• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

从人类电解剖图估算个性化最小浦肯野系统。

Estimation of Personalized Minimal Purkinje Systems From Human Electro-Anatomical Maps.

出版信息

IEEE Trans Med Imaging. 2021 Aug;40(8):2182-2194. doi: 10.1109/TMI.2021.3073499. Epub 2021 Jul 30.

DOI:10.1109/TMI.2021.3073499
PMID:33856987
Abstract

The Purkinje system is a heart structure responsible for transmitting electrical impulses through the ventricles in a fast and coordinated way to trigger mechanical contraction. Estimating a patient-specific compatible Purkinje Network from an electro-anatomical map is a challenging task, that could help to improve models for electrophysiology simulations or provide aid in therapy planning, such as radiofrequency ablation. In this study, we present a methodology to inversely estimate a Purkinje network from a patient's electro-anatomical map. First, we carry out a simulation study to assess the accuracy of the method for different synthetic Purkinje network morphologies and myocardial junction densities. Second, we estimate the Purkinje network from a set of 28 electro-anatomical maps from patients, obtaining an optimal conduction velocity in the Purkinje network of 1.95 ± 0.25 m/s, together with the location of their Purkinje-myocardial junctions, and Purkinje network structure. Our results showed an average local activation time error of 6.8±2.2 ms in the endocardium. Finally, using the personalized Purkinje network, we obtained correlations higher than 0.85 between simulated and clinical 12-lead ECGs.

摘要

浦肯野系统是一种心脏结构,负责通过心室以快速协调的方式传输电脉冲,以引发机械收缩。从电解剖图估计特定于患者的兼容浦肯野网络是一项具有挑战性的任务,它可以帮助改进电生理模拟模型或为治疗计划提供帮助,例如射频消融。在这项研究中,我们提出了一种从患者的电解剖图反演估计浦肯野网络的方法。首先,我们进行了一项模拟研究,以评估该方法对于不同的合成浦肯野网络形态和心肌连接密度的准确性。其次,我们从 28 名患者的一组电解剖图中估计了浦肯野网络,得到浦肯野网络中的最佳传导速度为 1.95±0.25m/s,以及浦肯野-心肌连接的位置和浦肯野网络结构。我们的结果显示,心内膜的平均局部激活时间误差为 6.8±2.2ms。最后,使用个性化的浦肯野网络,我们在模拟和临床 12 导联 ECG 之间获得了高于 0.85 的相关性。

