UCSF

In this technique development study, high-resolution peripheral quantitative computed tomography (HR-pQCT) was applied to non-invasively image and quantify 3D joint space morphology of the wrist and metacarpophalangeal (MCP) joints of patients with rheumatoid arthritis (RA). HR-pQCT imaging (82 μm voxel-size) of the dominant hand was performed in patients with diagnosed rheumatoid arthritis (RA, N = 16, age: 52.6 ± 12.8) and healthy controls (CTRL, N = 7, age: 50.1 ± 15.0). An automated computer algorithm was developed to segment wrist and MCP joint spaces. The 3D distance transformation method was applied to spatially map joint space width, and summarized by the mean joint space width (JSW), minimal and maximal JSW (JSW.MIN, JSW.MAX), asymmetry (JSW.AS), and distribution (JSW.SD)-a measure of joint space heterogeneity. In vivo precision was determined for each measure by calculating the smallest detectable difference (SDD) and root mean square coefficient of variation (RMSCV%) of repeat scans. Qualitatively, HR-pQCT images and pseudo-color JSW maps showed global joint space narrowing, as well as regional and focal abnormalities in RA patients. In patients with radiographic JSN at an MCP, JSW.SD was two-fold greater vs. CTRL (p < 0.01), and JSW.MIN was more than two-fold lower (p < 0.001). Similarly, JSW.SD was significantly greater in the wrist of RA patients vs. CTRL (p < 0.05). In vivo precision was highest for JSW (SDD: 100 μm, RMSCV: 2.1%) while the SDD for JSW.MIN and JSW.SD were 370 and 110 μm, respectively. This study suggests that in vivo quantification of 3D joint space morphology from HR-pQCT, could improve early detection of joint damage in rheumatological diseases.