Rheumatoid arthritis (RA) frequently affects the joints of the hands, with joint space narrowing (JSN) representing an important early marker of structural damage. The semi-quantitative Sharp/van der Heijde (SvdH) scoring system is widely used in clinical practice but is inherently subjective and susceptible to observer variability. Moreover, the complex anatomy of the wrist and substantial overlap of carpal bones pose challenges for automated quantitative assessment of wrist JSN on routine radiographs. This study aimed to introduce a novel quantitative assessment perspective and to clinically validate an automated, compactness-related quantification framework for evaluating wrist JSN in RA. This study initially enrolled 51 patients with RA. After excluding one case with severe carpal fusion that precluded anatomical differentiation, 50 patients (44 females and 6 males) were included in the final analysis. The cohort had a mean age of 61 years (range: 21–82), a median symptom duration of 9 years (IQR: 1–32), and a median follow-up interval for bilateral hand radiographs of 1.06 years (IQR: 0.82–1.30). To quantify global wrist JSN, 10 compactness-related metrics were computed based on the spatial distribution of bone centroids extracted from carpal segmentation masks. These metrics were validated against the wrist JSN subscore of the SvdH score (SvdH-JSN_wrist) and the total Sharp score (TSS) as gold standards. Several distance-based metrics among the compactness-related metrics showed significant negative correlations with the wrist joint space narrowing subscore of the Sharp/van der Heijde score (SvdH-JSN_wrist). Specifically, mean-pairwise-distance ($MPD$), root-mean-square-radius ($RMSR$), and median-radius ($R50$) showed moderate to strong correlations (r = −0.52 to −0.63, all $p\le 0.0001$) that were consistent at BL and FU. Correlations with TSS were weaker overall, with only $R50$ and its normalized form showing stable negative correlations (r = −0.40 to −0.43, p < 0.01). Longitudinal analyses showed limited correlations between metric changes and clinical score changes. The proposed automated compactness quantification framework enables objective and reliable assessment of wrist JSN on standard radiographs and complements conventional scoring systems by supporting automated and standardized evaluation of RA-related wrist structural changes.

Rheumatoid arthritis (RA) frequently involves the wrist joints, where early inflammation may induce subtle changes in carpal spatial architecture. This study investigated whether baseline (BL) ultrasound inflammation is associated with longitudinal changes in AI-derived compactness metrics and whether these metrics provide information complementary to conventional wrist radiographic scores. This study included 159 patients with early RA who underwent BL and follow-up (FU) bilateral wrist radiography and BL wrist ultrasound. Four AI-derived centroid-based compactness metrics—root-mean-square-radius (RMSR), mean pairwise distance (MPD), median radius (R50), and 90th-percentile-radius (R90)—were calculated, and their annualized changes were evaluated in relation to conventional wrist SvdH scores and BL ultrasound inflammation, including gray-scale (GS), power Doppler (PD), GS+PD, and vascularity percentage (VS%). Associations were assessed using correlation and subgroup analyses. AI-derived compactness metrics at BL and FU, as well as their annualized changes, were not significantly associated with conventional wrist radiographic scores. In contrast, BL ultrasound inflammation was significantly associated with subsequent increases in compactness metrics. BL GS, PD, and GS+PD scores showed significant positive correlations with annualized changes in RMSR, MPD, R50, and R90 (r = 0.18–0.25, p < 0.05). Subgroup analyses similarly demonstrated greater increases in compactness metrics in patients with positive GS or PD activity. Annualized changes in AI-derived compactness metrics were associated with baseline ultrasound inflammation but not with changes in conventional wrist radiographic scores. These findings suggest that AI-derived compactness metrics may provide complementary quantitative information on global carpal spatial architecture in early RA.