaux University, INSERM, U1215, 33000 Bordeaux, France
| | - Jonathan Ciron
- Neurology MS Clinic, Toulouse University Hospital, 31300 Toulouse, France
- Infinity, INSERM UMR1291, CNRS UMR5051, Toulouse III University, 31300 Toulouse, France
| | - David A Laplaud
- Neurology, Nantes University Hospital, CIC1314 INSERM, 44000 Nantes, France
- CR2TI INSERM U1064, Nantes University, 44000 Nantes, France
| | - Olivier Casez
- Neurology MS Clinic Grenoble, Grenoble Alpes University Hospital, 38700 Grenoble, France
- T-RAIG, TIMC-IMAG, Grenoble Alpes University, 38700 Grenoble, France
| | - Guillaume Mathey
- Neurology, Nancy University Hospital, 54000 Nancy, France
- Vandoeuvre-Lès-Nancy, Lorraine University, EA 4360 APEMAC, 54000 Nancy, France
| | - Jerome de Seze
- Clinical Investigation Center, Neurology, Strasbourg University Hospital, INSERM 1434, 67200 Strasbourg, France
| | - Burcu Zeydan
- Neurology and Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Naila Makhani
- Pediatrics and Neurology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Melih Tutuncu
- Department of Neurology, Istanbul University Cerrahpasa School of Medicine, 34098 Istanbul, Turkey
| | - Michael Levraut
- Neurology MS Clinic Nice, Pasteur 2 University Hospital, UR2CA-URRIS, Côte d’Azur University, Nice 06002, France
| | - Mikael Cohen
- Neurology MS Clinic Nice, Pasteur 2 University Hospital, UR2CA-URRIS, Côte d’Azur University, Nice 06002, France
| | - Eric Thouvenot
- Neurology, Nîmes University Hospital, 30900 Nîmes, France
- IGF, Montpellier University, CNRS, INSERM, 34295 Montpellier, France
| | - Daniel Pelletier
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
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22
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Gill AJ, Schorr EM, Gadani SP, Calabresi PA. Emerging imaging and liquid biomarkers in multiple sclerosis. Eur J Immunol 2023; 53:e2250228. [PMID: 37194443 PMCID: PMC10524168 DOI: 10.1002/eji.202250228] [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: 02/15/2023] [Revised: 04/10/2023] [Accepted: 05/12/2023] [Indexed: 05/18/2023]
Abstract
The advent of highly effective disease modifying therapy has transformed the landscape of multiple sclerosis (MS) care over the last two decades. However, there remains a critical, unmet need for sensitive and specific biomarkers to aid in diagnosis, prognosis, treatment monitoring, and the development of new interventions, particularly for people with progressive disease. This review evaluates the current data for several emerging imaging and liquid biomarkers in people with MS. MRI findings such as the central vein sign and paramagnetic rim lesions may improve MS diagnostic accuracy and evaluation of therapy efficacy in progressive disease. Serum and cerebrospinal fluid levels of several neuroglial proteins, such as neurofilament light chain and glial fibrillary acidic protein, show potential to be sensitive biomarkers of pathologic processes such as neuro-axonal injury or glial-inflammation. Additional promising biomarkers, including optical coherence tomography, cytokines and chemokines, microRNAs, and extracellular vesicles/exosomes, are also reviewed, among others. Beyond their potential integration into MS clinical care and interventional trials, several of these biomarkers may be informative of MS pathogenesis and help elucidate novel targets for treatment strategies.
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Affiliation(s)
- Alexander J. Gill
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Emily M. Schorr
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Sachin P. Gadani
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Peter A. Calabresi
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
- Department of Neuroscience, Baltimore, MD, US
- Department of Ophthalmology, Baltimore, MD, US
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23
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Solomon AJ, Arrambide G, Brownlee WJ, Flanagan EP, Amato MP, Amezcua L, Banwell BL, Barkhof F, Corboy JR, Correale J, Fujihara K, Graves J, Harnegie MP, Hemmer B, Lechner-Scott J, Marrie RA, Newsome SD, Rocca MA, Royal W, Waubant EL, Yamout B, Cohen JA. Differential diagnosis of suspected multiple sclerosis: an updated consensus approach. Lancet Neurol 2023; 22:750-768. [PMID: 37479377 DOI: 10.1016/s1474-4422(23)00148-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 03/14/2023] [Accepted: 03/31/2023] [Indexed: 07/23/2023]
Abstract
Accurate diagnosis of multiple sclerosis requires careful attention to its differential diagnosis-many disorders can mimic the clinical manifestations and paraclinical findings of this disease. A collaborative effort, organised by The International Advisory Committee on Clinical Trials in Multiple Sclerosis in 2008, provided diagnostic approaches to multiple sclerosis and identified clinical and paraclinical findings (so-called red flags) suggestive of alternative diagnoses. Since then, knowledge of disorders in the differential diagnosis of multiple sclerosis has expanded substantially. For example, CNS inflammatory disorders that present with syndromes overlapping with multiple sclerosis can increasingly be distinguished from multiple sclerosis with the aid of specific clinical, MRI, and laboratory findings; studies of people misdiagnosed with multiple sclerosis have also provided insights into clinical presentations for which extra caution is warranted. Considering these data, an update to the recommended diagnostic approaches to common clinical presentations and key clinical and paraclinical red flags is warranted to inform the contemporary clinical evaluation of patients with suspected multiple sclerosis.
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Affiliation(s)
- Andrew J Solomon
- Department of Neurological Sciences, Larner College of Medicine at the University of Vermont, University Health Center, Burlington, VT, USA.
| | - 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, Barcelona, Spain
| | - Wallace J Brownlee
- National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Eoin P Flanagan
- Departments of Neurology and Laboratory Medicine and Pathology and the Center for Multiple Sclerosis and Autoimmune Neurology, Mayo Clinic, Rochester, MN, USA
| | - Maria Pia Amato
- Department NEUROFARBA, University of Florence, Florence, Italy; IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Lilyana Amezcua
- Department of Neurology, University of Southern California, Keck School of Medicine, Los Angeles, CA, USA
| | - Brenda L Banwell
- Department of Neurology, University of Pennsylvania, Division of Child Neurology, Philadelphia, PA, USA; Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - John R Corboy
- Department of Neurology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Jorge Correale
- Department of Neurology, Fleni Institute of Biological Chemistry and Physical Chemistry (IQUIFIB), Buenos Aires, Argentina; National Council for Scientific and Technical Research/University of Buenos Aires, Buenos Aires, Argentina
| | - Kazuo Fujihara
- Department of Multiple Sclerosis Therapeutics, Fukushima Medical University School of Medicine, Koriyama, Japan; Multiple Sclerosis and Neuromyelitis Optica Center, Southern TOHOKU Research Institute for Neuroscience, Koriyama, Japan
| | - Jennifer Graves
- Department of Neurosciences, University of California, San Diego, CA, USA
| | | | - Bernhard Hemmer
- Department of Neurology, Klinikum rechts der Isar, Medical Faculty, Technische Universität München, Munich, Germany; Munich Cluster for Systems Neurology, Munich, Germany
| | - Jeannette Lechner-Scott
- Department of Neurology, John Hunter Hospital, Newcastle, NSW Australia; Hunter Medical Research Institute Neurology, University of Newcastle, Newcastle, NSW, Australia
| | - Ruth Ann Marrie
- Departments of Internal Medicine and Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Scott D Newsome
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, Neurology Unit, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Walter Royal
- Department of Neurobiology and Neuroscience Institute, Morehouse School of Medicine, Atlanta, GA, USA
| | - Emmanuelle L Waubant
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - Bassem Yamout
- Neurology Institute, Harley Street Medical Center, Abu Dhabi, United Arab Emirates
| | - Jeffrey A Cohen
- Mellen Center for MS Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
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Baskaran AB, Grebenciucova E, Shoemaker T, Graham EL. Current Updates on the Diagnosis and Management of Multiple Sclerosis for the General Neurologist. J Clin Neurol 2023; 19:217-229. [PMID: 37151139 PMCID: PMC10169923 DOI: 10.3988/jcn.2022.0208] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 11/04/2022] [Accepted: 01/04/2023] [Indexed: 05/09/2023] Open
Abstract
Multiple sclerosis (MS) is an immune-driven disease that affects the central nervous system and is characterized by acute-on-chronic demyelination attacks. It is a major cause of global neurological disability, and its prevalence has increased in the United States. Conceptual understandings of MS have evolved over time, including the identification of B cells as key factors in its pathophysiology. The foundation of MS management involves preventing flares so as to avoid long-term functional decline. Treatments may be categorized into low-, middle-, and high-efficacy medications based on their efficacy in relapse prevention. With 24 FDA-approved treatments for MS, individual therapy is chosen based on distinct mechanisms and potential side effects. This review provides a detailed update on the epidemiology, diagnosis, treatment advances, and major ongoing research investigations in MS.
