Fluorescence tomography plugin unit for spatial monitoring of T cell migration

Immunotherapy (IMT) is a cancer treatment that harnesses activated T cells to induce a targeted immune response against cancer. Preclinical IMT research has been limited because there are no effective methods to longitudinally image T cell biodistributions in mouse models, including ovarian cancer. This is an urgent unmet need because the only viable methods to monitor activated T cells, immunohistochemistry and FACs, are both terminal and ex vivo. Whole-body optical imaging of mouse models enables in vivo monitoring of fluorescence-labeled T cells, but light is strongly attenuated by tissue and images taken at the mouse surface are dependent on the optical tissue properties, the animal’s size and pose. There also is no anatomical reference available that could provide a means for required organ delineation along with T cell biodistribution analysis. In addition, manual Region-Of- Interest (ROI) delineation of fluorescence images for further data analysis is highly operator-dependent and time-consuming, resulting in poor data reproducibility and high variability. Therefore, InVivo Analytics seeks funding to develop InVivoFLUOR, an automated data analysis tool for 3D fluorescence tomography (FLt) of mouse models. It is comprised of: (1) a Body Conforming Animal Mold (BCAM) and mirror gantry for multi-view transillumination FLt and spatial registration of the animal’s geometry and pose; (2) an Organ Probability Map (OPM) for providing an organ template and optical tissue parameter distributions for biodistribution analysis and light propagation modeling; and (3) an operator-independent ROI delineation and classification tool for image data analysis that capitalizes on the inherent data congruency provided by the BCAM. In Aim 1, we will improve the FLt tool for multi-view imaging and enable image co-registration across animals with different size. In Aim 2, we will develop an automated ROI delineation and classification tool for producing operator-independent, quantitative, and reproducible study results. In Aim 3, we will automatically analyze fluorescence-labeled T cell biodistributions and co-register them to 3D bioluminescence maps of disseminated ovarian tumors. The ability to instantaneously quantify the T cell distribution in the same animal longitudinally, as opposed to sacrificing a different animal at every time point for T cell counting via FACs or histology, neither of which can identify sites where the activated T cells may be “hiding”, has a significant impact on the development and outcome of new IMTs with high accuracy. InVivoFLUOR will be part of our InVivoAX platform, a cloud-based Software-as-a-Service (SaaS), and will be sold to the pharmaceutical industry and research institutions as add-on to imaging systems with an installed base andgt;3,000 units worldwide. It will enable cross-platform data comparison and analysis, eliminate operator-dependent variability, increase data reproducibility, and will facilitate the translation of new therapeutics.InVivo Analytics seeks funding for developing an imaging and data analysis tool for mapping the 3D spatial biodistribution of fluorescent T cells in a small animal model of ovarian cancer. Analysis of T cell migration currently lacks the ability to obtain 3D spatial maps of T cells in the same animal in longitudinal studies. Therefore, InVivo Analytics will develop a 3D fluorescence tomography and data analysis tool, which can quantify T cell migration in the living animal, thereby allowing accurate monitoring of novel immunotherapies.