Faculty Opinions recommendation of Clinical and magnetic resonance imaging predictors of disease progression in multiple sclerosis: a nine-year follow-up study.

2013 ◽  
Author(s):  
Marco Rovaris
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Disease Progression ◽  
Resonance Imaging ◽  
Follow Up Study

Neuropsychological assessment in multiple sclerosis: a follow-up study with magnetic resonance imaging

1991 ◽  
Vol 238 (7) ◽  
pp. 395-400 ◽  
Author(s):  
C. Mariani ◽  
E. Farina ◽  
S. F. Cappa ◽  
G. P. Anzola ◽  
L. Faglia ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Neuropsychological Assessment ◽  
Resonance Imaging ◽  
Follow Up Study

Rate of ventricular enlargement in multiple sclerosis: a nine-year magnetic resonance imaging follow-up study

2008 ◽  
Vol 49 (5) ◽  
pp. 570-579 ◽  
Author(s):  
J. Martola ◽  
L. Stawiarz ◽  
S. Fredrikson ◽  
J. Hillert ◽  
J. Bergström ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Ventricular Enlargement ◽  
Resonance Imaging ◽  
Follow Up Study

Clinical and magnetic resonance imaging predictors of disease progression in multiple sclerosis: a nine-year follow-up study

2013 ◽  
Vol 20 (2) ◽  
pp. 220-226 ◽  
Author(s):  
L Lavorgna ◽  
S Bonavita ◽  
D Ippolito ◽  
R Lanzillo ◽  
G Salemi ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Disease Progression ◽  
Resonance Imaging ◽  
Clinical Progression ◽  
Cross Sectional ◽  
Mild Disease

Objective: The objective of this paper is to identify clinical or magnetic resonance imaging (MRI) predictors of long-term clinical progression in a large cohort of multiple sclerosis (MS) patients. Methods: A total of 241 relapsing–remitting (RR) MS patients were included in a nine-year follow-up (FU) study. The reference MRIs were acquired at baseline (BL) as part of a multicenter, cross-sectional, clinical-MRI study. Volumetric MRI metrics were measured by a fully automated, operator-independent, multi-parametric segmentation method. Clinical progression was evaluated as defined by: conversion from RR to secondary progressive (SP) disease course; progression of Expanded Disability Status Scale (EDSS); achievement and time to reach EDSS 4. Results: We concluded that conversion from RR to SP (OR 0.79; CI 0.7–0.9), progression of EDSS (OR 0.85; CI 0.77–0.93), achievement of EDSS 4 (OR 0.8; CI 0.7–0.9), and time to reach EDSS 4 (HR 0.88; CI 0.82–0.94) were all predicted by BL gray matter (GM) volume and, except for progression of EDSS, by BL EDSS (respectively: (OR 2.88; CI 1.9–4.36), (OR 2.7; CI 1.7–4.2), (HR 3.86; CI 1.94–7.70)). Conclusions: BL GM volume and EDSS are the best long-term predictors of disease progression in RRMS patients with a relatively long and mild disease.

Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year disability in multiple sclerosis

2016 ◽  
Vol 23 (1) ◽  
pp. 51-61 ◽  
Author(s):  
Tomas Uher ◽  
Manuela Vaneckova ◽  
Lukas Sobisek ◽  
Michaela Tyblova ◽  
Zdenek Seidl ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Cumulative Risk ◽  
Resonance Imaging ◽  
Cox Models ◽  
T2 Lesions ◽  
Therapeutic Decisions ◽  
The Individual

Background: Disease progression and treatment efficacy vary among individuals with multiple sclerosis. Reliable predictors of individual disease outcomes are lacking. Objective: To examine the accuracy of the early prediction of 12-year disability outcomes using clinical and magnetic resonance imaging (MRI) parameters. Methods: A total of 177 patients from the original Avonex-Steroids-Azathioprine study were included. Participants underwent 3-month clinical follow-ups. Cox models were used to model the associations between clinical and MRI markers at baseline or after 12 months with sustained disability progression (SDP) over the 12-year observation period. Results: At baseline, T2 lesion number, T1 and T2 lesion volumes, corpus callosum (CC), and thalamic fraction were the best predictors of SDP (hazard ratio (HR) = 1.7–4.6; p ⩽ 0.001–0.012). At 12 months, Expanded Disability Status Scale (EDSS) and its change, number of new or enlarging T2 lesions, and CC volume % change were the best predictors of SDP over the follow-up (HR = 1.7–3.5; p ⩽  0.001–0.017). A composite score was generated from a subset of the best predictors of SDP. Scores of ⩾4 had greater specificity (90%–100%) and were associated with greater cumulative risk of SDP (HR = 3.2–21.6; p < 0.001) compared to the individual predictors. Conclusion: The combination of established MRI and clinical indices with MRI volumetric predictors improves the prediction of SDP over long-term follow-up and may provide valuable information for therapeutic decisions.

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