Effect of AI-CAD assisting doctors with different seniority in CT image interpretation to predict the enlargement of hematoma in early stage of cerebral hemorrhage
Author:
Affiliation:

1.Department of Neurosurgery, Central Hospital of Dalian University of Technology, Dalian, Liaoning 116033, China;2.Department of Epidemiology, Dalian Medical University, Dalian, Liaoning 116044, China)

Clc Number:

R743;R5

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    Abstract:

    Aim To investigate the effect of artificial intelligence (AI) assisting doctors with different seniority in predicting the enlargement of hematoma in the early stage of cerebral hemorrhage. Methods A total of 108 patients diagnosed with cerebral hemorrhage in Central Hospital Affiliated to Dalian University of Technology were retrospectively collected. CT images at admission and 24 hours after admission were collected. DICOM images obtained from plain CT scan were input into AI-CAD model developed by Biomind in collaboration with Temple of Heaven. A total of 9 doctors of different senior-level were selected in neurosurgery department of our hospital. Firstly, independent prediction was applied in the patients and then the study predicted whether patients would delelop hematoma enlargement within 24 hours combined with the results of auxiliary AI. The accuracy of independent prediction of doctors with different seniority and assisted AI prediction of aneurysm stability was calculated respectively. McNemar of paired samples was used to test the significance of difference between independent prediction coincidence rate and assisted AI prediction accuracy among different doctors. Results The accuracy of high, middle and low seniority doctors independently predicting the early expansion of cerebral hemorrhage was 58.95%, 50.62% and 38.89%, respectively, and the accuracy of prediction was significantly improved after assisted AI (P<0.001), the highest increase rate was low seniority doctors (25.92%), followed by middle seniority doctors (19.75%) and high seniority doctors (11.73%). The ability of senior physicians to independently predict the expansion of intracerebral hemorrhage was strongest in patients and non-patients, with sensitivity of 18.75% (95%CI:9.44%~33.10%) and specificity of 65.94% (95%CI:59.98%~71.45%). The sensitivity of middle seniority doctors was 16.67% (95%CI:7.97%~30.76%), the specificity was 56.52% (95%CI:50.44%~62.42%), and the sensitivity of low seniority doctors was 8.33% (95%CI:2.70%~20.87%), the specificity was 44.20% (95%CI:38.29%~50.28%). However, after AI assisted the prediction of senior doctors, the sensitivity and specificity of each seniority group of doctors increased. The sensitivity of high seniority doctors was 60.42% (95%CI:45.29%~73.88%), the specificity was 72.46% (95%CI:66.72%~77.57%), the sensitivity of middle seniority doctors was 64.58% (95%CI:49.40%~77.45%), the specificity was 71.38% (95%CI:65.59%~76.56%), and the sensitivity of low seniority doctors was 68.75% (95%CI:53.60%~80.91%), the specificity was 64.13% (95%CI:58.13%~69.73%). Conclusion AI-CAD assisted doctors with high, middle and low seniority can improve the accuracy of predicting the enlargement of hematoma in early stage of cerebral hemorrhage, especially the ability of doctors with low seniority to find patients can be significantly improved, which can make up for the lack of work experience of doctors with low seniority to a certain extent.

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WEI Wei, FAN Wenjing, CHEN Xin, ZHANG Zheming, LI Guoliang, CHEN Dong. Effect of AI-CAD assisting doctors with different seniority in CT image interpretation to predict the enlargement of hematoma in early stage of cerebral hemorrhage[J]. Editorial Office of Chinese Journal of Arteriosclerosis,2024,32(5):429-436.

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History
  • Received:January 05,2024
  • Revised:March 13,2024
  • Online: May 09,2024
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