Effect of physical parameter differences on the performance of a knowledge-based partial arc VMAT RapidPlan model for left breast cancer

物理参数差异对基于知识的左侧乳腺癌部分弧VMAT RapidPlan模型性能的影响

阅读:1

Abstract

OBJECTIVE: To optimize the protection of organs at risk (OARs) in left breast cancer radiotherapy, this study investigated how physical parameter adjustments affect the performance of a Rapidplan-based dose-volume histogram (DVH) prediction model. METHODS: Twenty patients who underwent left breast-conserving surgery were enrolled. Partial arc volumetric modulated arc therapy (VMAT) plans were designed per patient, with X-direction field width set to half-beam and right breast (Breast-R) contoured as an avoidance structure to generate Rapidplan model. The model was used to predict and generate three plans: AP_partial arc (avoidance structure prioritized), RP_partial arc (no avoidance structure), and FP_partial arc (expanded field width). Dosimetric comparisons against the original plan evaluated the impact of parameter selection. RESULTS: AP_partial arc reduced mean doses of Breast-R, Heart, Lung-L, and Lung-R by 7.7 cGy, 9.8 cGy, 16.7 cGy, and 1.1 cGy, respectively (p < 0.05). Conversely, RP_partial arc increased mean dose of Breast-R by 66.3 cGy (p < 0.05). FP_partial arc raised V5 of Lung-L, V5 of Heart, and mean dose of Lung-L by 4.01%, 2.25%, and 36 cGy (p < 0.05). CONCLUSION: The knowledge-based partial arc model for rapid planning of left breast cancer accurately predicts the DVH of OARs. However, before performing dose prediction, physical parameters such as radiation field width and planned avoidance structures should be considered to reduce the risk of low-dose exposure volume to OARs and secondary cancer.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。