A Computationally Efficient Approach to Simulate Heart Rate Effects Using a Whole Human Heart Model.

Area of Science:

• Computational modeling
• Human heart electro-mechanics
• Medical device evaluation

Background:

• Computational modeling of the human heart is crucial for evaluating medical devices.
• The Dassault Systèmes Living Heart Human Model (LHHM) is a finite-element model previously calibrated for a resting heart rate (60 bpm).
• Replicating dynamic interactions between devices and the heart is challenging in traditional testing.

Purpose of the Study:

• To demonstrate that the LHHM can be recalibrated for heart rates ranging from 90 to 160 bpm.
• To adjust six physiologically meaningful parameters to achieve higher heart rates.
• To show the feasibility of using the LHHM for clinical investigations.

Main Methods:

• Adjusted six key physiological parameters in the LHHM.
• Simulated heart rates from 90 bpm to 160 bpm.
• Investigated AV delay optimization and hemodynamic differences between pacing and exercise.

Main Results:

• Recalibration of LHHM for 90-160 bpm was achieved by modifying sinoatrial node firing period, atrioventricular delay, preload, body resistance, arterial stiffness, and myofiber twitch force duration.
• Simulations showed optimal AV delay at 120 ms for 90 bpm, with peaks in stroke volume and systolic blood pressure.
• Cardiac output during exercise continued to increase up to 160 bpm, while pacing showed a plateauing effect above 100 bpm.

Conclusions:

• The LHHM can be effectively recalibrated to simulate a wide range of heart rates (90-160 bpm) by adjusting six parameters.
• The model is a feasible tool for clinical investigations, particularly for optimizing AV delay and understanding hemodynamic responses during pacing versus exercise.
• This enhanced model provides a valuable platform for in silico testing of medical devices across different physiological states.