99mTc radiolabeled papain nanoparticle: In silico dosimetry evaluation using Monte Carlo codes and the DM_BRA voxel phantom and OLINDA/EXM for internal dosimetry based on experimental biodistribution data

Green nanotechnology has gained prominence in developing biocompatible materials for therapeutic and diagnostic applications in oncology and nuclear medicine. An innovative system was presented, based on papain nanoparticles (P-NPs) synthesized by gamma irradiation and radiolabeled with technetium-99m (99mTc) for molecular imaging using SPECT. Papain, a protease extracted from Carica papaya, exhibits anticancer, antibacterial, and antioxidant properties, making it an excellent nanocarrier for radionuclides. Herein, an in silico dosimetry calculation was performed using the Monte Carlo (MC) codes MCNP6.2 and EGSnrc. The aim was to estimate and compare the absorbed dose per injected activity (mGy/MBq) between these codes in the organs and tissues of the DM_BRA mouse voxelized phantom, using the in vivo biodistribution data for 99mTc-P-NPs. The OLINDA/EXM internal dosimetry software was also used in this study, as it has animal models. Results indicate that 99mTc-P-NPs exhibit high tumor affinity, with a favorable distribution profile for breast cancer imaging. The results showed doses between the MC codes with percentage differences less than 11%, 6%, and 16% for the Healthy Balb/c Mice, 4T1 Tumor-Bearing Mice, and Spontaneous Breast Cancer Mice (MMTV-PyMT), respectively. For the doses obtained in OLINDA/EXM, the smallest percentage difference was 0.3% for MCNP6.2 and 0.2% for EGSnrc, considering all groups. The similarity between experimental data and Monte Carlo calculations highlights the reliability of the simulation method for estimating radiation biodistribution in healthy mice. This comparison underscores the importance of validating computational models with experimental data to ensure accurate predictions of organ-specific dose distributions.