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Affiliation(s)
| | - Elena Grebenciucova
- Division of Neuroimmunology, Division of Neuroinfectious Diseases, Northwestern University, Chicago, IL, USA
| | | | - Edith L Graham
- Division of Neuroimmunology, Division of Neuroinfectious Diseases, Northwestern University, Chicago, IL, USA.
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Okuda DT, Kantarci O, Lebrun-Frénay C, Sormani MP, Azevedo CJ, Bovis F, Hua LH, Amezcua L, Mowry EM, Hotermans C, Mendoza J, Walsh JS, von Hehn C, Vargas WS, Donlon S, Naismith RT, Okai A, Pardo G, Repovic P, Stüve O, Siva A, Pelletier D. Dimethyl Fumarate Delays Multiple Sclerosis in Radiologically Isolated Syndrome. Ann Neurol 2023; 93:604-614. [PMID: 36401339 DOI: 10.1002/ana.26555] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 11/14/2022] [Accepted: 11/17/2022] [Indexed: 11/21/2022]
Abstract
OBJECTIVE The radiologically isolated syndrome (RIS) represents the earliest detectable pre-clinical phase of multiple sclerosis (MS). This study evaluated the impact of therapeutic intervention in preventing first symptom manifestation at this stage in the disease spectrum. METHODS We conducted a multi-center, randomized, double-blinded, placebo-controlled study involving people with RIS. Individuals without clinical symptoms typical of MS but with incidental brain MRI anomalies consistent with central nervous system (CNS) demyelination were included. Within 12 MS centers in the United States, participants were randomly assigned 1:1 to oral dimethyl fumarate (DMF) 240 mg twice daily or placebo. The primary endpoint was the time to onset of clinical symptoms attributable to a CNS demyelinating event within a follow-up period of 96 weeks. An intention-to-treat analysis was applied to all participating individuals in the primary and safety investigations. The study is registered at ClinicalTrials.gov, NCT02739542 (ARISE). RESULTS Participants from 12 centers were recruited from March 9, 2016, to October 31, 2019, with 44 people randomized to dimethyl fumarate and 43 to placebo. Following DMF treatment, the risk of a first clinical demyelinating event during the 96-week study period was highly reduced in the unadjusted Cox proportional-hazards regression model (hazard ratio [HR] = 0.18, 95% confidence interval [CI] = 0.05-0.63, p = 0.007). More moderate adverse reactions were present in the DMF (34 [32%]) than placebo groups (19 [21%]) but severe events were similar (DMF, 3 [5%]; placebo, 4 [9%]). INTERPRETATION This is the first randomized clinical trial demonstrating the benefit of a disease-modifying therapy in preventing a first acute clinical event in people with RIS. ANN NEUROL 2023;93:604-614.
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Affiliation(s)
- Darin T Okuda
- Department of Neurology, Neuroinnovation Program, Multiple Sclerosis & Neuroimmunology Imaging Program, The University of Texas Southwestern Medical Center, Dallas, TX
| | | | | | - Maria Pia Sormani
- Department of Health Sciences, University of Genoa, Genoa, Italy.,Department of Health Sciences, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | | | - Francesca Bovis
- Department of Health Sciences, University of Genoa, Genoa, Italy
| | - Le H Hua
- Department of Neurology, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV
| | - Lilyana Amezcua
- Department of Neurology, University of Southern California, Los Angeles, CA
| | - Ellen M Mowry
- Department of Neurology-Neuroimmunology and Neurological Infections, Johns Hopkins University, Baltimore, MD
| | | | | | | | | | - Wendy S Vargas
- Department of Neurology, Columbia University Medical Center, New York, NY
| | - Stacy Donlon
- Department of Neuroimmunology, Multicare Auburn Medical Center, Tacoma, WA
| | | | - Annette Okai
- Department of Neurology, Baylor University Medical Center, Dallas, TX
| | - Gabriel Pardo
- Oklahoma Medical Research Foundation, Oklahoma City, OK
| | - Pavle Repovic
- Department of Neurology, Swedish Medical Center, Seattle, WA
| | - Olaf Stüve
- Department of Neurology, Neuroinnovation Program, Multiple Sclerosis & Neuroimmunology Imaging Program, The University of Texas Southwestern Medical Center, Dallas, TX.,Neurology Section, Dallas Veterans Affairs Medical Center, Dallas, TX
| | - Aksel Siva
- Department of Neurology, Cerrahpasa School of Medicine, Istanbul, Turkey
| | - Daniel Pelletier
- Department of Neurology, University of Southern California, Los Angeles, CA
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Quigley S, Yiannakas MC, Bede P, Meaney J, Kearney H. Neuropathologically informed imaging of cortical grey matter lesions in MS - A pilot study. Mult Scler Relat Disord 2023; 71:104555. [PMID: 36870314 DOI: 10.1016/j.msard.2023.104555] [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: 12/09/2022] [Revised: 01/06/2023] [Accepted: 02/05/2023] [Indexed: 02/10/2023]
Abstract
Multiple sclerosis (MS) is frequently misdiagnosed based on MRI abnormalities detected in the brain white matter. Cortical lesions have been well described neuropathologically, but remain challenging to detect in clinical practice. Therefore, the ability to detect cortical lesions offers real potential to reduce misdiagnosis. Cortical lesions have been shown to have a predilection for regions with CSF stasis - such as the insula and cingulate gyrus. This pathological observation forms the basis of our current pilot MR imaging study, which successfully uses high spatial resolution imaging of these two anatomical regions to clearly identify cortical lesions in MS.
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Affiliation(s)
- S Quigley
- Department of Neurology, St James's Hospital, Dublin, Ireland
| | - M C Yiannakas
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - P Bede
- Department of Neurology, St James's Hospital, Dublin, Ireland; Computational Neuroimaging Group (CNG), TBSI, Trinity College Dublin, Ireland
| | - J Meaney
- Centre for Advanced Medical Imaging, St James's Hospital and Trinity College Dublin, Dublin, Ireland
| | - H Kearney
- Department of Neurology, St James's Hospital, Dublin, Ireland; Academic Unit of Neurology, Trinity College Dublin, Ireland.
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Bachhuber A. [Diagnostic work-up, findings, and documentation of multiple sclerosis]. RADIOLOGIE (HEIDELBERG, GERMANY) 2023; 63:115-119. [PMID: 36658297 DOI: 10.1007/s00117-022-01104-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/01/2022] [Indexed: 01/21/2023]
Abstract
BACKGROUND Although multiple sclerosis is the most common chronic inflammatory demyelinating disease of the central nervous system, the rate of misdiagnosis in clinical practice is high. This is usually due to the inadequate application of the McDonald criteria and misinterpretation of images. OBJECTIVE This review focuses on typical clinical symptoms, choice of magnetic resonance imaging (MRI) sequences, correct application of the McDonald criteria, and finally interpretation of the images.
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Affiliation(s)
- Armin Bachhuber
- Klinik für Diagnostische und Interventionelle, Neuroradiologie, Universitätsklinikum des Saarlandes, Kirrberger Straße, 66424, Homburg-Saar, Deutschland.
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Tillema JM. Imaging of Central Nervous System Demyelinating Disorders. Continuum (Minneap Minn) 2023; 29:292-323. [PMID: 36795881 DOI: 10.1212/con.0000000000001246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
OBJECTIVE This article summarizes neuroimaging findings in demyelinating disease, the most common being multiple sclerosis. Revisions to criteria and treatment options have been ongoing, and MRI plays a pivotal role in diagnosis and disease monitoring. The common antibody-mediated demyelinating disorders with their respective classic imaging features are reviewed, as well as the differential diagnostic considerations on imaging. LATEST DEVELOPMENTS The clinical criteria of demyelinating disease rely heavily on imaging with MRI. With novel antibody detection, the range of clinical demyelinating syndromes has expanded, most recently with myelin oligodendrocyte glycoprotein-IgG antibodies. Imaging has improved our understanding of the pathophysiology of multiple sclerosis and disease progression, and further research is underway. The importance of increased detection of pathology outside of the classic lesions will have an important role as therapeutic options are expanding. ESSENTIAL POINTS MRI has a crucial role in the diagnostic criteria and differentiation among common demyelinating disorders and syndromes. This article reviews the typical imaging features and clinical scenarios that assist in accurate diagnosis, differentiation between demyelinating diseases and other white matter diseases, the importance of standardized MRI protocols in clinical practice, and novel imaging techniques.
