Evaluation of an automatic multiple sclerosis lesion quantification tool in an informatics-based MS e-folder system
2011
Multiple sclerosis (MS) is a demyelinating disease of the central nervous system. The chronic nature of MS necessitates
multiple MRI studies to track disease progression. We have presented an imaging informatics decision-support system,
called MS eFolder, designed to integrate patient clinical data with MR images and a computer-aided detection (CAD)
component for automatic white matter lesion quantification. The purpose of the MS eFolder is to comprehensively
present MS patient data for clinicians and radiologists, while providing a lesion quantification tool that can be objective
and consistent for MS tracking in longitudinal studies. The MS CAD algorithm is based on the K-nearest neighbor
(KNN) principles and has been integrated within the eFolder system. Currently, the system has been completed and the
CAD algorithm for quantifying MS lesions has undergone the expert evaluation in order to validate system performance
and accuracy. The evaluation methodology has been developed and the data has been collected, including over 100 MS
MRI cases with various age and ethnic backgrounds. The preliminary results of the evaluation are expected to include
sensitivity and specificity of lesion and non-lesion voxels in the white matter, the effectiveness of different probability
thresholds for each voxel, and comparison between CAD quantification results and radiologists' manual readings. The
results aim to show the effectiveness of a MS lesion CAD system to be used in a clinical setting, as well as a step closer
to full clinical implementation of the eFolder system.
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