Automated Objective Scoring of Histologically Apparent Cartilage Degeneration Using a Custom Image Analysis Program

Abstract

Histologic assessment of cartilage degradation has traditionally involved semiquantitative techniques, the most commonly utilized being the Mankin scale. Such assessments depend on human observer subjectivity, and thus have drawn criticism on the basis of associated inter- and intraobserver variability. We report a newly developed computational image analysis procedure for fully automated and fully objective assessment of the Mankin scale. Image processing routines were developed in a widely used programming environment (Matlab) to analyze cartilage degradation. One hundred and twenty-five histology images incorporating a wide range of degradation features were analyzed by the algorithm and by seven observers experienced in cartilage histologic assessment. Based on random effects linear statistical models, the computer program performed well, showing a correlation of 0.88 between its Mankin scores and latent (average of human observers') image scores. Regarding the four subcomponents of the Mankin scale, computer program correlations with observer scores were best for surface defect and proteoglycan depletion, but less favorable for cellularity and tidemark invasion. While limitations exist with image processing techniques, the new algorithm provides an objective and automated method for analyzing cartilage histology sections, consistent with human observer grading.