NCT07052773

Clinical Evaluation of the Lung Cancer AI-based Decision Support Tool in Low-Dose Lung CT

Blinded Retrospective Study to Clinically Validate the Accuracy of the Lung Cancer Detection System (LCDS) AI-based Decision Support Tool for Lung Cancer Low-Dose CT

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 100 (actual)
• Sponsor: Genesis Medical AI · Industry
• Sex: All
• Age: 50 Years – 79 Years
• Healthy volunteers: Not accepted

Summary

The goal of this observational study is to clinically validate the accuracy of an AI-based decision support tool-the Lung Cancer Detection System (LCDS)-for detecting lung nodules in asymptomatic adults aged 50-79 with a history of heavy smoking who underwent low-dose chest CT (LDCT) scans. The main questions it aims to answer are: * Can the LCDS accurately detect the presence of solid pulmonary nodules on LDCT scans, as measured by sensitivity and specificity? * How does the LCDS's performance compare to existing AI systems using the Area Under the Curve-Receiver Operating Characteristic (AUC/ROC) Curve? Researchers will compare the AI-based interpretations to a ground truth established by consensus among radiologists' double-readings to see if the LCDS can accurately classify cases as 'lung nodule presence' or 'lung nodule absence'. Participants will: * Have their de-identified LDCT scans (collected between 2018 and 2023) reviewed retrospectively. * Be evaluated through the LCDS tool, which will classify cases based on lung nodule presence. Contribute to performance evaluation using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and ROC analysis.

Conditions

• Lung Cancer Screening

Interventions

Type	Name	Description
DEVICE	Lung Cancer Detection System (LCDS)	An AI-based decision support software designed to detect solid pulmonary nodules on LDCT chest scans. In this study, the LCDS is applied retrospectively to 100 previously acquired LDCT scans, and its performance is compared to a ground truth established by double-read radiologist reports with arbitration.

Timeline

• Start date: 2023-10-26
• Primary completion: 2024-05-05
• Completion: 2024-05-05
• First posted: 2025-07-07
• Last updated: 2025-07-07

Locations

1 site across 1 country: Israel