| dc.description.abstract | 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 compute
S-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. | es_ES |