Department of Radiology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea.
Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, South Korea.
Eur Radiol. 2021 Jan;31(1):475-485. doi: 10.1007/s00330-020-07151-7. Epub 2020 Aug 14.
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.
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.
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.
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.
• 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.
我们旨在比较在全国性肺癌筛查计划中实施用于肺结节检测和测量的计算机化系统前后的 CT 解读结果。
我们的筛查计划于 2017 年 4 月启动，有 14 个参与机构。最初，所有 CT 均由各机构的解读系统和手动结节测量（常规系统）进行解读。在项目期间，引入了配备半自动化测量和计算机辅助检测（CAD）的基于云的 CT 解读系统（基于云的系统），用于肺结节检测。我们比较了基于 Lung-RADS 1.0 版本的肺癌诊断的阳性率和性能，在常规系统和基于云的系统之间进行比较。
共有 1821 名（男：女=1782:39，平均年龄 62.7 岁，16 例确诊肺癌）和 4666 名参与者（男：女=4560:106，平均年龄 62.8 岁，31 例确诊肺癌）分别纳入常规系统和基于云的系统。基于云的系统中检测到的结节数量明显更多（0.76 个/参与者 vs. 1.07 个/参与者，p<.001）。两个系统之间的阳性率没有显著差异（9.9% vs. 11.0%，p=.211），而基于云的系统中各机构之间的变异性显著较低（变异系数，0.519 vs. 0.311，p=.018）。基于 Lung-RADS 的敏感性（93.8% vs. 93.5%，p=.979）和特异性（90.9% vs. 89.6%，p=.132）在两个系统之间没有显著差异。
在全国性肺癌筛查计划中实施肺结节 CAD 和半自动测量，导致检测到的结节数量增加，各机构之间的阳性率变异性降低。
• 在肺癌筛查中，计算机辅助 CT 阅读比放射科医生单独阅读检测到更多的肺结节。• 计算机辅助阅读并未改变肺癌筛查的阳性率。• 计算机辅助 CT 阅读减少了肺癌筛查的机构间变异性。
