基于成像的数字双胞胎代患者的参数子集减少左心室机械失调
Tijmen Koopsen1, Nick van Osta2, Tim van Loon2
1Department of Biomedical Engineering, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands. t.koopsen@maastrichtuniversity.nl.
Biomedical engineering online
|May 14, 2024
概括
我们确定了一组可重现的75个参数,用于创建特定患者的心脏数字双胞胎 (DTs). 这项技术有助于表征左心室机械失调,并支持临床决策.
科学领域:
- 心血管生理学心血管生理学
- 计算生物学 计算生物学
- 医疗成像医学成像
背景情况:
- 数字双胞胎 (DTs) 整合患者成像数据,揭示心肌疾病基质导致左心室 (LV) 机械失调.
- 对于DTs,可靠的参数估计需要可识别的模型参数.
- 之前的研究并没有专注于在患有特定疾病的患者中对DTs的参数识别能力,例如左捆支部阻塞 (LBBB) 和心肌梗塞 (MI).
研究的目的:
- 确定可识别和可重复的参数子集,以生成患者特定的心脏DTs.
- 评估这些DT在LBBB和MI患者中表征机械失调的能力.
- 评估DT技术的临床适用性,用于患者特异性基质表征.
主要方法:
- 利用CircAdapt心脏模型与来自心力衰竭患者的非侵入性成像数据,减少喷射率 (HFrEF),LBBB和MI.
- 应用莫里斯查方法 (MSM) 来确定LV体积和应变的关键参数.
- 使用准蒙特卡洛模拟和粒子群优化,基于可识别性 (两声) 和可重现性 (类内相关系数) 的代缩小参数.
主要成果:
- 最初的270个MSM参数产生了高质量的DT,但缺乏可重复性.
- 代降低产生了75个参数的可重现子集,包括心脏输出和区域激活延迟.
- 减少的参数集产生了与患者相似的DTs,揭示了只有LBBB的DTs与只有MI的DTs (p<0.05) 相比,只有LBBB的DTs中较高的隔膜到侧壁工作负载失衡 (p<0.05).
结论:
- 灵敏度和可识别性分析成功确定了在LV机械失调患者中基于成像的心脏DTs的可重现参数子集.
- DT准确地反映了患者特定的心肌工作分布,基于他们潜在的疾病.
- 这种DT技术有助于患者特定的基质表征,并具有临床决策支持的潜力.
关键词:
数字双胞胎 数字双胞胎 数字双胞胎疾病的表征 疾病的表征可识别性的分析分析.左捆的分支区块的分支区块.机械失协调 机械失协调心肌梗塞的心脏病发作肌动脉应变菌株是什么心肌功能的工作.参数估计的参数估计.灵敏度分析是一种灵敏度分析.更多相关视频
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