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Volume 47 Issue 3
Mar.  2024
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Article Navigation >  Journal of Molecular Imaging  > 2024  >  47(3): 315-320
LI Ling, ZHENG Shuangshuang, LIU Li. Application value of artificial intelligence in the diagnosis of fresh rib fractures by physicians[J]. Journal of Molecular Imaging, 2024, 47(3): 315-320. doi: 10.12122/j.issn.1674-4500.2024.03.15
Citation: LI Ling, ZHENG Shuangshuang, LIU Li. Application value of artificial intelligence in the diagnosis of fresh rib fractures by physicians[J]. Journal of Molecular Imaging, 2024, 47(3): 315-320. doi: 10.12122/j.issn.1674-4500.2024.03.15
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Application value of artificial intelligence in the diagnosis of fresh rib fractures by physicians

doi: 10.12122/j.issn.1674-4500.2024.03.15

  • Department of Radiology, the Affiliated Fuxing Hospital of Capital Medical University, Beijing 100038, China

  • Received Date: 2023-12-26
    Available Online: 2024-04-17
  • Publish Date: 2024-03-20
    Abstract
  •   Objective  To investigate the difference of detection rate of fresh rib fracture lesions between radiology residents and attending physicians by artificial intelligence (AI) software and the consistency evaluation before and after application of AI, and to evaluate the improvement of efficiency of doctors at all levels in diagnosing fresh rib fractures after applying AI.  Methods  A total of 300 patients with acute chest trauma underwent chest CT scan, 152 of which were confirmed to be rib fracture. 6 physicians were divided into resident physician group and attending physician group, with three physicians in each. 300 randomly assigned CT images were reviewed independently. After the washout interval of 4 weeks, the physicians combined with AI read the film for second time. Chi-square test was used to compare the difference in the detection rate of fresh rib fracture lesions and different types of lesions between the two groups, and to evaluate the difference in consistency, sensitivity and specificity before and after the application of AI in each group.  Results  After applying AI, the detection rate of all fresh rib fractures, complete fractures and incomplete fractures by residents and attending physicians was higher than that by physicians alone, and the difference was statistically significant (P<0.001). The Kappa values and Phi coefficients of all rib fractures and incomplete fractures were significantly improved by residents + AI and attending physicians + AI, and the improvement of incomplete fractures was the most significant. The sensitivity of fresh rib fractures detected by residents+AI, attending physicians+AI were significantly different from that by residents and attending physicians alone (P<0.001), there was no significant difference in specificity.  Conclusion  AI can effectively improve the detection efficiency of fresh rib fractures among physicians of different levels, and improve the consistency and sensitivity among physicians of different levels.

     

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