Suppr超能文献

基于知识的模型在优化单乳和双乳容积调强弧形放疗计划中的性能

Performance of a Knowledge-Based Model for Optimization of Volumetric Modulated Arc Therapy Plans for Single and Bilateral Breast Irradiation.

作者信息

Fogliata Antonella, Nicolini Giorgia, Bourgier Celine, Clivio Alessandro, De Rose Fiorenza, Fenoglietto Pascal, Lobefalo Francesca, Mancosu Pietro, Tomatis Stefano, Vanetti Eugenio, Scorsetti Marta, Cozzi Luca

机构信息

Radiotherapy and Radiosurgery Department, Humanitas Clinical and Research Center, Milan-Rozzano, Italy.

Oncology Institute of Southern Switzerland, Bellinzona, Switzerland.

出版信息

PLoS One. 2015 Dec 21;10(12):e0145137. doi: 10.1371/journal.pone.0145137. eCollection 2015.

Abstract

PURPOSE

To evaluate the performance of a model-based optimisation process for volumetric modulated arc therapy, VMAT, applied to whole breast irradiation.

METHODS AND MATERIALS

A set of 150 VMAT dose plans with simultaneous integrated boost were selected to train a model for the prediction of dose-volume constraints. The dosimetric validation was done on different groups of patients from three institutes for single (50 cases) and bilateral breast (20 cases).

RESULTS

Quantitative improvements were observed between the model-based and the reference plans, particularly for heart dose. Of 460 analysed dose-volume objectives, 13% of the clinical plans failed to meet the constraints while the respective model-based plans succeeded. Only in 5 cases did the reference plans pass while the respective model-based failed the criteria. For the bilateral breast analysis, the model-based plans resulted in superior or equivalent dose distributions to the reference plans in 96% of the cases.

CONCLUSIONS

Plans optimised using a knowledge-based model to determine the dose-volume constraints showed dosimetric improvements when compared to earlier approved clinical plans. The model was applicable to patients from different centres for both single and bilateral breast irradiation. The data suggests that the dose-volume constraint optimisation can be effectively automated with the new engine and could encourage its application to clinical practice.

摘要

目的

评估基于模型的容积调强弧形放疗(VMAT)优化过程应用于全乳照射时的性能。

方法与材料

选择一组150个同时进行同步整合加量的VMAT剂量计划,用于训练预测剂量体积约束的模型。对来自三个机构的不同患者组进行剂量验证,包括单侧乳房(50例)和双侧乳房(20例)。

结果

基于模型的计划与参考计划相比有定量改善,尤其是心脏剂量。在分析的460个剂量体积目标中,1临床计划中有13%未满足约束条件,但相应的基于模型的计划成功满足。只有5例参考计划通过,而相应的基于模型的计划未达标准。对于双侧乳房分析,在96%的病例中,基于模型的计划产生的剂量分布优于或等同于参考计划。

结论

与早期批准的临床计划相比,使用基于知识的模型确定剂量体积约束优化的计划在剂量学上有改善。该模型适用于来自不同中心的单侧和双侧乳房照射患者。数据表明,剂量体积约束优化可以通过新引擎有效自动化,并可能鼓励其应用于临床实践。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b18/4686991/dc1dc948ebb0/pone.0145137.g001.jpg

相似文献

9
Investigation of pulsed IMRT and VMAT for re-irradiation treatments: dosimetric and delivery feasibilities.
Phys Med Biol. 2013 Nov 21;58(22):8179-96. doi: 10.1088/0031-9155/58/22/8179.
10
Comparison of whole-field simultaneous integrated boost VMAT and IMRT in the treatment of nasopharyngeal cancer.
Med Dosim. 2013 Winter;38(4):418-23. doi: 10.1016/j.meddos.2013.05.004. Epub 2013 Aug 22.

引用本文的文献

1
BreastWatch: A Varian Eclipse script tool for Community-Based automatic evaluation of breast treatment plans.
J Appl Clin Med Phys. 2025 Jun;26(6):e70080. doi: 10.1002/acm2.70080. Epub 2025 Apr 1.
2
Pro-active risk analysis of an in-house developed deep learning based autoplanning tool for breast Volumetric Modulated Arc Therapy.
Phys Imaging Radiat Oncol. 2024 Nov 22;32:100677. doi: 10.1016/j.phro.2024.100677. eCollection 2024 Oct.
3
4
Automated treatment planning for whole breast irradiation with individualized tangential IMRT fields.
J Appl Clin Med Phys. 2024 May;25(5):e14361. doi: 10.1002/acm2.14361. Epub 2024 Apr 20.
5
A method for beam's eye view breath-hold monitoring during breast volumetric modulated arc therapy.
Phys Imaging Radiat Oncol. 2023 Jan 25;25:100419. doi: 10.1016/j.phro.2023.100419. eCollection 2023 Jan.
9
Domain knowledge driven 3D dose prediction using moment-based loss function.
Phys Med Biol. 2022 Sep 14;67(18). doi: 10.1088/1361-6560/ac8d45.
10
Artificial Intelligence in Radiation Therapy.
IEEE Trans Radiat Plasma Med Sci. 2022 Feb;6(2):158-181. doi: 10.1109/TRPMS.2021.3107454. Epub 2021 Aug 24.

本文引用的文献

1
Evaluation of a knowledge-based planning solution for head and neck cancer.
Int J Radiat Oncol Biol Phys. 2015 Mar 1;91(3):612-20. doi: 10.1016/j.ijrobp.2014.11.014. Epub 2015 Jan 30.
4
Evaluation of volumetric modulated arc therapy for postmastectomy treatment.
Radiat Oncol. 2014 Feb 26;9:66. doi: 10.1186/1748-717X-9-66.
7
Predicting dose-volume histograms for organs-at-risk in IMRT planning.
Med Phys. 2012 Dec;39(12):7446-61. doi: 10.1118/1.4761864.
10
Flattening filter free vs flattened beams for breast irradiation.
Int J Radiat Oncol Biol Phys. 2013 Feb 1;85(2):506-13. doi: 10.1016/j.ijrobp.2012.03.040. Epub 2012 Jun 5.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验