A reduced order model formulation for left atrium flow: an atrial fibrillation case

IF 3 3区医学 Q2 BIOPHYSICS

Biomechanics and Modeling in Mechanobiology Pub Date : 2024-05-16 DOI:10.1007/s10237-024-01847-1

Caterina Balzotti, Pierfrancesco Siena, Michele Girfoglio, Giovanni Stabile, Jorge Dueñas-Pamplona, José Sierra-Pallares, Ignacio Amat-Santos, Gianluigi Rozza

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Abstract

A data-driven reduced order model (ROM) based on a proper orthogonal decomposition-radial basis function (POD-RBF) approach is adopted in this paper for the analysis of blood flow dynamics in a patient-specific case of atrial fibrillation (AF). The full order model (FOM) is represented by incompressible Navier–Stokes equations, discretized with a finite volume (FV) approach. Both the Newtonian and the Casson’s constitutive laws are employed. The aim is to build a computational tool able to efficiently and accurately reconstruct the patterns of relevant hemodynamics indices related to the stasis of the blood in a physical parametrization framework including the cardiac output in the Newtonian case and also the plasma viscosity and the hematocrit in the non-Newtonian one. Many FOM-ROM comparisons are shown to analyze the performance of our approach as regards errors and computational speed-up.

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左心房流动的减阶模型表述：心房颤动案例。

本文采用基于适当正交分解-径向基函数（POD-RBF）方法的数据驱动减阶模型（ROM）来分析心房颤动（AF）患者的血流动力学。全阶模型（FOM）由不可压缩纳维-斯托克斯方程表示，并采用有限体积（FV）方法进行离散化。牛顿和卡森构成定律均被采用。目的是建立一种计算工具，能够在物理参数化框架内高效、准确地重建与血液瘀滞相关的血液动力学指数模式，包括牛顿情况下的心输出量以及非牛顿情况下的血浆粘度和血细胞比容。许多 FOM-ROM 比较显示了我们的方法在误差和计算速度方面的性能分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Biomechanics and Modeling in Mechanobiology 工程技术-工程：生物医学

CiteScore

7.10

自引率

8.60%

发文量

119

审稿时长

6 months

期刊介绍： Mechanics regulates biological processes at the molecular, cellular, tissue, organ, and organism levels. A goal of this journal is to promote basic and applied research that integrates the expanding knowledge-bases in the allied fields of biomechanics and mechanobiology. Approaches may be experimental, theoretical, or computational; they may address phenomena at the nano, micro, or macrolevels. Of particular interest are investigations that (1) quantify the mechanical environment in which cells and matrix function in health, disease, or injury, (2) identify and quantify mechanosensitive responses and their mechanisms, (3) detail inter-relations between mechanics and biological processes such as growth, remodeling, adaptation, and repair, and (4) report discoveries that advance therapeutic and diagnostic procedures. Especially encouraged are analytical and computational models based on solid mechanics, fluid mechanics, or thermomechanics, and their interactions; also encouraged are reports of new experimental methods that expand measurement capabilities and new mathematical methods that facilitate analysis.