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Abstract #0193

DCE MRI-Based Computational Modeling of Interstitial Fluid Pressure and Velocity in Head and Neck Cancer: Initial Analysis

Eve LoCastro1, Yonggang Lu2, Ramesh Paudyal1, Yousef Mazaheri1,3, Vaios Hatzoglou3, Amaresha K. Shridhar1, Alan Ho4, Nancy Lee5, Joseph Deasy1, and Amita Shukla-Dave1,3

1Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 2Radiology, Medical College of Wisconsin, Milwaukee, WI, United States, 3Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 4Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 5Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States

We applied computational fluid modeling to head-and-neck cancer patients' DCE-MRI data using permeability maps from extended Tofts' model and tumor geometry from imaging. Interstitial fluid pressure (IFP) maps generated from computational fluid modeling depict heterogeneous distribution of elevated IFP and velocity in tumor tissue. We found significant correlation between tumor volume and IFP.

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