The Microdosimetric Gamma Model: A Novel Approach to Predict Analytically DNA Damage Based on In-Silico Simulations

Alejandro Bertolet

Massachusetts General Hospital and Harvard Medical School

"The Microdosimetric Gamma Model: A Novel Approach to Predict Analytically DNA Damage Based on In-Silico Simulations"

Purpose: Quantifying and characterizing DNA damage is critical for optimizing radiation therapy treatments, particularly in advanced modalities like proton and alpha-targeted therapy. This study presents the Microdosimetric Gamma Model (MGM), a novel approach that predicts DNA damage properties by utilizing microdosimetry theory. Methods: MGM provides the number of DNA damage sites and their complexities, which follow a Gamma distribution. Unlike current methods, MGM can characterize DNA damage for beams with multi-energy components, various time configurations, and spatial distributions. The output can be incorporated into repair models to predict cell killing, protein recruitment, chromosome aberrations, and other biological effects. We validated the MGM using TOPAS-nBio simulations for various radiation types. Results: MGM demonstrated excellent agreement with the simulated data, accurately predicting damage complexities for protons and alpha particles. We also predicted survival fraction curves for different cell lines, providing insights into the relative biological effectiveness (RBE) of different radiation types. Conclusions: The Microdosimetric Gamma Model offers a flexible framework for studying ionizing radiation's energy, time, and spatial aspects. It is a valuable tool for understanding and optimizing the biological effects of radiation therapy modalities like proton therapy, targeted alpha therapy, and helium therapy.

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