Abstract
Anti-melanoma differentiation-associated gene 5-positive dermatomyositis-associated interstitial lung disease (MDA5+ DM-ILD) is a life-threatening disease. This study aimed to develop a novel pulmonary CT visual scoring method for assessing the prognosis of the disease, and an artificial intelligence (AI) algorithm-based analysis and an idiopathic pulmonary fibrosis (IPF)-based scoring were conducted as comparators. A retrospective cohort of hospitalized patients with MDA5+ DM-ILD was analyzed. Since most fatalities occur within the first half year of the disease course, the primary outcome was the six-month all-cause mortality since the time of admission. A ground glass opacity (GGO) and consolidation-weighted CT visual scoring model for MDA5+ DM-ILD, namely ‘MDA5 score’, was then developed with C-index values of 0.80 (95%CI 0.75–0.86) in the derivation dataset (n = 116) and 0.84 (95%CI 0.71–0.97) in the validation dataset (n = 57), respectively. While, the AI algorithm-based analysis, namely ‘AI score’, yielded C-index 0.78 (95%CI 0.72–0.84) for the derivation dataset and 0.77 (95%CI 0.64–0.90) for the validation dataset. These findings suggest that the newly derived ‘MDA5 score’ may serve as an applicable prognostic predictor for MDA5+ DM-ILD and facilitate further clinical trial design. The AI based CT quantitative analysis provided a promising solution for ILD evaluation.
Highlights
Anti-melanoma differentiation-associated gene 5-positive dermatomyositis-associated interstitial lung disease (MDA5+ DM-ILD) is a life-threatening disease
When referring to a more rapid progressive disease, such as MDA5+ DM-ILD, the applicability has not been extensively validated. Fibrosis components such as traction bronchiectasis (TBE) and honeycombing changes were higher weighted in this ‘idiopathic pulmonary fibrosis (IPF) score’; whereas inflammation components, i.e., ground-glass opacity (GGO) and consolidation were less weighted
Comparable baseline clinical features, treatment and outcomes of the derivation dataset and validation dataset were listed in Supplementary table S1
Summary
Anti-melanoma differentiation-associated gene 5-positive dermatomyositis-associated interstitial lung disease (MDA5+ DM-ILD) is a life-threatening disease. A ground glass opacity (GGO) and consolidation-weighted CT visual scoring model for MDA5+ DM-ILD, namely ‘MDA5 score’, was developed with C-index values of 0.80 (95%CI 0.75–0.86) in the derivation dataset (n = 116) and 0.84 (95%CI 0.71–0.97) in the validation dataset (n = 57), respectively. Fibrosis components such as traction bronchiectasis (TBE) and honeycombing changes were higher weighted in this ‘IPF score’; whereas inflammation components, i.e., ground-glass opacity (GGO) and consolidation were less weighted Until recently, another simplified scoring method for M DA5+ DM-ILD was proposed with weighted two components of GGO and fibrosis[9, 10]. The aims of the current study were to establish a novel pulmonary HRCT visual scoring method for predicting the six-month mortality in a large single-centered cohort of patients with M DA5+ DM; and in parallel, to explore quantitative imaging assessment of this disease by applying artificial intelligence (AI) algorithm
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