人工智能的诊断性能用于儿童肺结节检测胸部计算机断层扫描:模拟较低辐射剂量的比较
Rida Salman1, HaiThuy N Nguyen2, Andrew C Sher1
1Edward B. Singleton Department of Radiology, Division of Body Imaging, Texas Children's Hospital and Baylor College of Medicine, 6701 Fannin St. Suite 470, Houston, TX, 77030, USA.
European journal of pediatrics
|September 12, 2023
概括
儿童肺结节的计算机辅助检测 (CAD) 显示出低灵敏度,即使在减少的辐射剂量. 然而,降低辐射剂量并没有显著影响CAD的性能,这表明在儿科CT扫描中有可能减少剂量.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 儿科成像学 儿科成像学
背景情况:
- 计算机辅助检测 (CAD) 证明了成人肺结节的高诊断性能.
- 使用各种成像技术,以尽量减少儿科患者的辐射暴露.
研究的目的:
- 评估商用计算机辅助检测 (CAD) 系统对儿科患者肺结节的诊断性能.
- 评估模拟较低辐射剂对该群体CAD表现的影响.
主要方法:
- 对30名小儿病患者 (12-18岁) 的回顾性分析,这些患者接受了胸部CT.
- 模拟较低的辐射剂量 (75%,50%,25%) 从标准剂量CT重建.
- 两名儿科放射科医生建立了一个参考标准;另外两名儿科放射科医生将不同剂量的CAD结果与参考结果进行了比较.
主要成果:
- 在参考标准中,共发现了109个结节.
- 肺部CAD分别在100%,75%,50%和25%的剂量下检测到60,62,58和62个结节.
- 灵敏度在剂量范围内从24%到27%不等,积极预测值从43%到52%. 在降低剂量 (p > 0.7) 时,在CAD性能上没有观察到统计学上显著的差异.
结论:
- 计算机辅助检测 (CAD) 在所有模拟剂量级别的儿科患者中检测肺结节的灵敏度较低.
- 从标准水平降低辐射剂量并没有显著地影响评估的肺 CAD 系统在这个儿科队列中的性能.
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