相似文献

1
Estimation of Personalized Minimal Purkinje Systems From Human Electro-Anatomical Maps.从人类电解剖图估算个性化最小浦肯野系统。
IEEE Trans Med Imaging. 2021 Aug;40(8):2182-2194. doi: 10.1109/TMI.2021.3073499. Epub 2021 Jul 30.
2
Automatic estimation of Purkinje-Myocardial junction hot-spots from noisy endocardial samples: A simulation study.从有噪声的心内膜样本中自动估计浦肯野-心肌连接热点:一项模拟研究。
Int J Numer Method Biomed Eng. 2018 Jul;34(7):e2988. doi: 10.1002/cnm.2988. Epub 2018 May 4.
3
Estimation of Purkinje trees from electro-anatomical mapping of the left ventricle using minimal cost geodesics.利用最小代价测地线对左心室的电解剖标测进行浦肯野树估计。
Med Image Anal. 2015 Aug;24(1):52-62. doi: 10.1016/j.media.2015.05.007. Epub 2015 May 21.
4
Digital twinning of the human ventricular activation sequence to Clinical 12-lead ECGs and magnetic resonance imaging using realistic Purkinje networks for in silico clinical trials.利用逼真的浦肯野网络将人心室激活序列进行数字孪生,以匹配临床12导联心电图和磁共振成像,用于计算机模拟临床试验。
Med Image Anal. 2024 May;94:103108. doi: 10.1016/j.media.2024.103108. Epub 2024 Feb 28.
5
Generating Purkinje networks in the human heart.在人类心脏中生成浦肯野网络。
J Biomech. 2016 Aug 16;49(12):2455-65. doi: 10.1016/j.jbiomech.2015.12.025. Epub 2015 Dec 22.
6
Purkinje-muscle reentry as a mechanism of polymorphic ventricular arrhythmias in a 3-dimensional model of the ventricles.浦肯野纤维-心肌折返作为心室三维模型中多形性室性心律失常的一种机制。
Circ Res. 1998 Jun 1;82(10):1063-77. doi: 10.1161/01.res.82.10.1063.
7
A quantitative structural and morphometric analysis of the Purkinje network and the Purkinje-myocardial junctions in pig hearts.猪心脏中浦肯野网络和浦肯野-心肌连接的定量结构和形态计量学分析。
J Anat. 2017 May;230(5):664-678. doi: 10.1111/joa.12594. Epub 2017 Mar 3.
8
Numerical approximation of the electromechanical coupling in the left ventricle with inclusion of the Purkinje network.包含浦肯野网络的左心室机电耦合的数值近似。
Int J Numer Method Biomed Eng. 2018 Jul;34(7):e2984. doi: 10.1002/cnm.2984. Epub 2018 May 16.
9
Intramural Purkinje fibers facilitate rapid ventricular activation in the equine heart.室壁浦肯野纤维促进马心脏的快速心室激活。
Acta Physiol (Oxf). 2023 Mar;237(3):e13925. doi: 10.1111/apha.13925. Epub 2023 Jan 18.
10
In situ Ca2+ dynamics of Purkinje fibers and its interconnection with subjacent ventricular myocytes.浦肯野纤维的原位钙动力学及其与下方心室肌细胞的相互联系。
J Mol Cell Cardiol. 2005 Apr;38(4):561-9. doi: 10.1016/j.yjmcc.2005.01.004.

引用本文的文献

1
Acute ischaemia and gap junction modulation modify propagation patterns across Purkinje-myocardial junctions.急性缺血和缝隙连接调节会改变浦肯野纤维-心肌连接部位的传导模式。
Front Physiol. 2025 May 6;16:1540400. doi: 10.3389/fphys.2025.1540400. eCollection 2025.
2
Nanosecond pulse electric field treatment initiates mitochondrial apoptosis pathway by inducing mitochondrial morphological changes in myocardial cells.纳秒级脉冲电场处理通过诱导心肌细胞线粒体形态变化启动线粒体凋亡途径。
J Interv Card Electrophysiol. 2024 Aug 2. doi: 10.1007/s10840-024-01828-5.
3
Digital twinning of cardiac electrophysiology for congenital heart disease.
心脏电生理学的数字孪生用于先天性心脏病。
J R Soc Interface. 2024 Jun;21(215):20230729. doi: 10.1098/rsif.2023.0729. Epub 2024 Jun 5.
4
Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation.心脏电生理学和心律失常发生的计算建模:迈向临床转化。
Physiol Rev. 2024 Jul 1;104(3):1265-1333. doi: 10.1152/physrev.00017.2023. Epub 2023 Dec 28.
5
Combination of personalized computational modeling and machine learning for optimization of left ventricular pacing site in cardiac resynchronization therapy.个性化计算建模与机器学习相结合用于优化心脏再同步治疗中左心室起搏部位
Front Physiol. 2023 Jul 11;14:1162520. doi: 10.3389/fphys.2023.1162520. eCollection 2023.
6
Enhanced optimization-based method for the generation of patient-specific models of Purkinje networks.基于增强优化的浦肯野网络个体化模型生成方法。
Sci Rep. 2023 Jul 21;13(1):11788. doi: 10.1038/s41598-023-38653-1.
7
Effects of cardiac growth on electrical dyssynchrony in the single ventricle patient.心脏生长对单心室患者电不同步的影响。
Comput Methods Biomech Biomed Engin. 2024 Jun;27(8):1011-1027. doi: 10.1080/10255842.2023.2222203. Epub 2023 Jun 14.