New hybrid voxelized/analytical primitive in Monte Carlo simulations for medical applications

Abstract

Monte Carlo simulations (MCS) applied in particle physics play a key role in medical imaging and particle therapy. In such simulations, particles are transported through voxelized phantoms derived from predominantly patient CT images. However, such voxelized object representation limits the incorporation of fine elements, such as artificial implants from CAD modeling or anatomical and functional details extracted from other imaging modalities. In this work we propose a new hYbrid Voxelized/ANalytical primitive (YVAN) that combines both voxelized and analytical object descriptions within the same MCS, without the need to simultaneously run two parallel simulations, which is the current gold standard methodology. Given that YVAN is simply a new primitive object, it does not require any modifications on the underlying MC navigation code. The new proposed primitive was assessed through a first simple MCS. Results from the YVAN primitive were compared against an MCS using a pure analytical geometry and the layer mass geometry concept. A perfect agreement was found between these simulations, leading to the conclusion that the new hybrid primitive is able to accurately and efficiently handle phantoms defined by a mixture of voxelized and analytical objects. In addition, two application-based evaluation studies in coronary angiography and intra-operative radiotherapy showed that the use of YVAN was 6.5% and 12.2% faster than the layered mass geometry method, respectively, without any associated loss of accuracy. However, the simplification advantages and differences in computational time improvements obtained with YVAN depend on the relative proportion of the analytical and voxelized structures used in the simulation as well as the size and number of triangles used in the description of the analytical object meshes.

Mesh modeling of system geometry and anatomy phantoms for realistic GATE simulations and their inclusion in SPECT reconstruction

“…Thus, each simulation world contains its own material properties, navigator, and geometry. This however hampers the computation efficiency of the simulation, is not yet available in GATE, and may require significant changes to the code itself (Bert et al 2016).…”

“…The surrounding air volume of the voxelized phantom is therefore eliminated by the usage of STL-based objects emulating the human anatomy which define its surface. This approach provides higher realism than primitives for defining the surface and complex interior structures of the human body while improving computation efficiency especially for whole-body simulation for which the use of voxelized phantoms leads to exhaustive memory consumption and computation time (Rogers 2006, Kim et al 2011, Yeom et al 2014, Bert et al 2016, Han et al 2018. In a final section, we described our reconstruction of such realistic GATE simulations employing STL files for modeling the AdaptiSPECT-C and the XCAT attenuation phantom via a 'hybrid' approach, which is based on the use of a voxelized version of the STL-based attenuation phantom employed in the simulation for attenuation correction in reconstruction.…”

MV‐based relative electron density estimation (iMREDe) for MR‐LINAC dose calculation

“…CBCT acquisitions were simulated using the GPU Geant4‐based Monte Carlo Simulations (GGEMS) 10 . GGEMS was recently released as an open‐source tool that can be used to simulate imaging and dosimetry applications using graphics processing units (GPU).…”

“…CBCT acquisitions were simulated using the GPU Geant4-based Monte Carlo Simulations (GGEMS). 10 GGEMS was recently released as an open-source tool that can be used to simulate imaging and dosimetry applications using graphics processing units (GPU).The tool utilizes voxelized volumes to track and detect photons. In this work, a mid-range GPU (NVIDIA RTX3060 with 12GB VRAM) was used to simulate all the CBCT acquisitions.…”

Modeling the impact of prostate edema on LDR brachytherapy: a Monte Carlo dosimetry study based on a 3D biphasic finite element biomechanical model

“…All the dosimetry calculations were based on 5x10 8 emitted particles per simulation with an average dose uncertainty of 2% in the prostate, using a full model of 125I seeds (STM1251, Bard Medical Division, Covington, GA, USA), commonly employedin prostate cancer brachytherapy, and previously modeled in Lemaréchal et al (2015) based on the geometry and composition described in Kirov and Williamson (2001). In addition, the use of a previously proposed hybrid navigator (Bert et al 2016) allowed to consider several seeds close together within the same voxel as well as considering inter-seed interactions as previously described in Lemaréchal et al (2015). Finally, in order to quantify the observed dose differences and potential impact, the V90 prostate (prostate volume receiving the 90% of 145 Gy), D90 prostate, D10 urethra, D2cc rectum and the D10 pubic bones' dose metrics were computed for all the edema scenarios for Day1 and Day30 (conventional and dynamic) dosimetry.…”