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<p>Modeling radiation-induced DNA damage is essential for understanding the relative biological effectiveness (RBE) of ionizing radiation. This study presents a simplified framework using the density-based spatial clustering of applications with noise (DBSCAN) algorithm and using simulated physical track structures to characterize DNA damage induced by 0.5–200&#xa0;MeV protons. The model assumed that (i) energy deposition ≥ 17.5&#xa0;eV induced DNA damage, (ii) at least two damage points within a distance <i>ε</i> formed a cluster, (iii) isolated damage points were treated as noises, and (iv) the cluster-to-noise ratio corresponded to the double strand break (DSB)-to-single strand break (SSB) yield ratio. From the clustering output, a new beam quality metric called Quality of Beam (QoB; clusters per particle per µm) and its normalized form (clusters per keV of deposited energy) were defined. For protons, normalized QoB exhibited a strong linear correlation with DSB yields, enabling direct estimation of DSB and SSB yields using a single conversion factor. Applying the same framework and model parameters to carbon ions revealed a similar linear relationship between normalized QoB and DSB yields up to LET values of 200&#xa0;keV µm⁻¹, beyond which the overkill effect emerged. The normalized QoB qualitatively reproduced RBE–LET trends and offered a biologically meaningful alternative to conventional metrics such as LET. Compared to full water radiolysis modeling, the DBSCAN framework was computationally efficient and provided a robust method for assessing ion beam quality and predicting DNA damage yields.</p>

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Predicting DNA damage yields and assessing beam quality for protons and carbon ions using a DBSCAN algorithm

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月24日

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  • Sanhanat Chaibura,
  • Thiansin Liamsuwan

摘要

Modeling radiation-induced DNA damage is essential for understanding the relative biological effectiveness (RBE) of ionizing radiation. This study presents a simplified framework using the density-based spatial clustering of applications with noise (DBSCAN) algorithm and using simulated physical track structures to characterize DNA damage induced by 0.5–200 MeV protons. The model assumed that (i) energy deposition ≥ 17.5 eV induced DNA damage, (ii) at least two damage points within a distance ε formed a cluster, (iii) isolated damage points were treated as noises, and (iv) the cluster-to-noise ratio corresponded to the double strand break (DSB)-to-single strand break (SSB) yield ratio. From the clustering output, a new beam quality metric called Quality of Beam (QoB; clusters per particle per µm) and its normalized form (clusters per keV of deposited energy) were defined. For protons, normalized QoB exhibited a strong linear correlation with DSB yields, enabling direct estimation of DSB and SSB yields using a single conversion factor. Applying the same framework and model parameters to carbon ions revealed a similar linear relationship between normalized QoB and DSB yields up to LET values of 200 keV µm⁻¹, beyond which the overkill effect emerged. The normalized QoB qualitatively reproduced RBE–LET trends and offered a biologically meaningful alternative to conventional metrics such as LET. Compared to full water radiolysis modeling, the DBSCAN framework was computationally efficient and provided a robust method for assessing ion beam quality and predicting DNA damage yields.