商业冠状动脉计算机断层血管学人工智能冠状动脉狭窄症的验证:一个横截面研究
Qi Han1, Feihua Jing2, Zhiguo Sun3
1Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Quantitative imaging in medicine and surgery
|June 7, 2023
概括
与放射科医生相比,商业冠状动脉计算机断层扫描血管造影人工智能 (CCTA-AI) 平台显示冠状动脉狭窄的诊断性能有所改善. 这种人工智能解决方案提供了更快的处理和可比或稍微更好的准确性,有助于临床决策.
科学领域:
- 心血管成像 - 心血管成像
- 人工智能在医学中的应用
- 放射学 放射学是一门学科.
背景情况:
- 商业冠状动脉计算机断层扫描血管学人工智能 (CCTA-AI) 平台正在临床使用中取得进展.
- 需要进一步的研究,以了解当前商业人工智能平台的功能和放射科医生的作用.
- 这项研究旨在将商业CCTA-AI平台的诊断性能与放射科医生阅读器进行比较.
研究的目的:
- 评估和比较商业CCTA-AI平台对冠状动脉狭窄的诊断性能与人类读者.
- 在多中心,多设备环境中评估CCTA-AI的效率和准确性.
主要方法:
- 一组318名疑似冠状动脉疾病 (CAD) 的患者使用CCTA和侵入性冠状动脉血管学 (ICA) 作为黄金标准进行了分析.
- CCTA-AI平台自动评估冠状动脉狭窄,而放射科医生则进行手动CCTA读数.
- 诊断性能在患者和细分水平上使用接收器操作特征 (ROC) 分析来评估,狭窄的截止值为50%和70%.
主要成果:
- 与放射科医生 (1,112.1s) 相比,CCTA-AI显著减少了每个患者的后处理时间 (20.4s).
- 在基于患者的分析中,CCTA-AI的曲线下面面积 (AUC) 比读取值更高 (模型1:0.85与0.61;模型2:0.78与0.64).
- 基于细分的分析显示CCTA-AI的AUC略高,在较高的狭窄值下改善了负预测值 (NPV),在较大的动脉中表现更好.
结论:
- 商业CCTA-AI平台为诊断冠状动脉狭窄提供了可行和高效的解决方案.
- CCTA-AI的诊断性能与经验丰富的放射科医生相美,甚至略高于他们.
- CCTA-AI显示出有助于CAD临床诊断和决策的潜力.
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