# PHASE I FAST TRACK TOPIC 461 CONFORMABLE SCINTILLATOR ARRAY FOR IN VIVO DOSIMETRY DURING RT

> **NIH NIH N43** · DOSEOPTICS, LLC · 2024 · $394,578

## Abstract

Real-time, optical imaging of dose and dose rate on the surface of a patient can be achieved with a new product methodology: a deformable scintillator array placed on the patient’s surface for imaging by a camera system mounted in the radiotherapy treatment room for both conventional and ultra-high dose rate (UHDR) deliveries. Additionally, a flat panel style scintillator could be placed for pre-treatment quality assurance (QA) of complex patient deliveries, specifically UHDR treatments. The seamless electronic readout of dose and dose rate delivery via high resolution, fast imaging, provides a treatment verification system that eliminates the labor and time required of existing in vivo dosimetry tools and that fills a gap in UHDR dosimetry. The goal of this project is to advance the development of scintillation imaging as a
reliable tool for dose and dose rate validation of FLASH and conventional radiotherapy beams. Phase I of this proposal is aimed at building and characterizing a prototype system; the Phase II proposal seeks to further advance the prototypes developed and tested in Phase I towards clinical implementation, via batch manufacturing, software upgrades, user testing, and the first clinical install.

## Key facts

- **NIH application ID:** 11210780
- **Project number:** 75N91024C00083-0-9999-1
- **Recipient organization:** DOSEOPTICS, LLC
- **Principal Investigator:** Petr Bruza
- **Activity code:** N43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $394,578
- **Award type:** —
- **Project period:** 2024-09-16 → 2025-09-15

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11210780

## Citation

> US National Institutes of Health, RePORTER application 11210780, PHASE I FAST TRACK TOPIC 461 CONFORMABLE SCINTILLATOR ARRAY FOR IN VIVO DOSIMETRY DURING RT (75N91024C00083-0-9999-1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11210780. Licensed CC0.

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