# TOPIC 421: BUILDING THE WORLD'S FIRST CLINICAL OXYGEN IMAGER FOR EFFICIENT CANCER TREATMENT

> **NIH NIH N43** · O2M TECHNOLOGIES, LLC · 2021 · $400,000

## Abstract

2019 Nobel prize in medicine for the discovery of oxygen signaling pathways highlights the importance of oxygenation as a physiologic parameter. Oxygenation plays a key role in cancer development and may affect its aggressiveness. Tumors have a highly heterogeneous oxygen environment which affects the outcome of chemo- and radiation treatment. Hypoxia, or low oxygenation, is an obstacle to successful cancer treatment. The accurate measurement of tissue oxygenation is necessary for oxygen guided radiation therapy (OGRT) that reduces the overall radiation dose. However, currently, clinicians do not have access to a quantitative oxygen imager that can be utilized for cancer treatment. In this Phase I proposal, we will
develop a human-size oxygen imaging instrument based on electron paramagnetic resonance oxygen imaging principles. The instrument will be tested with phantoms and a pilot rabbit study for its ability to provide 3D oxygen maps of a leg born VX-2 tumor. The success of this project will bring a translational technology from preclinical research to the clinical domain with a new product in the market, CAELI-9.

## Key facts

- **NIH application ID:** 10492291
- **Project number:** 75N91021C00034-0-9999-1
- **Recipient organization:** O2M TECHNOLOGIES, LLC
- **Principal Investigator:** MRIGNAYANI KOTECHA
- **Activity code:** N43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $400,000
- **Award type:** —
- **Project period:** 2021-09-16 → 2022-06-15

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10492291

## Citation

> US National Institutes of Health, RePORTER application 10492291, TOPIC 421: BUILDING THE WORLD'S FIRST CLINICAL OXYGEN IMAGER FOR EFFICIENT CANCER TREATMENT (75N91021C00034-0-9999-1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10492291. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*