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Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Clinical application of a novel computer-aided detection system based on three-dimensional CT images on pulmonary
Jian-Ye Zeng1, Hai-Hong Ye2, Shi-Xiong Yang1
1Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Guangxi Medical University Nanning 530031, China.
Abstract:
The aim of this study was to investigate the clinical application effects of a novel computer-aided detection (CAD) system based on three-dimensional computed tomography (CT) images on pulmonary nodule. 98 cases with pulmonary nodule (PN) in our hospital from Jun, 2009 to Jun, 2013 were analysed in this study. All cases underwent PN detection both by the simple spiral CT scan and by the computer-aided system based on 3D CT images, respectively. Postoperative pathological results were considered as the "gold standard", for both two checking methods, the diagnostic accuracies for determining benign and malignant PN were calculated. Under simple spiral CT scan method, 63 cases is malignant, including 50 true positive cases and 13 false positive cases from the "gold standard"; 35 cases is benign, 16 true negative case and 19 false negative cases, the Sensitivity 1 (Se1)=0.725, Specificity1 (Sp1)=0.448, Agreement rate1 (Kappa 1)=0.673, J1 (Youden's index 1)=0.173, LR(+)1=1.616, LR(-)1=0.499. Kappa 1=0.673 between the 0.4 and 0.75, has a moderate consistency. Underwent computer-aided detection (CAD) based on 3D CT method, 67cases is malignant, including 62 true positive cases and 7 false positive cases; 31 cases is benign, 24 true negative case and 7 false negative cases, Sensitivity 2 (Se2)=0.899, Specificity2 (Sp2)=0.828, Agreement rate (Kappa 2)=0.877, J2 (Youden's index 2)=0.727, LR(+)2=5.212, LR(-)2=0.123. Kappa 2=0.877 >0.75, has a good consistency. Computer-aided PN detecting system based on 3D CT images has better clinical application value, and can help doctor carry out early diagnosis of lung disease (such as cancer, etc.) through CT images.
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