Contrast-Ultrasound Dispersion Imaging

Advances in contrast-enhanced ultrasound (CEUS) imaging and processing have opened the possibility to perform quantitative measurements of blood flow dynamics and (micro)vascularity. This has been amply explored for cancer imaging, probing the angiogenic processes associated with cancer growth by dedicated contrast-ultrasound dispersion imaging (CUDI) methods. CUDI builds on the idea that contrast intravascular dispersion, better than perfusion, reflects those changes in the microvascular architectures that are caused by cancer angiogenesis. The passage of an intravenously injected bolus of ultrasound contrast agents is imaged by CEUS in the organ of interest. In order to assess the dispersion kinetics of the contrast agent, its transport through the microvascular bed is modeled as a convective-dispersion process. Several parameters can then be estimated that describe contrast dispersion by analysis of either the temporal or the spatiotemporal evolution of the contrast concentration. While temporal analysis requires model fitting of the time-intensity curve (TIC) measured at each pixel, the spatiotemporal analysis is performed by assessment of the similarity between neighboring TICs. Different measures of similarity have been proposed, ranging from spectral coherence to temporal correlation up to the statistical dependency of the TICs through their mutual information. More advanced methods have also been developed by the employment of local deconvolution techniques that allow the separate estimation of contrast velocity and dispersion, providing the possibility to estimate the entropy of the velocity field, which increases in angiogenic microvascular architectures because of their irregular structure. The transition from 2D to 3D CEUS has then paved the way for the development of 3D CUDI techniques. Next to providing more accurate modeling, a 3D approach allows analyzing large volumes, such as the entire prostate, by the intravascular injection of a single contrast agent bolus, thus facilitating the implementation of CUDI in a clinical workflow. This chapter will provide insights into the technical developments of CUDI with emphasis on its applications for kidney and especially prostate imaging.