心房颤动研究进展(计算机模拟与临床展望)

Muhammad Aneeq uz Zaman, D. Du
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引用次数: 0

摘要

心房颤动(AF)是一种心脏疾病,在过去的几十年里一直是一个研究得很好的话题。这个多学科领域的研究涉及信号处理、有限元分析、数学建模、优化和临床程序。本文对AF领域发表的期刊文章进行了全面的综述。从古老的基本概念到当今AF研究中涉及的专业现代技术,都进行了讨论。我们发现,在AF的建模和仿真方面已经发表了大量的研究文章。相比之下,研究者对AF患者的诊断和术后流程还没有完全了解和探索。AF的仿真和建模已经被许多研究者进行了研究。细胞模型、组织模型和几何模型等已被用于模拟AF。由于AF的性质非常复杂,迄今为止尚未完全了解AF的原因,但模拟结果得到了真实患者数据的验证。已经提出了许多算法来检测心房房颤的来源。房颤患者有许多消融策略,但寻找更有效的消融策略仍在进行中。不同阶段房颤患者的房颤管理也有文献讨论,但大多局限于持续性房颤患者。作者希望本研究有助于发现房颤分析和诊断方面的现有研究空白。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review on Atrial Fibrillation (Computer Simulation and Clinical Perspectives)
Atrial fibrillation (AF), a heart condition, has been a well-researched topic for the past few decades. This multidisciplinary field of study deals with signal processing, finite element analysis, mathematical modeling, optimization, and clinical procedure. This article is focused on a comprehensive review of journal articles published in the field of AF. Topics from the age-old fundamental concepts to specialized modern techniques involved in today’s AF research are discussed. It was found that a lot of research articles have already been published in modeling and simulation of AF. In comparison to that, the diagnosis and post-operative procedures for AF patients have not yet been totally understood or explored by the researchers. The simulation and modeling of AF have been investigated by many researchers in this field. Cellular model, tissue model, and geometric model among others have been used to simulate AF. Due to a very complex nature, the causes of AF have not been fully perceived to date, but the simulated results are validated with real-life patient data. Many algorithms have been proposed to detect the source of AF in human atria. There are many ablation strategies for AF patients, but the search for more efficient ablation strategies is still going on. AF management for patients with different stages of AF has been discussed in the literature as well but is somehow limited mostly to the patients with persistent AF. The authors hope that this study helps to find existing research gaps in the analysis and the diagnosis of AF.
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