Implementation of the cloud-based computerized interpretation system in a nationwide lung cancer screening with low-dose CT: comparison with the conventional reading system
Authors
Eui Jin Hwang, Jin Mo Goo, Hyae Young Kim, Jaeyoun Yi, Soon Ho Yoon, Yeol Kim
The study aimed to evaluate the impact of a cloud-based CT interpretation system equipped with semi-automated measurement and computer-aided detection (CAD) for lung nodules on a nationwide lung cancer screening program. The program initially relied on each institution's interpretation systems and manual nodule measurement. The cloud-based system, implemented by Coreline Soft using AVIEW LCS, was later introduced. Results showed that while the number of detected nodules significantly increased with the cloud-based system, the positive rate didn't significantly differ from the conventional system. However, the variability of positive rates across institutions significantly reduced with the cloud-based system. In terms of sensitivity and specificity based on Lung-RADS version 1.0, no significant difference was observed between the two systems. The findings suggest that CAD and semi-automated measurements can enhance nodule detection and reduce variability in positive rates across different institutions in a nationwide lung cancer screening program.