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Carnero Contentti E, López PA, Criniti J, Alonso R, Silva B, Luetic G, Correa-Díaz EP, Galleguillos L, Navas C, Soto de Castillo I, Hamuy FDDB, Gracia F, Tkachuk V, Weinshenker BG, Rojas JI. Frequency of NMOSD misdiagnosis in a cohort from Latin America: Impact and evaluation of different contributors. Mult Scler 2023; 29:277-286. [PMID: 36453614 DOI: 10.1177/13524585221136259] [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: 12/03/2022]
Abstract
BACKGROUND Neuromyelitis optica spectrum disorder (NMOSD) misdiagnosis (i.e. the incorrect diagnosis of patients who truly have NMOSD) remains an issue in clinical practice. We determined the frequency and factors associated with NMOSD misdiagnosis in patients evaluated in a cohort from Latin America. METHODS We retrospectively reviewed the medical records of patients with NMOSD, according to the 2015 diagnostic criteria, from referral clinics in six Latin American countries (Argentina, Chile, Paraguay, Colombia, Ecuador, and Venezuela). Diagnoses prior to NMOSD and ultimate diagnoses, demographic, clinical and paraclinical data, and treatment schemes were evaluated. RESULTS A total of 469 patients presented with an established diagnosis of NMOSD (73.2% seropositive) and after evaluation, we determined that 56 (12%) patients had been initially misdiagnosed with a disease other than NMOSD. The most frequent alternative diagnoses were multiple sclerosis (MS; 66.1%), clinically isolated syndrome (17.9%), and cerebrovascular disease (3.6%). NMOSD misdiagnosis was determined by MS/NMOSD specialists in 33.9% of cases. An atypical MS syndrome was found in 86% of misdiagnosed patients, 50% had NMOSD red flags in brain and/or spinal magnetic resonance imaging (MRI), and 71.5% were prescribed disease-modifying drugs. CONCLUSIONS NMOSD misdiagnosis is relatively frequent in Latin America (12%). Misapplication and misinterpretation of clinical and neuroradiological findings are relevant factors associated with misdiagnosis.
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Affiliation(s)
| | - Pablo A López
- Neuroimmunology Unit, Department of Neuroscience, Hospital Alemán, Buenos Aires, Argentina
| | - Juan Criniti
- Department of Internal Medicine, Hospital Alemán, Buenos Aires, Argentina
| | - Ricardo Alonso
- Neurology Department, Hospital J.M. Ramos Mejía, University of Buenos Aires, Buenos Aires, Argentina
| | - Berenice Silva
- Neurology Department, Hospital J.M. Ramos Mejía, University of Buenos Aires, Buenos Aires, Argentina/Sección Enfermedades Desmielinizantes, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
| | | | | | - Lorna Galleguillos
- Clínica Alemana de Santiago, Santiago, Chile; Universidad del Desarrollo, Santiago, Chile
| | - Carlos Navas
- Clínica Enfermedad Desmielinizante, Clinica Universitaria Colombia, Bogotá, Colombia
| | | | | | - Fernando Gracia
- Hospital Santo Tomas, Universidad Interamericana de Panamá, Panama City, Panamá
| | - Verónica Tkachuk
- Neuroimmunology Section, Department of Neurology, Hospital de Clínicas "José de San Martín," Buenos Aires, Argentina
| | | | - Juan Ignacio Rojas
- Centro de Esclerosis Múltiple de Buenos Aires (CEMBA), Buenos Aires, Argentina
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Cerebrospinal Fluid Biomarkers in Differential Diagnosis of Multiple Sclerosis and Systemic Inflammatory Diseases with Central Nervous System Involvement. Biomedicines 2023; 11:biomedicines11020425. [PMID: 36830963 PMCID: PMC9953577 DOI: 10.3390/biomedicines11020425] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/19/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Diagnosis of multiple sclerosis (MS) is established on criteria according to clinical and radiological manifestation. Cerebrospinal fluid (CSF) analysis is an important part of differential diagnosis of MS and other inflammatory processes in the central nervous system (CNS). METHODS In total, 242 CSF samples were collected from patients undergoing differential MS diagnosis because of the presence of T2-hyperintensive lesions on brain MRI. The non-MS patients were subdivided into systemic inflammatory diseases with CNS involvement (SID) or cerebrovascular diseases (CVD) or other non-inflammatory diseases (NID). All samples were analyzed for the presence of oligoclonal bands and ELISA was performed for detection of: INF gamma, IL-6, neurofilaments light chain (NF-L), GFAP, CHI3L1, CXCL13, and osteopontin. RESULTS The level of IL-6 (p = 0.024), osteopontin (p = 0.0002), and NF-L (p = 0.002) was significantly different among groups. IL-6 (p = 0.0350) and NF-L (p = 0.0015) level was significantly higher in SID compared to NID patients. A significantly higher level of osteopontin (p = 0.00026) and NF-L (p = 0.002) in MS compared to NID population was noted. ROC analysis found weak diagnostic power for osteopontin and NFL-L. CONCLUSIONS The classical and non-standard markers of inflammatory process and neurodegeneration do not allow for sufficient differentiation between MS and non-MS inflammatory CNS disorders. Weak diagnostic power observed for the osteopontin and NF-L needs to be further investigated.
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Shah AA, Piche J, Stewart B, Lyness C, Callaghan B, Solomon AJ. Limited diagnostic utility of serologic testing for neurologic manifestations of systemic disease in the evaluation of suspected multiple sclerosis: A single-center observational study. Mult Scler Relat Disord 2023; 69:104443. [PMID: 36521385 DOI: 10.1016/j.msard.2022.104443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 11/14/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND The clinical evaluation of a new diagnosis of MS typically includes serologic testing to evaluate for its many mimics, yet there is little data to guide approaches to such testing. OBJECTIVE To evaluate for the frequency and clinical significance of serologic testing for MS diagnostic evaluations. METHODS In a single MS subspeciality center retrospective study, new patient evaluations for MS over the course of a year were identified, and the results of serologic testing and diagnostic evaluation extracted. Retrospective longitudinal diagnostic assessment was performed to confirm the accuracy of initial serological testing assessments. RESULTS 150 patients had 823 serologic tests. 40 (5%) tests were positive, and resulted in 117 additional serologic tests, 10 radiographs, and 2 biopsies. 77 (51%) patients were diagnosed with a non-demyelinating disorder. Serologic testing results did not change any diagnosis, yet in some patients, it resulted in unnecessary additional testing and diagnostic delay. CONCLUSIONS Serologic testing in the clinical assessment for routine MS resulted in unnecessary diagnostic delay, additional testing, and considerable healthcare cost.
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Affiliation(s)
- Anna A Shah
- Department of Neurology & Rocky Mountain MS Center, University of Colorado School of Medicine, Academic Office 1, B-185, 12631 East 17th Avenue, Aurora, CO 80045, USA.
| | - Jessica Piche
- Department of Neurology, University of Michigan School of Medicine, Ann Arbor, MI, USA
| | | | | | - Brian Callaghan
- Department of Neurology, University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Andrew J Solomon
- Department of Neurological Sciences, Lartner College of Medicine at the University of Vermont School, Burlington, VT, USA
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Aybek S, Chan A. The borderland of multiple sclerosis and functional neurological disorder: A call for clinical research and vigilance. Eur J Neurol 2023; 30:3-8. [PMID: 36135345 DOI: 10.1111/ene.15568] [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: 02/20/2022] [Revised: 07/29/2022] [Accepted: 08/12/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND PURPOSE Functional neurological disorders (FNDs) have attracted much attention from the neurological medical community over the last decades as new developments in neurosciences have reduced stigma around these by showing brain network dysfunctions. An overlap with other neurological conditions such as multiple sclerosis (MS) is well known by clinicians but there is a lack of clinical and fundamental research in this field to better define diagnosis and therapeutic decisions, as well as a lack of deep understanding of the underlying pathophysiology. AIM We aimed to provide a critical commentary on the state of knowledge about the borderland between FNDs and MS. METHODS We based our commentary on a joint point of view between an FND specialist and an MS expert. RESULTS A brief review of the previous literature and relevant new studies covering the overlap between FNDs and MS is presented, along with suggestions for future research directions. CONCLUSION There are clear diagnostic criteria for both FNDs and MS and a strict application of these will help better diagnosis and prevent unnecessary treatment escalation in MS or absence of referral to multimodal therapy in FND. Better teaching of younger neurologists is needed as well as prospective research focusing on pathophysiology.
