Research on the proximity functions of microdosimetry of low energy electrons in liquid water based on different Monte Carlo codes

MIMC-β: microdosimetric assessment method for internal exposure ofβ-emitters based on mesh-type cell cluster model

The method combining Monte Carlo (MC) simulation and mesh-type cell models provides a way to accurately assess the cellular dose induced byβ-emitters. Although this approach allows for a specific evaluation of various nuclides and cell type combinations, the associated time cost for obtaining results is relatively high. In this work, we propose a Microdosimetric assessment method for Internal exposure ofβ-emitters based on Mesh-type Cell cluster models (abbreviated as MIMC-β). This approach is applied to evaluate the dose in various types of cells (human bronchial epithelial cells, BEAS-2B; normal human liver cells, L-O2; and normal human small intestine epithelial cells, FHs74Int) exposed toβ-emitters. Furthermore, microdosimetric quantity based on the cell cluster model are employed to estimate the relative biological effectiveness (RBE) ofβ-emitters. The results indicate that this method can accurately and rapidly predict cellular doses caused by different types ofβ-emitters, significantly mitigating the efficiency challenges associated with directly employing MC to estimate the overall dose of the mesh-type cell cluster model. In comparison with results obtained from direct simulations of uniform administration ofβ- sources using PHITS for validation, the cellular cluster overallS-values obtained through MIMC-βshow discrepancies mostly below 5%, with the minimum deviation reaching 1.35%. Small sampling sizes within the cell nucleus led to larger average lineal energies. In comparison to C-14, the differences in cellular cluster average lineal energy for Cs-134, Cs-137, and I-131 are negligible, resulting in close numerical estimations of RBE based on lineal energy. The MIMC-βcan be extended to diverse cell types andβ-emitters. Additionally, the RBE assessment based on the cell cluster model offers valuable insights for predicting radiobiological damage resulting from internal exposure byβ-emitters. This method is expected to find applicability in various realistic scenarios, including radiation protection and radioligand therapy.