端粒酶逆转录酶启动子 (pTERT) 突变状态在 WHO IV 级神经胶质瘤患者的决策和预测预后中发挥着关键作用。本研究旨在评估弥散加权成像 (DWI) 对预测 WHO IV 级胶质瘤 pTERT 突变状态的价值。获得了 266 例 WHO IV 级胶质瘤患者的磁共振 (MR) 成像 (MRI) 数据和分子信息在医院并分为训练集、验证集。训练集与验证集的比例约为 10:3。我们为每种 MR 模态（包括结构 MRI（T1 加权、T2 加权和对比增强 T1 加权）和 DWI*）训练相同的残差卷积神经网络 (ResNet)，以比较 DWI 和传统结构 MRI 之间的预测能力核磁共振成像。我们还探讨了不同感兴趣区域 (ROI) 对 pTERT 突变状态预测结果的影响。结构 MRI 模式对 pTERT 突变状态的预测效果较差（准确度 = 51%-54%；曲线下面积 [AUC]=0.545-0.571） ，而 DWI 与其 ADC 图相结合产生了最佳的预测性能（准确度 = 85.2%，AUC = 0.934）。包括放射学和临床特征并没有进一步提高预测 pTERT 突变状态的性能。整个肿瘤体积产生了最佳的预测性能。DWI技术在预测WHO IV级胶质瘤的pTERT突变方面显示出巨大的潜力，应将其纳入临床实践中的WHO IV级胶质瘤的MRI协议中。这是第一个大规模模型研究验证 DWI 对 WHO IV 级神经胶质瘤中 pTERT 的预测价值。© 作者 2024。由牛津大学出版社代表英国放射学会出版。版权所有。如需权限，请发送电子邮件至：journals.permissions@oup.com。

Telomerase reverse transcriptase promoter (pTERT) mutation status plays a key role in making decisions and predicting prognoses for patients with WHO grade IV glioma. This study was conducted to assess the value of diffusion-weighted imaging (DWI) for predicting pTERT mutation status in WHO grade IV glioma.Magnetic resonance (MR) imaging (MRI) data and molecular information were obtained for 266 patients with WHO grade IV glioma at the Hospital and divided into training, validation sets. The ratio of training to validation set was approximately 10:3. We trained the same residual convolutional neural network (ResNet) for each MR modality, including structural MRIs (T1-weighted, T2-weighted, and contrast-enhanced T1-weighted) and DWI*, to compare the predictive capacities between DWI and conventional structural MRI. We also explored the effects of different regions of interest (ROIs) on pTERT mutation status prediction outcomes.Structural MRI modalities poorly predicted the pTERT mutation status (accuracy = 51%-54%; area under the curve [AUC]=0.545-0.571), whereas DWI combined with its ADC maps yielded the best predictive performance (accuracy = 85.2%, AUC = 0.934). Including the radiological and clinical characteristics did not further improve the performance for predicting pTERT mutation status. The entire tumor volume yielded the best prediction performance.DWI technology shows promising potential for predicting pTERT mutations in WHO grade IV glioma and should be included in the MRI protocol for WHO grade IV glioma in clinical practice.This is the first large-scale model study to validate the predictive value of DWI for pTERT in WHO grade IV glioma.© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.