Abstract #2004

Quantitative Analysis of Glioblastoma Treatment Using Dynamic Relaxation Contrast MRI at 9.4T

Jia Guo¹, Nanyan Zhu², Yanping Sun³, Sabrina J. Gjerswold-Selleck⁴, Hong-Jian Wei^5,6, Pavan S. Upadhyayula^6,7, Angeliki Mela^6,7, Cheng-Chia Wu^5,6, Peter D. Canoll^6,7, John T. Vaughan⁴, Douglas L. Rothman⁸, and Scott A. Small⁹

¹Department of Psychiatry, and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States, ²Department of Biological Science, Columbia University, New York, NY, United States, ³Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, United States, ⁴Department of Biomedical Engineering, Columbia University, New York, NY, United States, ⁵Department of Radiation Oncology, Columbia University, New York, NY, United States, ⁶Columbia University Irving Medical Center, Columbia University, New York, NY, United States, ⁷Department of Pathology and Cell Biology, Columbia University, New York, NY, United States, ⁸Departments of Diagnostic Radiology, or Biomedical Engineering, Yale University, New Haven, CT, United States, ⁹Departments of Neurology, Radiology or Psychiatry, Columbia University, New York, NY, United States

This abstract describes a novel dynamic T2-relaxation contrast magnetic resonance imaging (DRC-MRI) protocol for mapping the cerebral perfusion dynamics in mice. We demonstrate how to quantify cerebral perfusion dynamics with the proposed DRC modeling, which combines features of both dynamic and the steady-state methods. Quantitative analysis on both simulated and in vivo experimental data are performed. We first validate the reliability of our DRC modeling protocol with healthy mice before we apply the protocol on a tumor treatment study. We are able to demonstrate its ability to model the treatment effect of Etoposide on Glioblastoma in mice.

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