Date of Award

Summer 8-15-2019

Author's School

Graduate School of Arts and Sciences

Author's Department


Degree Name

Doctor of Philosophy (PhD)

Degree Type



Multiple Sclerosis (MS) is an unpredictable, often disabling disease of the central nervous system (CNS) that disrupts the flow of information within the brain, and between the brain the body. MS is the most common progressive neurologic disease of young adults, affecting approximately 2.3 million people worldwide. It is estimated that more than 700,000 individuals are affected by MS in United States. While MS has been studied for decades, the cause of it is still not definite and a fully effective treatment for MS is not yet available. Magnetic resonance imaging (MRI) has been used extensively in MS diagnosis and for monitoring disease. Clinical T1W, T2W and Fluid Attenuated Inversion Recovery (FLAIR) images are able to detect focal WM lesions with high accuracy and are used in MS diagnosis. However, standard clinical MRI lacks specificity to MS pathology and correlates only modestly with MS disability. Many studies have been devoted to the development and experimental validation of quantitative methods sensitive to myelin damage (hallmark of MS), primarily by means of multiexponential T2 imaging of water trapped between myelin layers, magnetization transfer (MT) and diffusion tensor imaging. These techniques have not gained traction in clinical practice, prompting searches for novel, more pathologically specific and efficient approaches. In this thesis, two novel MRI techniques developed in our lab, quantitative Gradient Recalled Echo (qGRE) and Multi-Angular-Relaxometry of Tissue (SMART), were used to quantitatively study MS tissue damage. Our qGRE technique (which is an advanced version of GEPCI – gradient echo plural contrast imaging) is based on quantitative measurements of the transverse relaxation properties of the Gradient Recalled Echo (GRE) MRI signal. This quantitative qGRE approach allows estimation of tissue damage in MS lesions and normal appearing WM and GM. An innovative qGRE method of data analysis allows separation of tissue-cellular-specific (R2t* relaxation rate constant) from Blood Oxygen Level Dependent (BOLD) contributions to the total GRE MRI signal decay rate constant (R2*). Since BOLD effect causes variations in MRI signal that occur with physiological state-dependent changes in blood flow and/or oxygen consumption, the R2t* values more specifically reflect the tissue-cellular component of R2*. The tissue-cellular-specific (R2t*) MRI relaxation parameter depends on the environment of water molecules (the main source of MRI signal): higher concentrations of proteins, lipids, and other constituents of biological tissue and cellular constituents (sources of MRI signal relaxation) leading to higher relaxation rate constants. Our results showed that R2t* can sensitively detect MS-related pathology in cortical NAGM, subcortical NAWM and WM lesions. The method demonstrated tissue damage patterns in the CNS of the MS cohort. Our data shed light on the interrelationships of damage throughout the brain and cervical spinal cord, while supporting the idea of MS as a global CNS disease. In addition, our data demonstrated that while spinal cord CSA is a reliable marker for changes in motor functions, the reduction in the R2t* of GM and WM is a reliable indicator of cognitive dysfunction. The SMART technique is also based on a GRE MRI sequence (but with multiple flip angles) and a model of GRE signal that accounts for cross-relaxation effects between “free” and “bound” water proton pools. Importantly, no MT pulses are used in SMART approach, thus overcoming high RF energy deposition associated with existing qMT approaches for evaluation of tissue macromolecular content. From a single protocol this technique can generate quantitative macromolecular proton fraction (MPF) images along with naturally co-registered quantitative images of longitudinal (R1=1/T1) and transverse (R2*=1/T2*) signal relaxation rate constants, and spin density. The SMART technique allows quantitative assessments of central nervous system (CNS) simultaneously using several tissue contrasts. Our results showed that the SMART metrics can distinguish progressive MS from relapsing-remitting MS (RRMS) and correlate with clinical assessments. Without applying either MT or 180° radiofrequency pulses, SMART MRI generates high resolution quantitative images with various contrasts, and is safe for high-field MRI, making it a useful outcome measure in clinical trials.


English (en)

Chair and Committee

Joseph Ackerman Dmitriy Yablonskiy

Committee Members

Joseph Ackerman, Dmitriy Yablonskiy, Dewey Holten, Sophia Hayes,


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