使用标准胸部X射线的深度学习来预测患有心室隔膜缺陷的儿童的肺动脉高压:一种新的方法
Zhixin Li1, Gang Luo1, Zhixian Ji1
1Heart Center, Women and Children's Hospital, Qingdao University, Qingdao, China.
Frontiers in cardiovascular medicine
|January 29, 2024
概括
应用于胸部X射线的人工智能 (AI) 可以预测心室隔膜缺陷 (VSD) 的儿童肺动脉高血压 (PAH) 风险. 这种人工智能工具对在VSD患者中早期检测和及时治疗PAH充满希望.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 在先天性心脏病 (CHD) 中肺动脉高血压 (PAH) 风险评估对于早期干预至关重要.
- 心室隔膜缺陷 (VSD) 是一种常见的冠心病形式,其中可以发展PAH.
- 在VSD患者中及时识别PAH风险对于有效管理至关重要.
研究的目的:
- 调查人工智能 (AI) 在预测肺动脉高血压 (PAH) 风险的潜力,在使用胸部X射线 (CXRs) 的腹腔隔膜缺陷 (VSD) 的患者.
- 开发和验证人工智能算法,用于在VSD患者中PAH早期风险分层.
主要方法:
- 一项回顾性研究包括831名VSD患者 (161名PAH-VSD患者,670名没有).
- 一个残留神经网络 (ResNet) 模型被训练在胸部放射图上,以根据他们患有PAH的风险对VSD患者进行分类.
- 该研究的终点是VSD儿童在手术前或手术后发生的PAH.
主要成果:
- 人工智能算法在验证集中表现出强的性能,曲线下的面积 (AUC) 为0.82.
- 在一个独立的测试组中,人工智能算法的AUC为0.81,显著超过人类观察者 (AUC为0.65).
- 类激活映射 (CAM) 揭示了人工智能模型专注于肺动脉段的预测.
结论:
- 应用于胸部X射线的人工智能可以有效地识别患有肺动脉高血压风险的VSD患者.
- 基于人工智能的CXR分析为VSD患者早期PAH风险评估提供了一个有希望的非侵入性工具.
- 这些初步发现支持使用人工智能来改善VSD中PAH的早期检测和管理策略.
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