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针对不同患者体位的成人及儿童头颈部放射治疗的深度学习分割模型的验证

Validation of a deep-learning segmentation model for adult and pediatric head and neck radiotherapy in different patient positions.

作者信息

Chen Linda, Platzer Patricia, Reschl Christian, Schafasand Mansure, Nachankar Ankita, Lukas Hajdusich Christoph, Kuess Peter, Stock Markus, Habraken Steven, Carlino Antonio

机构信息

MedAustron Ion Therapy Center, Department of Medical Physics, Wiener Neustadt, Austria.

Erasmus MC Cancer Institute, University Medical Center, Department of Radiotherapy, Rotterdam, the Netherlands.

出版信息

Phys Imaging Radiat Oncol. 2023 Dec 27;29:100527. doi: 10.1016/j.phro.2023.100527. eCollection 2024 Jan.

DOI:10.1016/j.phro.2023.100527
PMID:38222671
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10787237/
Abstract

BACKGROUND AND PURPOSE

Autocontouring for radiotherapy has the potential to significantly save time and reduce interobserver variability. We aimed to assess the performance of a commercial autocontouring model for head and neck (H&N) patients in eight orientations relevant to particle therapy with fixed beam lines, focusing on validation and implementation for routine clinical use.

MATERIALS AND METHODS

Autocontouring was performed on sixteen organs at risk (OARs) for 98 adult and pediatric patients with 137 H&N CT scans in eight orientations. A geometric comparison of the autocontours and manual segmentations was performed using the Hausdorff Distance 95th percentile, Dice Similarity Coefficient (DSC) and surface DSC and compared to interobserver variability where available. Additional qualitative scoring and dose-volume-histogram (DVH) parameters analyses were performed for twenty patients in two positions, consisting of scoring on a 0-3 scale based on clinical usability and comparing the mean (D) and near-maximum (D) dose, respectively.

RESULTS

For the geometric analysis, the model performance in head-first-supine straight and hyperextended orientations was in the same range as the interobserver variability. HD95, DSC and surface DSC was heterogeneous in other orientations. No significant geometric differences were found between pediatric and adult autocontours. The qualitative scoring yielded a median score of ≥ 2 for 13/16 OARs while 7/32 DVH parameters were significantly different.

CONCLUSIONS

For head-first-supine straight and hyperextended scans, we found that 13/16 OAR autocontours were suited for use in daily clinical practice and subsequently implemented. Further development is needed for other patient orientations before implementation.

摘要

背景与目的

放射治疗中的自动轮廓勾画有显著节省时间和减少观察者间差异的潜力。我们旨在评估一种用于头颈部(H&N)患者的商业自动轮廓勾画模型在与固定束线粒子治疗相关的八个方向上的性能,重点是常规临床应用的验证和实施。

材料与方法

对98例成人和儿童患者的137次头颈部CT扫描在八个方向上的16个危及器官(OARs)进行自动轮廓勾画。使用95% 百分位的豪斯多夫距离、骰子相似系数(DSC)和表面DSC对自动轮廓和手动分割进行几何比较,并与可用的观察者间差异进行比较。对20例患者在两个位置进行了额外的定性评分和剂量体积直方图(DVH)参数分析,包括基于临床可用性在0 - 3分的量表上评分,并分别比较平均剂量(D)和近最大剂量(D)。

结果

对于几何分析,头先仰卧位直位和过伸位的模型性能与观察者间差异处于同一范围。在其他方向上,HD95、DSC和表面DSC存在异质性。儿童和成人自动轮廓之间未发现显著的几何差异。定性评分中,16个OARs中有13个的中位数评分≥2,而32个DVH参数中有7个存在显著差异。

结论

对于头先仰卧位直位和过伸位扫描,我们发现16个OARs中的13个自动轮廓适合日常临床实践并随后实施。在实施之前,其他患者体位还需要进一步改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fcc/10787237/931ba362e6ef/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fcc/10787237/eff78a97bd2f/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fcc/10787237/b436988aeada/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fcc/10787237/26bd3bdded4e/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fcc/10787237/931ba362e6ef/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fcc/10787237/eff78a97bd2f/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fcc/10787237/b436988aeada/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fcc/10787237/26bd3bdded4e/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fcc/10787237/931ba362e6ef/gr4.jpg

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