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Affiliation(s)
- Selma Aybek
- Psychosomatic Medicine Unit, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Andrew Chan
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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Editorial Comment: Gadolinium-Based Contrast Agent and the Central Vein Sign. AJR Am J Roentgenol 2023; 220:125. [PMID: 36069490 DOI: 10.2214/ajr.22.28454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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Daboul L, O'Donnell CM, Cao Q, Amin M, Rodrigues P, Derbyshire J, Azevedo C, Bar-Or A, Caverzasi E, Calabresi P, Cree BAC, Freeman L, Henry RG, Longbrake EE, Nakamura K, Oh J, Papinutto N, Pelletier D, Samudralwar RD, Suthiphosuwan S, Schindler MK, Sotirchos ES, Sicotte NL, Solomon AJ, Shinohara RT, Reich DS, Ontaneda D, Sati P. Effect of GBCA Use on Detection and Diagnostic Performance of the Central Vein Sign: Evaluation Using a 3-T FLAIR* Sequence in Patients With Suspected Multiple Sclerosis. AJR Am J Roentgenol 2023; 220:115-125. [PMID: 35975888 PMCID: PMC10016223 DOI: 10.2214/ajr.22.27731] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND. The central vein sign (CVS) is a proposed MRI biomarker of multiple sclerosis (MS). The impact of gadolinium-based contrast agent (GBCA) administration on CVS evaluation remains poorly investigated. OBJECTIVE. The purpose of this study was to assess the effect of GBCA use on CVS detection and on the diagnostic performance of the CVS for MS using a 3-T FLAIR* sequence. METHODS. This study was a secondary analysis of data from the pilot study for the prospective multicenter Central Vein Sign: A Diagnostic Biomarker in Multiple Sclerosis (CAVS-MS), which recruited adults with suspected MS from April 2018 to February 2020. Participants underwent 3-T brain MRI including FLAIR and precontrast and post-contrast echo-planar imaging T2*-weighted acquisitions. Postprocessing was used to generate combined FLAIR and T2*-weighted images (hereafter, FLAIR*). MS diagnoses were established using the 2017 McDonald criteria. Thirty participants (23 women, seven men; mean age, 45 years) were randomly selected from the CAVS-MS pilot study cohort. White matter lesions (WMLs) were marked using FLAIR* images. A single observer, blinded to clinical data and GBCA use, reviewed marked WMLs on FLAIR* images for the presence of the CVS. RESULTS. Thirteen of 30 participants had MS. Across participants, on precontrast FLAIR* imaging, 218 CVS-positive and 517 CVS-negative WMLs were identified; on post-contrast FLAIR* imaging, 269 CVS-positive and 459 CVS-negative WMLs were identified. The fraction of WMLs that were CVS-positive on precontrast and postcontrast images was 48% and 58% in participants with MS and 7% and 10% in participants without MS, respectively. The median patient-level CVS-positivity rate on precontrast and postcontrast images was 43% and 67% for participants with MS and 4% and 8% for participants without MS, respectively. In a binomial model adjusting for MS diagnoses, GBCA use was associated with an increased likelihood of at least one CVS-positive WML (odds ratio, 1.6; p < .001). At a 40% CVS-positivity threshold, the sensitivity of the CVS for MS increased from 62% on precontrast images to 92% on postcontrast images (p = .046). Specificity was not significantly different between precontrast (88%) and postcontrast (82%) images (p = .32). CONCLUSION. GBCA use increased CVS detection on FLAIR* images, thereby increasing the sensitivity of the CVS for MS diagnoses. CLINICAL IMPACT. The postcontrast FLAIR* sequence should be considered for CVS evaluation in future investigational trials and clinical practice.
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Affiliation(s)
- Lynn Daboul
- Department of Neurology, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD
- Cleveland Clinic Lerner College of Medicine, Cleveland, OH
| | - Carly M O'Donnell
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Quy Cao
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Moein Amin
- Neurological Institute, Cleveland Clinic, Cleveland, OH
| | | | | | - Christina Azevedo
- Department of Neurology, University of Southern California, Los Angeles, CA
| | - Amit Bar-Or
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Eduardo Caverzasi
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Peter Calabresi
- Department of Neurology, Johns Hopkins University, Baltimore, MD
| | - Bruce A C Cree
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Leorah Freeman
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, TX
| | - Roland G Henry
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | | | - Kunio Nakamura
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
| | - Jiwon Oh
- Division of Neurology, St. Michael's Hospital, University of Toronto, ON, Canada
| | - Nico Papinutto
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Daniel Pelletier
- Department of Neurology, University of Southern California, Los Angeles, CA
| | - Rohini D Samudralwar
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX
| | - Suradech Suthiphosuwan
- Department of Medical Imaging, St. Michael's Hospital, University of Toronto, ON, Canada
| | - Matthew K Schindler
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | | | - Nancy L Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Andrew J Solomon
- Department of Neurological Sciences, Larner College of Medicine, The University of Vermont, Burlington, VT
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
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Argentinean consensus recommendations for the use of telemedicine in clinical practice in adult people with multiple sclerosis. Neurol Sci 2023; 44:667-676. [PMID: 36319902 PMCID: PMC9628297 DOI: 10.1007/s10072-022-06471-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 10/20/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND The use of telemedicine has quickly increased during of the COVID-19 pandemic. Given that unmet needs and barriers to multiple sclerosis (MS) care have been reported, telemedicine has become an interesting option to the care of these patients. The objective of these consensus recommendations was to elaborate a guideline for the management of people with MS using telemedicine in order to contribute to an effective and high-quality healthcare. METHODS A panel of Argentinean neurologist's experts in neuroimmunological diseases and dedicated to the diagnosis, management,and care of MS patients gathered virtually during 2021 and 2022 to conduct a consensus recommendation on the use of telemedicine in clinical practice in adult people with MS. To reach consensus, the methodology of "formal consensus RAND/UCLA Appropriateness method" was used. RESULTS Recommendations were established based on relevant published evidence and expert opinion focusing on definitions, general characteristics and ethical standards, diagnosis of MS, follow-up (evaluation of disability and relapses of MS), identification and treatment of relapses, and finally disease-modifying treatments using telemedicine. CONCLUSION The recommendations of this consensus would provide a useful guide for the proper use of telemedicine for the assessment, follow-up, management, and treatment of people with MS. We suggest the use of these guidelines to all the Argentine neurologists committed to the care of people with MS.
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Mey GM, Mahajan KR, DeSilva TM. Neurodegeneration in multiple sclerosis. WIREs Mech Dis 2023; 15:e1583. [PMID: 35948371 PMCID: PMC9839517 DOI: 10.1002/wsbm.1583] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 06/28/2022] [Accepted: 07/11/2022] [Indexed: 01/31/2023]
Abstract
Axonal loss in multiple sclerosis (MS) is a key component of disease progression and permanent neurologic disability. MS is a heterogeneous demyelinating and neurodegenerative disease of the central nervous system (CNS) with varying presentation, disease courses, and prognosis. Immunomodulatory therapies reduce the frequency and severity of inflammatory demyelinating events that are a hallmark of MS, but there is minimal therapy to treat progressive disease and there is no cure. Data from patients with MS, post-mortem histological analysis, and animal models of demyelinating disease have elucidated patterns of MS pathogenesis and underlying mechanisms of neurodegeneration. MRI and molecular biomarkers have been proposed to identify predictors of neurodegeneration and risk factors for disease progression. Early signs of axonal dysfunction have come to light including impaired mitochondrial trafficking, structural axonal changes, and synaptic alterations. With sustained inflammation as well as impaired remyelination, axons succumb to degeneration contributing to CNS atrophy and worsening of disease. These studies highlight the role of chronic demyelination in the CNS in perpetuating axonal loss, and the difficulty in promoting remyelination and repair amidst persistent inflammatory insult. Regenerative and neuroprotective strategies are essential to overcome this barrier, with early intervention being critical to rescue axonal integrity and function. The clinical and basic research studies discussed in this review have set the stage for identifying key propagators of neurodegeneration in MS, leading the way for neuroprotective therapeutic development. This article is categorized under: Immune System Diseases > Molecular and Cellular Physiology Neurological Diseases > Molecular and Cellular Physiology.
