Imaging of the dispersion coefficient of Ultrasound contrast agents by Wiener system identification for prostate cancer localization

Prostate cancer (PCa) is the most prevalent form of cancer in Western men; however, reliable tools for PCa detection and localization are lacking. Dynamic Contrast Enhanced Ultrasound (DCE-US) is a diagnostic tool that allows analysis of vascularization, by imaging an intravenously injected microbubble bolus. The localization of angiogenic vascularization associated with the development of tumors is of particular interest. Recently, methods aiming at estimating contrast dispersion to localize angiogenesis have shown promise. However, independent estimation of dispersion was not possible due to the ambiguity between dispersive and convective processes. Therefore, in this study we propose a new method that considers the vascular network as a dynamic linear system, whose impulse response can be locally identified by solving the Wiener-Hopf equations. To facilitate characterization, model-based parameter estimation is employed, permitting the determination of the apparent dispersion coefficient (D), velocity (v), and Péclet number (Pe) of the system. A preliminary clinical evaluation using data recorded from 10 patients shows that the proposed method can be applied effectively to DCE-US, and is able to locally characterize the hemodynamics in the prostate.