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1.
Biomed Phys Eng Express ; 10(3)2024 Apr 04.
Artigo em Inglês | MEDLINE | ID: mdl-38518360

RESUMO

The Accurate dosage prediction in Radiation Therapy is challenging, prompting a need for precision beyond conventional clinical Treatment Planning Systems (TPS). Monte Carlo-based methods are sought for their superior accuracy. The aim of this study is to compare dose distributions between the ACUROS algorithm and the GATE platform in various tissue densities and field sizes, focusing on smaller fields. This study was initiated with a homogeneous validation of the TrueBeam STX system, using measurements obtained from the Centre Hospitalier Interregional Edith Cavell (CHIREC) in Brussels. The validation compared dosimetric functions (Percentage Depth Dose (PDD), Dose profile (DP) and Collimator scatter fraction (CSF)) employing the GAMMA index with a 2% / 2 mm criterion tolerance. Following this, heterogeneous studies examined dose distributions between the ACUROS algorithm and the GATE platform in various tissue densities and field sizes, with a specific focus on smaller fields. Simulations were conducted using both platforms on chest phantoms with heterogeneous slabs representing bone, lung, and heart, each housing a central tumor. The impact of electronic equilibrium on tumors for different small field sizes was evaluated. Results showed a remarkable 99% agreement between measurements and GATE calculations in the homogeneous validation of the TrueBeam STX system. However, in heterogeneous studies, ACUROS consistently overestimated lung doses by up to 8% compared to GATE simulation, especially evident with a flattening filter and smaller beam sizes at density interfaces. This highlights significant dose estimation discrepancies between ACUROS and GATE, emphasizing the need for precise calculations. The findings support exploring Monte Carlo-based methods for enhanced accuracy in Radiation Therapy treatment planning.


Assuntos
Radiometria , Planejamento da Radioterapia Assistida por Computador , Planejamento da Radioterapia Assistida por Computador/métodos , Simulação por Computador , Algoritmos , Pulmão
2.
Phys Med ; 54: 189-199, 2018 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-30017561

RESUMO

The new developments of the FLUKA Positron-Emission-Tomography (PET) tools are detailed. FLUKA is a fully integrated Monte Carlo (MC) particle transport code, used for an extended range of applications, including Medical Physics. Recently, it provided the medical community with dedicated simulation tools for clinical applications, including the PET simulation package. PET is a well-established imaging technique in nuclear medicine, and a promising method for clinical in vivo treatment verification in hadrontherapy. The application of clinically established PET scanners to new irradiation environments such as hadrontherapy requires further experimental and theoretical research to which MC simulations could be applied. The FLUKA PET tools, besides featuring PET scanner models in its library, allow the configuration of new PET prototypes via the FLUKA Graphical User Interface (GUI) Flair. Both the beam time structure and scan time can be specified by the user, reproducing PET acquisitions in time, in a particle therapy scenario. Furthermore, different scoring routines allow the analysis of single and coincident events, and identification of parent isotopes generating annihilation events. Two reconstruction codes are currently supported: the Filtered Back-Projection (FBP) and Maximum-Likelihood Expectation Maximization (MLEM), the latter embedded in the tools. Compatibility with other reconstruction frameworks is also possible. The FLUKA PET tools package has been successfully tested for different detectors and scenarios, including conventional functional PET applications and in beam PET, either using radioactive sources, or simulating hadron beam irradiations. The results obtained so far confirm the FLUKA PET tools suitability to perform PET simulations in R&D environment.


Assuntos
Método de Monte Carlo , Tomografia por Emissão de Pósitrons/métodos , Processamento de Imagem Assistida por Computador , Razão Sinal-Ruído
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