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Affiliation(s)
- Gabrielle M. Mey
- Department of NeurosciencesLerner Research Institute, Cleveland Clinic Foundation, and Case Western Reserve UniversityClevelandOhioUSA
| | - Kedar R. Mahajan
- Department of NeurosciencesLerner Research Institute, Cleveland Clinic Foundation, and Case Western Reserve UniversityClevelandOhioUSA
- Mellen Center for MS Treatment and ResearchNeurological Institute, Cleveland Clinic FoundationClevelandOhioUSA
| | - Tara M. DeSilva
- Department of NeurosciencesLerner Research Institute, Cleveland Clinic Foundation, and Case Western Reserve UniversityClevelandOhioUSA
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Flanagan EP, Geschwind MD, Lopez-Chiriboga AS, Blackburn KM, Turaga S, Binks S, Zitser J, Gelfand JM, Day GS, Dunham SR, Rodenbeck SJ, Clardy SL, Solomon AJ, Pittock SJ, McKeon A, Dubey D, Zekeridou A, Toledano M, Turner LE, Vernino S, Irani SR. Autoimmune Encephalitis Misdiagnosis in Adults. JAMA Neurol 2023; 80:30-39. [PMID: 36441519 PMCID: PMC9706400 DOI: 10.1001/jamaneurol.2022.4251] [Citation(s) in RCA: 64] [Impact Index Per Article: 64.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 09/22/2022] [Indexed: 11/29/2022]
Abstract
Importance Autoimmune encephalitis misdiagnosis can lead to harm. Objective To determine the diseases misdiagnosed as autoimmune encephalitis and potential reasons for misdiagnosis. Design, Setting, and Participants This retrospective multicenter study took place from January 1, 2014, to December 31, 2020, at autoimmune encephalitis subspecialty outpatient clinics including Mayo Clinic (n = 44), University of Oxford (n = 18), University of Texas Southwestern (n = 18), University of California, San Francisco (n = 17), University of Washington in St Louis (n = 6), and University of Utah (n = 4). Inclusion criteria were adults (age ≥18 years) with a prior autoimmune encephalitis diagnosis at a participating center or other medical facility and a subsequent alternative diagnosis at a participating center. A total of 393 patients were referred with an autoimmune encephalitis diagnosis, and of those, 286 patients with true autoimmune encephalitis were excluded. Main Outcomes and Measures Data were collected on clinical features, investigations, fulfillment of autoimmune encephalitis criteria, alternative diagnoses, potential contributors to misdiagnosis, and immunotherapy adverse reactions. Results A total of 107 patients were misdiagnosed with autoimmune encephalitis, and 77 (72%) did not fulfill diagnostic criteria for autoimmune encephalitis. The median (IQR) age was 48 (35.5-60.5) years and 65 (61%) were female. Correct diagnoses included functional neurologic disorder (27 [25%]), neurodegenerative disease (22 [20.5%]), primary psychiatric disease (19 [18%]), cognitive deficits from comorbidities (11 [10%]), cerebral neoplasm (10 [9.5%]), and other (18 [17%]). Onset was acute/subacute in 56 (52%) or insidious (>3 months) in 51 (48%). Magnetic resonance imaging of the brain was suggestive of encephalitis in 19 of 104 patients (18%) and cerebrospinal fluid (CSF) pleocytosis occurred in 16 of 84 patients (19%). Thyroid peroxidase antibodies were elevated in 24 of 62 patients (39%). Positive neural autoantibodies were more frequent in serum than CSF (48 of 105 [46%] vs 7 of 91 [8%]) and included 1 or more of GAD65 (n = 14), voltage-gated potassium channel complex (LGI1 and CASPR2 negative) (n = 10), N-methyl-d-aspartate receptor by cell-based assay only (n = 10; 6 negative in CSF), and other (n = 18). Adverse reactions from immunotherapies occurred in 17 of 84 patients (20%). Potential contributors to misdiagnosis included overinterpretation of positive serum antibodies (53 [50%]), misinterpretation of functional/psychiatric, or nonspecific cognitive dysfunction as encephalopathy (41 [38%]). Conclusions and Relevance When evaluating for autoimmune encephalitis, a broad differential diagnosis should be considered and misdiagnosis occurs in many settings including at specialized centers. In this study, red flags suggesting alternative diagnoses included an insidious onset, positive nonspecific serum antibody, and failure to fulfill autoimmune encephalitis diagnostic criteria. Autoimmune encephalitis misdiagnosis leads to morbidity from unnecessary immunotherapies and delayed treatment of the correct diagnosis.
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Affiliation(s)
- Eoin P. Flanagan
- Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota
- Center for Multiple Sclerosis and Autoimmune Neurology, Department of Neurology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Michael D. Geschwind
- Department of Neurology, University of California, San Francisco (UCSF), San Francisco
| | | | - Kyle M. Blackburn
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas
| | - Sanchit Turaga
- Autoimmune Neurology Group, West Wing, Level 3, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Sophie Binks
- Autoimmune Neurology Group, West Wing, Level 3, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Jennifer Zitser
- Department of Neurology, University of California, San Francisco (UCSF), San Francisco
- Movement Disorders Unit, Department of Neurology, Tel Aviv Sourazky Medical Center, Affiliate of Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Jeffrey M. Gelfand
- Department of Neurology, University of California, San Francisco (UCSF), San Francisco
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida
- Washington University in St Louis, St Louis, Missouri
| | | | | | | | | | - Sean J. Pittock
- Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota
- Center for Multiple Sclerosis and Autoimmune Neurology, Department of Neurology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Andrew McKeon
- Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota
- Center for Multiple Sclerosis and Autoimmune Neurology, Department of Neurology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Divyanshu Dubey
- Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota
- Center for Multiple Sclerosis and Autoimmune Neurology, Department of Neurology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Anastasia Zekeridou
- Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota
- Center for Multiple Sclerosis and Autoimmune Neurology, Department of Neurology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Michel Toledano
- Center for Multiple Sclerosis and Autoimmune Neurology, Department of Neurology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Lindsey E. Turner
- Graduate School of Health Sciences, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Steven Vernino
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas
| | - Sarosh R. Irani
- Autoimmune Neurology Group, West Wing, Level 3, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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Yavaş HG, Sağtaş E. Central vein sign: comparison of multiple sclerosis and leukoaraiosis. Turk J Med Sci 2022; 52:1933-1942. [PMID: 36945994 PMCID: PMC10390208 DOI: 10.55730/1300-0144.5541] [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: 05/09/2022] [Accepted: 09/21/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Leukoaraiosis produces white matter lesions (WML) similar to multiple sclerosis (MS) on brain magnetic resonance imaging (MRI), and the distinction between these two conditions is difficult radiologically. This study aimed to investigate the role of the central vein sign (CVS) in susceptibility-weighted imaging (SWI) sequence in distinguishing MS lesions from leukoaraiosis lesions in Turkish population. METHODS In this prospective study, axial SWI and sagittal three-dimensional fluid-attenuated inversion recovery (3DFLAIR) were obtained in 374 consecutive patients. The study consisted of 169 (89 MS patients, 80 patients with leukoaraiosis) patients according to the inclusion and exclusion criteria. Two observers evaluated MR images by consensus, and observers were unaware of the patient's clinical findings. Locations (periventricular, juxtacortical, and deep white matter) and the presence of CVS were investigated for each of the lesions. Differences between patients in the leukoaraiosis and MS groups were investigated using the Mann-Whitney U test or chi-square analysis. In addition, receiver operating characteristic (ROC) analysis was used to analyze the diagnostic performance of CVS. RESULTS A total of 1908 WMLs (1265 MS lesions, 643 leukoaraiosis) were detected in 169 patients. The CVS was significantly higher in the MS lesions (p < 0.001). The CVS positivity rate in periventricular WMLs was higher than in juxtacortical WMLs or deep WMLs, both for all patients and for patients with MS (p < 0.001). The area under the curve (AUC) of the ROC analysis was 0.88 (95% confidence interval 0.83-0.93) for CVS in the distinction of MS lesions and leukoaraiosis. DISCUSSION The presence of CVS in the SWI sequence can be used as an auxiliary finding for the diagnosis of MS in the differentiation of MS and leukoaraiosis lesions.
