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基于知识的计划模型的更新方法,以提高前列腺癌容积调强弧形治疗计划的质量和可变性。

An updating approach for knowledge-based planning models to improve plan quality and variability in volumetric-modulated arc therapy for prostate cancer.

机构信息

Department of Medical Physics, Graduate School of Medical Sciences, Kindai University, Osakasayama, Japan.

Department of Radiotherapy, Takarazuka City Hospital, Kohama, Takarazuka, Japan.

出版信息

J Appl Clin Med Phys. 2021 Sep;22(9):113-122. doi: 10.1002/acm2.13353. Epub 2021 Aug 2.

DOI:10.1002/acm2.13353
PMID:34338435
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8425874/
Abstract

PURPOSE

The purpose of this study was to compare the dose-volume parameters and regression scatter plots of the iteratively improved RapidPlan (RP) models, specific knowledge-based planning (KBP) models, in volumetric-modulated arc therapy (VMAT) for prostate cancer over three periods.

METHODS

A RP1 model was created from 47 clinical intensity-modulated radiation therapy (IMRT)/VMAT plans. A RP2 model was created to exceed dosimetric goals which set as the mean values +1SD of the dose-volume parameters of RP1 (50 consecutive new clinical VMAT plans). A RP3 model was created with more strict dose constraints for organs at risks (OARs) than RP1 and RP2 models (50 consecutive anew clinical VMAT plans). Each RP model was validated against 30 validation plans (RP1, RP2, and RP3) that were not used for model configuration, and the dose-volume parameters were compared. The Cook's distances of regression scatterplots of each model were also evaluated.

RESULTS

Significant differences (p < 0.05) between RP1 and RP2 were found in D (101.5% vs. 101.9%), homogeneity index (3.90 vs. 4.44), 95% isodose conformity index (1.22 vs. 1.20) for the target, V (47.3% vs. 45.7%), V (27.9% vs. 27.1%), V (16.4% vs. 15.2%), and V (0.4% vs. 0.2%) for the rectal wall, and V (43.8% vs. 41.8%) and V (21.3% vs. 20.5%) for the bladder wall, whereas only V (15.2% vs. 15.8%) of the rectal wall differed significantly between RP2 and RP3. The proportions of cases with a Cook's distance of <1.0 (RP1, RP2, and RP3 models) were 55%, 78%, and 84% for the rectal wall, and 77%, 68%, and 76% for the bladder wall, respectively.

CONCLUSIONS

The iteratively improved RP models, reflecting the clear dosimetric goals based on the RP feedback (dose-volume parameters) and more strict dose constraints for the OARs, generated superior dose-volume parameters and the regression scatterplots in the model converged. This approach could be used to standardize the inverse planning strategies.

摘要

目的

本研究旨在比较前列腺癌容积调强弧形治疗(VMAT)中迭代改进的 RapidPlan(RP)模型、特定基于知识的计划(KBP)模型的剂量-体积参数和回归散点图,这三个时期。

方法

从 47 例临床调强放疗(IMRT)/VMAT 计划中创建一个 RP1 模型。RP2 模型旨在超过剂量体积参数的平均水平+1SD(50 例新临床 VMAT 计划),创建一个 RP2 模型以满足剂量体积参数。RP3 模型为危及器官(OARs)设置了比 RP1 和 RP2 模型更严格的剂量限制(50 例新临床 VMAT 计划)。每个 RP 模型都针对 30 个验证计划(RP1、RP2 和 RP3)进行了验证,这些计划未用于模型配置,并且比较了剂量-体积参数。还评估了每个模型回归散点图的 Cook 距离。

结果

在目标方面,RP1 和 RP2 之间存在显著差异(p<0.05),D(101.5% vs. 101.9%)、均匀性指数(3.90 vs. 4.44)、95%等剂量一致性指数(1.22 vs. 1.20),V(47.3% vs. 45.7%)、V(27.9% vs. 27.1%)、V(16.4% vs. 15.2%)和 V(0.4% vs. 0.2%)直肠壁,以及 V(43.8% vs. 41.8%)和 V(21.3% vs. 20.5%)膀胱壁,而仅直肠壁的 V(15.2% vs. 15.8%)在 RP2 和 RP3 之间存在显著差异。直肠壁和膀胱壁的 Cook 距离<1.0 的病例比例(RP1、RP2 和 RP3 模型)分别为 55%、78%和 84%,77%、68%和 76%。

结论

迭代改进的 RP 模型反映了基于 RP 反馈(剂量-体积参数)的明确剂量学目标,以及对 OARs 的更严格的剂量限制,生成了更好的剂量-体积参数和模型收敛的回归散点图。这种方法可用于标准化逆向规划策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f54/8425874/cc4b8dd49f8e/ACM2-22-113-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f54/8425874/28b6d54715af/ACM2-22-113-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f54/8425874/bc5b4b256b5b/ACM2-22-113-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f54/8425874/d4c9da9e71a1/ACM2-22-113-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f54/8425874/cc4b8dd49f8e/ACM2-22-113-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f54/8425874/28b6d54715af/ACM2-22-113-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f54/8425874/bc5b4b256b5b/ACM2-22-113-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f54/8425874/d4c9da9e71a1/ACM2-22-113-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f54/8425874/cc4b8dd49f8e/ACM2-22-113-g002.jpg

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