Cross-Modality Imaging of Murine Tumor Vasculature—a Feasibility Study

Lydia M. Zopf, Patrick Heimel, Stefan H. Geyer, Anoop Kavirayani, Susanne Reier, Vanessa Fröhlich, Alexander Stiglbauer-Tscholakoff, Zhe Chen, Lukas Nics, Jelena Zinnanti, Wolfgang Drexler, Markus Mitterhauser, Thomas Helbich, Wolfgang J. Weninger, Paul Slezak, Anna Obenauf, Katja Bühler, Andreas Walter
Molecular Imaging and Biology2021
Tumor vasculature and angiogenesis play a crucial role in tumor progression. Their visualization is therefore of utmost importance to the community. In this proof-of-principle study, we have established a novel cross-modality imaging (CMI) pipeline to characterize exactly the same murine tumors across scales and penetration depths, using orthotopic models of melanoma cancer. This allowed the acquisition of a comprehensive set of vascular parameters for a single tumor. The workflow visualizes capillaries at different length scales, puts them into the context of the overall tumor vessel network and allows quantification and comparison of vessel densities and morphologies by different modalities. The workflow adds information about hypoxia and blood flow rates. The CMI approach includes well-established technologies such as magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), and ultrasound (US), and modalities that are recent entrants into preclinical discovery such as optical coherence tomography (OCT) and high-resolution episcopic microscopy (HREM). This novel CMI platform establishes the feasibility of combining these technologies using an extensive image processing pipeline. Despite the challenges pertaining to the integration of microscopic and macroscopic data across spatial resolutions, we also established an open-source pipeline for the semi-automated co-registration of the diverse multiscale datasets, which enables truly correlative vascular imaging. Although focused on tumor vasculature, our CMI platform can be used to tackle a multitude of research questions in cancer biology.
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