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新型受限单中心立体定向体放射治疗(a-RESIST)同步治疗两肺病变的自动化与整合。

Automation and integration of a novel restricted single-isocenter stereotactic body radiotherapy (a-RESIST) method for synchronous two lung lesions.

机构信息

Medical Physics Graduate Program, Department of Radiation Medicine, University of Kentucky, Lexington, KY, 40508, USA.

出版信息

J Appl Clin Med Phys. 2021 Jul;22(7):56-65. doi: 10.1002/acm2.13259. Epub 2021 May 25.

DOI:10.1002/acm2.13259
PMID:34032380
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8292708/
Abstract

Synchronous treatment of two lung lesions using a single-isocenter volumetric modulated arc therapy (VMAT) stereotactic body radiation therapy (SBRT) plan can decrease treatment time and reduce the impact of intrafraction motion. However, alignment of both lesions on a single cone beam CT (CBCT) can prove difficult and may lead to setup errors and unacceptable target coverage loss. A Restricted Single-Isocenter Stereotactic Body Radiotherapy (RESIST) method was created to minimize setup uncertainties and provide treatment delivery flexibility. RESIST utilizes a single-isocenter placed at patient's midline and allows both lesions to be planned separately but treated in the same session. Herein is described a process of automation of this novel RESIST method. Automation of RESIST significantly reduced treatment planning time while maintaining the benefits of RESIST. To demonstrate feasibility, ten patients with two lung lesions previously treated with a single-isocenter clinical VMAT plan were replanned manually with RESIST (m-RESIST) and with automated RESIST (a-RESIST). a-RESIST method automatically sets isocenter, creates beam geometry, chooses appropriate dose calculation algorithms, and performs VMAT optimization using an in-house trained knowledge-based planning model for lung SBRT. Both m-RESIST and a-RESIST showed lower dose to normal tissues compared to manually planned clinical VMAT although a-RESIST provided slightly inferior, but still clinically acceptable, dose conformity and gradient indices. However, a-RESIST significantly reduced the treatment planning time to less than 20 min and provided a higher dose to the lung tumors. The a-RESIST method provides guidance for inexperienced planners by standardizing beam geometry and plan optimization using DVH estimates. It produces clinically acceptable two lesions VMAT lung SBRT plans efficiently. We have further validated a-RESIST on phantom measurement and independent pretreatment dose verification of another four selected 2-lesions lung SBRT patients and implemented clinically. Further development of a-RESIST for more than two lung lesions and refining this approach for extracranial oligometastastic abdominal/pelvic SBRT, including development of automated simulated collision detection algorithm, merits future investigation.

摘要

使用单中心容积旋转调强放疗(VMAT)立体定向体部放疗(SBRT)计划同步治疗两个肺部病变可以减少治疗时间并降低分次内运动的影响。然而,在单次锥形束 CT(CBCT)上对齐两个病变可能很困难,并且可能导致设置错误和无法接受的靶区覆盖丢失。创建了受限的单中心立体定向体部放疗(RESIST)方法,以最大限度地减少设置不确定性并提供治疗交付的灵活性。RESIST 使用放置在患者中线的单个等中心,并允许分别计划两个病变,但在同一疗程中进行治疗。本文描述了这种新的 RESIST 方法的自动化过程。RESIST 的自动化大大减少了治疗计划时间,同时保持了 RESIST 的优势。为了证明可行性,对之前使用单中心临床 VMAT 计划治疗的十个具有两个肺部病变的患者进行了手动 RESIST(m-RESIST)和自动 RESIST(a-RESIST)的重新计划。a-RESIST 方法自动设置等中心,创建射束几何形状,选择适当的剂量计算算法,并使用内部训练的基于知识的肺部 SBRT 规划模型进行 VMAT 优化。尽管 a-RESIST 提供了稍差但仍可接受的剂量适形性和梯度指数,但 m-RESIST 和 a-RESIST 与手动计划的临床 VMAT 相比,对正常组织的剂量较低。然而,a-RESIST 将治疗计划时间显著减少到 20 分钟以下,并为肺部肿瘤提供了更高的剂量。a-RESIST 方法通过使用剂量体积直方图(DVH)估计值来标准化射束几何形状和计划优化,为缺乏经验的规划者提供了指导。它高效地生成具有临床可接受的两个病变 VMAT 肺部 SBRT 计划。我们已经在幻影测量和另外四个选定的 2 个病变肺部 SBRT 患者的独立预处理剂量验证中进一步验证了 a-RESIST,并在临床上实施了该方法。为了治疗两个以上的肺部病变和为颅外寡转移的腹部/骨盆 SBRT 改进这种方法,包括开发自动模拟碰撞检测算法,值得进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aaa9/8292708/4f93fcba447f/ACM2-22-56-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aaa9/8292708/90d4028cae51/ACM2-22-56-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aaa9/8292708/2e8702684973/ACM2-22-56-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aaa9/8292708/8b740586b510/ACM2-22-56-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aaa9/8292708/4f93fcba447f/ACM2-22-56-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aaa9/8292708/90d4028cae51/ACM2-22-56-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aaa9/8292708/2e8702684973/ACM2-22-56-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aaa9/8292708/6cebc680b538/ACM2-22-56-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aaa9/8292708/8b740586b510/ACM2-22-56-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aaa9/8292708/4f93fcba447f/ACM2-22-56-g004.jpg

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本文引用的文献

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A novel restricted single-isocenter stereotactic body radiotherapy (RESIST) method for synchronous multiple lung lesions to minimize setup uncertainties.一种用于同步多发肺病变的新型受限单中心立体定向体部放疗(RESIST)方法,以尽量减少摆位不确定性。
Med Dosim. 2021;46(4):419-425. doi: 10.1016/j.meddos.2021.05.005. Epub 2021 Jun 18.
2
Risk of target coverage loss for stereotactic body radiotherapy treatment of synchronous lung lesions via single-isocenter volumetric modulated arc therapy.立体定向体部放疗治疗同步性肺部病变时,通过单等中心容积旋转调强放疗技术导致靶区覆盖丢失的风险。
J Appl Clin Med Phys. 2021 Jan;22(1):251-260. doi: 10.1002/acm2.13145. Epub 2020 Dec 20.
3
Development and clinical validation of a robust knowledge-based planning model for stereotactic body radiotherapy treatment of centrally located lung tumors.
用于中央型肺肿瘤立体定向体部放射治疗的稳健的基于知识的计划模型的开发与临床验证
J Appl Clin Med Phys. 2021 Jan;22(1):146-155. doi: 10.1002/acm2.13120. Epub 2020 Dec 7.
4
An open-source tool to visualize potential cone collisions while planning SRS cases.一种用于在计划立体定向放射治疗(SRS)病例时可视化潜在视锥碰撞的开源工具。
J Appl Clin Med Phys. 2020 Oct;21(10):40-47. doi: 10.1002/acm2.12998. Epub 2020 Aug 11.
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A practical method for predicting patient-specific collision in radiotherapy.一种用于预测放疗中个体化碰撞的实用方法。
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Limiting treatment plan complexity by applying a novel commercial tool.通过应用一种新颖的商业工具来限制治疗计划的复杂性。
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Integration of automation into an existing clinical workflow to improve efficiency and reduce errors in the manual treatment planning process for total body irradiation (TBI).将自动化整合到现有的临床工作流程中,以提高全身照射(TBI)手动治疗计划过程的效率并减少错误。
J Appl Clin Med Phys. 2020 Jul;21(7):100-106. doi: 10.1002/acm2.12894. Epub 2020 May 19.
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