This multicenter retrospective study is designed to develop and validate a CT-based multimodal risk stratification approach for postoperative local recurrence after curative-intent resection of non-small cell lung cancer (NSCLC). The approach integrates clinicopathologic variables, intratumoral and peritumoral radiomics, tumor-based 2.5D deep learning features, whole-lung deep learning features, and operative text features to capture complementary information related to tumor phenotype, pulmonary background, and surgical findings. Predictive performance and clinical utility will be evaluated in internal and external validation cohorts using the concordance index, time-dependent area under the receiver operating characteristic curve, decision curve analysis, and risk reclassification analyses. The objective of this study is to assess whether multimodal CT-based risk stratification may improve postoperative risk assessment and support individualized surveillance and management strategies.
Age range
18 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Postoperative local recurrence
Timeframe: From the date of surgery to first documented local recurrence, up to 3 years