Investigating tumor perfusion, glycolysis and pH environments with multimodal in vivo imaging

Qi Qi, The University of Western Ontario

Abstract

Background: Cancer cells have a complex microenvironment that helps create optimal conditions for cancer proliferation. Nutrients such as glucose will pass through a tortuous and leaky vascular structure developed by cancer cells, and are subsequently distributed and transported inside the cancer cells to meet their metabolic demands. This leaky and poorly organized vasculature leads to a buildup in the interstitial fluid pressure surrounding the tumor, subsequently resulting in tumor hypoxia. Due to an overreliance on glycolysis, more acid and protons are produced by cancer cells, leading to a more acidic environment which, in combination with tumor hypoxia, often leads to a poor patient outcome. This thesis aims to explore the intrinsic relationship between tumor perfusion, glycolysis and its pH environment using a C6 rat model of glioma.

Methods: All subjects were implanted with 1 million C6 glioma cells using stereotactic surgery. The growth of tumor cells was monitored either with computed tomography perfusion (CTP) or magnetic resonance imaging (MRI). Once tumors had reached the optimal size, tumor perfusion was measured using CTP. Tumor glycolytic metabolism was measured using positron emission tomography (PET) with ¹⁸F-flurodeoxyglucose (FDG) and MR spectroscopy imaging (MRSI) using hyperpolarized [1-¹³C]pyruvate. Chemical exchange saturation (CEST) MRI was also used to investigate tumor glucose distribution (glucose contrast enhancement, or ∆CEST) and pH environments (intra-/extracellular pH, pH_i and pH_e respectively and simultaneously) during/after a glucose infusion/injection. All experimental procedures were completed within 24 hours. Measurements of tumor perfusion, glycolysis, ∆CEST and pH environments were correlated using Pearson’s correlation.

Results: Tumor perfusion measurement of permeability surface-area product (PS) was significantly correlated with tumor glycolysis measurement of Lac:Pyr from hyperpolarized MRSI as well as ∆CEST. Tumor Lac:Pry was also significantly correlated with tumor pH_i. Tumor metabolic rate of glucose derived from dynamic PET was significantly correlated with tumor pH_i and pH_e.

Conclusion: This research showed the possibility of measuring the intracellular and extracellular pH environment simultaneously. Multimodal imaging approaches provided a more complete picture of the tumor microenvironment and helped elucidate the intrinsic relationship between tumor perfusion, glycolysis and the pH environment.