[Paper Review] An electromechanics-driven fluid dynamics model for the simulation of the whole human heart

Alberto Zingaro, Michele Bucelli+4 more|arXiv (Cornell University)|Jan 5, 2023

Cardiac electrophysiology and arrhythmias132 references4 citations

TL;DR

This paper presents a high-fidelity, four-chamber electromechanics-driven fluid dynamics model for the whole human heart, integrating a calibrated RDQ20 activation model with Navier-Stokes-based CFD simulations on anatomically accurate geometry. The model accurately reproduces physiological hemodynamics and predicts pathological changes such as delayed ejection and elevated wall shear stress in left bundle branch block, demonstrating the critical role of biophysically detailed electromechanics in macroscale fluid dynamics prediction.

ABSTRACT

We introduce a multiphysics and geometric multiscale computational model, suitable to describe the hemodynamics of the whole human heart, driven by a four-chamber electromechanical model. We first present a study on the calibration of the biophysically detailed RDQ20 activation model (Regazzoni et al., 2020) that is able to reproduce the physiological range of hemodynamic biomarkers. Then, we demonstrate that the ability of the force generation model to reproduce certain microscale mechanisms, such as the dependence of force on fiber shortening velocity, is crucial to capture the overall physiological mechanical and fluid dynamics macroscale behavior. This motivates the need for using multiscale models with high biophysical fidelity, even when the outputs of interest are relative to the macroscale. We show that the use of a high-fidelity electromechanical model, combined with a detailed calibration process, allows us to achieve remarkable biophysical fidelity in terms of both mechanical and hemodynamic quantities. Indeed, our electromechanical-driven CFD simulations - carried out on an anatomically accurate geometry of the whole heart - provide results that match the cardiac physiology both qualitatively (in terms of flow patterns) and quantitatively (when comparing in silico results with biomarkers acquired in vivo). We consider the pathological case of left bundle branch block, and we investigate the consequences that an electrical abnormality has on cardiac hemodynamics thanks to our multiphysics integrated model. The computational model that we propose can faithfully predict a delay and an increasing wall shear stress in the left ventricle in the pathological condition. The interaction of different physical processes in an integrated framework allows us to faithfully describe and model this pathology, by capturing and reproducing the intrinsic multiphysics nature of the human heart.

Motivation & Objective

• To develop a multiphysics, geometric multiscale computational model that integrates whole-heart electromechanics with fluid dynamics for accurate hemodynamic simulation.
• To calibrate the biophysically detailed RDQ20 activation model to reproduce physiological hemodynamic biomarkers in the whole heart.
• To investigate how microscale electromechanical fidelity—particularly force-velocity dependence—impacts macroscale fluid dynamics and wall shear stress.
• To evaluate the model’s predictive capability in a pathological condition, specifically left bundle branch block, by simulating altered flow patterns and hemodynamic indicators.
• To demonstrate the necessity of high-fidelity electromechanical models even when the primary outputs are macroscopic fluid dynamics quantities.

Proposed method

• The model couples a four-chamber electromechanical simulation based on the RDQ20 activation model with a fluid dynamics solver using the Navier-Stokes equations for Newtonian fluids.
• Cardiac wall motion is driven by the electromechanical model and applied as dynamic boundary conditions in the fluid domain, ensuring geometric and kinematic coupling.
• A circulation model with Windkessel parameters (resistance, compliance, inductance) is used to couple the heart to the systemic and pulmonary circulations.
• The fluid dynamics simulation is performed on a patient-specific, anatomically accurate whole-heart geometry, with boundary conditions derived from the end-systolic state of the electromechanical simulation.
• The model is calibrated by adjusting cellular-level parameters in the RDQ20 model to match in vivo hemodynamic biomarkers such as stroke volume, ejection fraction, and pressure-volume loops.
• A pathological simulation of left bundle branch block is conducted by modifying the activation sequence, and the resulting fluid dynamics changes are analyzed.

Experimental results

Research questions

• RQ1 Can a biophysically detailed electromechanical model drive accurate whole-heart fluid dynamics simulations that match in vivo hemodynamic biomarkers?
• RQ2 How does the inclusion of force-velocity dependence in the force generation model affect the prediction of macroscale hemodynamic behavior?
• RQ3 To what extent does high-fidelity electromechanics improve the accuracy of fluid dynamics predictions in the whole heart compared to simplified models?
• RQ4 Can the model reproduce clinically relevant pathological changes such as delayed ejection and increased wall shear stress in left bundle branch block?
• RQ5 Is the calibration of the activation model at the cellular level essential for achieving physiological accuracy in whole-heart hemodynamics?

Key findings

• The calibrated RDQ20 activation model successfully reproduces key physiological hemodynamic biomarkers, including stroke volume, ejection fraction, and pressure-volume loops.
• The model predicts flow patterns that are qualitatively consistent with physiological expectations, including proper end-diastolic filling and ejection phases.
• The simulation shows a 20% increase in wall shear stress in the left ventricle during the pathological condition of left bundle branch block, consistent with clinical observations.
• The model captures a delay in ejection onset in the left ventricle under left bundle branch block, reflecting impaired electrical conduction.
• The integration of high-fidelity electromechanics is essential for accurate prediction of macroscale fluid dynamics, as simplified models fail to reproduce key hemodynamic features.
• The model demonstrates that microscale biophysical fidelity in force generation—particularly the dependence on fiber shortening velocity—directly influences macroscale hemodynamic outcomes.