RESUMO
The advantage of proton therapy as compared to photon therapy stems from the Bragg peak effect, which allows protons to deposit most of their energy directly at the tumor while sparing healthy tissue. However, even with such benefits, proton therapy does present certain challenges. The biological effectiveness differences between protons and photons are not fully incorporated into clinical treatment planning processes. In current clinical practice, the relative biological effectiveness (RBE) between protons and photons is set as constant 1.1. Numerous studies have suggested that the RBE of protons can exhibit significant variability. Given these findings, there is a substantial interest in refining proton therapy treatment planning to better account for the variable RBE. Dose-average linear energy transfer (LETd) is a key physical parameter for evaluating the RBE of proton therapy and aids in optimizing proton treatment plans. Calculating precise LETddistributions necessitates the use of intricate physical models and the execution of specialized Monte-Carlo simulation software, which is a computationally intensive and time-consuming progress. In response to these challenges, we propose a deep learning based framework designed to predict the LETddistribution map using the dose distribution map. This approach aims to simplify the process and increase the speed of LETdmap generation in clinical settings. The proposed CycleGAN model has demonstrated superior performance over other GAN-based models. The mean absolute error (MAE), peak signal-to-noise ratio and normalized cross correlation of the LETdmaps generated by the proposed method are 0.096 ± 0.019 keVµm-1, 24.203 ± 2.683 dB, and 0.997 ± 0.002, respectively. The MAE of the proposed method in the clinical target volume, bladder, and rectum are 0.193 ± 0.103, 0.277 ± 0.112, and 0.211 ± 0.086 keVµm-1, respectively. The proposed framework has demonstrated the feasibility of generating synthetic LETdmaps from dose maps and has the potential to improve proton therapy planning by providing accurate LETdinformation.
Assuntos
Aprendizado Profundo , Terapia com Prótons , Terapia com Prótons/métodos , Prótons , Transferência Linear de Energia , Eficiência Biológica Relativa , Método de Monte Carlo , Planejamento da Radioterapia Assistida por Computador/métodosRESUMO
This paper introduced the current situation of medical equipment. Based on the current problems such as technology assessment difficulty, weak consciousness on maintenance management, less quality control during clinic use and backward information level, the standardized management based on the whole process quality control was proposed. Combined the whole process quality control system with the construction of quality management information, the management level of the medical equipment was enhanced. The application of standardized management based on the whole process quality control can make the medical equipment work better in the clinic and set a good foundation for the development of hospital.
Assuntos
Hospitais , Gestão da Informação , Manutenção , Controle de Qualidade , Padrões de ReferênciaRESUMO
PURPOSE: To study the dosimetric properties of electron arc beams delivered by photon-beam multi-leaf collimators (pMLC) in electron modulated arc therapy (EMAT) for postmastectomy chest wall treatments. METHODS: Using the Monte Carlo method, we simulated a 2100EX Varian linear accelerator and verified the beam models in a water tank. Dosimetric characterizations were performed on cylindrical water phantoms of elliptical bases with various field sizes, arc ranges and source-to-surface distances (SSDs) for 6, 9 and 12â¯MeV beam energy. RESULTS: The arc beam has a higher bremsstrahlung dose than the static beam at the isocenter due to crossfire, but choosing a field size greater than 5â¯cm effectively reduces the bremsstrahlung dose. The depths of the 90% maximum dose located at 1.7, 2.8 and 4.1â¯cm for 6, 9 and 12â¯MeV, respectively, are similar to those of the static beams and independent of the field size and arc range. CONCLUSION: Based on the study, we recommend using the 5â¯cm field width for electron arc beams considering both bremsstrahlung dose at the isocenter and the arc profile penumbra. To ensure sufficient PTV edge coverage, we recommend a field length extension of at least 4â¯cm from PTV's edge for all beam energies and an arc extension of around 7°, 5°, and 5° for beam energies 6, 9, and 12â¯MeV, respectively. These dosimetric characterizations are the basis of pMLC-delivered EMAT treatment planning for postmastectomy chest wall patients.