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Independent 3D dose calculation for IMRT based on simplification of beam model and collapsed-cone convolution/superposition algorithm / 中华放射肿瘤学杂志
Chinese Journal of Radiation Oncology ; (6): 795-799, 2017.
Article in Chinese | WPRIM | ID: wpr-620246
ABSTRACT
Objective To realize independent 3D dose calculation for intensity-modulated radiotherapy (IMRT) by building a two-source beam model of medical linear accelerator combined with a collapsed-cone convolution/superposition (CCCS) algorithm.Methods Two-source beam models of medical linear accelerators (Varian and Elekta) were built to calculate the 3D dose distributions using the CCCS algorithm.Scp,percent depth dose,and off-axis dose distribution were compared with the scanning data of ion chamber to confirm the calculation model.Twelve intensity-modulated treatment plans from each accelerator (a total of 24 plans) were selected for comparison.The calculation results of treatment planning system (TPS) were independently validated,and further compared with the measurement results of detector matrix.Results The dose deviations at the center of rectangle fields were lower than 1%,the deviation between doses at the same position in the field was not higher than 1%,and the positional deviation in the penumbra region was not higher than 1 mm.Gamma analysis based on 3%/3 mm standard was used to compare the results calculated by detectors and TPS.The pass rates were higher than 90%.Conclusions The independent 3D dose calculation for IMRT based on two-source beam model combined with CCCS algorithm has been successfully set up.The comparison between regular field and IMRT plan indicates that this method and calculation model can be used for independent 3D dose calculation of clinical plan.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Radiation Oncology Year: 2017 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Radiation Oncology Year: 2017 Type: Article