Automatic Cartilage Segmentation for Delayed Gadolinium-Enhanced Magnetic Resonance Imaging of Hip Joint Cartilage: A Feasibility Study

Objective Automatic segmentation for biochemical cartilage evaluation holds promise for an efficient and reader-independent analysis. This pilot study aims to investigate the feasibility and to compare delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) hip joint assessment with manual segmentation of acetabular and femoral head cartilage and dGEMRIC hip joint assessment using automatic surface and volume processing software at 3 Tesla. Design Three-dimensional (3D) dGEMRIC data sets of 6 patients with hip-related pathology were assessed (1) manually including multiplanar image reformatting and regions of interest (ROI) analysis and (2) automated by using a combined surface and volume processing software. For both techniques, T1Gd values were obtained in acetabular and femoral head cartilage at 7 regions (anterior, anterior-superior, superior-anterior, superior, superior-posterior, posterior-superior, and posterior) in central and peripheral portions. Correlation between both techniques was calculated utilizing Spearman’s rank correlation coefficient. Results A high correlation between both techniques was observed for acetabular (ρ = 0.897; P < 0.001) and femoral head (ρ = 0.894; P < 0.001) cartilage in all analyzed regions of the hip joint (ρ between 0.755 and 0.955; P < 0.001). Conclusions Automatic cartilage segmentation with dGEMRIC assessment for hip joint cartilage evaluation seems feasible providing high to excellent correlation with manually performed ROI analysis. This technique is feasible for an objective, reader-independant and reliable assessment of biochemical cartilage status.