Meeting Banner
Abstract #3176

Classification of Cartilage Degradation and Quantification of Matrix Composition Through Multiparametric Support Vector Machine Analysis

Ping-Chang Lin1, Onyi Irrechukwu1, Remy Roque1, Richard G. Spencer1

1National Institute on Aging, National Institutes of Health, Baltimore, MD, United States

Univariate classification, as is implicitly used in analyses of cartilage matrix using MRI parameters, exhibits limited ability to discriminate between control and degraded tissue. In view of these limitations, we undertook a multivariate support vector machine (SVM) analysis of bovine nasal cartilage (BNC) samples with pathomimetic degradation using trypsin and collagenase. Our current results, that the sets (T1, km), (T1, T2, km) and (T1, km, ADC) exhibit particularly favorable classification properties, are consistent with our previous study, indicating that these parameter combinations may emerge as particularly useful in multivariate cartilage matrix characterization