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Updated: Jun 1, 2026

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Assessing the use of digital radiography and a real-time interactive pulmonary nodule analysis system for large
1The Department of Radiology, Beijing Friendship Hospital-Affiliated Capital Medical University, 95 YongAn Road, XuanWu District, Beijing 100050, China.
Rationale And Objectives:
To assess the use of chest digital radiograph (DR) assisted with a real-time interactive pulmonary nodule analysis system in large population lung cancer screening.
Materials And Methods:
346 DR/CR patient studies with corresponding CT images were selected from 12,500 patients screened for lung cancer from year 2007 to 2009. Two expert chest radiologists established CT-confirmed Gold Standard of nodules on DR/CR images with consensus. These cases were read by eight other chest radiologists (participating radiologists) first without using a real-time interactive pulmonary nodule analysis system and then re-read using the system. Performances of participating radiologists and the computer system were analyzed.
Results:
The computer system achieved similar performance on DR and CR images, with a detection rate of 76% and an average FPs of 2.0 per image. Before and after using the computer-aided detection system, the nodule detection sensitivities of the participating radiologists were 62.3% and 77.3% respectively, and the A(z) values increased from 0.794 to 0.831. Statistical analysis demonstrated statically significant improvement for the participating radiologists after using the computer analysis system with a P-value 0.05.
Conclusion:
The computer system could help radiologists identify more lesions, especially small ones that are more likely to be overlooked on chest DR/CR images, and could help reduce inter-observer diagnostic variations, while its FPs were easy to recognize and dismiss. It is suggested that DR/CR assisted by the real-time interactive pulmonary nodule analysis system may be an effective means to screen large populations for lung cancer.
