Evaluation and comparison of PENHAN and FLUKA Monte Carlo codes for small-scale dosimetry in targeted radionuclide...

Objective.This study aims to comprehensively compare the PENHAN and FLUKA Monte Carlo codes for low-energy alpha particle transport and small-scale dosimetry using alpha-emitting radionuclides, and to assess their suitability for such applications.Approach.Two studies were performed through Monte Carlo simulations. First, monoenergetic alpha particles (3-10 MeV) were distributed in a micrometric water sphere and the dose deposition within it was calculated. Second, a simplified spherical cell model with uniformly distributed alpha-emitting radionuclides was used to computeS-values. PENHAN and FLUKA results were compared, and potential sources of discrepancy between them were analyzed. In addition, both codes were benchmarked against MIRDcell, an analytical tool widely used for dosimetric calculations in Targeted radionuclide therapy.Main results.In the monoenergetic study, the primary source of discrepancy between PENHAN and FLUKA was the stopping powers used for alpha particles. When the same stopping powers were employed, both codes yielded statistically compatible results, except at 3.0 and 3.5 MeV, where FLUKA showed an anomalous behavior. In the cell model, variations were below 3% but not negligible even when using identical stopping powers, suggesting an additional source of discrepancy: differences in the radionuclide emission spectra, particularly in the electron component. In both studies, PENHAN and FLUKA results were overall in good agreement with those from MIRDcell.Significance.This study demonstrates, for the first time, the suitability of PENHAN for low-energy alpha transport and small-scale dosimetry with alpha emitters, provided that accurate stopping powers are employed. It also supports the reliability of FLUKA in these scenarios and shows that both codes yield compatible results when using consistent stopping power datasets and radionuclide emission spectra. This work further highlights the importance of validating Monte Carlo codes in medical physics to ensure the reliability and reproducibility of their results.