# Improved optical Monte Carlo simulation through standardization, robustness, and training

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2022 · $239,375

## Abstract

Project Summary/ Abstract
 This application is an administrative supplement to grant R01 EB027130, which develops new optical
Monte Carlo simulation tools for nuclear medicine in the opensource GATE/Geant4 simulators. The work
proposed here will improve these tools through standardization, robustness, and training with the
objective of enabling more users to fully utilize the tools we freely release.
 GATE/Geant4 is the main simulation platform in nuclear imaging and therapy. It includes optical transport
in scintillators, but the optical models are highly inaccurate. We have developed and integrated into GATE a
new optical model, the “LUT Davis model” that addresses this limitation. The two primary objectives of the
parent award are 1) to develop and freely distribute computational tools to generate custom optical surface
LUTs, and 2) to develop optical models for photon timing studies and establish a comprehensive simulation
framework for detector timing optimization. We have developed a free standalone application for users to
describe their custom surfaces, using custom code entirely developed by research scientists and trainees.
This supplement will apply software engineering methods to improve the LUT Davis standalone app
robustness, portability, documentation, and integration in GATE.
Two specific aims are proposed that include software development and new training. Aim 1 will improve the
robustness and flexibility of the LUT Davis app and enhance its responsiveness to the needs of the nuclear
imaging research community. Refactoring the standalone app in one of the most utilized programming
languages (Python) that is freely accessible will be more aligned with our open science philosophy and will
offer the possibility to integrate the optical surface design into simulation frameworks developed by users.
We anticipate this to increase the standalone usage, make the code more reusable, and further accelerate
research. These software developments will be associated with new training dedicated to optical simulation.
 Aim 2 focuses on refactoring the API that calls the GATE LUT Davis model in the simulations. Our 2-
pronged approach will restructure the current GATE source code workflow and prepare for the new GATE
under development. Cleaner code will make simulations faster and more robust by reducing computation
errors and streamlining processes. The new GATE will be entirely Python-based to speed up and ease data
transfer from GATE to analysis tools, overall making it a faster, easier, and more agile simulation toolkit
responsive to dynamic user needs and more compliant with software standards.
Our objective is to increase the impact of these tools by enabling more users to fully utilize the functionalities
we create and release. Empowering the scientific community with enhanced simulation software will
accelerate the development of nuclear imaging technology.

## Key facts

- **NIH application ID:** 10584410
- **Project number:** 3R01EB027130-03S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** Emilie Roncali
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $239,375
- **Award type:** 3
- **Project period:** 2022-09-30 → 2023-09-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10584410

## Citation

> US National Institutes of Health, RePORTER application 10584410, Improved optical Monte Carlo simulation through standardization, robustness, and training (3R01EB027130-03S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10584410. Licensed CC0.

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