Lung Cancer Screening Using Low-dose CT Scans in Women Aged 50 to 74 With Smoking History

What this Trial Is About

This research aims to evaluate whether a single general radiologist, trained in lung cancer screening, can accurately read low-dose thoracic CT scans compared to the traditional double reading by expert radiologists. The study focuses on women aged 50 to 74 years who are at risk for lung cancer due to a significant history of smoking. It also explores the use of artificial intelligence to assist in lung nodule detection during the reading process. Participants will undergo low-dose CT scans of the chest at three time points baseline, one year, and two years. Initially, the CT scans will be reviewed onsite by a trained general radiologist first without and then with the assistance of an AI algorithm designed to detect lung nodules. Meanwhile, two expert chest radiologists will independently read all scans, resolving any disagreements through consensus. Patient care decisions will be based on the expert double reading results. Criteria for positive findings include nodules exceeding specific size or growth thresholds. During the study, participants will be monitored through these annual CT scans for two years, with adherence to screening and smoking cessation impact also assessed. Researchers will analyze diagnostic accuracy, concordance between readers and AI, psychological effects, comorbidity detection, and cost implications. The main outcome is the performance of trained radiologists in lung cancer screening over two years, alongside evaluation of AIs added value and other secondary outcomes related to screening effectiveness and participant health.

Lung Cancer Screening With Low-dose CT Scan in Women : Implementation Study