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Tumor vasculature varies widely among patients and is an important factor in disease progression and treatment response. Characterizing tumor fluid flows, often using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), is therefore a key component of disease assessment. In our work, we applied a computational fluid dynamical model we have developed, called the unbalanced regularized optimal mass transport (urOMT) method, to quantify and visualize fluid flow behaviors in breast tumors. Unlike the popular Tofts model, the urOMT model includes cross-voxel transport by solving an advection-diffusion equation. The urOMT outputs can reveal time-varying changes of physical transport properties at a local voxel level and can also visualize directional trend of the cross-voxel flows. Results for DCE-MRI studies of ten breast cancer patients each at four time points during neoadjuvant chemotherapy indicate that urOMT-produced metrics, flux, influx and efflux are potentially valuable biomarkers for evaluating therapeutic responses.
Chen et al. (Tue,) studied this question.