A Computed Tomography Radiomics-Based Prediction Model on Interstitial Lung Disease in Anti-MDA5-Positive Dermatomyositis

Objectives: Anti-melanoma differentiation-associated gene 5-positive dermatomyositis-associated interstitial lung disease (MDA5+ DM-ILD) is a life-threatening disease. The current study aimed to quantitatively assess the pulmonary high-resolution computed tomography (HRCT) images of MDA5+ DM-ILD by applying the radiomics approach and establish a multidimensional risk prediction model for the 6-month mortality. Methods: This retrospective study was conducted in 228 patients from two centers, namely, a derivation cohort and a longitudinal internal validation cohort in Renji Hospital, as well as an external validation cohort in Guangzhou. The derivation cohort was randomly divided into training and testing sets. The primary outcome was 6-month all-cause mortality since the time of admission. Baseline pulmonary HRCT images were quantitatively analyzed by radiomics approach, and a radiomic score (Rad-score) was generated. Clinical predictors selected by univariable Cox regression were further incorporated with the Rad-score, to enhance the prediction performance of the final model (Rad-score plus model). In parallel, an idiopathic pulmonary fibrosis (IPF)-based visual CT score and ILD-GAP score were calculated as comparators. Results: The Rad-score was significantly associated with the 6-month mortality, outperformed the traditional visual score and ILD-GAP score. The Rad-score plus model was successfully developed to predict the 6-month mortality, with C-index values of 0.88 [95% confidence interval (CI), 0.79-0.96] in the training set (n = 121), 0.88 (95%CI, 0.71-1.0) in the testing set (n = 31), 0.83 (95%CI, 0.68-0.98) in the internal validation cohort (n = 44), and 0.84 (95%CI, 0.64-1.0) in the external validation cohort (n = 32). Conclusions: The radiomic feature was an independent and reliable prognostic predictor for MDA5+ DM-ILD.