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使用不同成像方式对胰腺癌立体定向放疗靶区定义的观察者间一致性。

Interobserver agreement on definition of the target volume in stereotactic radiotherapy for pancreatic adenocarcinoma using different imaging modalities.

机构信息

Department of Radiation Oncology, University Medical Center Freiburg, Robert Koch Str 3, Freiburg, Germany.

Department of Radiation Oncology, University Medical Center Muenster, Muenster, Germany.

出版信息

Strahlenther Onkol. 2023 Nov;199(11):973-981. doi: 10.1007/s00066-023-02085-7. Epub 2023 Jun 2.

Abstract

PURPOSE

The aim of this study was to evaluate interobserver agreement (IOA) on target volume definition for pancreatic cancer (PACA) within the Radiosurgery and Stereotactic Radiotherapy Working Group of the German Society of Radiation Oncology (DEGRO) and to identify the influence of imaging modalities on the definition of the target volumes.

METHODS

Two cases of locally advanced PACA and one local recurrence were selected from a large SBRT database. Delineation was based on either a planning 4D CT with or without (w/wo) IV contrast, w/wo PET/CT, and w/wo diagnostic MRI. Novel compared to other studies, a combination of four metrics was used to integrate several aspects of target volume segmentation: the Dice coefficient (DSC), the Hausdorff distance (HD), the probabilistic distance (PBD), and the volumetric similarity (VS).

RESULTS

For all three GTVs, the median DSC was 0.75 (range 0.17-0.95), the median HD 15 (range 3.22-67.11) mm, the median PBD 0.33 (range 0.06-4.86), and the median VS was 0.88 (range 0.31-1). For ITVs and PTVs the results were similar. When comparing the imaging modalities for delineation, the best agreement for the GTV was achieved using PET/CT, and for the ITV and PTV using 4D PET/CT, in treatment position with abdominal compression.

CONCLUSION

Overall, there was good GTV agreement (DSC). Combined metrics appeared to allow a more valid detection of interobserver variation. For SBRT, either 4D PET/CT or 3D PET/CT in treatment position with abdominal compression leads to better agreement and should be considered as a very useful imaging modality for the definition of treatment volumes in pancreatic SBRT. Contouring does not appear to be the weakest link in the treatment planning chain of SBRT for PACA.

摘要

目的

本研究旨在评估德国放射肿瘤学会(DEGRO)放射外科和立体定向放射治疗工作组内胰腺癌(PACA)靶区定义的观察者间一致性(IOA),并确定成像方式对靶区定义的影响。

方法

从一个大型 SBRT 数据库中选择了两个局部晚期 PACA 病例和一个局部复发病例。基于计划的 4DCT(带或不带 IV 对比剂)、带或不带 PET/CT、带或不带诊断性 MRI 进行勾画。与其他研究相比,本研究创新性地使用了四项指标的组合来整合靶区分割的多个方面:Dice 系数(DSC)、Hausdorff 距离(HD)、概率距离(PBD)和体积相似性(VS)。

结果

对于所有三个 GTV,中位数 DSC 为 0.75(范围 0.17-0.95),中位数 HD 为 15(范围 3.22-67.11)mm,中位数 PBD 为 0.33(范围 0.06-4.86),中位数 VS 为 0.88(范围 0.31-1)。对于 ITV 和 PTV,结果相似。当比较用于勾画的成像方式时,使用 PET/CT 时 GTV 的一致性最佳,使用 4D PET/CT 在治疗位置并进行腹部加压时 ITV 和 PTV 的一致性最佳。

结论

总体而言,GTV 具有良好的一致性(DSC)。综合指标似乎可以更有效地检测观察者间的差异。对于 SBRT,4D PET/CT 或 3D PET/CT 在治疗位置并进行腹部加压应作为胰腺 SBRT 治疗体积定义的非常有用的成像方式。对于 PACA 的 SBRT 治疗计划链,勾画似乎不是最薄弱的环节。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae4/10598103/fe54edff1fd4/66_2023_2085_Fig1_HTML.jpg

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本文引用的文献

1
Metrics to evaluate the performance of auto-segmentation for radiation treatment planning: A critical review.
Radiother Oncol. 2021 Jul;160:185-191. doi: 10.1016/j.radonc.2021.05.003. Epub 2021 May 11.
2
ESTRO ACROP guidelines for target volume definition in pancreatic cancer.
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4
Auto-segmentation of pancreatic tumor in multi-parametric MRI using deep convolutional neural networks.
Radiother Oncol. 2020 Apr;145:193-200. doi: 10.1016/j.radonc.2020.01.021. Epub 2020 Feb 8.
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Strahlenther Onkol. 2018 Sep;194(9):843-854. doi: 10.1007/s00066-018-1314-2. Epub 2018 May 25.
9
Planning benchmark study for SBRT of early stage NSCLC : Results of the DEGRO Working Group Stereotactic Radiotherapy.
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