Pharmacokinetic modeling of targeted microbubbles: applications in angiogenesis imaging and therapy monitoring

Introduction The recognition of the key role of angiogenesis for cancer growth has opened new frontiers in oncology1. In cancer therapy, the development of novel drugs aimed at blocking angiogenic processes has spurred the need for imaging biomarkers able to assess and predict the response to therapy. In response, targeted contrast agents have been developed providing selective enhancement in areas of active angiogenesis by binding to specific molecules over-expressed in angiogenic tumor vasculature. In the context of ultrasound molecular imaging (USMI), the first and currently only clinical-translatable targeted ultrasound contrast agent (tUCA) is obtained from conventional UCA by decoration of the microbubble shell with ligands targeting the vascular endothelial growth receptor factor 2 (VEGFR2), over-expressed in several solid tumors1. Assessment of the level of binding has been adopted as an indirect way of quantifying angiogenesis. Semi-quantitatively, this is done by looking at the late-enhancement (LE) several minutes after injection, often in conjunction with the application of a high-pressure US burst to derive the differential targeted enhancement (dTE), i.e., the difference in the acoustic signal before and after the application of the high-pressure burst1,2. For quantitative assessment, we recently proposed pharmacokinetic modeling of the binding kinetics of tUCA by the first-pass binding model (FPB), enabling quantification of angiogenesis by estimation of the microbubble binding rate (Kb)3. Here, we show the feasibility of the method for angiogenesis imaging in 11 rat models of prostate cancer, and for therapy monitoring of colorectal cancer in 17 mice undergoing anti-angiogenic treatment. Methods Time-intensity curves extracted at each pixel/voxel of USMI loops were fitted by the FPB model for estimation of the microbubble binding rate Kb. This was compared to semi-quantitative assessment by LE and dTE for: (i) angiogenesis imaging of prostate cancer by comparing parameter values in cancer and healthy regions of interest (ROIs) in 11 rats; (ii) anti-angiogenic therapy monitoring by comparing parameter values in responders, non-responders, and control mice at 5 time points during anti-angiogenic treatment. Results and Discussion Table I shows the differences in USMI parameters in healthy and tumor ROIs, obtained in 11 prostate-tumor bearing rats. Figure 1 shows the changes in USMI parameters during antiangiogenic treatment, obtained in 17 colorectal cancer-bearing mice. The results suggest the microbubble binding rate Kb to be a promising quantitative biomarker of angiogenesis, enabling the distinction between healthy and cancer tissue, and the early prediction of the response to anti-antiangiogenic therapy.