Machine learning identification of thresholds to discriminate osteoarthritis and rheumatoid arthritis synovial inflammation

BackgroundWe sought to identify features that distinguish osteoarthritis (OA) and rheumatoid arthritis (RA) hematoxylin and eosin (H&E)-stained synovial tissue samples.MethodsWe compared fourteen pathologist-scored histology features and computer vision-quantified cell density (147 OA and 60 RA patients) in H&E-stained synovial tissue samples from total knee replacement (TKR) explants. A random forest model was trained using disease state (OA vs RA) as a classifier and histology features and/or computer vision-quantified cell density as inputs.ResultsSynovium from OA patients had increased mast cells and fibrosis (p < 0.001), while synovium from RA patients exhibited increased lymphocytic inflammation, lining hyperplasia, neutrophils, detritus, plasma cells, binucleate plasma cells, sub-lining giant cells, fibrin (all p < 0.001), Russell bodies (p = 0.019), and synovial lining giant cells (p = 0.003). Fourteen pathologist-scored features allowed for discrimination between OA and RA, producing a micro-averaged area under the receiver operating curve (micro-AUC) of 0.85 +/- 0.06. This discriminatory ability was comparable to that of computer vision cell density alone (micro-AUC = 0.87 +/- 0.04). Combining the pathologist scores with the cell density metric improved the discriminatory power of the model (micro-AUC = 0.92 +/- 0.06). The optimal cell density threshold to distinguish OA from RA synovium was 3400 cells/mm(2), which yielded a sensitivity of 0.82 and specificity of 0.82.ConclusionsH&E-stained images of TKR explant synovium can be correctly classified as OA or RA in 82% of samples. Cell density greater than 3400 cells/mm(2) and the presence of mast cells and fibrosis are the most important features for making this distinction.

Automated summary

This study aimed to differentiate osteoarthritis (OA) and rheumatoid arthritis (RA) by examining hematoxylin and eosin (H&E)-stained synovial tissue samples. OA patients exhibited increased mast cells and fibrosis, while RA patients showed increased lymphocytic inflammation, lining hyperplasia, neutrophils, detritus, plasma cells, binucleate plasma cells, sub-lining giant cells, fibrin, Russell bodies, and synovial lining giant cells. Combining pathologist scores with cell density metrics improved the classification accuracy.