McDonald criteria

McDonald criteria

The McDonald criteria refer to a set of diagnostic guidelines for multiple sclerosis (MS) that incorporate clinical factors, cerebrospinal fluid (CSF) findings, and magnetic resonance imaging (MRI) appearances. These criteria were developed by Polman et al. in 2005 and updated in 2011, and are used to facilitate the diagnosis of MS in patients who present with early symptoms suggestive of the disease.From: Imaging for Students [2012], Deep learning of brain lesion patterns and user-defined clinical and MRI features for predicting conversion to multiple sclerosis from clinically isolated syndrome [2019]

Central nervous system

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Published in David A Lisle, Imaging for Students, 2012

David A Lisle

Because of the importance of achieving a correct diagnosis in young adults, diagnostic criteria have been developed. Known as the ‘McDonald criteria’, these were released in 2001 and revised in 2005. The McDonald criteria incorporate a combination of clinical factors, CSF findings (oligoclonal IgG bands) and MRI appearances to diagnose MS.

Deep learning of brain lesion patterns and user-defined clinical and MRI features for predicting conversion to multiple sclerosis from clinically isolated syndrome

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Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2019

Youngjin Yoo, Lisa Y. W. Tang, David K. B. Li, Luanne Metz, Shannon Kolind, Anthony L. Traboulsee, Roger C. Tam

Multiple sclerosis (MS) is a neurological disorder characterised by inflammation, demyelination and degeneration in the central nervous system. There is increasing evidence that early detection and intervention can improve long-term prognosis. However, the disease course of MS is highly variable, especially in its early stages, and it is difficult to predict which patients would progress more quickly and therefore benefit from more proactive treatment. The McDonald criteria (Polman et al. 2005, 2011), which are a combination of clinical and magnetic resonance imaging (MRI) indicators of disease activity, facilitate the diagnosis of MS in patients who present early symptoms suggestive of MS.

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Central nervous system

Deep learning of brain lesion patterns and user-defined clinical and MRI features for predicting conversion to multiple sclerosis from clinically isolated syndrome