纤维性导电性的不确定性量化对非典型左前庭的计算模型衍生废除的纤维导电效应
Jake A Bergquist1,2,3, Ben A Orkild1,2,3, Eric Paccione1,2,3
1Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
Computing in cardiology
|October 6, 2025
概括
计算模型有助于心律失常治疗,但面临着输入不确定性. 在非典型的左心房 (ALAF) 引导切除模型中的不确定性量化,缩小电路并考虑纤维组织变异性.
科学领域:
- 计算心脏病学计算心脏病学
- 生物医学工程 生物医学工程
- 医学物理 医学物理
背景情况:
- 心脏计算模型对于治疗复杂的心律失常,如非典型的左心房 (ALAF),至关重要.
- 这些模型中的输入不确定性可以显著影响治疗策略的有效性.
- 参数变异性,特别是纤维组织导电性的对切除计划的影响需要进行彻底的研究.
研究的目的:
- 开发和应用一个计算模型引导的废弃计划工具,用于ALAF.
- 通过参数不确定性量化 (UQ) 来评估纤维组织导电性不确定性对切除模式的影响.
- 展示一种方法来呈现包含参数不确定性的剥离策略.
主要方法:
- 为ALAF开发一个以计算模型为指导的废弃计划工具.
- 应用参数不确定性量化 (UQ) 来评估模型输出对纤维组织导电性的敏感性.
- 对特定患者的ALAF模型进行模拟,以测试切除计划工具和UQ.
主要成果:
- 模型引导的除工具成功地将模拟的ALAF电路从10个减少到4个.
- 不确定性量化显示,纤维质导电性对建议的切除部位有很大的影响.
- UQ提供了一种可视化除策略的方法,同时考虑到输入参数的不确定性.
结论:
- 不确定性量化 (UQ) 提供了对参数可变性对心律失常模型影响的关键见解.
- 这种UQ方法提供了一种可靠的方法,用于探索复发性心律失常的预测不确定性.
- 该研究强调了UQ在为临床应用提供可靠,不确定性意识的建模结果方面的实用性.
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