Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China.
Peter Boris Centre for Addiction Research, McMaster University & St. Joseph's Health Care Hamilton, 100 West 5th Street, Hamilton, ON, L8P 3R2, Canada.
BMC Med Imaging. 2023 Apr 13;23(1):55. doi: 10.1186/s12880-023-01012-7.
To evaluate the value of a deep learning-based computer-aided diagnostic system (DL-CAD) in improving the diagnostic performance of acute rib fractures in patients with chest trauma.
CT images of 214 patients with acute blunt chest trauma were retrospectively analyzed by two interns and two attending radiologists independently firstly and then with the assistance of a DL-CAD one month later, in a blinded and randomized manner. The consensusdiagnosis of fib fracture by another two senior thoracic radiologists was regarded as reference standard. The rib fracture diagnostic sensitivity, specificity, positive predictive value, diagnostic confidence and mean reading time with and without DL-CAD were calculated and compared.
There were 680 rib fracture lesions confirmed as reference standard among all patients. The diagnostic sensitivity and positive predictive value of interns weresignificantly improved from (68.82%, 84.50%) to (91.76%, 93.17%) with the assistance of DL-CAD, respectively. Diagnostic sensitivity and positive predictive value of attendings aided by DL-CAD (94.56%, 95.67%) or not aided (86.47%, 93.83%), respectively. In addition, when radiologists were assisted by DL-CAD, the mean reading time was significantly reduced, and diagnostic confidence was significantly enhanced.
DL-CAD improves the diagnostic performance of acute rib fracture in chest trauma patients, which increases the diagnostic confidence, sensitivity, and positive predictive value for radiologists. DL-CAD can advance the diagnostic consistency of radiologists with different experiences.
评估基于深度学习的计算机辅助诊断系统（DL-CAD）在提高胸部创伤患者急性肋骨骨折诊断性能中的价值。
回顾性分析了 214 例急性钝性胸部创伤患者的 CT 图像，两名住院医师和两名主治放射科医师首先独立进行分析，一个月后在盲法和随机的情况下借助 DL-CAD 进行分析。由另外两名资深胸部放射科医师的共识诊断为肋骨骨折的参考标准。计算并比较了有和没有 DL-CAD 时的肋骨骨折诊断灵敏度、特异性、阳性预测值、诊断信心和平均阅读时间。
所有患者中共有 680 处肋骨骨折病变被确认为参考标准。在 DL-CAD 的辅助下，住院医师的诊断灵敏度和阳性预测值分别从（68.82%，84.50%）显著提高到（91.76%，93.17%）。主治医生在使用或不使用 DL-CAD 的情况下（94.56%，95.67%），诊断灵敏度和阳性预测值分别为（86.47%，93.83%）。此外，当放射科医师使用 DL-CAD 辅助诊断时，平均阅读时间显著减少，诊断信心显著增强。
DL-CAD 提高了胸部创伤患者急性肋骨骨折的诊断性能，增加了放射科医师的诊断信心、灵敏度和阳性预测值。DL-CAD 可以提高不同经验水平的放射科医师的诊断一致性。
