Harshan Ravi

Graduation Semester and Year

2015

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Biomedical Engineering

Department

Bioengineering

First Advisor

Hanzhang Lu

Abstract

Cerebrovascular reactivity (CVR) is a measure of dilation capacity of cerebral vasculature. It is an important biomarker for the vascular functionality and integrity, and may have clinical indications in stroke, atherosclerosis, Moyamoya disease, multiple sclerosis, brain tumor, and other neurological disorders. The most commonly used approach to measure CVR is by applying a physiological maneuver to alter the arterial carbon dioxide (CO2) concentration (e.g. inhaling a small amount of CO2 which is a potent vasodilator), while continuously acquiring BOLD MR images. However, the current method suffers from several limitations related to specificity, sensitivity, and physiological modeling of the measured signal. The goal of my thesis study is to improve on these aspects and ultimately provide a clinically-ready CVR imaging procedure that could v be immediately translational. The proposal’s goals have been accomplished through the following specific aims: Aim 1: Improve the specificity of CVR signal by optimization of imaging protocol. Although positive CVR, i.e. increased BOLD signal with CO2 inhalation, is expected in healthy brain, recently the presence of negative CVR has been reported using the current CVR imaging protocol, which can potentially compromise the interpretability of CVR data in clinical applications. In Aim 1, we performed simulation and experimental studies to provide a mechanistic understanding of this observation and showed that the negative CVR reported in the literature is an artifactual signal due to improper selection of imaging parameter. We further re-optimize the BOLD imaging parameters such that negative CVR is no longer present. Aim 2: Improve the sensitivity of CVR mapping by applying a fast imaging technology, multiband MRI sequence. CVR mapping inherently has low sensitivity as it relies on small BOLD signal changes in response to CO2 inhalation, similar to fMRI. Recently, it has been shown that brain fMRI signal can be more robustly measured when using a fast imaging technology called multiband acquisition, and the technology has received wide attention. We hypothesize that multiband acquisition can also improve the sensitivity of vi CVR data, by collecting images at a higher temporal resolution. In Aim 2, we examined the benefit of multiband acquisition in CVR mapping by comparing CVR data collected with multiband factor of 2 (imaging two times faster) and 3 (imaging three times faster) to those with regular acquisition. Aim 3: Investigate modeling and nonlinearity issues in CVR data analysis. The previous two aims examined data acquisition strategies in CVR mapping. The present aim focuses on issues related to data analysis. A linear relationship is usually assumed between EtCO2 and the BOLD signal, making linear model the most widely used model in CVR analysis. However, recent reports have suggested a nonlinear relationship between BOLD signal and arterial CO2 concentration. In Aim 3, we proposed an improved modeling scheme that incorporates possible nonlinearity while preserving the linear effect, through which we investigated the extent of nonlinear effect in CVR data and its dependence on age.

Keywords

Cerebrovascular reactivity, CO2, Cerebrospinal fluid, MRI, Gas inhalation, Brain, Multiband, Nonlinear model

Disciplines

Biomedical Engineering and Bioengineering | Engineering

Comments

Degree granted by The University of Texas at Arlington

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