GATE Monte Carlo dosimetry in 90Y TARE planning: influence of simulation parameters and image resampling on dosimetric accuracy and optimization of computational times

Daniele Pistone, Antonio Italiano, Lucrezia Auditore, Ernesto Amato, Alfredo Campennì, Sergio Baldari


Direct Monte Carlo (MC) simulation is considered the gold standard approach for internal dosimetry in nuclear medicine, and it is increasingly used in planning Trans-Arterial Radio-Embolization (TARE) of HepatoCellular Carcinoma (HCC) {and hepatic metastases}. However its computational times, longer with respect to other simplified approaches, constitute a limiting factor, especially when dealing with {large size and finely discretized voxelized volumes}. Aim of this work was the investigation of the influence of cuts on the production of secondary particles and of input CT images resamplings on dosimetric accuracy and computational time in patient-specific voxel-level MC simulations of 90Y-labelled glass microspheres TARE treatment, to find optimal combinations of settings for speeding up such simulations. GATE GEANT4 interface was used to perform simulations employing CT and 99mTc SPECT as input data, examining multiple CT resolutions (via CT resamplings characterized by voxel volume factors 2, 8, and 64 with respect to native one, and a CT resampling with SPECT resolution) and production cuts (0.01 mm, 0.05 mm, 0.1 mm, 0.5 mm and some more, specific for each resampling). Increasing cut length and reducing CT resolution produces an early rapid decrease followed by a late slow decrease of simulation time as a function of this two parameters. A reduction up to 30% with respect to reference simulation time, while preserving acceptable dosimetric accuracy, was obtained. The best combination of settings among the examined ones resulted the choice of CT resampling with 8 times the native voxel volume and of 0.1-0.5 mm cut, ensuring dosimetric agreement within 1% in liver-related VOIs, while reducing simulation time to 45%.


Internal dosimetry; TARE; 90 Y; Monte Carlo; GATE; GEANT4.

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Copyright (c) 2021 Daniele Pistone, Antonio S. Italiano, Lucrezia Auditore, Ernesto Amato, Alfredo Campennì, Sergio Baldari

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