Seminar: Applying New Dynamic Models to Near-Infrared Spectroscopy Measurements of Cerebral Changes

Student: Nima Khalifehsoltani

Supervisors: Dr. Vladislav Toronov and Dr. Keith St. Lawrence

Abstract

Near-infrared spectroscopy (NIRS) and hemodynamic models jointly unravel cerebral hemodynamics, crucial during cardiac arrest and cardiopulmonary resuscitation (CPR). NIRS measures chromophores like Oxy, Deoxyhemoglobin and Cytochrome C oxidase, while hemodynamic models mathematically connect physiological processes, aiding the analysis of cerebral blood volume, flow, and oxygen metabolism.
Optical techniques like NIRS, diffuse correlation spectroscopy (DCS), and laser Doppler flowmetry (LDF) monitor physiological dynamics, complemented by hemodynamic models representing cerebral blood flow, volume, and oxygenation dynamics. This study integrates hemometabolic models with NIRS, LDF, and DCS data, focusing on cardiac arrest's impact on the pig’s brain. A hemometabolic model applied to NIRS during cardiac events aims to describe observed phenomena, understand microvasculature behavior, and compare parameters with known values. Statistical analysis reveals significant differences in baseline and post-cardiac arrest values.
Objectives include model validation and enhancing applicability, understanding microvasculature behavior and improving CPR outcomes. This integrated approach contributes valuable insights into cerebral hemodynamics during critical events, refining models and enhancing understanding for improved treatment outcomes. Using the reverse of the hemometabolic model, we assessed various important physiological factors, including the oxygen diffusion rate from blood to tissue, the volume fractions of arterioles and venules, and the Fåhraeus factor. Statistical analysis revealed notable variances in the values of certain parameters between the baseline and post-cardiac arrest conditions.