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将剂量学梯度和腮腺迁移纳入口干症预测

Incorporation of Dosimetric Gradients and Parotid Gland Migration Into Xerostomia Prediction.

作者信息

Astaburuaga Rosario, Gabryś Hubert S, Sánchez-Nieto Beatriz, Floca Ralf O, Klüter Sebastian, Schubert Kai, Hauswald Henrik, Bangert Mark

机构信息

Department of Medical Physics in Radiation Oncology, Deutsches Krebsforschungszentrum, Heidelberg, Germany.

Medical Faculty of Heidelberg, Universität Heidelberg, Heidelberg, Germany.

出版信息

Front Oncol. 2019 Jul 31;9:697. doi: 10.3389/fonc.2019.00697. eCollection 2019.

Abstract

Due to the sharp gradients of intensity-modulated radiotherapy (IMRT) dose distributions, treatment uncertainties may induce substantial deviations from the planned dose during irradiation. Here, we investigate if the planned mean dose to parotid glands in combination with the dose gradient and information about anatomical changes during the treatment improves xerostomia prediction in head and neck cancer patients. Eighty eight patients were retrospectively analyzed. Three features of the contralateral parotid gland were studied in terms of their association with the outcome, i.e., grade ≥ 2 (G2) xerostomia between 6 months and 2 years after radiotherapy (RT): planned mean dose (MD), average lateral dose gradient (GRADX), and parotid gland migration toward medial (PGM). PGM was estimated using daily megavoltage computed tomography (MVCT) images. Three logistic regression models where analyzed: based on (1) MD only, (2) MD and GRADX, and (3) MD, GRADX, and PGM. Additionally, the cohort was stratified based on the median value of GRADX, and a univariate analysis was performed to study the association of the MD with the outcome for patients in low- and high-GRADX domains. The planned MD failed to recognize G2 xerostomia patients (AUC = 0.57). By adding the information of GRADX (second model), the model performance increased to AUC = 0.72. The addition of PGM (third model) led to further improvement in the recognition of the outcome (AUC = 0.79). Remarkably, xerostomia patients in the low-GRADX domain were successfully identified (AUC = 0.88) by the MD alone. Our results indicate that GRADX and PGM, which together serve as a proxy of dosimetric changes, provide valuable information for xerostomia prediction.

摘要

由于调强放射治疗(IMRT)剂量分布的梯度较大,治疗不确定性可能会在照射过程中导致与计划剂量产生显著偏差。在此,我们研究腮腺的计划平均剂量与剂量梯度以及治疗期间解剖结构变化信息相结合,是否能改善头颈部癌患者的口干症预测。对88例患者进行了回顾性分析。研究了对侧腮腺的三个特征与放疗(RT)后6个月至2年口干症结果(即≥2级(G2)口干症)之间的关联:计划平均剂量(MD)、平均横向剂量梯度(GRADX)以及腮腺向内侧的迁移(PGM)。使用每日兆伏级计算机断层扫描(MVCT)图像估计PGM。分析了三个逻辑回归模型:基于(1)仅MD,(2)MD和GRADX,以及(3)MD、GRADX和PGM。此外,根据GRADX的中位数对队列进行分层,并进行单变量分析以研究MD与低GRADX和高GRADX领域患者结果之间的关联。计划MD未能识别出G2口干症患者(AUC = 0.57)。通过添加GRADX信息(第二个模型),模型性能提高到AUC = 0.72。添加PGM(第三个模型)导致对结果的识别进一步改善(AUC = 0.79)。值得注意的是,仅MD就能成功识别低GRADX领域的口干症患者(AUC = 0.88)。我们的结果表明,GRADX和PGM共同作为剂量学变化的代表,为口干症预测提供了有价值的信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a11/6684756/8a4d044e25be/fonc-09-00697-g0001.jpg

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