Identifying Lung Fibrosis Progression in Systemic Rheumatic Diseases Using Blood Biomarkers and AI-Based Lung Imaging

What this Trial Is About

This research focuses on connective tissue diseases CTDs, which are systemic rheumatic disorders involving abnormal immune responses and fibrosis of organs. A common and serious complication is interstitial lung disease ILD, affecting 10 to 50% of CTD patients and leading to disability and death. Current methods to screen and predict ILD progression are limited, so this study aims to find new biomarkers using serum extracellular vesicles EVs and artificial intelligence AI analysis of lung imaging to better identify lung involvement in CTD patients. The study will enroll 200 patients with CTDs, split evenly between those with and without ILD. Participants will provide blood samples for EV analysis, which includes proteomic and transcriptomic profiling. Lung involvement will be assessed using high-resolution computed tomography HRCT scans analyzed by AI software. Patients will be followed for 12 months to compare EV profiles and AI-based imaging differences between progressive and non-progressive ILD cases. The study includes multiple CTD types and uses specific autoantibody profiles to identify high-risk patients. Participants will undergo blood collection and HRCT scans at enrollment, with follow-up visits at 6 and 12 months to monitor lung function and disease progression. Researchers will measure changes in EV proteins and RNA, along with AI-driven lung imaging features such as lung volume, texture, airway, and vessel analysis. The study also monitors standard laboratory biomarkers for ILD. The total study duration is approximately 92 weeks, including enrollment, follow-up, and data analysis phases.

Early Recognition of Progressive Lung Fibrosis in Systemic Rheumatic Diseases