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pH-weighted Molecular Magnetic Resonance Imaging in Gliomas


Magnetic resonance imaging is an integral part of medical diagnoses, treatment, and evaluation of patients with brain tumors. While standard anatomical imaging is useful, it does not provide information about molecular-level tumor characteristics that may spatially and temporally vary throughout the tumor. As such, there remains a need for the development of novel MRI techniques that can be used for evaluation of tumor growth and treatment response in patients with glioma undergoing radiochemotherapy. Extracellular acidosis is a hallmark of cancer and is intertwined with other common characteristics of the tumor microenvironment including hypoxia and angiogenesis. Therefore, the central objective of this dissertation was to develop a non-invasive imaging technique for identifying regions of acidosis within glioma and surrounding tissues using MRI. The most common types of glioma are highly aggressive and often require radiochemotherapy, which can result in variable responses across the patient population. Information about the acidity characteristics of these gliomas and the surrounding tissue may allow us to more accurately select targets for biopsy and radiation therapy, identify which patients are responding well to treatment, and predict prognosis.

Chemical exchange saturation transfer (CEST) MRI is a molecular imaging technique that generates contrast indirectly from protons on labile functional groups such as amines, amides, and hydroxyls. CEST image contrast is dependent on the exchange rate between bulk water protons and these functional groups, which is in turn dependent upon local pH. Because of this, we hypothesized that we could utilize CEST MRI for pH-weighted imaging in human tissues. By developing simulations of the Bloch-McConnell equations governing chemical exchange, we have shown that the CEST contrast generated by fast-exchanging amino acid amine protons increases with decreasing pH within a physiologically relevant range (6.0-7.4). We have also incorporated experimental scan parameters into these simulations to more accurately simulate the CEST contrast obtained during clinical data acquisition. Data were acquired in amino acid phantoms at varying pH and concentration, verifying our image contrast was dependent on pH. Our pH-weighted MRI sequence was also applied in animal models of glioma, providing evidence it can be used to generate unique contrast within tumors and can serve as a potential biomarker for response to treatment.

Our CEST MRI method was then applied serially in a cohort of glioblastoma patients undergoing treatment with standard radiochemotherapy, along with select cases of patients undergoing targeted biopsy. Results showed that tumor acidity characteristics were predictive of progression-free survival in the glioblastoma patient cohort. Acidity of targets selected for biopsy on pH-weighted images was indicative of tumor within those biopsy samples. To improve the imaging time of our sequence, we then upgraded the readout to utilize echo-planar imaging (EPI) rather than the standard gradient echo method. This allowed for whole brain coverage and multiple averages within a reduced scan time. The pH-weighted CEST-EPI sequence was applied in healthy volunteers and in a cohort of glioma patients prior to biopsy, in order to select targets for biopsy in regions of acidic and non-acidic tumor tissue. A subset of these patients also underwent PET imaging using 18F-FDOPA, an amino acid analog, near the time of their their pH-weighted scan. 18F-FDOPA uptake was shown to correlate quantitatively and qualitatively with regions of acidity, although pH-weighted imaging provided unique contrast in some cases. pH-weighted MRI was also acquired in recurrent glioblastoma patients before and after the start of treatment with bevacizumab. Acidity was shown to decrease after bevacizumab treatment, and in some cases acidic regions with no apparent contrast enhancement were shown to develop contrast enhancement on follow-up images, indicating that acidic lesions on pH-weighted MRI may be predictive of further tumor growth. Two additional advanced pH-weighted CEST MRI techniques were also implemented. CEST-EPI with a multi-echo readout was developed and acquired in a small cohort of glioma patients. The short and long echoes can provide sensitivity to more and less restricted water molecules, respectively. Separately, our CEST simulation incorporating T1 and T2 maps was used to quantitatively calculate estimates of pH in each image voxel for a subset of patients and animal models. This allows us to correct for T1 and T2 effects and generate numerical estimates of pH rather than pH-weighted images.

Together, these experiments and results present a comprehensive description of pH-weighted molecular MRI in gliomas. This technique has the potential to be implemented clinically for detection of acidosis in gliomas and other brain pathologies.

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