Mathematical modeling of the combined effects of thermal burn and local irradiation

Radiation combined injury (RCI), resulting from ionizing radiation exposure accompanied by other injuries such as burn, laceration, or fracture, is associated with higher rates of mortality and severe effects. Current available models lack the ability to capture synergistic effects associated with RCI and/or rely on data-driven approaches that are limited in their predictive capabilities. To address this, we developed a mechanistic mathematical model for local radiation exposure combined with burn injury that captures the inflammatory response and early fibroblast activity associated with injury resolution. We utilized sensitivity analysis and parameter sampling methods to leverage limited data. The model was able to reproduce inflammatory and fibroblast behavior consistent with observed thermal injury and combined injury profiles. The formulation of a mechanistic model for combined injury adds increased modeling flexibility allowing for further exploration of the underlying inflammatory mechanisms and provides a framework for leveraging minimal data for improved predictive models of RCI.

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Publication Details

Journal
PLoS ONE
Published
2026-02-10
DOI
https://doi.org/10.1371/journal.pone.0341595
Primary Topic
Effects of Radiation Exposure
Type
article
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article

Mathematical modeling of the combined effects of thermal burn and local irradiation

Quintessa Hay, Rafael G. Henríquez-Rivera, Tyler Dant, Kidist Maxwell et al.
PLoS ONE
Effects of Radiation Exposure
article

Mathematical modeling of the combined effects of thermal burn and local irradiation

Quintessa Hay, Rafael G. Henríquez-Rivera, Tyler Dant, Kidist Maxwell, Rachel Jennings, Amy Creel, Kyle Gaffney, Christina Wagner, Ginu Unnikrishnan
article en

Abstract

Radiation combined injury (RCI), resulting from ionizing radiation exposure accompanied by other injuries such as burn, laceration, or fracture, is associated with higher rates of mortality and severe effects. Current available models lack the ability to capture synergistic effects associated with RCI and/or rely on data-driven approaches that are limited in their predictive capabilities. To address this, we developed a mechanistic mathematical model for local radiation exposure combined with burn injury that captures the inflammatory response and early fibroblast activity associated with injury resolution. We utilized sensitivity analysis and parameter sampling methods to leverage limited data. The model was able to reproduce inflammatory and fibroblast behavior consistent with observed thermal injury and combined injury profiles. The formulation of a mechanistic model for combined injury adds increased modeling flexibility allowing for further exploration of the underlying inflammatory mechanisms and provides a framework for leveraging minimal data for improved predictive models of RCI.

PLoS ONEVol. 21(2)
Computer Algorithms for Medicine (AT), Rocky Mountain Scientific Laboratory (United States) (US), Takeda (United States) (US), Applied Research Associates (United States) (US), Takeda (Japan) (JP)
Good health and well-being
Openalex Percentile: Top 61%
Effects of Radiation Exposure
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Mathematical modeling of the combined effects of thermal burn and local irradiation — Quintessa Hay, Rafael G. Henríquez-Rivera, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS