The British journal of radiology · 2018
Predicting the dose absorbed by organs at risk during intensity modulated radiation therapy for nasopharyngeal carcinoma.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
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.
Pang Haowen, Sun Xiaoyang, Yang Bo, Wu Jingbo
Аннотация
OBJECTIVE:: To develop a model for predicting the dose absorbed by organ at risk (OAR) during intensity modulated radiation therapy for nasopharyngeal carcinoma (NPC).
METHODS:: 55 patients underwent intensity modulated radiation therapy for NPC. The OARs were divided into several suborgans, and SPSS software was used to evaluate multiple linear method for fitting the normalized volume for each suborgan, normalized mean dose (Dmean) Dnm (Dnm = Dmean/Dprescription), and normalized D10%-D100% values Dn10%-n100%(Dn10%-n100% = D10%-D100%/Dprescription) for each OAR. Based on the Matlab software, the predicted Dn10%-n100% value was fitted to obtain the predicted DVH curve.
RESULTS:: The multiple linear fitting formulas revealed significant results for the oral cavity Dn100% (p = 0.017), the parotid gland Dn100% (p = 0.001), and the remaining OAR (all p < 0.0001). The correlation coefficients and p values indicated that the fitting formula was a good fit. The p values for the White test show that the prediction model is robust. This method was successfully used for verification cases.
CONCLUSION:: The present study provided a simple and effective model for predicting the dose absorbed by OAR for NPC.
ADVANCES IN KNOWLEDGE:: This method is a relatively simple mathematical model, just use prescription dose and V0-Vn to predict the Dmean and D10%-100%, which predict does not require buying new modules of treatment planning software or extracting the distance of each sampling point of the OAR with the dose information.
METHODS:: 55 patients underwent intensity modulated radiation therapy for NPC. The OARs were divided into several suborgans, and SPSS software was used to evaluate multiple linear method for fitting the normalized volume for each suborgan, normalized mean dose (Dmean) Dnm (Dnm = Dmean/Dprescription), and normalized D10%-D100% values Dn10%-n100%(Dn10%-n100% = D10%-D100%/Dprescription) for each OAR. Based on the Matlab software, the predicted Dn10%-n100% value was fitted to obtain the predicted DVH curve.
RESULTS:: The multiple linear fitting formulas revealed significant results for the oral cavity Dn100% (p = 0.017), the parotid gland Dn100% (p = 0.001), and the remaining OAR (all p < 0.0001). The correlation coefficients and p values indicated that the fitting formula was a good fit. The p values for the White test show that the prediction model is robust. This method was successfully used for verification cases.
CONCLUSION:: The present study provided a simple and effective model for predicting the dose absorbed by OAR for NPC.
ADVANCES IN KNOWLEDGE:: This method is a relatively simple mathematical model, just use prescription dose and V0-Vn to predict the Dmean and D10%-100%, which predict does not require buying new modules of treatment planning software or extracting the distance of each sampling point of the OAR with the dose information.