Novel Morphological and Appearance Features for Predicting Physical Disability from MR Images in Multiple Sclerosis Patients
Physical disability in patients with multiple sclerosis is determined by functional ability and quantified with numerical scores. In vivo studies using magnetic resonance imaging (MRI) have found that these scores correlate with spinal cord atrophy (loss of tissue), where atrophy is commonly measured by spinal cord volume or cross-sectional area. However, this correlation is generally weak to moderate, and improved measures would strengthen the utility of imaging biomarkers. We propose novel spinal cord morphological and MRI-based appearance features. Select features are used to train regression models to predict patients’ physical disability scores. We validate our models using 30 MRI scans of different patients with varying levels of disability. Our results suggest that regression models trained with multiple spinal cord features predict clinical disability better than a model based on the volume of the spinal cord alone.
KeywordsSpinal Cord Expand Disability Status Scale Clinical Score Expand Disability Status Scale Score Simple Linear Regression Model
JK, RT, and GH were partially supported by NSERC and Biogen Idec Canada. CM was supported by the Canadian Breast Cancer Foundation and the Canadian Cancer Society Research Institute.
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