Autoregulation in a simulator-based educational model of intracranial physiology

To implement a realistic autoregulation mechanism to enhance an existing educational brain model that displays in real-time the cerebral metabolic rate (CMRO2), cerebral blood flow (CBF), cerebral blood volume (CBV), intracranial pressure (ICP), and cerebral perfusion pressure (CPP).

A dynamic cerebrovascular resistance (CVR) feedback loop adjusts automatically to maintain CBF within a range of the CPP and defines autoregulation. The model obtains physiologic parameters from a full-scale patient simulator. We assumed that oxygen demand and arterial partial pressure of carbon dioxide (CO2 responsivity) are the two major factors involved in determining CBF. In addition, our brain model increases oxygen extraction up to 70% once CBF becomes insufficient to support CMRO2. The model was validated against data from the literature.

The model's response varied less than 9% from the literature data. Similarly, based on correlation coefficients between the brain model and experimental data, a good fit was obtained for curves describing the relationship between CBF and PaCO2 at a mean arterial blood pressure of 150 mm Hg (R2 = 0.92) and 100 mm Hg (R2 = 0.70).

The autoregulated brain model, with incorporated CO2 responsivity and a variable oxygen extraction, automatically produces changes in CVR, CBF, CBV, and ICP consistent with literature reports, when run concurrently with a METI full-scale patient simulator (Medical Education Technologies, Inc., Sarasota, Florida). Once the model is enhanced to include herniation, vasospasm, and drug effects, its utility will be expanded beyond demonstrating only basic neuroanesthesia concepts.