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一项关于在Halcyon和RayStation系统上对肺癌放疗计划进行自动渐进优化的回顾性研究。

A retrospective study of automatic progressive optimization for lung cancer radiotherapy plans on the Halcyon and RayStation systems.

作者信息

Shao Kainan, Du Fenglei, Qiu Lingyun, Zhang Yinghao, Li Yucheng, Ding Jieni, Zhan Wenming, Chen Weijun

机构信息

Department of Radiation Oncology, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, China.

Department of Radiation Physics, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China.

出版信息

PeerJ. 2025 Aug 5;13:e19831. doi: 10.7717/peerj.19831. eCollection 2025.


DOI:10.7717/peerj.19831
PMID:40786101
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12333610/
Abstract

This study aims to evaluate the feasibility of using RayStation's scripting function to generate automated radiotherapy plans for non-small cell lung cancer (NSCLC) patients on a Varian Halcyon accelerator and to compare their dosimetric characteristics with those of retrospectively collected manual clinical plans. A total of 63 conventional fractionation plans for NSCLC, previously designed using RayStation 4.5 for a variety of linear accelerators-including Trilogy, TrueBeam, Halcyon, and Elekta Infinity-were compared with automated plans generated using RayStation 9.0 for Halcyon. This heterogeneous control group was chosen to reflect real-world clinical practice across multiple platforms. Target coverage, doses to organs at risk (OARs), monitor units, and plan complexity were assessed. The automated plans showed improved dose conformity and lower OAR exposure under the planning configuration used. However, these differences should be interpreted with caution, as the comparison involved different treatment planning systems (TPS) versions and hardware platforms. Further controlled studies using the same TPS and linac are needed to validate the observed improvements.

摘要

本研究旨在评估使用RayStation脚本功能在瓦里安Halcyon加速器上为非小细胞肺癌(NSCLC)患者生成自动放射治疗计划的可行性,并将其剂量学特征与回顾性收集的手动临床计划的剂量学特征进行比较。总共63个NSCLC的常规分割计划,以前使用RayStation 4.5为包括Trilogy、TrueBeam、Halcyon和医科达Infinity在内的各种直线加速器设计,与使用RayStation 9.0为Halcyon生成的自动计划进行了比较。选择这个异质性对照组以反映多个平台的真实世界临床实践。评估了靶区覆盖情况、危及器官(OAR)的剂量、监测单位和计划复杂性。在所用的计划配置下,自动计划显示出更好的剂量适形性和更低的OAR受照剂量。然而,这些差异应谨慎解释,因为比较涉及不同的治疗计划系统(TPS)版本和硬件平台。需要使用相同的TPS和直线加速器进行进一步的对照研究,以验证观察到的改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/68a16ad67cfb/peerj-13-19831-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/cda87020d23c/peerj-13-19831-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/8bfc0e2f05e5/peerj-13-19831-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/9e987355d8d3/peerj-13-19831-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/dcc18f60ddfc/peerj-13-19831-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/4aea9da5241f/peerj-13-19831-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/68a16ad67cfb/peerj-13-19831-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/cda87020d23c/peerj-13-19831-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/8bfc0e2f05e5/peerj-13-19831-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/9e987355d8d3/peerj-13-19831-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/dcc18f60ddfc/peerj-13-19831-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/4aea9da5241f/peerj-13-19831-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50d0/12333610/68a16ad67cfb/peerj-13-19831-g006.jpg

相似文献

[1]
A retrospective study of automatic progressive optimization for lung cancer radiotherapy plans on the Halcyon and RayStation systems.

PeerJ. 2025-8-5

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本文引用的文献

[1]
Comparative analysis of VMAT plans on Halcyon and infinity for lung cancer radiotherapy.

PLoS One. 2025-2-11

[2]
Dosimetric performance evaluation of the Halcyon treatment platform for stereotactic radiotherapy: A pooled study.

Medicine (Baltimore). 2023-9-8

[3]
Fully automated volumetric modulated arc therapy planning for locally advanced rectal cancer: feasibility and efficiency.

Radiat Oncol. 2023-9-5

[4]
Improving knowledge-based treatment planning for lung cancer radiotherapy with automatic multi-criteria optimized training plans.

Acta Oncol. 2023-10

[5]
A novel automated planning approach for multi-anatomical sites cancer in Raystation treatment planning system.

Phys Med. 2023-5

[6]
NCCN Guidelines® Insights: Non-Small Cell Lung Cancer, Version 2.2023.

J Natl Compr Canc Netw. 2023-4

[7]
Improving normal tissue sparing using scripting in endometrial cancer radiation therapy planning.

Radiat Environ Biophys. 2023-5

[8]
Treatment time of image-guided radiotherapy with a Halcyon 2.0 system.

J Med Imaging Radiat Sci. 2023-3

[9]
Advances in Automated Treatment Planning.

Semin Radiat Oncol. 2022-10

[10]
Implementation of automatic plan optimization in Italy: Status and perspectives.

Phys Med. 2021-12

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