Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, South Korea.
Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, South Korea.
J Neuroradiol. 2022 Jan;49(1):59-65. doi: 10.1016/j.neurad.2021.02.007. Epub 2021 Mar 11.
Increasing evidence suggests that genomic and molecular markers need to be integrated in grading of meningioma. Telomerase reverse transcriptase promoter (TERTp) mutation is receiving attention due to its clinical relevance in the treatment of meningiomas. The predictive ability of conventional and diffusion MRI parameters for determining the TERTp mutation status in grade II meningiomas has yet been identified.
In this study, 63 patients with surgically confirmed grade II meningiomas (56 TERTp wildtype, 7 TERTp mutant) were included. Conventional imaging features were qualitatively assessed. The maximum diameter, volume of the tumors and histogram parameters from the apparent diffusion coefficient (ADC) were assessed. Independent clinical and imaging risk factors for TERTp mutation were investigated using multivariable logistic regression. The discriminative value of the prediction models with and without imaging features was evaluated.
In the univariable regression, older age (odds ratio [OR] = 1.13, P = 0.005), larger maximum diameter (OR = 1.09, P = 0.023), larger volume (OR = 1.04, P = 0.014), lower mean ADC (OR = 0.02, P = 0.025), and lower ADC 10th percentile (OR = 0.01, P = 0.014) were predictors of TERTp mutation. In multivariable regression, age (OR = 1.13, P = 0.009) and ADC 10th percentile (OR = 0.01, P = 0.038) were independent predictors of variables for predicting the TERTp mutation status. The performance of the prediction model increased upon inclusion of imaging parameters (area under the curves of 0.86 and 0.91, respectively, without and with imaging parameters).
Older age and lower ADC 10th percentile may be useful parameters to predict TERTp mutation in grade II meningiomas.
越来越多的证据表明，基因组和分子标志物需要整合到脑膜瘤分级中。由于端粒酶逆转录酶启动子 (TERTp) 突变在脑膜瘤治疗中的临床相关性，因此受到关注。目前尚不清楚常规和弥散 MRI 参数对于确定 II 级脑膜瘤 TERTp 突变状态的预测能力。
本研究纳入了 63 例经手术证实的 II 级脑膜瘤患者（56 例 TERTp 野生型，7 例 TERTp 突变型）。对常规影像学特征进行定性评估。评估肿瘤的最大直径、体积和表观扩散系数 (ADC) 的直方图参数。采用多变量逻辑回归分析 TERTp 突变的独立临床和影像学危险因素。评估有无影像学特征的预测模型的判别价值。
单变量回归分析显示，年龄较大（优势比 [OR] = 1.13，P = 0.005）、最大直径较大（OR = 1.09，P = 0.023）、体积较大（OR = 1.04，P = 0.014）、平均 ADC 值较低（OR = 0.02，P = 0.025）、ADC 值第 10 百分位数较低（OR = 0.01，P = 0.014）是 TERTp 突变的预测因素。多变量回归分析显示，年龄（OR = 1.13，P = 0.009）和 ADC 值第 10 百分位数（OR = 0.01，P = 0.038）是预测 TERTp 突变状态的独立预测因素。纳入影像学参数后，预测模型的性能提高（无影像学参数时曲线下面积分别为 0.86 和 0.91）。
年龄较大和 ADC 值第 10 百分位数较低可能是预测 II 级脑膜瘤 TERTp 突变的有用参数。