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Affiliation(s)
- Hüseyin Gökhan Yavaş
- Department of Radiology, Ahi Evran University Kırşehir Education and Research Hospital, Kırşehir, Turkey
| | - Ergin Sağtaş
- Department of Radiology, Faculty of Medicine, Pamukkale University, Denizli, Turkey
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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.
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Sasserath T, Robertson AL, Mendez R, Hays TT, Smith E, Cooper H, Akanda N, Rumsey JW, Guo X, Farkhondeh A, Pradhan M, Baumgaertel K, Might M, Rodems S, Zheng W, Hickman JJ. An induced pluripotent stem cell-derived NMJ platform for study of the NGLY1-Congenital Disorder of Deglycosylation. ADVANCED THERAPEUTICS 2022; 5:2200009. [PMID: 36589922 PMCID: PMC9798846 DOI: 10.1002/adtp.202200009] [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: 01/07/2022] [Indexed: 01/05/2023]
Abstract
There are many neurological rare diseases where animal models have proven inadequate or do not currently exist. NGLY1 Deficiency, a congenital disorder of deglycosylation, is a rare disease that predominantly affects motor control, especially control of neuromuscular action. In this study, NGLY1-deficient, patient-derived induced pluripotent stem cells (iPSCs) were differentiated into motoneurons (MNs) to identify disease phenotypes analogous to clinical disease pathology with significant deficits apparent in the NGLY1-deficient lines compared to the control. A neuromuscular junction (NMJ) model was developed using patient and wild type (WT) MNs to study functional differences between healthy and diseased NMJs. Reduced axon length, increased and shortened axon branches, MN action potential (AP) bursting and decreased AP firing rate and amplitude were observed in the NGLY1-deficient MNs in monoculture. When transitioned to the NMJ-coculture system, deficits in NMJ number, stability, failure rate, and synchronicity with indirect skeletal muscle (SkM) stimulation were observed. This project establishes a phenotypic NGLY1 model for investigation of possible therapeutics and investigations into mechanistic deficits in the system.
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Affiliation(s)
- Trevor Sasserath
- Hesperos, Inc., 12501 Research Parkway, Suite 100, Orlando, FL 32826 USA
| | - Ashley L Robertson
- Hesperos, Inc., 12501 Research Parkway, Suite 100, Orlando, FL 32826 USA
| | - Roxana Mendez
- University of Central Florida, NanoScience Technology Center, 12424 Research Parkway, Suite 400, Orlando, FL 32826 USA
| | - Tristan T Hays
- Hesperos, Inc., 12501 Research Parkway, Suite 100, Orlando, FL 32826 USA
| | - Ethan Smith
- Hesperos, Inc., 12501 Research Parkway, Suite 100, Orlando, FL 32826 USA
| | - Helena Cooper
- Hesperos, Inc., 12501 Research Parkway, Suite 100, Orlando, FL 32826 USA
| | - Nesar Akanda
- University of Central Florida, NanoScience Technology Center, 12424 Research Parkway, Suite 400, Orlando, FL 32826 USA
| | - John W Rumsey
- Hesperos, Inc., 12501 Research Parkway, Suite 100, Orlando, FL 32826 USA
| | - Xiufang Guo
- University of Central Florida, NanoScience Technology Center, 12424 Research Parkway, Suite 400, Orlando, FL 32826 USA
| | - Atena Farkhondeh
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Building C, Room 310W Rockville, MD 20850, USA
| | - Manisha Pradhan
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Building C, Room 310W Rockville, MD 20850, USA
| | - Karsten Baumgaertel
- Travere Therapeutics, 3611 Valley Centre Drive, Suite 300, San Diego, CA, USA
| | - Matthew Might
- University of Alabama at Birmingham, Hugh Kaul Precision Medicine Institute, 510 20th St S, Office 858B, Birmingham, AL 35210, USA
| | - Steven Rodems
- Travere Therapeutics, 3611 Valley Centre Drive, Suite 300, San Diego, CA, USA
| | - Wei Zheng
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Building C, Room 310W Rockville, MD 20850, USA
| | - James J Hickman
- Hesperos, Inc., 12501 Research Parkway, Suite 100, Orlando, FL 32826 USA
- University of Central Florida, NanoScience Technology Center, 12424 Research Parkway, Suite 400, Orlando, FL 32826 USA
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Ezcurra Díaz G, Nuñez Marin F, Blanco Guillermo I, Ramo-Tello C. Diagnostic confusion of demyelinating lesions and incidental diagnosis of a new pathogenic mutation of the FLNA gene. Neurologia 2022; 37:818-820. [PMID: 35668010 DOI: 10.1016/j.nrleng.2021.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 11/19/2021] [Indexed: 01/31/2023] Open
Affiliation(s)
- G Ezcurra Díaz
- Servicio de Neurología, Departamento de Neurociencias, Hospital Universitario Germans Trias i Pujol, Badalona, Barcelona, Spain.
| | - F Nuñez Marin
- IDI (Institut de Diagnòstic per la Imatge), Badalona, Barcelona, Spain
| | - I Blanco Guillermo
- Servicio de Genética Clínica, Hospital Universitario Germans Trias i Pujol, Badalona, Barcelona, Spain
| | - C Ramo-Tello
- Unidad de EM-Neuroinmunología, Departamento de Neurociencias, Hospital Universitario Germans Trias I Pujol, Badalona, Barcelona, Spain
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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: 8] [Impact Index Per Article: 4.0] [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.
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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
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Anderson NE. In defence of general neurology. Pract Neurol 2022; 22:448-449. [PMID: 36162854 DOI: 10.1136/pn-2022-003567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/12/2022] [Indexed: 11/03/2022]
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La Rosa F, Wynen M, Al-Louzi O, Beck ES, Huelnhagen T, Maggi P, Thiran JP, Kober T, Shinohara RT, Sati P, Reich DS, Granziera C, Absinta M, Bach Cuadra M. Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues. Neuroimage Clin 2022; 36:103205. [PMID: 36201950 PMCID: PMC9668629 DOI: 10.1016/j.nicl.2022.103205] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 09/09/2022] [Accepted: 09/16/2022] [Indexed: 12/14/2022]
Abstract
The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, some MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL), visible in specialized magnetic resonance imaging (MRI) sequences, have shown higher specificity in differential diagnosis. Moreover, studies have shown that CL and PRL are potential prognostic biomarkers, the former correlating with cognitive impairments and the latter with early disability progression. As machine learning-based methods have achieved extraordinary performance in the assessment of conventional imaging biomarkers, such as white matter lesion segmentation, several automated or semi-automated methods have been proposed as well for CL, PRL, and CVS. In the present review, we first introduce these MS biomarkers and their imaging methods. Subsequently, we describe the corresponding machine learning-based methods that were proposed to tackle these clinical questions, putting them into context with respect to the challenges they are facing, including non-standardized MRI protocols, limited datasets, and moderate inter-rater variability. We conclude by presenting the current limitations that prevent their broader deployment and suggesting future research directions.
