脊髓弥漫性中线胶质瘤伴组蛋白H3 K27M突变与野生型的鉴别：磁共振成像比较
Differentiation between spinal cord diffuse midline glioma with histone H3 K27M mutation and wild type: comparative magnetic resonance imaging.
作者信息
Jung Jo Sung, Choi Yoon Seong, Ahn Sung Soo, Yi Seong, Kim Se Hoon, Lee Seung-Koo
机构信息
Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea.
Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea.
出版信息
Neuroradiology. 2019 Mar;61(3):313-322. doi: 10.1007/s00234-019-02154-8. Epub 2019 Jan 20.
PURPOSE
Diffuse midline glioma with histone H3 K27M mutation is a new entity described in the 2016 update of the World Health Organization Classification of Tumors of the Central Nervous System. The purpose of this study was to evaluate the clinical and imaging characteristics to predict the presence of H3 K27M mutation in spinal cord glioma using a machine learning-based classification model.
METHODS
A total of 41 spinal cord glioma patients consisting of 24 H3 K27M mutants and 17 wild types were enrolled in this retrospective study. A total of 17 clinical and radiological features were evaluated. The random forest (RF) model was trained with the clinical and radiological features to predict the presence of H3 K27M mutation. The diagnostic ability of the RF model was evaluated using receiver operating characteristic (ROC) analysis. Area under the ROC curves (AUC) was calculated.
RESULTS
MR imaging features of spinal cord diffuse midline gliomas were heterogeneous. Hemorrhage was the only variable that was able to differentiate H3 K27M mutated tumors from wild-type tumors in univariate analysis (p = 0.033). RF classifier yielded 0.632 classification AUC (95% CI, 0.456-0.808), 63.4% accuracy, 45.8% sensitivity, and 88.2% specificity.
CONCLUSION
Our findings indicate that clinical and radiological features are associated with H3 K27M mutation status in spinal cord glioma.
目的
组蛋白H3 K27M突变的弥漫性中线胶质瘤是2016年更新的世界卫生组织中枢神经系统肿瘤分类中描述的一种新实体。本研究的目的是使用基于机器学习的分类模型评估脊髓胶质瘤中H3 K27M突变存在情况的临床和影像特征，以进行预测。
方法
本项回顾性研究共纳入41例脊髓胶质瘤患者，其中24例为H3 K27M突变型，17例为野生型。共评估了17项临床和放射学特征。使用临床和放射学特征训练随机森林（RF）模型，以预测H3 K27M突变的存在情况。使用受试者工作特征（ROC）分析评估RF模型的诊断能力。计算ROC曲线下面积（AUC）。
结果
脊髓弥漫性中线胶质瘤的磁共振成像特征具有异质性。在单因素分析中，出血是唯一能够区分H3 K27M突变肿瘤与野生型肿瘤的变量（p = 0.033）。RF分类器的分类AUC为0.632（95%CI，0.456 - 0.808），准确率为63.4%，灵敏度为45.8%，特异度为88.2%。
结论
我们的研究结果表明，脊髓胶质瘤的临床和放射学特征与H3 K27M突变状态相关。
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