Threshold Analysis and Biodistribution of Fluorescently Labeled Bevacizumab in Human Breast Cancer

Maximillian Koch, Johannes S de Jong, Jürgen Glatz, Panagiotis Symvoulidis, Laetitia E Lamberts, Arthur Adams, Mariëtte E.G Kranendonk, Anton G.T. Terwisscha van Scheltinga, Michaela Aichler, Liesbeth Jansen, Jakob de Vries, Marjolijn N. Lub-de Hooge, Carolina P Schröder, Annelies Jorritsma-Smit, Matthijs D Linssen, Esther de Boer, Bert van der Vegt, Wouter B. Nagengast, Sjoerd G. Elias, Sabrina Oliveira, Arjen Witkamp, Willem P.Th.M. Mali, Elsken van der Wall, Beatriz P Garcia-Allende, Paul J Van Diest, Elisabeth G de Vries, Axel Walch, Gooitzen M. van Dam, Vasilis Ntziachristos

Abstract

In vivo tumor labeling with fluorescent agents may assist endoscopic and surgical guidance for cancer therapy as well as create opportunities to directly observe cancer biology in patients. However, malignant and non-malignant tissues are usually distinguished on fluorescence images by applying empirically determined fluorescence intensity thresholds. Here we report the development of fSTREAM, a set of analytic methods designed to streamline the analysis of surgically excised breast tissues by collecting and statistically processing hybrid multi-scale fluorescence, color, and histology readouts toward precision fluorescence imaging. fSTREAM addresses core questions of how to relate fluorescence intensity to tumor tissue and how to quantitatively assign a normalized threshold that sufficiently differentiates tumor tissue from healthy tissue. Using fSTREAM we assessed human breast tumors stained in vivo with fluorescent bevacizumab at microdose levels Showing that detection of such levels is achievable, we validated fSTREAM for high-resolution mapping of the spatial pattern of labeled antibody and its relation to the underlying cancer pathophysiology and tumor border on a per patient basis. We demonstrated a 98% sensitivity and 79% specificity when using labelled bevacizumab to outline the tumor mass. Overall, our results illustrate a quantitative approach to relate fluorescence signals to malignant tissues and improve the theranostic application of fluorescence molecular imaging.