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

IF 2.1 4区医学 Japanese Journal of Radiology Pub Date : 2025-07-01 Epub Date: 2025-03-05 DOI:10.1007/s11604-025-01754-0

Anthony Jaillat, Catherine Cyteval, Marie-Pierre Baron Sarrabere, Hamza Ghomrani, Yoav Maman, Yann Thouvenin, Maxime Pastor

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Abstract

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.

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人工智能在骨盆和髋部骨折检测中的附加价值。

目的：评估人工智能（AI）在放射科医师和急诊医师骨盆骨折影像学检测中的附加价值。材料与方法：在这项回顾性研究中，一名初级放射科医生回顾了2020年3月至2021年6月期间因怀疑骨盆骨折而入院的急诊患者的940张x光片。放射科医生单独分析x光片，然后使用人工智能系统（BoneView）。在100个随机抽样的检查中，与其他五名读者（三名放射科医生和两名具有3-30年经验的急诊医生）一起重复了同样的程序。参考诊断是基于患者在急诊入院后几个月内的全套医学影像学检查和医疗记录。结果：940例患者共确诊633例骨盆骨折（髋部64.8%，骨盆环35.2%），100例患者共确诊68例骨盆骨折（髋部60%，骨盆环40%）。在整个数据集中，初级放射科医生在人工智能辅助下获得了显着的灵敏度提高(Se-PELVIC = 77.25%至83.73%；p -HIP 93.24 ~ 96.49%；p -骨盆环54.60% ~ 64.50%；p -骨盆= 95.24% ~ 93.25%；p = 0.005, Spe-HIP = 98.30% ~ 96.90%；p = 0.005)。在100例患者样本中，两位急诊医生在整个骨盆区域的骨折检测灵敏度提高了+ 14.70% （p = 0.0011）和+ 10.29% (p)。结论：人工智能提高了急诊医生和放射科医生在骨盆骨折筛查方面经验有限的诊断性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Japanese Journal of Radiology Medicine-Radiology, Nuclear Medicine and Imaging

自引率

4.80%

发文量

133

期刊介绍： Japanese Journal of Radiology is a peer-reviewed journal, officially published by the Japan Radiological Society. The main purpose of the journal is to provide a forum for the publication of papers documenting recent advances and new developments in the field of radiology in medicine and biology. The scope of Japanese Journal of Radiology encompasses but is not restricted to diagnostic radiology, interventional radiology, radiation oncology, nuclear medicine, radiation physics, and radiation biology. Additionally, the journal covers technical and industrial innovations. The journal welcomes original articles, technical notes, review articles, pictorial essays and letters to the editor. The journal also provides announcements from the boards and the committees of the society. Membership in the Japan Radiological Society is not a prerequisite for submission. Contributions are welcomed from all parts of the world.