Eugene Kim1, B.
Douglas Ward2, Arvind P. Pathak3
1Department
of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United
States; 2Department of Biophysics, Medical College of Wisconsin,
Milwaukee, WI, United States; 3Russell H. Morgan Department of
Radiology and Radiological Science, The Johns Hopkins University School of
Medicine, Baltimore, MD, United States
The finite perturber method (FPM) and Monte Carlo simulations were used to compute steady-state susceptibility contrast (SSC)-MRI biomarkers of fractional blood volume (FBV), vessel size (VSI), and vessel density (N) for tumor vasculature from μCT data and for an ensemble of randomly oriented cylinders (RC). For the μCT data, the correlations between simulated and true biomarker values were lower and the median errors greater compared to the RC data, indicating that vascular morphology significantly affects the accuracy of these biomarkers. The FPM can be used to elucidate how various biophysical factors affect the SSC-MRI signal and help develop more accurate imaging biomarkers of angiogenesis.