PINPOINT: Integrating Computer Assisted Detection and Virtual Nodule Clinics for Early Lung Cancer Detection in Routine Practice, A Pilot Study.

BACKGROUND: Incidental pulmonary nodules (IPN) detected on routine chest CT scans represent an opportunity for early lung cancer diagnosis but are frequently missed or not managed appropriately. Computer-assisted detection (CAD) software and patient tracking through virtual nodule clinics (VNCs) may improve IPN detection and management. This study explored the feasibility and effectiveness of implementation of CAD combined with VNCs in routine practice. PATIENTS AND METHODS: A dedicated IPN program integrating CAD for analysis of all chest CT scans and a navigator-supervised VNC was implemented across 6 European hospitals. Aggregated clinical and radiological data were collected from the VNC application. Feasibility outcomes including CAD failure rate, nodule detection rate, patient flagging in the VNC, lung cancer diagnosis, and site-level adoption and continued software use, were evaluated using descriptive statistics. RESULTS: 65,344 patients were included from program initiation until January 2025, with a mean duration of 14 months (range 8-25). CAD software successfully analyzed 99.5% of scans and detected abnormalities in 62.7% (40,954) of scanned patients. Radiologists flagged 619 patients for IPN management, 10 of whom (1.6%) were diagnosed with lung cancer. All lung cancers were early-stage. CAD use was maintained in all sites, with radiologists reporting increased diagnostic confidence. The VNC was perceived as a valuable safety-net, although insufficient resources and workflow disruptions limited consistent use. CONCLUSION: This pilot demonstrates feasibility of CAD and VNCs in routine workflows. CAD showed promising technical reliability and detection performance. VNC uptake could be further optimized by supporting the navigator role with dedicated resources and improving ease of use.