Lung Cancer Screening
AI Solution

To evaluate performance of AI as a standalone reader in ultra-low-dose CT lung cancer baseline screening, and compare it to that of experienced radiologists. Volumetric nodule measurements were performed by five experienced blinded radiologists, and independently assessed using an AI lung cancer screening prototype (aview LCS, v1.0.34, Coreline Soft, Co. ltd, Seoul, Korea) to automatically detect, measure, and classify solid nodules. Our results suggest that through the use of AI as an impartial reader in baseline lung cancer screening, negative-misclassification results could exceed that of four out of five experienced radiologists, and radiologists’ workload could be drastically diminished by up to 86.7%.

The Korean Lung Cancer Screening Project (K-LUCAS) is a single-arm cohort study that was conducted from February 2017 to evaluate the feasibility of implementing an organized national lung cancer screening program in Korea High-risk population aged 55–74 years with more than a 30-pack-year smoking history was recruited. The screening results were reported using the Lung Imaging Reporting and Data System (Lung-RADS), suggested by the American College of Radiology. K-LUCAS was performed by a network-based diagnosis supporting system using a computer-aided detection (CAD) program (aview LCS, Corelinesoft) to maintain screening quality. K-LUCAS provided promising evidence supporting the implementation of a national lung cancer screening program to detect lung cancer at an early stage and promote smoking cessation for participants in Asian population.