Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, The Netherlands.
Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, United States.
Radiother Oncol. 2018 Sep;128(3):459-466. doi: 10.1016/j.radonc.2018.06.012. Epub 2018 Jun 26.
This study investigated whether Magnetic Resonance image biomarkers (MR-IBMs) were associated with xerostomia 12 months after radiotherapy (Xer) and to test the hypothesis that the ratio of fat-to-functional parotid tissue is related to Xer. Additionally, improvement of the reference Xer model based on parotid gland dose and baseline xerostomia, with MR-IBMs was explored.
Parotid gland MR-IBMs of 68 head and neck cancer patients were extracted from pre-treatment T1-weighted MR images, which were normalized to fat tissue, quantifying 21 intensity and 43 texture image characteristics. The performance of the resulting multivariable logistic regression models after bootstrapped forward selection was compared with that of the logistic regression reference model. Validity was tested in a small external cohort of 25 head and neck cancer patients.
High intensity MR-IBM P90 (the 90th intensity percentile) values were significantly associated with a higher risk of Xer. High P90 values were related to high fat concentration in the parotid glands. The MR-IBM P90 significantly improved model performance in predicting Xer (likelihood-ratio-test; p = 0.002), with an increase in internally validated AUC from 0.78 (reference model) to 0.83 (P90). The MR-IBM P90 model also outperformed the reference model (AUC = 0.65) on the external validation cohort (AUC = 0.83).
Pre-treatment MR-IBMs were associated to radiation-induced xerostomia, which supported the hypothesis that the amount of predisposed fat within the parotid glands is associated with Xer. In addition, xerostomia prediction was improved with MR-IBMs compared to the reference model.
本研究旨在探讨磁共振成像生物标志物（MR-IBMs）是否与放疗后 12 个月的口干症（Xer）有关，并检验以下假设，即功能性腮腺组织与脂肪组织的比例与 Xer 相关。此外，还探讨了基于腮腺剂量和基线口干症，结合 MR-IBMs 来改进参考 Xer 模型。
从 68 例头颈部癌症患者的治疗前 T1 加权磁共振图像中提取腮腺 MR-IBMs，对其进行脂肪组织归一化，定量分析 21 个强度和 43 个纹理图像特征。经过 bootstrapped 向前选择的多变量逻辑回归模型的性能与逻辑回归参考模型进行了比较。在 25 例头颈部癌症患者的小外部队列中进行了验证。
高强度 MR-IBM P90（第 90 个强度百分位数）值与 Xer 风险较高显著相关。高 P90 值与腮腺内高脂肪浓度有关。MR-IBM P90 显著提高了 Xer 预测的模型性能（似然比检验；p=0.002），内部验证 AUC 从参考模型的 0.78 增加到 0.83（P90）。在外部验证队列中，MR-IBM P90 模型也优于参考模型（AUC=0.65）（AUC=0.83）。
治疗前的 MR-IBMs 与放疗引起的口干症有关，这支持了以下假设，即腮腺内易发生的脂肪量与 Xer 有关。此外，与参考模型相比，MR-IBMs 提高了 Xer 的预测能力。
