Suppr超能文献

清理后的基于商业知识的治疗计划对前列腺癌容积调强弧形治疗的影响。

Influence of Cleaned-up Commercial Knowledge-Based Treatment Planning on Volumetric-Modulated Arc Therapy of Prostate Cancer.

作者信息

Tamura Mikoto, Monzen Hajime, Matsumoto Kenji, Kubo Kazuki, Ueda Yoshihiro, Kamima Tatsuya, Inada Masahiro, Doi Hiroshi, Nakamatsu Kiyoshi, Nishimura Yasumasa

机构信息

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

Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan.

出版信息

J Med Phys. 2020 Apr-Jun;45(2):71-77. doi: 10.4103/jmp.JMP_109_19. Epub 2020 Jul 20.

Abstract

PURPOSE

This study aimed to investigate the influence of cleaned-up knowledge-based treatment planning (KBP) models on the plan quality for volumetric-modulated arc therapy (VMAT) of prostate cancer.

MATERIALS AND METHODS

Thirty prostate cancer VMAT plans were enrolled and evaluated according to four KBP modeling methods as follows: (1) model not cleaned - trained by fifty other clinical plans (KBP); (2) cases cleaned by removing plans that did not meet all clinical goals of the dosimetric parameters, derived from dose-volume histogram (DVH) (KBP); (3) cases cleaned outside the range of ±1 standard deviation through the principal component analysis regression plots (KBP); and (4) cases cleaned using both methods (2) and (3) (KBP). Rectal and bladder structures in the training models numbered 34 and 48 for KBP, 37 and 33 for KBP, and 26 and 33 for KBP, respectively. The dosimetric parameters for each model with one-time auto-optimization were compared.

RESULTS

All KBP models improved target dose coverage and conformity and provided comparable sparing of organs at risks (rectal and bladder walls). There were no significant differences in plan quality among the KBP models. Nevertheless, only the KBP model generated no cases of >1% V (prescribed dose) to the rectal wall, whereas the KBP, KBP, and KBP models included two, four, and three cases, respectively, which were difficult to overcome with KBP because the planning target volume (PTV) and rectum regions overlapped.

CONCLUSIONS

The cleaned-up KBP model based on DVH and regression plots improved plan quality in the PTV-rectum overlap region.

摘要

目的

本研究旨在探讨经过清理的基于知识的治疗计划(KBP)模型对前列腺癌容积调强弧形放疗(VMAT)计划质量的影响。

材料与方法

纳入30例前列腺癌VMAT计划,并根据以下四种KBP建模方法进行评估:(1)未清理的模型 - 由其他50个临床计划训练(KBP);(2)通过去除不符合剂量体积直方图(DVH)剂量学参数所有临床目标的计划进行清理的病例(KBP);(3)通过主成分分析回归图在±1标准差范围外进行清理的病例(KBP);以及(4)使用方法(2)和(3)两者进行清理的病例(KBP)。训练模型中的直肠和膀胱结构,KBP分别为34个和第48个,KBP分别为37个和33个,KBP分别为26个和33个。比较每个模型进行一次自动优化后的剂量学参数。

结果

所有KBP模型均改善了靶区剂量覆盖和适形性,并对危及器官(直肠和膀胱壁)提供了相当的保护。KBP模型之间的计划质量无显著差异。然而,只有KBP模型未产生直肠壁接受>1%V(处方剂量)的病例,而KBP、KBP和KBP模型分别包含2例、4例和3例,由于计划靶区(PTV)与直肠区域重叠,这些病例用KBP难以克服。

结论

基于DVH和回归图的清理后的KBP模型改善了PTV - 直肠重叠区域的计划质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05fa/7416859/284a6d87f155/JMP-45-71-g001.jpg

相似文献

1
Influence of Cleaned-up Commercial Knowledge-Based Treatment Planning on Volumetric-Modulated Arc Therapy of Prostate Cancer.
J Med Phys. 2020 Apr-Jun;45(2):71-77. doi: 10.4103/jmp.JMP_109_19. Epub 2020 Jul 20.
2
Dosimetric features-driven machine learning model for DVH prediction in VMAT treatment planning.
Med Phys. 2019 Feb;46(2):857-867. doi: 10.1002/mp.13334. Epub 2019 Jan 2.
5
Impact of database quality in knowledge-based treatment planning for prostate cancer.
Pract Radiat Oncol. 2018 Nov-Dec;8(6):437-444. doi: 10.1016/j.prro.2018.03.004. Epub 2018 Mar 13.
7
Highly Efficient Training, Refinement, and Validation of a Knowledge-based Planning Quality-Control System for Radiation Therapy Clinical Trials.
Int J Radiat Oncol Biol Phys. 2017 Jan 1;97(1):164-172. doi: 10.1016/j.ijrobp.2016.10.005. Epub 2016 Oct 13.

引用本文的文献

本文引用的文献

3
Knowledge-based planning for oesophageal cancers using a model trained with plans from a different treatment planning system.
Acta Oncol. 2020 Mar;59(3):274-283. doi: 10.1080/0284186X.2019.1691257. Epub 2019 Nov 22.
4
Inter-planner variation in treatment-plan quality of plans created with a knowledge-based treatment planning system.
Phys Med. 2019 Nov;67:132-140. doi: 10.1016/j.ejmp.2019.10.032. Epub 2019 Nov 6.
6
Mechanical performance of a commercial knowledge-based VMAT planning for prostate cancer.
Radiat Oncol. 2018 Aug 31;13(1):163. doi: 10.1186/s13014-018-1114-y.
7
Creation of knowledge-based planning models intended for large scale distribution: Minimizing the effect of outlier plans.
J Appl Clin Med Phys. 2018 May;19(3):215-226. doi: 10.1002/acm2.12322. Epub 2018 Apr 6.
9
Dosimetric comparison of RapidPlan and manually optimized plans in volumetric modulated arc therapy for prostate cancer.
Phys Med. 2017 Dec;44:199-204. doi: 10.1016/j.ejmp.2017.06.026. Epub 2017 Jul 10.
10
RapidPlan head and neck model: the objectives and possible clinical benefit.
Radiat Oncol. 2017 Apr 27;12(1):73. doi: 10.1186/s13014-017-0808-x.

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