Objectives: We aimed to compare the CT interpretation before and after the implementation of a computerized system for lung nodule detection and measurements in a nationwide lung cancer screening program. Methods: Our screening program started in April 2017, with 14 participating institutions. Initially, all CTs were interpreted using interpretation systems in each institution and manual nodule measurement (conventional system). A cloud-based CT interpretation system, equipped with semi-automated measurement and CAD (computer-aided detection) for lung nodules (cloud-based system), was implemented during the project. Positive rates and performances for lung cancer diagnosis based on the Lung-RADS version 1.0 were compared between the conventional and cloud-based systems. Results: A total of 1821 (M:F = 1782:39, mean age 62.7 years, 16 confirmed lung cancers) and 4666 participants (M:F = 4560:106, mean age 62.8 years, 31 confirmed lung cancers) were included in the conventional and cloud-based systems, respectively. Significantly more nodules were detected in the cloud-based system (0.76 vs. 1.07 nodule/participant, p <.001). Positive rate did not differ significantly between the two systems (9.9% vs. 11.0%, p =.211), while their variability across institutions was significantly lower in the cloud-based system (coefficients of variability, 0.519 vs. 0.311, p =.018). The Lung-RADS-based sensitivity (93.8% vs. 93.5%, p =.979) and specificity (90.9% vs. 89.6%, p =.132) did not differ significantly between the two systems. Conclusion: Implementation of CAD and semi-automated measurement for lung nodules in a nationwide lung cancer screening program resulted in increased number of detected nodules and reduced variability in positive rates across institutions. Key Points: • Computer-aided CT reading detected more lung nodules than radiologists alone in lung cancer screening. • Positive rate in lung cancer screening did not change with computer-aided reading. • Computer-aided CT reading reduced inter-institutional variability in lung cancer screening.
- Early detection of cancer
- Image interpretation, computer-assisted
- Lung neoplasms
- Observer variation
- Tomography, X-ray computed