Closed-Loop Multiscale Computational Model of Human Blood Circulation. Applications to Ballistocardiography

Abstract

Cardiac mechanical activity leads to periodic changes in the distribution of blood throughout the body, which causes micro-oscillations of the body’s center of mass and can be measured by ballistocardiography (BCG). However, many of the BCG findings are based on parameters whose origins are poorly understood. Here, we generate simulated multidimensional BCG signals based on a more exhaustive and accurate computational model of blood circulation than previous attempts. This model consists in a closed loop 0D-1D multiscale representation of the human blood circulation. The 0D elements include the cardiac chambers, cardiac valves, arterioles, capillaries, venules, and veins, while the 1D elements include 55 systemic and 57 pulmonary arteries. The simulated multidimensional BCG signal is computed based on the distribution of blood in the different compartments and their anatomical position given by whole-body magnetic resonance angiography on a healthy young subject. We use this model to analyze the elements affecting the BCG signal on its different axes, allowing a better interpretation of clinical records. We also evaluate the impact of filtering and healthy aging on the BCG signal. The results offer a better view of the physiological meaning of BCG, as compared to previous models considering mainly the contribution of the aorta and focusing on longitudinal acceleration BCG. The shape of experimental BCG signals can be reproduced, and their amplitudes are in the range of experimental records. The contributions of the cardiac chambers and the pulmonary circulation are non-negligible, especially on the lateral and transversal components of the velocity BCG signal. The shapes and amplitudes of the BCG waveforms are changing with age, and we propose a scaling law to estimate the pulse wave velocity based on the time intervals between the peaks of the acceleration BCG signal. We also suggest new formulas to estimate the stroke volume and its changes based on the BCG signal expressed in terms of acceleration and kinetic energy.

Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography—A Narrative Review

“…Dock [ 50 ] also believed that the right ventricle played only a minor role in the generation of the BCG phenomenon and that the changes in its activity during respiration seemed insufficient to produce the respiratory variability in the BCG records. A recent numerical model by Rabineau et al also confirmed this [ 65 ]. They also compared the stroke volumes predicted by Starr’s formula (1) with values generated by the computational model.…”

“…They also compared the stroke volumes predicted by Starr’s formula (1) with values generated by the computational model. They reported that although a positive correlation was found using this formula, it is not ideal for estimating intra-subject variations of stroke volume [ 65 ].…”

Non-invasive cardiac kinetic energy distribution: a new marker of heart failure with impaired ejection fraction (KINO-HF)

“…As such, the ventricular dilation can impede the expected decrease of SCG in the iLVEF group but not the decrease of BCG. The essence of BCG is to measure micromovements of the body in reaction to blood flow through the vasculature, mainly the aorta, making this metric less sensitive to mechanical LV motion and LV dilatation ( 35 ).…”

Reactive Cu2+-peptide intermediates revealed by kinetic studies gain relevance by matching time windows in copper metallomics

“…In the bloodstream, the change has additional aspects of visiting various tissues in the body, combined with significantly different flow rates in arteries, capillaries, and veins. 25 Therefore, the chemical reactions depending on these periodicities, or constituting them, must occur within specific timeframes and additionally in specific volumes. Below, we explore the emerging relevance of these factors for metallomics of Cu(II) transport in blood and in the brain.…”