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Reliability of classifying multiple sclerosis disease activity using magnetic resonance imaging in a multiple sclerosis clinic.

Abstract：

OBJECTIVE:To assess the reliability of new magnetic resonance imaging (MRI) lesion counts by clinicians in a multiple sclerosis specialty clinic. DESIGN:An observational study. SETTING:A multiple sclerosis specialty clinic. PATIENTS:Eighty-five patients with multiple sclerosis participating in a National Institutes of Health–supported longitudinal study were included. INTERVENTION:Each patient had a brain MRI scan at entry and 6 months later using a standardized protocol. MAIN OUTCOME MEASURES:The number of new T2 lesions, newly enlarging T2 lesions, and gadolinium-enhancing lesions were measured on the 6-month MRI using a computer-based image analysis program for the original study. For this study, images were reanalyzed by an expert neuroradiologist and 3 clinician raters. The neuroradiologist evaluated the original image pairs; the clinicians evaluated image pairs that were modified to simulate clinical practice. New lesion counts were compared across raters, as was classification of patients as MRI active or inactive. RESULTS:Agreement on lesion counts was highest for gadolinium-enhancing lesions, intermediate for new T2 lesions, and poor for enlarging T2 lesions. In 18% to 25% of the cases, MRI activity was classified differently by the clinician raters compared with the neuroradiologist or computer program. Variability among the clinical raters for estimates of new T2 lesions was affected most strongly by the image modifications that simulated low image quality and different head position. CONCLUSIONS:Between-rater variability in new T2 lesion counts may be reduced by improved standardization of image acquisitions, but this approach may not be practical in most clinical environments. Ultimately, more reliable, robust, and accessible image analysis methods are needed for accurate multiple sclerosis disease-modifying drug monitoring and decision making in the routine clinic setting.

journal_name

JAMA Neurol

journal_title

JAMA neurology

authors

Erbayat Altay E,Fisher E,Jones SE,Hara-Cleaver C,Lee JC,Rudick RA

doi

10.1001/2013.jamaneurol.211

subject

Has Abstract

pub_date

2013-03-01 00:00:00

pages

338-44

issue

eissn

2168-6149

issn

2168-6157

journal_volume

pub_type

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Reliability of classifying multiple sclerosis disease activity using magnetic resonance imaging in a multiple sclerosis clinic.