Investigating the relationship between radiographic joint space width loss and deep learning-derived magnetic resonance imaging-based cartilage thickness loss in the medial weight-bearing region of the tibiofemoral joint

Objective: To investigate the relationship between measures of radiographic joint space width (JSW) loss and magnetic resonance imaging (MRI)-based cartilage thickness loss in the medial weight-bearing region of the tibiofemoral joint over 12–24 months. To stratify this relationship by clinically meaningful subgroups (sex and pain status). Design: We analyzed a subset of knees (n ​= ​256) from the Osteoarthritis Initiative (OAI) likely in early stage OA based on joint space narrowing (JSN) measurements. Natural logarithm transformation was used to approximate near normal distributions for JSW loss. Pearson Correlation coefficients described the relationship between ln-transformed JSW loss and several versions of deep learning-derived MRI-based cartilage thickness loss parameters (minimum, maximum, and mean) in subregions of the femoral condyle, tibial plateau, and combined femoral and tibial regions. Linear mixed-effects models evaluated the associations between the ln-transformed radiographic and MRI-derived measures including potential confounders. Results: We found weak correlations between ln-transformed JSW loss and MRI-based cartilage thickness ranging from R ​= ​−0.13 (p ​= ​0.20) to R ​= ​0.26 (p ​