Application of artificial intelligence in CT diagnosis of thoracic fracture

LIU Yu-meng; WU Ruo-dai; LU Chao; LYU Yun-gang; YE Hai; CHEN Liang; ZHOU Min-min; LI Guang-yao; WU Song-xiong; WU Guang-yao

doi:10.13820/j.cnki.gdyx.20225230

Abstract：Objective To investigate the diagnostic performance and application value of an artificial intelligence(AI)bone disease diagnosis system in the diagnosis of thoracic fractures.Methods A retrospective analysis was per-formed on 726 cases of thoracic fractures confirmed by chest CT re-examination 3-6 weeks after trauma emergency ad-mission at Shenzhen University General Hospital.The recall rate,precision rate,and F1 score of AI,two radiologists,and the radiologists assisted by AI in diagnosing thoracic fractures were calculated.Results The recall rate and F1 score of AI in detecting rib fractures were 0.91 and 0.92,respectively,both higher than those of Radiologist 1(0.77,0.85)and Radiologist 2(0.84,0.90).The precision rate of AI(0.92)was lower than that of Radiologist 1(0.95)and Radi-ologist 2(0.96).With AI assistance,the recall rate,precision rate,and F1 score of Radiologist 1 and Radiologist 2 in detecting rib fractures were 0.94,0.95,0.94 and 0.97,0.98,0.97,respectively.For detecting other thoracic frac-tures,the recall rate and F1 score of AI(0.90,0.90)were higher than those of Radiologist 1(0.62,0.74)and Radiol-ogist 2(0.73,0.81).With AI assistance,the recall rate,precision rate,and F1 score of Radiologist 1 and Radiologist 2 in detecting other thoracic fractures were 0.94,0.95,0.94 and 0.97,0.97,0.97,respectively.Conclusion AI can efficiently and sensitively detect thoracic fractures in chest CT scans of emergency trauma patients,potentially optimizing the diagnosis and treatment process for emergency trauma patients.