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Abstract #3918

An Efficient Computational Approach to Characterize DSC-MRI Signals Arising from Heterogeneous Vascular Networks

Natenael B. Semmineh1, Junzhong Xu1, Christopher Chad Quarles1

1Radiology & Radiological Sciences, Vanderbilt University, Nashville, TN, United States


Given the heterogeneous nature of blood vessels within tissue and the dependence of susceptibility field gradients on vascular geometry the assumption that a linear relationship, with a spatially uniform rate constant termed the vascular susceptibility calibration factor (kp), exists between the CA concentration and the measured transverse relaxation rate change, could significantly impact the reliability of DSC-MRI hemodynamic measurements. We propose the use of an efficient computational method to estimate the extent of kp heterogeneity across normal and tumor tissue and to assess the reliability of DSC-MRI measures of blood volume and blood flow.

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