In silico analysis of the Frank-Starling mechanism and its relationship with vascular filling therapy

The Frank-Starling (FS) mechanism is an essential regulatory mechanism of cardiac output. It is defined as follows: if more blood enters the ventricle, preload increases and, as an immediate response, the stroke volume (SV, the ejected blood volume) increases. It is commonly assumed that the length-dependent activation (LDA), a cellular property, underlies the FS mechanism. As preload increases, the length of cardiac fibers increases and they produce a greater contractile force. To investigate this presumed relationship between LDA and the FS mechanism, a 6-chamber lumped-parameter model of the cardiovascular system (CVS) is proposed. In this model, the active contraction of both ventricles is described at the cellular scale. This ensures that our multiscale model of ventricular contraction is able to link the important microscopic variables (cellular length and force) to the macroscopic variables (ventricular volume and pressure). We show that the FS mechanism is a deeply dynamical response to a change in preload, and this response is driven by LDA. But we also demonstrate that the maximal produced force is not a reliable index to determine SV variations upon preload increase.
We then use our model to investigate the relationship between the FS mechanism and vascular filling. The latter is a commonly used therapy in intensive care units, where fluid infusions are performed in order to restore the patient’s cardiac output. It is believed that increasing the circulating blood volume increases the preload, hence the SV. We perform vascular filling (and emptying) simulations with our CVS model and observe two things. First, LDA is responsible for the increase in SV following vascular filling. Second, preload is not the only variable to monitor in order to predict the patient response to fluid therapy. Afterload should also be considered, as fluid infusions also impact the resistance to blood ejection, which tends to counterbalance the LDA effect and reduce the expected SV increase.