Author ORCID Identifier

https://orcid.org/0000-0003-4652-5235

Date Available

7-19-2019

Year of Publication

2019

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Engineering

Department/School/Program

Biomedical Engineering

First Advisor

Dr. Ai-Ling Lin

Second Advisor

Dr. Guoqiang Yu

Abstract

The high prevalence and mortality of cerebrovascular disease has led to the development of several methods to measure cerebral blood flow (CBF) in vivo. One of these, arterial spin labeling (ASL), is a quantitative magnetic resonance imaging (MRI) technique with the advantage that it is completely non-invasive. The quantification of CBF using ASL requires correction for a tissue specific parameter called the brain-blood partition coefficient (BBPC). Despite regional and inter-subject variability in BBPC, the current recommended implementation of ASL uses a constant assumed value of 0.9 mL/g for all regions of the brain, all subjects, and even all species.

The purpose of this dissertation is 1) to apply ASL to a novel population to answer an important clinical question in the setting of Down syndrome, 2) to demonstrate proof of concept of a rapid technique to measure BBPC in mice to improve CBF quantification, and 3) to translate the correction method by applying it to a population of healthy canines using equipment and parameters suitable for use with humans.

Chapter 2 reports the results of an ASL study of adults with Down syndrome (DS). This population is unique for their extremely high prevalence of Alzheimer’s disease (AD) and very low prevalence of systemic cardiovascular risk factors like atherosclerosis and hypertension. This prompted the hypothesis that AD pathology would lead to the development of perfusion deficits in people with DS despite their healthy cardiovascular profile. The results demonstrate that perfusion is not compromised in DS participants until the middle of the 6th decade of life after which measured global CBF was reduced by 31% (p=0.029). There was also significantly higher prevalence of residual arterial signal in older participants with DS (60%) than younger DS participants (7%, p = 0.005) or non-DS controls (0%, p < 0.001). This delayed pattern of perfusion deficits in people with DS differs from observations in studies of sporadic AD suggesting that adults with DS benefit from an improved cardiovascular risk profile early in life.

Chapter 3 introduces calibrated short TR recovery (CaSTRR) imaging as a rapid method to measure BBPC and its development in mice. This was prompted by the inability to account for potential changes in BBPC due to age, brain atrophy, or the accumulation of hydrophobic A-β plaques in the ASL study of people with DS in Chapter 2. The CaSTRR method reduces acquisition time of BBPC maps by 87% and measures a significantly higher BBPC in cortical gray matter (0.99±0.04 mL/g,) than white matter in the corpus callosum (0.93±0.05 mL/g, p=0.03). Furthermore, when CBF maps are corrected for BBPC, the contrast between gray and white matter regions of interest is improved by 14%. This demonstrates proof of concept for the CaSTRR technique.

Chapter 4 describes the application of CaSTRR on healthy canines (age 5-8 years) using a 3T human MRI scanner. This represents a translation of the technique to a setting suitable for use with a human subject. Both CaSTRR and pCASL acquisitions were performed and further optimization brought the acquisition time of CaSTRR down to 4 minutes which is comparable to pCASL. Results again show higher BBPC in gray matter (0.83 ± 0.05 mL/g) than white matter (0.78 ± 0.04 mL/g, p = 0.007) with both values unaffected by age over the range studied. Also, gray matter CBF is negatively correlated with age (p = 0.003) and BBPC correction improved the contrast to noise ratio by 3.6% (95% confidence interval = 0.6 – 6.5%).

In summary, the quantification of ASL can be improved using BBPC maps derived from the novel, rapid CaSTRR technique.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2019.333

Funding Information

NIH Grant #R01HD064993

NIH Grant #R01AG054459

NIH Grant #T32AG057461

NIH Grant #K01AG040164

NIH Shared Instrumentation Grant #1S10RR029541-01

F. Joseph Halcomb III, M.D. Fellowship for Engineering in Medicine

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