UCLA

The reprogrammed energy metabolism and the dysfunctional vascular network of tumors create a hypoxic and acidic microenvironment, which is related to various malignant properties of cancer and poor patient prognosis. We have developed an amine chemical exchange saturation transfer (CEST) sequence with spin-and-gradient echo (SAGE) echo-planar imaging (EPI) readout to evaluate tumor acidity and hypoxia in human gliomas simultaneously. Amine CEST provided pH-sensitivity through labeling the endogenous amine protons that undergo chemical exchange with water protons, with a pH-dependent exchange rate. On the other hand, the reversible transverse relaxation rate quantified using the multi-echo EPI readout reflects oxygen extraction through sensitivity to paramagnetic deoxyhemoglobin.

This dissertation focused on developing and validating this novel dual-function imaging technique, mainly from three aspects: the technical development and validation, the biological validation, and the clinical validation of the proposed pH- and oxygen-sensitive CEST-SAGE-EPI technique in human gliomas. We have developed a new post-processing method for improved $B_0$ correction. A customized CEST physical phantom was designed and developed with validated temporal stability. We also evaluated the CEST contrast variability in healthy volunteers and the normal-appearing contralateral brain regions in glioma patients. The proposed pH- and oxygen-sensitive imaging biomarkers showed significant correlations with the tumor cell metabolomics features and MRI-guided biopsy tissue biomarkers, which validated the biological bases of the imaging biomarkers. Additionally, we have examined the association between tumor acidity with tumor vascularity, as measured by perfusion MRI. Lastly, we investigated the clinical usefulness of the biomarkers to characterize different glioma genotypes, predict patient prognosis, and monitor treatment responses.

In summary, this dissertation demonstrated that the novel dual-function pH- and oxygen-sensitive imaging technique reflects the abnormal metabolism in glioma patients and has the potential to provide clinical values for patient diagnosis, prognosis, and treatment efficacy assessment.