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Life sciences · Observational Study
ClinicalTrials.gov · September 15, 2026
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Observational Study.
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Registry record from ClinicalTrials.gov (NCT07820423). This is a study registration, not published results. Lead sponsor: Central South University. Recruitment status: RECRUITING. Study type: OBSERVATIONAL. Enrollment: 600 participants (ESTIMATED). Conditions: Lung Cancer Associated With Cystic Airspaces. Primary outcome measures: Predictive performance of the AI-based multimodal radiomics model for pathological high-risk features in LCCA , Within 30 days after surgery. Brief summary: The goal of this observational study is to develop and validate an artificial intelligence (AI)-based multimodal radiomics model that integrates preoperative CT imaging features and clinical data to predict pathological high-risk features in patients with lung cancer associated with cystic airspaces (LCCA). The main questions it aims to answer are: Can an AI-based multimodal radiomics model accurately predict pathological high-risk features in LCCA before surgery? Does the integration of CT imaging features and clinical variables improve preoperative risk stratification compared with imaging or clinical information alone?