Development and Application of AcidoCEST MRI for Evaluating Tumor Acidosis in Pre-Clinical Cancer Models

Tumor acidosis is an important biomarker in cancer. We have developed a noninvasive imaging method, termed acidosis Chemical Exchange Saturation Transfer (acidoCEST) MRI to measure extracellular pH (pHe) in the tumor microenvironment. Chapter 1 introduces the importance of measuring tumor acidosis a...

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Bibliographic Details
Main Author: Chen, Liu Qi
Other Authors: Pagel, Mark D.
Language:en_US
Published: The University of Arizona. 2014
Subjects:
MRI
Online Access:http://hdl.handle.net/10150/323450
Description
Summary:Tumor acidosis is an important biomarker in cancer. We have developed a noninvasive imaging method, termed acidosis Chemical Exchange Saturation Transfer (acidoCEST) MRI to measure extracellular pH (pHe) in the tumor microenvironment. Chapter 1 introduces the importance of measuring tumor acidosis and presents various imaging modalities and their shortcoming to measure pHe. Chapter 2 describes the optimization of acidoCEST MRI for in vivo pHe measurement. The acidoCEST MRI protocol consists of a CEST-FISP acquisition and Lorentzian line shape fittings. We determined the optimal saturation time, saturation power and bandwidth, 5 sec, 2.8 µT and 90 Hz respectively. We also tried various routes of administration to increase contrast agent uptake in the tumor. We decided upon 200 µL bolus followed by 150 µL/hr infusion. The optimized acidoCEST MRI protocol was tested on a mammary carcinoma mouse model of MDA- MB-231. Our method can detect an increase in pHe in the bladder and tumor of the mice treated with bicarbonate. We used this optimized acidoCEST MRI method to measure pHe in lymphoma tumor model of Raji, Ramos and Granta 519 as described in Chapter 3. Pixel-wise pHe maps showed tumor heterogeneity. The pHe of Raji, Ramos and Granta 519 were determined to be mildly acidic with no significant difference. Chapter 4 describes the evolution of pixel-wise analysis in more detail. Besides the pHe map and spatial heterogeneity, we were able to determine the % contrast agent uptake. We monitored these biomarkers in two different mammary carcinoma mouse models, MDA- MB-231 and MCF-7 longitudinally and made comparisons between the different tumor models: MCF-7 were more acidic, more heterogeneous and faster growing than MDA- MB-231.