Journal of applied clinical medical physics · 2021
Automated algorithm for calculation of setup corrections and planning target volume margins for offline image-guided radiotherapy protocols.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Abubakar Auwal, Zamri Nada Alia M, Shaukat Shazril Imran, Mohd Zin Hafiz
Аннотация
PURPOSE: Each radiotherapy center should have a site-specific planning target volume (PTV) margins and image-guided (IG) radiotherapy (IGRT) correction protocols to compensate for the geometric errors that can occur during treatment. This study developed an automated algorithm for the calculation and evaluation of these parameters from cone beam computed tomography (CBCT)-based IG-intensity modulated radiotherapy (IG-IMRT) treatment.
METHODS AND MATERIALS: A MATLAB algorithm was developed to extract the setup errors in three translational directions (x, y, and z) from the data logged by the CBCT system during treatment delivery. The algorithm also calculates the resulted population setup error and PTV margin based on the van Herk margin recipe and subsequently estimates their respective values for no action level (NAL) and extended no action level (eNAL) offline correction protocols. The algorithm was tested on 25 head and neck cancer (HNC) patients treated using IG-IMRT.
RESULTS: The algorithms calculated that the HNC patients require a PTV margin of 3.1, 2.7, and 3.2 mm in the x-, y-, and z-direction, respectively, without IGRT. The margin can be reduced to 2.0, 2.2, and 3.0 mm in the x-, y-, and z-direction, respectively, with NAL and 1.6, 1.7, and 2.2 mm in the x-, y-, and z-direction, respectively, with eNAL protocol. The results obtained were verified to be the same with the margins calculated using an Excel spreadsheet. The algorithm calculates the weekly offline setup error correction values automatically and reduces the risk of input data error observed in the spreadsheet.
CONCLUSIONS: In conclusion, the algorithm provides an automated method for optimization and reduction of PTV margin using logged setup errors from CBCT-based IGRT.
METHODS AND MATERIALS: A MATLAB algorithm was developed to extract the setup errors in three translational directions (x, y, and z) from the data logged by the CBCT system during treatment delivery. The algorithm also calculates the resulted population setup error and PTV margin based on the van Herk margin recipe and subsequently estimates their respective values for no action level (NAL) and extended no action level (eNAL) offline correction protocols. The algorithm was tested on 25 head and neck cancer (HNC) patients treated using IG-IMRT.
RESULTS: The algorithms calculated that the HNC patients require a PTV margin of 3.1, 2.7, and 3.2 mm in the x-, y-, and z-direction, respectively, without IGRT. The margin can be reduced to 2.0, 2.2, and 3.0 mm in the x-, y-, and z-direction, respectively, with NAL and 1.6, 1.7, and 2.2 mm in the x-, y-, and z-direction, respectively, with eNAL protocol. The results obtained were verified to be the same with the margins calculated using an Excel spreadsheet. The algorithm calculates the weekly offline setup error correction values automatically and reduces the risk of input data error observed in the spreadsheet.
CONCLUSIONS: In conclusion, the algorithm provides an automated method for optimization and reduction of PTV margin using logged setup errors from CBCT-based IGRT.