Purpose: Clinical trials have yielded promising results for Lutetium Prostate Specific Membrane Antigen (Lu-PSMA) therapy in metastatic castration resistant prostate cancer (mCRPC) patients. However, the development of precise methods for internal dosimetry and accurate dose estimation has been considered ongoing research. This study aimed to calculate the absorbed dose to the critical organs and metastasis regions using GATE 9.0 Monte Carlo simulation (MCS) as a gold standard to compare the OLINDA 1.1 and IDAC 2.1 software.

Material And Methods: This study investigated absorbed doses to different organs in 9 mCRPC patients during their first treatment cycle. Whole-body planar images were acquired at 1 ± 0.5, 4 ± 0.5, 24 ± 2, 48 ± 2, 72 ± 2, and 144 ± 2 h post-injection, with SPECT/CT images obtained at 24 ± 2 h. Absorbed doses were calculated for five organs and the entire metastasis regions using GATE, OLINDA, and IDAC platforms. The spherical method was used to determine and compare the absorbed doses in metastatic regions and undefined organs in OLINDA and IDAC Phantom.

Results: The organ-absorbed dose calculations produced by GATE were consistent with those obtained from OLINDA and IDAC. The average percentage differences in absorbed dose for all organs between Monte Carlo calculations and the estimated from IDAC and OLINDA were -0.24 ± 2.14% and 5.16 ± 5.66%, respectively. There was a significant difference between GATE and both IDAC (17.55 ± 29.1%) and OLINDA (25.86 ± 18.04%) in determining absorbed doses to metastatic areas using the spherical model.

Conclusion: The absorbed dose of organs in the first treatment cycle remained below tolerable limits. However, cumulative absorbed doses should be considered for the administered activities in the next cycles of treatment. While Monte Carlo, IDAC, and OLINDA results were aligned for organ dose calculations, patient-specific dosimetry may be necessary due to anatomical and functional changes. Accurate dose estimation for undefined organs and metastatic regions using the spherical model is significantly influenced by tissue density, highlighting the value of CT imaging.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11612135PMC
http://dx.doi.org/10.1186/s40658-024-00691-7DOI Listing

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