부산대학교 도서관

Objective To investigate whether digital activity fluorescence optical imaging (FOI) patterns of inflammation can identify distinct rheumatoid arthritis (RA) phenotypes. Methods The hands of newly diagnosed patients with RA were evaluated by clinical examination, musculoskeletal ultrasound, and FOI. Inflammation on FOI was defined when capillary leakage and/or fluorophore perfusion was present. The FOI composite image was quantified into a digital disease activity (DACT) score, using novel computerized algorithms. Unsupervised clustering on FOI inflammatory patterns was used to identify subgroups of patients relative to anticyclic citrullinated peptides (ACPA) and/or rheumatoid factor (RF). Results Of 1326 examined hand joints in 39 patients with RA (72% female; 56% ever‐smokers; 54% RF positive and 69% ACPA positive), 400 (30%) showed inflammation by FOI, and 95% (37 of 39) of patients had DACT‐FOI scores greater than 1. Unsupervised analysis on FOI patterns revealed two patient clusters, cluster 1 (n = 29) and cluster 2 (n = 10). The proportion of seropositive patients was significantly higher in cluster 1 versus cluster 2 (90%, 26 of 29 vs. 30%, 3 of 10; P