The aim of this work is validating the Monte Carlo Internal Dosimetry (MCID) tool for internal dosimetry, which allows personalized treatment planning starting from patient-specific images and direct Monte Carlo (MC) simulations. The absorbed dose for different computational phantoms, calculated with MC and with conventional MIRD methods at both organ and voxel level, were compared, obtaining differences of about 0.3% and within 3%, respectively, whereas differences increased (up to 14%) introducing tissue heterogeneities in phantoms. The absorbed dose of spheres with different radius (10 mm ≤ r ≤ 30 mm), calculated from MC code and from OLINDA/EXM was also compared, obtaining differences varying in the range 2–9% after correcting for partial volume effects (PVEs) from imaging. This work validated the MCID tool which allows the fast generation of input macros for MC simulations, starting from patient-specific images. It also shows the impact of tissue inhomogeneities on dosimetric results and their relevance for an accurate dosimetric plan.
A. Milano, A.V.G. (2022). In silico validation of MCID tool for voxel dosimetry applied to 90Y radioembolization of liver malignancies. IL NUOVO CIMENTO C, 45(6), 1-4 [10.1393/ncc/i2022-22197-1].
In silico validation of MCID tool for voxel dosimetry applied to 90Y radioembolization of liver malignancies
N. Lanconelli;
2022
Abstract
The aim of this work is validating the Monte Carlo Internal Dosimetry (MCID) tool for internal dosimetry, which allows personalized treatment planning starting from patient-specific images and direct Monte Carlo (MC) simulations. The absorbed dose for different computational phantoms, calculated with MC and with conventional MIRD methods at both organ and voxel level, were compared, obtaining differences of about 0.3% and within 3%, respectively, whereas differences increased (up to 14%) introducing tissue heterogeneities in phantoms. The absorbed dose of spheres with different radius (10 mm ≤ r ≤ 30 mm), calculated from MC code and from OLINDA/EXM was also compared, obtaining differences varying in the range 2–9% after correcting for partial volume effects (PVEs) from imaging. This work validated the MCID tool which allows the fast generation of input macros for MC simulations, starting from patient-specific images. It also shows the impact of tissue inhomogeneities on dosimetric results and their relevance for an accurate dosimetric plan.File | Dimensione | Formato | |
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