开发和验证计算机断层扫描心肌 perfusion 成像放射模型的主要不良心血管事件的预测:一个多中心研究
Zhiqi Zhong1,2, Dong Li3, Shengliang Liu4
1Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, #85 Wujin Rd, Shanghai, China.
使用CT心肌输液成像 (CT-MPI) 放射性特征的新组合模型显著改善了疑似冠状动脉疾病患者的主要不良心血管事件 (MACE) 的预测.
科学领域:
- 心血管成像 - 心血管成像
- 无线电学 (Radiomics) 是一种无线电学.
- 医疗人工智能 医疗人工智能
背景情况:
- 准确预测主要不良心血管事件 (MACE) 对疑似冠状动脉疾病患者的风险分层至关重要.
- CT心肌 perfusion 成像 (CT-MPI) 提供详细的 perfusion 参数以进行全面的表征.
研究的目的:
- 开发和验证MACE的综合预测模型.
- 该模型整合了临床风险因素,冠状动脉样硬化特征和CT-MPI的放射性特征.
主要方法:
- 追溯招募784名接受冠状动脉CT血管造影 (CCTA) 和CT-MPI的患者.
- 在八个CT-MPI输液参数图上进行了放射性分析.
- 开发了三种模型:仅临床因素,临床因素+心肌血流,临床因素+心肌血流+放射性评分.
主要成果:
- 组合模型 (模型3) 在培训,内部和外部验证集 (C指数高达0.898) 中显示出优异的MACE预测性能.
- 模型3显著优于只有临床因素或临床因素加上心肌血流量的模型 (p < 0.05).
- 外部验证显示,模型3在1,3和5年的MACE预测中 (高达0.890) 实现了高时间依赖的AUC值.
结论:
- 多参数CT-MPI的放射特征捕捉了与MACE相关的宏血管和微血管 perfusion异常.
- 与传统方法相比,开发的组合模型为MACE预测提供了更好的预后性能.
- 该模型保持了高的可解释性,同时改善了MACE风险分层.
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