T2 Analysis of the Entire Osteoarthritis Initiative Dataset.

While substantial work has been done to understand the relationships between cartilage T2 relaxation times and Osteoarthritis (OA), diagnostic and prognostic abilities of T2 on large population yet need to be established. Using 3921 manually annotated 2D multi-slice multi-echo (MSME) spin-echo MRI volume, a segmentation model for automatic knee cartilage segmentation was built and evaluated. The optimized model was then used to calculate T2 values on the entire OAI dataset composed of longitudinal acquisitions of 4,796 unique patients, 25,729 MRI studies in total. Cross-sectional relationships between T2 values, OA risk factors, radiographic OA and pain were analyzed in the entire OAI dataset. The performance of T2 values in predicting future incidence of radiographic OA as well as total knee replacement (TKR) were also explored. Automatic T2 values were comparable with manual ones. Significant associations between T2 relaxation times and demographic and clinical variables were found. Subjects in the highest 25% quartile of tibio-femoral T2 values had 5 times higher risk of radiographic OA incidence 2 years later. Elevation of medial femur T2 values was significantly associated with TKR after 5 years (coeff=0.10, p-value=0.036, CI= (0.01,0.20)). Our results demonstrate that T2 predicted radiographic OA and TKR and may thus serve as an early biomarker in diagnosis and prediction of OA. This article is protected by copyright. All rights reserved.