Journal of Innovative Optical Health Sciences, Volume. 15, Issue 2, 2250013(2022)

Comparison of two reader modes of computer-aided diagnosis in lung nodules on low-dose chest CT scan

[in Chinese]1, [in Chinese]1, [in Chinese]1, [in Chinese]2, [in Chinese]1, [in Chinese]1, [in Chinese]1, [in Chinese]1, [in Chinese]1, and [in Chinese]1、*
Author Affiliations
  • 1Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Dadao 1095(#), Wuhan 430030, Hu Bei, P. R. China
  • 2Department of Radiology, Shenzhen Maternity & Child Healthcare Hospital ,Affiliated to Southern Medical University, Hongli, Shenzhen 518028, P. R. China
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    Low-dose computerized tomography (LDCT) scanning is of great significance for monitoring and management of pulmonary nodules on chest computerized tomography (CT). Nevertheless, the malignant potential of these nodules is often difficult to detect, especially for some smaller pulmonary nodules on LDCT images. Recent advances using the state-of-art computer-aided detection (CAD) system have attempted to address this problem by identifying small nodules that can be easily missed during clinical practice. CAD is used in two reading modes: Concurrentreader (CR) mode or second-reader (SR) mode. In this study, we prospectively evaluated the efficiency of a CAD system's SR and CR modes in detecting pulmonary nodules on LDCT. We found that the SR mode improves pulmonary nodule detection regardless of the dose and experience level, especially for interns in the low-dose setting. The CR mode maintains the sensitivity of SR mode while significantly decreasing reading times.

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    [in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese]. Comparison of two reader modes of computer-aided diagnosis in lung nodules on low-dose chest CT scan[J]. Journal of Innovative Optical Health Sciences, 2022, 15(2): 2250013

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    Paper Information

    Received: Sep. 9, 2021

    Accepted: Nov. 29, 2021

    Published Online: Feb. 28, 2022

    The Author Email: (xialiming2017@outlook.com)

    DOI:10.1142/s1793545822500134

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