ArticlePhysical review. E2021
Generalized stochastic microdosimetric model: The main formulation.
Article in Physical review. E, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 21 citations in OpenAlex.
- Particle Beam Radiobiology Status and Challenges: A PTCOG Radiobiology Subcommittee Report.International journal of particle therapy · 2024Review
- A spatial measure-valued model for radiation-induced DNA damage kinetics and repair under protracted irradiation condition.Journal of mathematical biology · 2024Article
- On the Emergence of the Deviation from a Poisson Law in Stochastic Mathematical Models for Radiation-Induced DNA Damage: A System Size Expansion.Entropy (Basel, Switzerland) · 2023Article
- The complexity of DNA damage by radiation follows a Gamma distribution: insights from the Microdosimetric Gamma Model.Frontiers in oncology · 2023Article
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Authors and funding
6 authors at 1 institution in 2 countries.
Funding
Abstract
The present work introduces a rigorous stochastic model, called the generalized stochastic microdosimetric model (GSM^{2}), to describe biological damage induced by ionizing radiation. Starting from the microdosimetric spectra of energy deposition in tissue, we derive a master equation describing the time evolution of the probability density function of lethal and potentially lethal DNA damage induced by a given radiation to a cell nucleus. The resulting probability distribution is not required to satisfy any a priori conditions. After the initial assumption of instantaneous irradiation, we generalized the master equation to consider damage induced by a continuous dose delivery. In addition, spatial features and damage movement inside the nucleus have been taken into account. In doing so, we provide a general mathematical setting to fully describe the spatiotemporal damage formation and evolution in a cell nucleus. Finally, we provide numerical solutions of the master equation exploiting Monte Carlo simulations to validate the accuracy of GSM^{2}. Development of GSM^{2} can lead to improved modeling of radiation damage to both tumor and normal tissues, and thereby impact treatment regimens for better tumor control and reduced normal tissue toxicities.
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