Models And Algorithms To Determine Cerebral Activation Using Near Infrared Spectroscopy

Abstract

The specific aims of this dissertation were to develop: (1) Correlations between experimental protocols and oxygenated, deoxygenated, and total hemoglobin concentrations in the brain (2) Mathematical models to associate blood flow and oxygen consumption rate of the activated brain regions with measured hemodynamic changes (3) A phantom that models brain vasculature compliance to validate developed mathematical models in a controlled setup. The primary imaging modality used in the experimentation phase of this research was near infrared spectroscopy. Previously published multimodality measurements were also used to validate the mathematical models.

The single compartment Windkessel model was extended to describe flow-volume dynamics during long duration stimulus and include oxygen transport to tissue. An inductive multi-compartment model was developed which enables the estimation of compartmentalized hemodynamic changes with the modeling of measured oxy- and deoxyhemoglobin changes based on a pseudo-Bayesian framework for multimodality data. In addition, a solution to the single and multi-compartment deductive neurovascular model was also developed. This model defines the relationship between the presented stimulus and the neural activity it elicits which in turn gives rise to the vascular changes. Finally a vascular phantom was developed in the laboratory to validate the flow-volume relationships using compliant vasculature.