Quantifying Cutaneous Dermatomyositis: A Novel 3D Image-Based Approach
Issued Date
2026-01-01
Resource Type
eISSN
14992752
Scopus ID
2-s2.0-105026575768
Pubmed ID
41033834
Journal Title
Journal of Rheumatology
Volume
53
Issue
1
Start Page
68
End Page
76
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Rheumatology Vol.53 No.1 (2026) , 68-76
Suggested Citation
Pongtarakulpanit N., Bishnoi A., Chandra T., Dzanko S., Gkiaouraki E., Keret S., Silva R.L., Sriram S., Saygin D., Liarski V.M., Ascherman D.P., Oddis C.V., Moghadam-Kia S., Aggarwal R. Quantifying Cutaneous Dermatomyositis: A Novel 3D Image-Based Approach. Journal of Rheumatology Vol.53 No.1 (2026) , 68-76. 76. doi:10.3899/jrheum.2025-0537 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/114631
Title
Quantifying Cutaneous Dermatomyositis: A Novel 3D Image-Based Approach
Corresponding Author(s)
Other Contributor(s)
Abstract
OBJECTIVE: Visual examination of skin lesions has considerable subjectivity and interrater variability. This study assessed the feasibility of a 3D image-based assessment of cutaneous disease activity in dermatomyositis (DM). METHODS: Patients with DM were evaluated in a prospective study at 2 timepoints for skin rash assessment using the Cutaneous Dermatomyositis Disease Area and Severity Index (CDASI) and 3D images. A 3D image disease activity score (3DAS) was calculated based on the percentage of the rashes relative to the total body surface area, multiplied by the degree of rash redness. The construct validity and responsiveness of 3DAS were evaluated using the Spearman correlation coefficient (r) against standard CDASI and patient-reported outcome measures (PROMs). A generalized linear regression model assessed the relationship between the 3D image-derived rash area and redness with the CDASI score. RESULTS: Twenty-seven patients with DM (81.5% female, 96.3% White; median age 50.0 years) were enrolled. The median (IQR) CDASI score at baseline was 6.0 (IQR 0.0-17.0). For the construct validity, 3DAS correlated strongly with the CDASI (r = 0.83; P < 0.001) and PROMs. The generalized linear regression analysis identified the rash area and redness from 3D images as significant predictors of the CDASI score. Regarding responsiveness, absolute changes from baseline in the 3DAS correlated strongly with the CDASI score (r = 0.61; P = 0.004). CONCLUSION: Our results demonstrate favorable validity and responsiveness of the 3D images for evaluating rashes in patients with DM. The 3D image-derived rash area and redness are significant predictors of CDASI scores.