Department of Radiology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Department of Radiology, Mount Sinai School of Medicine, New York, NY.
J Thorac Imaging. 2018 Nov;33(6):390-395. doi: 10.1097/RTI.0000000000000362.
Lung cancer at its earliest stage is typically manifested on computed tomography as a pulmonary nodule, which could be detected by low-dose multidetector computed tomography technology and the use of thinner collimation. Within the last 2 decades, computer-aided detection (CAD) of pulmonary nodules has been developed to meet the increasing demand for lung cancer screening computed tomography with a larger set of images per scan. This review introduced the basic techniques and then summarized the up-to-date applications of CAD systems in clinical and research programs and in the low-dose lung cancer screening trials, especially in the detection of small pulmonary nodules and missed lung cancers. Many studies have already shown that the CAD systems could increase the sensitivity and reduce the false-positive rate in the diagnosis of pulmonary nodules, especially for the small and isolated nodules. Further improvements to the current CAD schemes are needed to detect nodules accurately, particularly for subsolid nodules.
肺癌在早期阶段通常在计算机断层扫描（CT）上表现为肺结节，这可以通过低剂量多排 CT 技术和更薄的准直来检测。在过去的 20 年中，为了满足对扫描图像数量更大的肺癌筛查 CT 的需求，计算机辅助检测（CAD）技术已经发展起来。本文介绍了 CAD 的基本技术，然后总结了 CAD 系统在临床和研究计划以及在低剂量肺癌筛查试验中的最新应用，特别是在检测小的肺结节和漏诊肺癌方面。许多研究已经表明，CAD 系统可以提高肺结节诊断的敏感性并降低假阳性率，尤其是对小的和孤立的结节。需要对当前的 CAD 方案进行进一步改进，以更准确地检测结节，特别是亚实性结节。
