Fast interactive simulations of cardiac electrical activity in anatomically accurate heart structures by compressing sparse uniform cartesian grids

IF 4.9 2区 医学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

Abstract

Background and Objective:

Numerical simulations are valuable tools for studying cardiac arrhythmias. Not only do they complement experimental studies, but there is also an increasing expectation for their use in clinical applications to guide patient-specific procedures. However, numerical studies that solve the reaction–diffusion equations describing cardiac electrical activity remain challenging to set up, are time-consuming, and in many cases, are prohibitively computationally expensive for long studies. The computational cost of cardiac simulations of complex models on anatomically accurate structures necessitates parallel computing. Graphics processing units (GPUs), which have thousands of cores, have been introduced as a viable technology for carrying out fast cardiac simulations, sometimes including real-time interactivity. Our main objective is to increase the performance and accuracy of such GPU implementations while conserving computational resources.

Methods:

In this work, we present a compression algorithm that can be used to conserve GPU memory and improve efficiency by managing the sparsity that is inherent in using Cartesian grids to represent cardiac structures directly obtained from high-resolution MRI and mCT scans. Furthermore, we present a discretization scheme that includes the cross-diagonal terms in the computational cell to increase numerical accuracy, which is especially important for simulating thin tissue sections without the need for costly mesh refinement.

Results:

Interactive WebGL simulations of atrial/ventricular structures (on PCs, laptops, tablets, and phones) demonstrate the algorithm’s ability to reduce memory demand by an order of magnitude and achieve calculations up to 20x faster. We further showcase its superiority in slender tissues and validate results against experiments performed in live explanted human hearts.

Conclusions:

In this work, we present a compression algorithm that accelerates electrical activity simulations on realistic anatomies by an order of magnitude (up to 20x), thereby allowing the use of finer grid resolutions while conserving GPU memory. Additionally, improved accuracy is achieved through cross-diagonal terms, which are essential for thin tissues, often found in heart structures such as pectinate muscles and trabeculae, as well as Purkinje fibers. Our method enables interactive simulations with even interactive domain boundary manipulation (unlike finite element/volume methods). Finally, agreement with experiments and ease of mesh import into WebGL paves the way for virtual cohorts and digital twins, aiding arrhythmia analysis and personalized therapies.
通过压缩稀疏的均匀直角坐标网格,在解剖精确的心脏结构中快速交互模拟心电活动。
背景和目的:数值模拟是研究心律失常的重要工具。它们不仅是对实验研究的补充,而且越来越多的人期望将其用于临床应用,以指导针对特定患者的治疗过程。然而,求解描述心电活动的反应-扩散方程的数值研究仍然具有挑战性,需要耗费大量时间,而且在许多情况下,长期研究的计算成本高得令人望而却步。在解剖结构精确的复杂模型上进行心脏模拟的计算成本需要并行计算。图形处理器(GPU)拥有成千上万个内核,是进行快速心脏模拟(有时包括实时互动)的可行技术。我们的主要目标是在节约计算资源的同时提高 GPU 实现的性能和准确性:在这项工作中,我们提出了一种压缩算法,通过管理使用笛卡尔网格直接表示从高分辨率核磁共振成像和 mCT 扫描中获得的心脏结构时固有的稀疏性,该算法可用于节省 GPU 内存并提高效率。此外,我们还提出了一种离散化方案,其中包括计算单元中的对角线项,以提高数值精度,这对于模拟薄组织切片尤为重要,而无需进行昂贵的网格细化:结果:对心房/心室结构的交互式 WebGL 仿真(在个人电脑、笔记本电脑、平板电脑和手机上)表明,该算法能够将内存需求降低一个数量级,并将计算速度提高 20 倍。我们进一步展示了该算法在纤细组织中的优越性,并通过在活体植入人体心脏中进行的实验验证了结果:在这项工作中,我们提出了一种压缩算法,该算法可将真实解剖结构的电活动模拟速度提高一个数量级(高达 20 倍),从而允许使用更精细的网格分辨率,同时节省 GPU 内存。此外,我们还通过交叉对角线项提高了精度,这对薄组织至关重要,而薄组织通常存在于栉状肌、小梁等心脏结构以及浦肯野纤维中。我们的方法可以进行交互式模拟,甚至可以进行交互式域边界操作(与有限元/体积方法不同)。最后,与实验的一致性和网格导入 WebGL 的简便性为虚拟队列和数字双胞胎铺平了道路,有助于心律失常分析和个性化治疗。
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来源期刊
Computer methods and programs in biomedicine
Computer methods and programs in biomedicine 工程技术-工程:生物医学
CiteScore
12.30
自引率
6.60%
发文量
601
审稿时长
135 days
期刊介绍: To encourage the development of formal computing methods, and their application in biomedical research and medical practice, by illustration of fundamental principles in biomedical informatics research; to stimulate basic research into application software design; to report the state of research of biomedical information processing projects; to report new computer methodologies applied in biomedical areas; the eventual distribution of demonstrable software to avoid duplication of effort; to provide a forum for discussion and improvement of existing software; to optimize contact between national organizations and regional user groups by promoting an international exchange of information on formal methods, standards and software in biomedicine. Computer Methods and Programs in Biomedicine covers computing methodology and software systems derived from computing science for implementation in all aspects of biomedical research and medical practice. It is designed to serve: biochemists; biologists; geneticists; immunologists; neuroscientists; pharmacologists; toxicologists; clinicians; epidemiologists; psychiatrists; psychologists; cardiologists; chemists; (radio)physicists; computer scientists; programmers and systems analysts; biomedical, clinical, electrical and other engineers; teachers of medical informatics and users of educational software.
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