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基于呼吸相关锥形束 CT 数据集的无框架肺 SBRT 治疗边缘呼吸运动影响的回顾性分析。

Retrospective analysis of the impact of respiratory motion in treatment margins for frameless lung SBRT based on respiratory-correlated CBCT data-sets.

机构信息

Institute of Radiation Physics, Lausanne University Hospital, Lausanne, Switzerland.

Clinique des Grangettes, Chêne-Bougeries, Switzerland.

出版信息

J Appl Clin Med Phys. 2020 Oct;21(10):170-178. doi: 10.1002/acm2.13034. Epub 2020 Sep 30.

DOI:10.1002/acm2.13034
PMID:32996669
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7592980/
Abstract

PURPOSE

To investigate the impact of respiratory motion in the treatment margins for lung SBRT frameless treatments and to validate our treatment margins using 4D CBCT data analysis.

METHODS

Two hundred and twenty nine fractions with early stage NSCLC were retrospectively analyzed. All patients were treated in frameless and free breathing conditions. The treatment margins were calculated according to van Herk equation in Mid-Ventilation. For each fraction, three 4D CBCT scans, pre- and postcorrection, and posttreatment, were acquired to assess target baseline shift, target localization accuracy and intra-fraction motion errors. A bootstrap analysis was performed to assess the minimum number of patients required to define treatment margins.

RESULTS

The retrospectively calculated target-baseline shift, target localization accuracy and intra-fraction motion errors agreed with the literature. The best tailored margins to our cohort of patients were retrospectively computed and resulted in agreement with already published data. The bootstrap analysis showed that fifteen patients were enough to assess treatment margins.

CONCLUSIONS

The treatment margins applied to our patient's cohort resulted in good agreement with the retrospectively calculated margins based on 4D CBCT data. Moreover, the bootstrap analysis revealed to be a promising method to verify the reliability of the applied treatment margins for safe lung SBRT delivery.

摘要

目的

研究在无框架肺 SBRT 治疗中呼吸运动对治疗边缘的影响,并使用 4D CBCT 数据分析验证我们的治疗边缘。

方法

回顾性分析了 229 例早期非小细胞肺癌患者的资料。所有患者均在无框架和自由呼吸条件下进行治疗。根据 Mid-Ventilation 中的 van Herk 方程计算治疗边缘。对于每个分次,采集三个 4D CBCT 扫描,分别是预校正、校正后和治疗后,以评估靶区基线移动、靶区定位准确性和分次内运动误差。采用 bootstrap 分析来评估定义治疗边缘所需的最小患者数量。

结果

回顾性计算的靶区基线移动、靶区定位准确性和分次内运动误差与文献相符。根据 4D CBCT 数据,我们为患者群体回顾性计算出的最佳定制边缘与已发表的数据一致。bootstrap 分析表明,十五名患者足以评估治疗边缘。

结论

应用于患者群体的治疗边缘与基于 4D CBCT 数据的回顾性计算边缘有较好的一致性。此外,bootstrap 分析表明,它是验证应用于安全肺 SBRT 治疗的治疗边缘可靠性的一种很有前途的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/ced1721ff9f9/ACM2-21-170-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/add345bafbe8/ACM2-21-170-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/89c4d8df89c9/ACM2-21-170-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/795acec9e34b/ACM2-21-170-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/38293c14d669/ACM2-21-170-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/ced1721ff9f9/ACM2-21-170-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/add345bafbe8/ACM2-21-170-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/89c4d8df89c9/ACM2-21-170-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/795acec9e34b/ACM2-21-170-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/38293c14d669/ACM2-21-170-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f21/7592980/ced1721ff9f9/ACM2-21-170-g005.jpg

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