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Key Words
- ms, multiple sclerosis
- mri, magnetic resonance imaging
- dl, deep learning
- ml, machine learning
- cl, cortical lesions
- prl, paramagnetic rim lesions
- cvs, central vein sign
- wml, white matter lesions
- flair, fluid-attenuated inversion recovery
- mprage, magnetization prepared rapid gradient-echo
- gm, gray matter
- wm, white matter
- psir, phase-sensitive inversion recovery
- dir, double inversion recovery
- mp2rage, magnetization-prepared 2 rapid gradient echoes
- sels, slowly evolving/expanding lesions
- cnn, convolutional neural network
- xai, explainable ai
- pv, partial volume
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Affiliation(s)
- Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Maxence Wynen
- CIBM Center for Biomedical Imaging, Switzerland; ICTeam, UCLouvain, Louvain-la-Neuve, Belgium; Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erin S Beck
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Till Huelnhagen
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Pietro Maggi
- Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Department of Neurology, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Department of Neurology, CHUV, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Tobias Kober
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analysis (CBICA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA; Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Switzerland; Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Martina Absinta
- IRCCS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
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Galym A, Akhmetova N, Zhaksybek M, Safina S, Boldyreva MN, Rakhimbekova FK, Idrissova ZR. Clinical and Genetic Analysis in Pediatric Patients with Multiple Sclerosis and Related Conditions: Focus on DR Genes of the Major Histocompatibility Complex. Open Neurol J 2022. [DOI: 10.2174/1874205x-v16-e2207200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Introduction:
There are several diseases recognized as variants of MS: post-infectious acute disseminated encephalitis, multiple sclerosis (MS), Rasmussen leukoencephalitis and Schilder's leukoencephalitis and related, but separate neuroimmune condition – Neuromyelitis Devic’s. In Kazakhstan diagnosis of such diseases was rare and immune modified treatment was only admitted after the age of 18. Clinical and immunogenetic study of MS spectrum diseases in Kazakhstan would allow to justify early targeted treatment.
Objective:
The aim of the study was to investigate genes of the main complex of human histocompatibility (MHC) associated with diseases of MS spectrum in Kazakhstani population.
Methods:
Complex clinical, neuroimaging and immunogenetic studies were performed in 34 children (24 girls, 10 boys) aged 4 to 18 years. 21 children were diagnosed with MS (11 Kazakh origin and 10 – Russian; 4 boys, 17 girls), 7 with leucoencephalitis (all Kazakh, 5 boys, 2 girls) and 6 with Devic neuromyelitis optica (all Kazakh, 1 boy, 5 girls). Genotyping of HLA DRB1, DQA1, DQB1 genes was performed for all patients.
Results:
MS group was characterized by classical relapsing-remitting MS. Predominant haplotype as a linkage complex was DRB1*15:01~DQA1*01:02~DQB1*06:02 in 20 (47.6%) of 42 DR-alleles, in 16 (76.2%) patients. MS relative risk (RR) was 13,36 for ethnic Kazakhs and RR=5,55 in Russians.
Leukoencephalitis had 7 children, with 28.6% mortality rate. The haplotype DRB1*15:01~DQA1*01:02~DQB1*06:02 as a linkage complex was detected 3 patients (4 alleles), RR=5,88.
Devic’s neuromyelitis optica (NMO) clinical course was characterized by fast and prolonged progression. There was predominance of DRB1*14 allele with RR=3,38.
Conclusion:
Summarizing, in the Kazakh population the haplotype DRB1*15:01∼DQA1*01:02∼DQB1*06:02 as a linkage complex was associated with prediction to MS and leukoencephalitis, but not to Devic’s NMO. Our study highlights the importance of awareness of MS and related disorders diagnosis which allows to implement early admission of disease-modified treatment in pediatric MS in Kazakhstan.
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Meaton I, Altokhis A, Allen CM, Clarke MA, Sinnecker T, Meier D, Enzinger C, Calabrese M, De Stefano N, Pitiot A, Giorgio A, Schoonheim MM, Paul F, Pawlak MA, Schmidt R, Granziera C, Kappos L, Montalban X, Rovira À, Wuerfel J, Evangelou N. Paramagnetic rims are a promising diagnostic imaging biomarker in multiple sclerosis. Mult Scler 2022; 28:2212-2220. [PMID: 36017870 DOI: 10.1177/13524585221118677] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
BACKGROUND White matter lesions (WMLs) on brain magnetic resonance imaging (MRI) in multiple sclerosis (MS) may contribute to misdiagnosis. In chronic active lesions, peripheral iron-laden macrophages appear as paramagnetic rim lesions (PRLs). OBJECTIVE To evaluate the sensitivity and specificity of PRLs in differentiating MS from mimics using clinical 3T MRI scanners. METHOD This retrospective international study reviewed MRI scans of patients with MS (n = 254), MS mimics (n = 91) and older healthy controls (n = 217). WMLs, detected using fluid-attenuated inversion recovery MRI, were analysed with phase-sensitive imaging. Sensitivity and specificity were assessed for PRLs. RESULTS At least one PRL was found in 22.9% of MS and 26.1% of clinically isolated syndrome (CIS) patients. Only one PRL was found elsewhere. The identification of ⩾1 PRL was the optimal cut-off and had high specificity (99.7%, confidence interval (CI) = 98.20%-99.99%) when distinguishing MS and CIS from mimics and healthy controls, but lower sensitivity (24.0%, CI = 18.9%-36.6%). All patients with a PRL showing a central vein sign (CVS) in the same lesion (n = 54) had MS or CIS, giving a specificity of 100% (CI = 98.8%-100.0%) but equally low sensitivity (21.3%, CI = 16.4%-26.81%). CONCLUSION PRLs may reduce diagnostic uncertainty in MS by being a highly specific imaging diagnostic biomarker, especially when used in conjunction with the CVS.
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Affiliation(s)
- Isobel Meaton
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Nottingham, UK
| | - Amjad Altokhis
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Nottingham, UK
| | - Christopher Martin Allen
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Nottingham, UK
| | - Margareta A Clarke
- Institute of Imaging Science, Vanderbilt University Medical Center, Vanderbilt University, Nashville, TN, USA
| | - Tim Sinnecker
- Medical Image Analysis Center AG and Department of Biomedical Engineering, University Basel, Basel, Switzerland
| | - Dominik Meier
- Medical Image Analysis Center AG and Department of Biomedical Engineering, University Basel, Basel, Switzerland
| | | | - Massimiliano Calabrese
- Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Alain Pitiot
- Laboratory of Image and Data Analysis, Ilixa Ltd, London, UK
| | - Antonio Giorgio
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Friedemann Paul
- Neurocure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Mikolaj A Pawlak
- Department of Neurology and Cerebrovascular Disorders, Poznan University of Medical Sciences, Poznan, Poland
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Cristina Granziera
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital, University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital, University of Basel, Basel, Switzerland
| | - Xavier Montalban
- Centre d'Esclerosi Multiple de Catalunya (Cemcat), Department of Neurology/Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jens Wuerfel
- Medical Image Analysis Center AG and Department of Biomedical Engineering, University Basel, Basel, Switzerland/Neurocure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Nikos Evangelou
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Nottingham, UK
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Abstract
PURPOSE OF REVIEW The diagnosis of multiple sclerosis (MS) can be made based on clinical symptoms and signs alone or a combination of clinical and paraclinical features. Diagnostic criteria for MS have evolved over time, and the latest version facilitates earlier diagnosis of MS in those presenting with typical clinical syndromes. This article summarizes the current diagnostic criteria for MS, typical and atypical presentations of MS, and when diagnostic criteria should be applied with caution. RECENT FINDINGS The most recent version of the MS diagnostic criteria has the benefits of simplicity and greater sensitivity in comparison to previous iterations. However, misdiagnosis remains a significant issue in MS clinical care, even at MS specialty centers. It is, therefore, evident that careful clinical application of the current version of the diagnostic criteria is necessary and that tools improving the diagnostic accuracy of MS would be of substantial clinical utility. Emerging diagnostic biomarkers that may be useful in this regard, including the central vein sign, paramagnetic rim lesions, and fluid biomarkers, are discussed. SUMMARY Current MS diagnostic criteria facilitate the early diagnosis of MS in people presenting with typical clinical syndromes but should be used cautiously in those presenting with atypical syndromes and in special populations. Clinical judgment and existing paraclinical tools, including sequential MRIs of the neuraxis and laboratory tests, are useful in minimizing misdiagnosis and facilitating the accurate diagnosis of MS. Diagnostic biomarkers that may facilitate or refute a diagnosis of MS in these settings, and emerging imaging and fluid biomarkers may eventually become available for use in clinical settings.
