目的 探讨CT不同重建算法图像对人工智能(AI)辅助肋骨骨折检测效能的影响及AI辅助诊断系统对放射科住院医师诊断急诊外伤肋骨骨折诊断效能的影响.方法 收集急诊胸部外伤病史的患者 50 例,所有患者均利用256 层螺旋CT进行胸部CT成像,使用Standard、Lung、Bone和Soft 4 种不同kernel重建算法进行图像重建,计算并比较 AI 在不同重建算法胸部 CT 图像下对肋骨骨折识别灵敏度、特异度及准确度的差异.结果 AI在Standard、Lung、Bone 和 Soft 4 种算法下对骨折检出的灵敏度分别为 75.74%、86.63%、89.60%和69.31%,Lung 和 Bone 算法下AI对肋骨骨折检出的灵敏度高于Standard和Soft(P<0.05).AI在Standard、Lung、Bone和Soft 4 种算法下对骨折检出的特异度分别为93.88%、93.17%、93.78%和94.18%,4 种算法比较差异无统计学意义(P>0.05).AI在4 种算法下的准确度分别为90.82%、92.07%,93.07%和89.98%,4 种算法比较差异有统计学意义(P<0.05).放射科住院医师不使用AI和使用AI诊断肋骨骨折的灵敏度分别为82.18%、96.53%,特异度分别为95.08%、94.78%,准确度分别为92.90%、95.08%,使用AI后对肋骨骨折诊断的灵敏度及准确度均明显提高(P<0.05),而特异度比较差异无统计学意义(P>0.05).放射科住院医师不使用AI诊断所用的时间为(240.79±63.20)s,使用 AI 所用的时间为(105.26±57.20)s,两个时间比较差异有统计学意义(P<0.05).结论 放射科住院医师利用AI能够明显缩短急诊外伤肋骨骨折诊断所用时间,提高工作效率,而且能够提高其对于急诊外伤肋骨骨折诊断的准确性.AI在帮助放射科住院医师更准确、更快速识别肋骨骨折中具有重要的价值.
Performance evaluation of artificial intelligence(AI)detection system in the diagnosis of emergency traumatic rib fractures
Objective To evaluate the impact of different CT reconstruction algorithms on the efficiency of artificial intelligence(AI)detection system for rib fracture diagnosis and to explore the impact of AI assisted diagnostic systems on the diagnostic efficiency of radiology resident physicians in diagnosing emergency traumatic rib fractures.Methods A total of 50 patients with emergent chest trau-ma underwent chest CT examination(Revolution CT,GE Healthcare)were retrospectively collected.All patients were reconstructed with Standard/Lung/Bone/Soft algorithms.The sensitivity,specificity and accuracy of rib fracture detection under different reconstruction algo-rithms by AI were compared.Results The sensitivities of AI for rib fractures detection under the four algorithms of Standard,Lung,Bone and Soft were 75.74%,86.63%,89.60%and 69.31%,respectively.The sensitivity of AI for rib fractures detection under the Lung and Bone algorithms was higher than that of Standard and Soft(P<0.05).The specificities of AI for rib fractures detection under Standard,Lung,Bone and Soft algorithms were 93.88%、93.17%、93.78%and 94.18%,respectively,with no statistical significance(P>0.05).The accuracies of the four algorithms were 90.82%、92.07%、93.07%and 89.98%,respectively,and the difference was statistically significant(P<0.05).The sensitivities of residents in the diagnosis of rib fracture without AI and with AI were 82.18%and 96.53%,the specificities were 95.08%and 94.78%,and the accuracies were 92.90%and 95.08%,respectively.The sensitivity and accuracy of doctors in the diagnosis of rib fracture were significantly improved after using AI(P<0.05).There was no significant differ-ence in specificity(P>0.05).The reading time using AI(105.26±57.20 s)was greatly reduced compared with that without using AI(240.79±63.20)s(P<0.05).Conclusion The AI-assisted diagnostic system significantly improved rib fracture detection sensitiv-ity and reduced diagnostic time.AI technology is of great value in assisting residents physicians to identify rib fractures more accurately and quickly in emergency department.
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