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.
Bibliographical notePublisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
All Science Journal Classification (ASJC) codes
- Radiology Nuclear Medicine and imaging
- Clinical Neurology
- Cardiology and Cardiovascular Medicine