# Fluorescence tomography plugin unit for spatial monitoring of T cell migration

> **NIH NIH R44** · IN VIVO ANALYTICS, INC. · 2021 · $969,173

## Abstract

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 >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 ...

## Key facts

- **NIH application ID:** 10264164
- **Project number:** 5R44CA243827-03
- **Recipient organization:** IN VIVO ANALYTICS, INC.
- **Principal Investigator:** Alexander D. Klose
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $969,173
- **Award type:** 5
- **Project period:** 2019-09-17 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10264164

## Citation

> US National Institutes of Health, RePORTER application 10264164, Fluorescence tomography plugin unit for spatial monitoring of T cell migration (5R44CA243827-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10264164. Licensed CC0.

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