基于深度学习的实时图像指导和自动左心室测量,以减少测试-重新测试可变性
Håkon Pettersen1,2, Sigbjorn Sabo1,3, David Pasdeloup1
1Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Trøndelag, Norway.
Open heart
|December 8, 2025
概括
人工智能 (AI) 辅助回声心脏学,结合基于深度学习 (DL) 的实时指导和自动测量,显著减少左心室 (LV) 测量的变化. 对于经验丰富的操作员来说,自动测量比实时指导更有益.
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:
- 心声图对于评估左心室 (LV) 功能至关重要.
- 手动测量的变化可能会影响诊断的准确性.
- 深度学习 (DL) 提供了改善心声回声分析的潜力.
研究的目的:
- 评估结合基于实时DL的指导和自动测量的对LV体积和应变分析的影响.
- 为了比较使用人工智能辅助心声谱与标准心声谱的LV测量的变化.
主要方法:
- 47名患有心脏病理的患者接受了两个超声波医生和一名参考心脏病学家的心声回声扫描.
- 每位患者的超声波仪使用一个实时DL指导工具来防止LV预先缩短.
- 人工智能辅助心电回声学 (自动化DL测量) 与标准心电回声学 (手动测量) 相比.
主要成果:
- 与标准心声相比,人工智能辅助心声学显示LV终端-透气体 (EDV),终端-静脉体 (ESV) 和全球纵向应变 (GLS) 的变化系数明显较低.
- 两种方法的LV射出分数 (EF) 的变化系数在两种方法之间是相似的.
- 探索性分析表明,自动测量,而不是指导工具,是导致变化的原因.
结论:
- 人工智能辅助回声心脏学,整合DL引导和自动测量,大大降低了LV EDV,ESV和GLS的变化.
- 对于经验丰富的操作人员来说,自动测量比对心声回声图的实时指导更有好处.
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