量化皮肤皮肌炎:一种新的基于3D图像的方法。

Nantakarn Pongtarakulpanit,Anuradha Bishnoi,Tanya Chandra,Sedin Dzanko,Eugenia Gkiaouraki,Shiri Keret,Raisa Lomanto Silva,Shreya Sriram,Didem Saygin,Vladimir M Liarski,Dana P Ascherman,Chester V Oddis,Siamak Moghadam-Kia,Rohit Aggarwal
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摘要

目的皮肤病变的视觉检查具有相当大的主观性和差异。本研究评估了基于3D图像评估皮肌炎(DM)皮肤病活动性的可行性。方法前瞻性研究采用皮肤皮肌炎疾病面积和严重程度指数(CDASI)和3D图像,在2个时间点对sdm患者进行皮疹评估。根据皮疹相对于体表总面积的百分比乘以皮疹发红程度,计算出“3D图像疾病活动评分(3DAS)”。采用Spearman相关系数(rsp)对标准CDASI和患者报告结果测量(PROMs)评估3DAS的结构效度和反应性。广义线性回归模型评估三维图像衍生的皮疹面积和发红与CDASI评分之间的关系。结果纳入27例糖尿病患者(女性81.5%,白人96.3%,中位年龄50.0岁)。基线时CDASI评分中位数(IQR)为6.0(0.0 - 17.0)。在构效度上,3DAS与CDASI和PROMs呈显著相关(rsp = 0.83, p < 0.001)。广义线性回归分析确定3D图像中的皮疹面积和发红是CDASI评分的重要预测因子。关于反应性,3DAS从基线的绝对变化与CDASI评分密切相关(rsp = 0.61, p = 0.004)。结论三维影像对糖尿病患者皮疹的评价具有良好的有效性和响应性。三维图像衍生的皮疹面积和红色是CDASI评分的重要预测因子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantifying Cutaneous Dermatomyositis: A Novel 3D Image-based Approach.
OBJECTIVE Visual examination of skin lesions has considerable subjectivity and inter-rater variability. This study assessed the feasibility of a 3D image-based assessment of cutaneous disease activity in dermatomyositis (DM). METHODS DM patients were evaluated in a prospective study at 2 time points 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 (rsp) 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 27 DM patients (81.5% female, 96.3% White; median age 50.0 years) were enrolled. The median (IQR) CDASI score at baseline was 6.0 (0.0 - 17.0). For the construct validity, 3DAS correlated strongly with the CDASI (rsp = 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 (rsp = 0.61, p = 0.004). CONCLUSION Our results demonstrate favorable validity and responsiveness of the 3D images for evaluating rash in DM patients. The 3D image-derived rash area and redness are significant predictors of CDASI scores.
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