ln silico simulation of the interaction among autoregulatory mechanisms regulating cerebral blood flow rate in the healthy and systolic heart failure conditions during exercise.

In this study, a computational model was proposed to assess the interaction among systemic arteriolar resistance control, heart rate control, ventricular elastance control, venous compliance control, respiratory control, cerebral autoregulation mechanisms, and cerebral CO reactivity for both healthy and heart failure conditions. The aim of the study is to develop a computational model to evaluate cerebral blood flow rate during exercise for both healthy and systolic heart failure conditions. The simulations were performed at rest and during exercise. Furthermore, Monte Carlo analysis was used to estimate the range of the controlled parameters for each condition. The mean arterial pressure increased progressively with respect to workload during exercise in both healthy and heart failure conditions. Total cerebral blood flow rate was found 730 mL/min at rest in the healthy cardiovascular system model. As for the simulation during exercise, the increments in cerebral blood flow rate were 11% at 25 W workload, 20% at 50 W workload, and 24% at 75 W workload. The left ventricular ejection fraction decreased from 54 to 26% in the cardiovascular model simulating heart failure. Also, total cerebral blood flow rate decreased to 604 mL/min at rest in the cardiovascular system model simulating heart failure. The increments in cerebral blood flow rate in the simulation during exercise were 14% at 25 W workload, 24% at 50 W workload, and 30% at 75 W workload in the case of heart failure. The proposed numerical model simulates cerebral blood flow rate within physiological range during exercise and heart failure.