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一篇关于心电图成像逆问题的专家综述,用于非侵入性识别房颤驱动因素。

An expert review of the inverse problem in electrocardiographic imaging for the non-invasive identification of atrial fibrillation drivers.

机构信息

Institute of Biomedical Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China.

Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Guangdong, China.

出版信息

Comput Methods Programs Biomed. 2023 Oct;240:107676. doi: 10.1016/j.cmpb.2023.107676. Epub 2023 Jun 10.

Abstract

BACKGROUND AND OBJECTIVE

Electrocardiographic imaging (ECGI) has emerged as a non-invasive approach to identify atrial fibrillation (AF) driver sources. This paper aims to collect and review the current research literature on the ECGI inverse problem, summarize the research progress, and propose potential research directions for the future.

METHODS AND RESULTS

The effectiveness and feasibility of using ECGI to map AF driver sources may be influenced by several factors, such as inaccuracies in the atrial model due to heart movement or deformation, noise interference in high-density body surface potential (BSP), inconvenient and time-consuming BSP acquisition, errors in solving the inverse problem, and incomplete interpretation of the AF driving source information derived from the reconstructed epicardial potential. We review the current research progress on these factors and discuss possible improvement directions. Additionally, we highlight the limitations of ECGI itself, including the lack of a gold standard to validate the accuracy of ECGI technology in locating AF drivers and the challenges associated with guiding AF ablation based on post-processed epicardial potentials due to the intrinsic difference between epicardial and endocardial potentials.

CONCLUSIONS

Before performing ablation, ECGI can provide operators with predictive information about the underlying locations of AF driver by non-invasively and globally mapping the biatrial electrical activity. In the future, endocardial catheter mapping technology may benefit from the use of ECGI to enhance the diagnosis and ablation of AF.

摘要

背景与目的

心电图成像是一种非侵入性方法,可用于识别心房颤动(AF)的驱动源。本文旨在收集和回顾目前关于心电图成象逆问题的研究文献,总结研究进展,并提出未来的潜在研究方向。

方法与结果

心电图成象可能会受到多种因素的影响,例如由于心脏运动或变形导致心房模型不准确、高密度体表电势(BSP)中的噪声干扰、BSP 采集不方便且耗时、逆问题求解误差以及对重建心外膜电势得出的 AF 驱动源信息的不完全解释。我们回顾了这些因素的当前研究进展,并讨论了可能的改进方向。此外,我们还强调了心电图成象本身的局限性,包括缺乏金标准来验证定位 AF 驱动的心电图成象技术的准确性,以及由于心外膜和心内膜电势之间的固有差异,基于后处理的心外膜电势指导 AF 消融所面临的挑战。

结论

在进行消融之前,心电图成象可以通过非侵入性和全局地映射双心房电活动,为操作人员提供关于 AF 驱动源潜在位置的预测信息。未来,心内膜导管标测技术可能受益于心电图成象的使用,以增强 AF 的诊断和消融。

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