Year: 2015
Type: dissertation
Abstract: Cerebrovascular reactivity (CVR) is a measure of dilation capacity of\ncerebral vasculature. It is an important biomarker for the vascular\nfunctionality and integrity, and may have clinical indications in stroke,\natherosclerosis, Moyamoya disease, multiple sclerosis, brain tumor, and\nother neurological disorders. The most commonly used approach to\nmeasure CVR is by applying a physiological maneuver to alter the arterial\ncarbon dioxide (CO2) concentration (e.g. inhaling a small amount of CO2\nwhich is a potent vasodilator), while continuously acquiring BOLD MR\nimages. However, the current method suffers from several limitations\nrelated to specificity, sensitivity, and physiological modeling of the\nmeasured signal. The goal of my thesis study is to improve on these aspects\nand ultimately provide a clinically-ready CVR imaging procedure that could \nv\nbe immediately translational. The proposal’s goals have been accomplished\nthrough the following specific aims:\nAim 1: Improve the specificity of CVR signal by optimization of\nimaging protocol.\nAlthough positive CVR, i.e. increased BOLD signal with CO2\ninhalation, is expected in healthy brain, recently the presence of negative\nCVR has been reported using the current CVR imaging protocol, which can\npotentially compromise the interpretability of CVR data in clinical\napplications. In Aim 1, we performed simulation and experimental studies\nto provide a mechanistic understanding of this observation and showed that\nthe negative CVR reported in the literature is an artifactual signal due to\nimproper selection of imaging parameter. We further re-optimize the BOLD\nimaging parameters such that negative CVR is no longer present.\nAim 2: Improve the sensitivity of CVR mapping by applying a fast\nimaging technology, multiband MRI sequence.\nCVR mapping inherently has low sensitivity as it relies on small\nBOLD signal changes in response to CO2 inhalation, similar to fMRI.\nRecently, it has been shown that brain fMRI signal can be more robustly\nmeasured when using a fast imaging technology called multiband\nacquisition, and the technology has received wide attention. We\nhypothesize that multiband acquisition can also improve the sensitivity of \nvi\nCVR data, by collecting images at a higher temporal resolution. In Aim 2,\nwe examined the benefit of multiband acquisition in CVR mapping by\ncomparing CVR data collected with multiband factor of 2 (imaging two times\nfaster) and 3 (imaging three times faster) to those with regular acquisition.\nAim 3: Investigate modeling and nonlinearity issues in CVR data\nanalysis.\nThe previous two aims examined data acquisition strategies in CVR\nmapping. The present aim focuses on issues related to data analysis. A\nlinear relationship is usually assumed between EtCO2 and the BOLD signal,\nmaking linear model the most widely used model in CVR analysis. However,\nrecent reports have suggested a nonlinear relationship between BOLD\nsignal and arterial CO2 concentration. In Aim 3, we proposed an improved\nmodeling scheme that incorporates possible nonlinearity while preserving\nthe linear effect, through which we investigated the extent of nonlinear effect\nin CVR data and its dependence on age.
Author: Harshan Ravi
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2519038226