近距离放射治疗
医学
放射治疗计划
直方图
平面图(考古学)
乙状窦函数
计算机科学
人工智能
放射科
放射治疗
图像(数学)
人工神经网络
历史
考古
作者
Emily Flower,J. Sykes,E. Sullivan,G. Busuttil,Niluja Thiruthaneeswaran,E. C. Cosgriff,Jennifer Chard,A.L. Salkeld,David Thwaites
标识
DOI:10.1016/j.brachy.2023.05.004
摘要
Purpose Toxicity from cervical brachytherapy has been demonstrated to correlate with the D2cm3 of the bladder, rectum, and bowel. This suggests a simplified version of knowledge-based planning investigating the relationship of the overlap distance for 2cm3 and the D2cm3 from planning may be possible. This work demonstrates the feasibility of simple knowledge-based planning to predict the D2cm3, detect suboptimal plans, and improve plan quality. Methods and materials The overlap volume histogram (OVH) method was used to determine the distance for 2cm3 of overlap between the OAR and CTV_HR. Linear plots modeled the OAR D2cm3 and 2cm3 overlap distance. Two datasets of 20 patients (plans from 43 insertions in each dataset) were used to create two independent models, and the performance of each model was compared using cross-validation. Doses were scaled to ensure consistent CTV_HR D90 values. The predicted D2cm3 is entered as the maximum constraint in the inverse planning algorithm. Results Mean bladder D2cm3 decreased by 2.9% for the models from each dataset, mean rectal D2cm3 decreased 14.9% for the model from dataset 1 and 6.0% for the model from dataset 2, mean sigmoid D2cm3 decreased 10.7% for the model from dataset 1 and 6.1% for the model from dataset 2, mean bowel D2cm3 decreased 4.1% for the model from dataset 1 but no statistically significant difference was observed for the model from dataset 2. Conclusions A simplified knowledge-based planning method was used to predict D2cm3 and was able to automate optimization of brachytherapy plans for locally advanced cervical cancer.
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