ArticleFrontiers in oncology2023
The complexity of DNA damage by radiation follows a Gamma distribution: insights from the Microdosimetric Gamma Model.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- DNA damage complexity as a predictor of cell survival: a microscopic Monte Carlo-based modeling framework for photon, proton and carbon ion irradiation.Physics in medicine and biology · 2026Article
- Space- and Time-Defined Monte Carlo Dosimetry Explains Ovarian Cancer Cell Viability in Targeted α-Particle Therapy With Astatine 211-ParaThanatrace.International journal of radiation oncology, biology, physics · 2025Article
- Extending the microdosimetry gamma model (MGM) to estimate induced DNA damage and its complexity at macroscopic scale by protons and helium ions.Physics in medicine and biology · 2025Article
- Effects of Radiation Dose on Lubricants: A Review of Experimental Studies.ACS applied materials & interfaces · 2025Review
- NRG Oncology White Paper on the Relative Biological Effectiveness in Proton Therapy.International journal of radiation oncology, biology, physics · 2025Review
- Systematic data analysis pipeline for quantitative morphological cell phenotyping.Computational and structural biotechnology journal · 2024Review
- AMBER: A Modular Model for Tumor Growth, Vasculature and Radiation Response.Bulletin of mathematical biology · 2024Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Introduction: DNA damage is the main predictor of response to radiation therapy for cancer. Its Q8 quantification and characterization are paramount for treatment optimization, particularly in advanced modalities such as proton and alpha-targeted therapy. Methods: We present a novel approach called the Microdosimetric Gamma Model (MGM) to address this important issue. The MGM uses the theory of microdosimetry, specifically the mean energy imparted to small sites, as a predictor of DNA damage properties. MGM provides the number of DNA damage sites and their complexity, which were determined using Monte Carlo simulations with the TOPAS-nBio toolkit for monoenergetic protons and alpha particles. Complexity was used together with a illustrative and simplistic repair model to depict the differences between high and low LET radiations. Results: DNA damage complexity distributions were were found to follow a Gamma distribution for all monoenergetic particles studied. The MGM functions allowed to predict number of DNA damage sites and their complexity for particles not simulated with microdosimetric measurements (yF) in the range of those studied. Discussion: Compared to current methods, MGM allows for the characterization of DNA damage induced by beams composed of multi-energy components distributed over any time configuration and spatial distribution. The output can be plugged into ad hoc repair models that can predict cell killing, protein recruitment at repair sites, chromosome aberrations, and other biological effects, as opposed to current models solely focusing on cell survival. These features are particularly important in targeted alpha-therapy, for which biological effects remain largely uncertain. The MGM provides a flexible framework to study the energy, time, and spatial aspects of ionizing radiation and offers an excellent tool for studying and optimizing the biological effects of these radiotherapy modalities.
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