The Added Value of Computer-aided Detection of Small Pulmonary Nodules and Missed Lung Cancers

• Published in: Journal of thoracic imaging Vol. 33; no. 6; p. 390
• Main Authors: Cai, Jiali, Xu, Dongming, Liu, Shiyuan, Cham, Matthew D
• Format: Journal Article
• Language: English
• Published: United States 01.11.2018
• Subjects: Humans; Image Processing, Computer-Assisted - methods; Lung - diagnostic imaging; Lung Neoplasms - diagnostic imaging; Multiple Pulmonary Nodules - diagnostic imaging; Sensitivity and Specificity; Solitary Pulmonary Nodule - diagnostic imaging; Tomography, X-Ray Computed - methods
• ISSN: 1536-0237
• 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.