Fractal dimension of tumor microvasculature by dynamic contrast-enhanced ultrasound

Angiogenesis plays a fundamental role in the growth of several types of cancer. Characterization of the microvascular architecture has therefore gained attention as a possible tool for cancer localization. However, the available options to assess the main features characterizing the microvascular architecture require immunohistological analysis of the resected tumors. Contrast-enhanced ultrasound (CEUS) provides new options for minimally-invasive investigation of the microvasculature by spatiotemporal analysis of the ultrasound-contrast-agent (UCA) transport kinetics. In this work, we propose a novel method to analyze CEUS data. The fractal dimension (FD) of the flow distribution is employed as a geometrical feature to characterize the microvascular architecture. To this end, the fractal dimension of parametric maps reflecting blood flow, such as UCA wash-in rate and peak enhancement, is derived for areas representing different microvascular architectures. Subcutaneous xenograft models of DU-145 and PC-3 prostate-cancer lines in mice were employed as they show marked differences in the spatial distribution of the microvascular density (MVD) inside the tumor. The ability of the method to differentiate between these models was therefore evaluated. For validation purposes, comparison with immunohistological MVD and FD assessment, as well as with UCA dispersion maps, was also performed. The results show good agreement between FD and MVD assessment, with the proposed method able to differentiate between the two cancer lines.