Electronic Thesis and Dissertation Repository

Thesis Format

Monograph

Degree

Doctor of Philosophy

Program

Medical Biophysics

Supervisor

Dr. Robert Bartha

Abstract

The most malignant form of diffuse infiltrative gliomas, glioblastoma multiforme (GBM), is the most common primary brain tumor in adults. Diffuse gliomas are characterized by extensive, diffuse infiltration of tumor cells into neighboring tissues. Due to the diffuse glioma growth pattern, curative treatment is not possible.

Conventional MRI has failed to accurately define the extent of brain tumor invasion, grade the tumor preoperatively, and predict treatment effects, making biopsy the gold standard. Histological analysis of brain tissue is currently the most accurate and reliable means of assessing brain pathology. However, developing noninvasive biomarkers that could provide information about tissue pathology \textit{in vivo} in humans would be invaluable, as it would enable a dynamic view of pathological processes and their impact on function in health and disease. In fact, the heterogeneous nature of glioma tumors and the existence of necrosis and inflammatory regions make biopsy challenging and increase the incidence of unsuccessful biopsies and the underestimation of the tumor grade. Diffusion tensor imaging (DTI), a standard diffusion magnetic resonance imaging (dMRI) technique, can non-invasively probe the brain microstructure and provide indicators of cell morphology and organization. More recently, the development of the neurite orientation dispersion and density imaging (NODDI) technique has allowed the estimation of the density and orientation dispersion of neurites using dMRI. Additionally, chemical exchange saturation transfer (CEST) is an advanced MRI technique that offers unique insights into the molecular composition and physiological properties of tissues by detecting the exchange of magnetization between protons in water and those on mobile proteins and other metabolites. The overreaching goal of this thesis was to characterize the tumor microenvironment using advanced diffusion MRI and tumor pH using chemical exchange saturation transfer MRI following treatment. This work is vital to determine whether these quantitative MRI methods could provide future benefits for clinical assessments. The C6 glioma rat model, a reproducible GBM model replicating many human glioma features, was used throughout the thesis to study glioma microstructure and microenvironment.

The comparison of dMRI contrasts demonstrated that the NODDI contrasts complemented the DTI contrasts and provided potentially greater contrast between the tumor and surrounding tissue than that produced by anatomical images or DTI. Specifically, the elevated isotropic volume fraction (IsoVF) value in the tumor tissue better-discriminated tumor tissue compared to other contrasts and did not provide the same information as that provided by conventional T2 weighted imaging. The feasibility of DTI and NODDI to characterize the properties of water diffusion within \textit{ex vivo} brain tumor and surrounding tissue was also confirmed. Observed diffusion changes within tumors were consistent with the structural changes visible in conventional histology. The chemical exchange saturation transfer method of monitoring tissue pH was also successfully able to detect pH changes in the C6 tumor after pharmacologically inhibiting the NHE1 transporter using Cariporide.

The NODDI dMRI and CEST pH-weighted imaging methods were both sensitive to variations in the tumor microenvironment. As these techniques continue to evolve and improve, they could contribute to advances in personalized medicine, where visualization of tumor microenvironment is determined non-invasively and used to guide treatment planning and monitoring.

Summary for Lay Audience

Lost productivity and reduced quality of life are often intrinsically associated with the diagnosis of a brain tumor because of the adverse effects of these lesions on nervous system function. Furthermore, the physician faces a significant challenge in attempting to prescribe a treatment protocol that will control the tumor and improve patient survival while maintaining the patient's neural abilities and avoiding treatment-associated morbidity. Despite the use of multimodal therapies, the median survival time remains 12--15 months for patients with the most malignant form of brain tumor, glioblastoma multiforme (GBM). GBM recurrence following treatment is common due to peritumoral migration and invasion, which are significant factors in therapeutic failure. Therefore, clear elucidation of the glioma microenvironment and the tumor margins will improve treatment protocols. Noninvasive brain cancer imaging guides treatment strategies and post-treatment follow-up. However, there is a need for better non-invasive imaging methods to more precisely characterize tumors to optimize treatment planning.

This thesis aims to characterize the tumor microenvironment using advanced diffusion MRI and tumor pH using chemical exchange saturation transfer (CEST) MRI and specifically to evaluate whether new contrasts provide complementary information to existing measures. Diffusion tensor imaging (DTI) measures the molecular diffusion of water in brain tissues. DTI provides insight into the microscopic details of tissue architecture. Neurite orientation dispersion and density imaging (NODDI) is a newer dMRI method sensitive to the microstructural features of neurites, including orientation and density. CEST can be used to monitor tissue acidity or pH, which can be altered by some drugs.

This thesis demonstrated that a specific NODDI metric provides improved detection of a specific tumor type compared to conventional dMRI. The NODDI-based isotropic volume fraction contrast best identifies tumor tissue and may reflect changes in tissue composition. The acidity-weighted CEST metric was also shown to be sensitive to differences in tumor acidity compared to other brain tissue and could detect changes in tumor acidity after drug injection. This work demonstrates that these advanced MRI methods could be used to characterize tumors in new ways that may provide clinical benefits in the future.

Available for download on Sunday, May 25, 2025

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