Estimation and Control of Low Dose Radiation Response by Mixed NN of Physical Model and Information Processing Model

2022 Fiscal Year Final Research Report

• Project/Area Number: 19K20396
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 62010:Life, health and medical informatics-related
• Research Institution: National Institute of Technology (KOSEN), Kure College (2021-2022); Tokyo Institute of Technology (2019-2020)
• Principal Investigator: Hattori Yuya 呉工業高等専門学校, 電気情報工学分野, 准教授 (30709803)
• Project Period (FY): 2019-04-01 – 2023-03-31
• Keywords: 数理モデル / 低線量放射線 / 細胞群

Outline of Final Research Achievements

Stress responses in cultured cell populations exposed to low doses of radiation are different from those in high-dose radiation. In this study, based on a cellular automaton model of a three-dimensional cell population, we constructed a neural network model of the intracellular stress response that simulates the spatiotemporal dynamics of the low-dose radiation stress response. Using this model, it was confirmed that experimental data on the dose and time dependence of cell survival response were represented.

Free Research Field

数理生物

Academic Significance and Societal Importance of the Research Achievements

本研究は、細胞群の低線量放射線ストレス応答の予測とメカニズム解明を数理的に実施するための基礎的な研究である。これにより、高線量放射線からの外挿ではない、生体内ストレス応答に基づいた低線量放射線のリスク評価や、放射線治療における照射方法の計画立案への貢献も期待できる。