Application value of deep learning-based computer-aided diagnosis system in diagnosing rib fractures
ZHANG Bin1, CHENG Yue1, DU Jingbo1, CHEN Tianjin2, LIAO Jianyong1
1. Department of Radiology, Daxing Teaching Hospital of Capital Medical University, Beijing 102600, China; 2. Department of Radiology, Beijing Municipal Corps Hospital of Chinese People's Armed Police Force, Beijing 100027, China
AbstractObjective To explore the application value of deep learning-based computer-aided diagnosis system(DL-CAD) in assisting radiologists to diagnose rib fractures.Methods A total of 330 patients with 7920 ribs who underwent chest CT examination due to acute chest trauma in Daxing Teaching Hospital of Capital Medical University from January 2022 to December 2022 were selected. Two rounds of image reading (traditional manual mode and DL-CAD assisted mode) were performed by junior and senior radiologists respectively. The differences in sensitivity, specificity, AUC value, reading time, and diagnostic confidence were statistically analyzed.Results A total of 975 fractures were confirmed, including 450 non-displaced fractures and 525 displaced fractures. There were statistically significant differences in sensitivity, reading time, diagnostic confidence, and AUC value between the two modes (P<0.05), but no statistically significant difference in specificity (P>0.05). There were statistical differences in sensitivity and AUC in the diagnosis of displaced fractures and non-displaced fractures between the two modes of reading (P<0.05), and no statistically different in specificity (P>0.05). The sensitivity and AUC value in the diagnosis of non-displaced fractures were significantly improved in DL-CAD assisted mode (39.33% vs. 76.22%; 0.658 vs. 0.844; 41.67% vs. 77.33%; 0.671 vs. 0.61).Conclusions DL-CAD can help radiologists improve the efficiency of the diagnosis of rib fractures, shorten the reading time, and enhance the diagnostic confidence, which is conducive to the development of clinical work. DL_CAD-assisted diagnosis results in similar diagnostic performance between junior and senior radiologists.
ZHANG Bin,CHENG Yue,DU Jingbo等. Application value of deep learning-based computer-aided diagnosis system in diagnosing rib fractures[J]. Med. J. Chin. Peop. Armed Poli. Forc., 2023, 34(8): 656-659.
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2023, Vol. 34 
