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与传统基于计划靶区的光子立体定向体部放射治疗肺肿瘤的计划相比,对大体肿瘤体积进行稳健优化。

Robust optimization of the Gross Tumor Volume compared to conventional Planning Target Volume-based planning in photon Stereotactic Body Radiation Therapy of lung tumors.

机构信息

Department of Oncology, Lillebaelt Hospital, University Hospital of Southern Denmark, Vejle, Denmark; Institute for Regional Health Research, University of Southern Denmark, Odense M, Denmark.

Department of Oncology, Lillebaelt Hospital, University Hospital of Southern Denmark, Vejle, Denmark.

出版信息

Acta Oncol. 2024 Jun 20;63:448-455. doi: 10.2340/1651-226X.2024.40049.

DOI:10.2340/1651-226X.2024.40049
PMID:38899392
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11332535/
Abstract

BACKGROUND

Robust optimization has been suggested as an approach to reduce the irradiated volume in lung Stereotactic Body Radiation Therapy (SBRT). We performed a retrospective planning study to investigate the potential benefits over Planning Target Volume (PTV)-based planning.

MATERIAL AND METHODS

Thirty-nine patients had additional plans using robust optimization with 5-mm isocenter shifts of the Gross Tumor Volume (GTV) created in addition to the PTV-based plan used for treatment. The optimization included the mid-position phase and the extreme breathing phases of the 4D-CT planning scan. The plans were compared for tumor coverage, isodose volumes, and doses to Organs At Risk (OAR). Additionally, we evaluated both plans with respect to observed tumor motion using the peak tumor motion seen on the planning scan and cone-beam CTs.

RESULTS

Statistically significant reductions in irradiated isodose volumes and doses to OAR were achieved with robust optimization, while preserving tumor dose. The reductions were largest for the low-dose volumes and reductions up to 188 ccm was observed. The robust evaluation based on observed peak tumor motion showed comparable target doses between the two planning methods. Accumulated mean GTV-dose was increased by a median of 4.46 Gy and a non-significant increase of 100 Monitor Units (MU) was seen in the robust optimized plans.

INTERPRETATION

The robust plans required more time to prepare, and while it might not be a feasible planning strategy for all lung SBRT patients, we suggest it might be useful for selected patients.

摘要

背景

稳健优化被认为是一种减少肺部立体定向体部放射治疗(SBRT)中照射体积的方法。我们进行了一项回顾性计划研究,以调查与基于计划靶区(PTV)的计划相比的潜在益处。

材料和方法

39 名患者接受了额外的计划,除了用于治疗的 PTV 计划外,还使用稳健优化创建了 5mm 等中心偏移的大体肿瘤体积(GTV)。优化包括 4D-CT 计划扫描的中位置相和极端呼吸相。比较了肿瘤覆盖、等剂量体积和危及器官(OAR)剂量的计划。此外,我们还根据计划扫描和锥形束 CT 上观察到的肿瘤运动,评估了两种计划。

结果

稳健优化实现了照射等剂量体积和 OAR 剂量的显著降低,同时保持了肿瘤剂量。低剂量体积的降低最大,观察到的降低高达 188ccm。基于观察到的峰值肿瘤运动的稳健评估表明,两种计划方法的靶区剂量相当。累积平均 GTV 剂量增加了 4.46Gy,稳健优化计划的 100 个监测单位(MU)增加了 100MU。

解释

稳健的计划需要更多的时间来准备,虽然它可能不是所有肺部 SBRT 患者的可行计划策略,但我们建议它可能对某些患者有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/087a/11332535/e81b8566fe10/AO-63-40049-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/087a/11332535/2bd4a692bd26/AO-63-40049-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/087a/11332535/d9a1931c90f0/AO-63-40049-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/087a/11332535/dbd57be34c03/AO-63-40049-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/087a/11332535/e81b8566fe10/AO-63-40049-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/087a/11332535/2bd4a692bd26/AO-63-40049-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/087a/11332535/d9a1931c90f0/AO-63-40049-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/087a/11332535/dbd57be34c03/AO-63-40049-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/087a/11332535/e81b8566fe10/AO-63-40049-g004.jpg

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Some Like It Hot: The Value of Dose and Hot Spots in Lung Stereotactic Body Radiation Therapy.有些人喜欢热疗:肺部立体定向体部放射治疗中剂量和热点的价值。
Int J Radiat Oncol Biol Phys. 2023 Sep 1;117(1):1-5. doi: 10.1016/j.ijrobp.2023.03.056. Epub 2023 Aug 11.
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Tumour motion analysis from planning to end of treatment course for a large cohort of peripheral lung SBRT targets.
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Acta Oncol. 2021 Nov;60(11):1407-1412. doi: 10.1080/0284186X.2021.1949036. Epub 2021 Jul 10.
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Time of PTV is ending, robust optimization comes next.计划靶区(PTV)时间即将结束,接下来是稳健优化。
Cancer Radiother. 2020 Oct;24(6-7):676-686. doi: 10.1016/j.canrad.2020.06.016. Epub 2020 Aug 26.
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