Evaluation of Cerebral Blood Flow and Cerebral Autoregulation Using Synthetic Data and In Silico Modeling

The classic view of static cerebral autoregulatory function suggests that cerebral blood flow (CBF) remains relatively stable across a wide range of mean arterial pressure (MAP). Recent studies propose a narrow autoregulatory range, as the methods used to manipulate MAP may also influence CBF. This study evaluates static cerebral autoregulatory function using simulations and synthetic data, providing a theoretical framework for understanding static autoregulatory mechanisms in controlled conditions.

Data for the relation between MAP and CBF were generated using a numerical model simulating the cardio and cerebrovascular systems and CBF regulation mechanisms. The influence of the cardio and cerebrovascular parameters on CBF was evaluated utilizing sensitivity analyses, and the independent effects of the hemodynamic parameters on CBF were assessed using partial regression analysis.

Sensitivity analysis showed that CBF is influenced by the systemic arteriolar resistance and arterial CO₂ pressure. Partial regression analysis showed that the systemic arteriolar resistance and arterial CO₂ pressure had significant effects on CBF, and the effect of MAP on CBF was significant, with a weak correlation.

Synthetic data and simulations are feasible to evaluate static cerebral autoregulation and provide a theoretical framework for understanding mechanisms in controlled conditions.