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Huang YT, Giacomini PS, Massie R, Venkateswaran S, Trudelle AM, Fadda G, Sharifian-Dorche M, Boudjani H, Poliquin-Lasnier L, Airas L, Saveriano AW, Ziller MG, Miller E, Martinez-Rios C, Wilson N, Davila J, Rush C, Longbrake EE, Longoni G, Macaron G, Bernard G, Tampieri D, Antel J, Brais B, La Piana R. The White Matter Rounds experience: The importance of a multidisciplinary network to accelerate the diagnostic process for adult patients with rare white matter disorders. Front Neurol 2022; 13:928493. [PMID: 35959404 PMCID: PMC9359417 DOI: 10.3389/fneur.2022.928493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 06/30/2022] [Indexed: 11/18/2022] Open
Abstract
Introduction Adult genetic leukoencephalopathies are rare neurological disorders that present unique diagnostic challenges due to their clinical and radiological overlap with more common white matter diseases, notably multiple sclerosis (MS). In this context, a strong collaborative multidisciplinary network is beneficial for shortening the diagnostic odyssey of these patients and preventing misdiagnosis. The White Matter Rounds (WM Rounds) are multidisciplinary international online meetings attended by more than 30 physicians and scientists from 15 participating sites that gather every month to discuss patients with atypical white matter disorders. We aim to present the experience of the WM Rounds Network and demonstrate the value of collaborative multidisciplinary international case discussion meetings in differentiating and preventing misdiagnoses between genetic white matter diseases and atypical MS. Methods We retrospectively reviewed the demographic, clinical and radiological data of all the subjects presented at the WM Rounds since their creation in 2013. Results Seventy-four patients (mean age 44.3) have been referred and discussed at the WM Rounds since 2013. Twenty-five (33.8%) of these patients were referred by an MS specialist for having an atypical presentation of MS, while in most of the remaining cases, the referring physician was a geneticist (23; 31.1%). Based on the WM Rounds recommendations, a definite diagnosis was made in 36/69 (52.2%) patients for which information was available for retrospective review. Of these diagnosed patients, 20 (55.6%) had a genetic disease, 8 (22.2%) had MS, 3 (8.3%) had both MS and a genetic disorder and 5 (13.9%) had other non-genetic conditions. Interestingly, among the patients initially referred by an MS specialist, 7/25 were definitively diagnosed with MS, 5/25 had a genetic condition (e.g., X-linked adrenoleukodystrophy and hereditary small vessel diseases like Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) and COL4A1-related disorder), and one had both MS and a genetic demyelinating neuropathy. Thanks to the WM Rounds collaborative efforts, the subjects who currently remain without a definite diagnosis, despite extensive investigations performed in the clinical setting, have been recruited in research studies aimed at identifying novel forms of genetic MS mimickers. Conclusions The experience of the WM Rounds Network demonstrates the benefit of collective discussions on complex cases to increase the diagnostic rate and decrease misdiagnosis in patients with rare or atypical white matter diseases. Networks of this nature allow physicians and scientists to compare and share information on challenging cases from across the world, provide a basis for future multicenter research studies, and serve as model for other rare diseases.
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Affiliation(s)
- Yu Tong Huang
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Paul S. Giacomini
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Rami Massie
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Sunita Venkateswaran
- Department of Pediatrics, Division of Neurology, CHEO, University of Ottawa, Ottawa, ON, Canada
| | | | - Giulia Fadda
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Maryam Sharifian-Dorche
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Hayet Boudjani
- Department of Neurology, Maisonneuve-Rosemont Hospital, Université de Montréal, Montreal, QC, Canada
| | | | - Laura Airas
- Division of Clinical Neurosciences, Turku University Hospital and University of Turku, Turku, Finland
| | - Alexander W. Saveriano
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Matthias Georg Ziller
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Department of Neurology, St. Mary's Hospital, Montreal, QC, Canada
| | - Elka Miller
- Department of Medical Imaging, CHEO, University of Ottawa, Ottawa, ON, Canada
| | | | - Nagwa Wilson
- Department of Medical Imaging, CHEO, University of Ottawa, Ottawa, ON, Canada
| | - Jorge Davila
- Department of Medical Imaging, CHEO, University of Ottawa, Ottawa, ON, Canada
| | - Carolina Rush
- Division of Neurology, Neuroscience Department, University of Ottawa, Ottawa, ON, Canada
| | - Erin E. Longbrake
- Department of Neurology, Yale MS Center, Yale School of Medicine, North Haven, CT, United States
| | - Giulia Longoni
- Department of Pediatrics, Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Gabrielle Macaron
- Department of Neurology, Hotel Dieu de France Hospital, Saint Joseph University, Beirut, Lebanon
| | - Geneviève Bernard
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Department of Specialized Medicine, Division of Medical Genetics, McGill University Health Center, Montreal, QC, Canada,Child Health and Human Development Program, Research Institute of the McGill University Health Center, Montreal, QC, Canada,Departments of Pediatrics and Human Genetics, McGill University, Montreal, QC, Canada
| | - Donatella Tampieri
- Department of Diagnostic Radiology, Kingston Health Science Centre, Queen's University, Kingston, ON, Canada
| | - Jack Antel
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Bernard Brais
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Roberta La Piana
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Department of Diagnostic Radiology, McGill University, Montreal, QC, Canada,*Correspondence: Roberta La Piana
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Wang B, Li X, Li H, Xiao L, Zhou Z, Chen K, Gui L, Hou X, Fan R, Chen K, Wu W, Li H, Hu X. Clinical, Radiological and Pathological Characteristics Between Cerebral Small Vessel Disease and Multiple Sclerosis: A Review. Front Neurol 2022; 13:841521. [PMID: 35812110 PMCID: PMC9263123 DOI: 10.3389/fneur.2022.841521] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 05/19/2022] [Indexed: 11/13/2022] Open
Abstract
Cerebral small vessel disease (CSVD) and multiple sclerosis (MS) are a group of diseases associated with small vessel lesions, the former often resulting from the vascular lesion itself, while the latter originating from demyelinating which can damage the cerebral small veins. Clinically, CSVD and MS do not have specific signs and symptoms, and it is often difficult to distinguish between the two from the aspects of the pathology and imaging. Therefore, failure to correctly identify and diagnose the two diseases will delay early intervention, which in turn will affect the long-term functional activity for patients and even increase their burden of life. This review has summarized recent studies regarding their similarities and difference of the clinical manifestations, pathological features and imaging changes in CSVD and MS, which could provide a reliable basis for the diagnosis and differentiation of the two diseases in the future.
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Affiliation(s)
- Bijia Wang
- Department of Neurology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xuegang Li
- Department of Neurosurgery, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Haoyi Li
- Department of Neurosurgery, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Li Xiao
- Department of Neurology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Zhenhua Zhou
- Department of Neurology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Kangning Chen
- Department of Neurology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Li Gui
- Department of Neurology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xianhua Hou
- Department of Neurology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Rong Fan
- Department of Neurology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Kang Chen
- Department of Radiology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Wenjing Wu
- Department of Radiology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Haitao Li
- Department of Radiology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
- *Correspondence: Haitao Li
| | - Xiaofei Hu
- Department of Radiology, First Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
- Xiaofei Hu
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Cognitive Decline in Older People with Multiple Sclerosis—A Narrative Review of the Literature. Geriatrics (Basel) 2022; 7:geriatrics7030061. [PMID: 35735766 PMCID: PMC9223056 DOI: 10.3390/geriatrics7030061] [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: 04/15/2022] [Revised: 06/02/2022] [Accepted: 06/02/2022] [Indexed: 12/04/2022] Open
Abstract
Several important questions regarding cognitive aging and dementia in older people with multiple sclerosis (PwMS) are the focus of this narrative review: Do older PwMS have worse cognitive decline compared to older people without MS? Can older PwMS develop dementia or other neurodegenerative diseases such as Alzheimer’s disease (AD) that may be accelerated due to MS? Are there any potential biomarkers that can help to determine the etiology of cognitive decline in older PwMS? What are the neural and cellular bases of cognitive aging and neurodegeneration in MS? Current evidence suggests that cognitive impairment in MS is distinguishable from that due to other neurodegenerative diseases, although older PwMS may present with accelerated cognitive decline. While dementia is prevalent in PwMS, there is currently no consensus on defining it. Cerebrospinal fluid and imaging biomarkers have the potential to identify disease processes linked to MS and other comorbidities—such as AD and vascular disease—in older PwMS, although more research is required. In conclusion, one should be aware that multiple underlying pathologies can coexist in older PwMS and cause cognitive decline. Future basic and clinical research will need to consider these complex factors to better understand the underlying pathophysiology, and to improve diagnostic accuracy.
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