Added value of artificial intelligence for the detection of pelvic and hip fractures

被引:0
作者
Jaillat, Anthony [1 ]
Cyteval, Catherine [1 ]
Sarrabere, Marie-Pierre Baron [1 ]
Ghomrani, Hamza [2 ]
Maman, Yoav [2 ]
Thouvenin, Yann [1 ]
Pastor, Maxime [1 ]
机构
[1] Montpellier Univ Hosp, Dept Med Imaging, Osteoarticular Med Imaging Sect, Montpellier, France
[2] Lapeyronie Univ Hosp, Emergency Dept, Montpellier, France
关键词
Artificial intelligence; Hip fracture; Femoral fracture; Bones; Radiography;
D O I
10.1007/s11604-025-01754-0
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose To assess the added value of artificial intelligence (AI) for radiologists and emergency physicians in the radiographic detection of pelvic fractures. Materials & methods In this retrospective study, one junior radiologist reviewed 940 X-rays of patients admitted to emergency for a fall with suspicion of pelvic fracture between March 2020 and June 2021. The radiologist analyzed the X-rays alone and then using an AI system (BoneView). In a random sample of 100 exams, the same procedure was repeated alongside five other readers (three radiologists and two emergency physicians with 3-30 years of experience). The reference diagnosis was based on the patient's full set of medical imaging exams and medical records in the months following emergency admission. Results A total of 633 confirmed pelvic fractures (64.8% from hip and 35.2% from pelvic ring) in 940 patients and 68 pelvic fractures (60% from hip and 40% from pelvic ring) in the 100-patient sample were included. In the whole dataset, the junior radiologist achieved a significant sensitivity improvement with AI assistance (Se-PELVIC = 77.25% to 83.73%; p < 0.001, Se-HIP 93.24 to 96.49%; p < 0.001 and Se-PELVIC RING 54.60% to 64.50%; p < 0.001). However, there was a significant decrease in specificity with AI assistance (Spe(-PELVIC) = 95.24% to 93.25%; p = 0.005 and Spe(-HIP) = 98.30% to 96.90%; p = 0.005). In the 100-patient sample, the two emergency physicians obtained an improvement in fracture detection sensitivity across the pelvic area + 14.70% (p = 0.0011) and + 10.29% (p < 0.007) respectively without a significant decrease in specificity. For hip fractures, E1's sensitivity increased from 59.46% to 70.27% (p = 0.04), and E2's sensitivity increased from 78.38% to 86.49% (p = 0.08). For pelvic ring fractures, E1's sensitivity increased from 12.90% to 32.26% (p = 0.012), and E2's sensitivity increased from 19.35% to 32.26% (p = 0.043). Conclusion AI improved the diagnostic performance for emergency physicians and radiologists with limited experience in pelvic fracture screening.
引用
收藏
页码:1166 / 1175
页数:10
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