Cross-engine transformation-based fast dose calculation for MRI-Linac online treatment planning.
Аннотация
PURPOSE: To propose a novel magnetic field dose calculation method based on transformation from pencil beam (PB) to Monte Carlo (MC) distribution for MRI-Linac online treatment planning.
METHODS
The novel magnetic field dose calculation algorithm was established by a PB dose engine and a magnetic field with tissue inhomogeneity influence correction network. The correction network was constructed with a Res-UNet framework, including residual modules and an encoding-decoding path, by inputting three-dimensional PB dose and patient electron density map, and outputting transformed dose distribution. The influences of magnetic fields and tissue heterogeneity were considered and corrected simultaneously in the correction model. A total of 110 clinically treated static beam IMRT plans were collected, including plans for brain, head-and-neck, lung, and rectum cases. A total of 90 cases were used and enhanced to train and validate the model, and the other 20 cases were for test. By comparing the proposed pipeline-generated dose distribution with original input PB dose and corresponding MC dose, the feasibility and effectiveness of the method was evaluated.
RESULTS
Results on both beam dose and plan dose accuracy comparisons on all investigated four tumor sites show great consistency between the cross-dose-engine transformation generations and the MC results, with averaged plan mean absolute error of 0.90% ± 0.13% for the voxel-wise dose difference and 98.33% ± 1.07% gamma passing rate at the 2%/2 mm criteria. The whole PB calculation and transformation process can be completed within second.
CONCLUSIONS
We have successfully developed a fast novel magnetic field dose calculation pipeline based on transformation from PB distribution to MC distribution for MRI-Linac online treatment planning.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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