Deep Learning: Assessment of meningioma subtypes by semantic and radiomic features

The clinical management of meningioma, the most common adult primary intracranial tumors, is guided by tumor grade and biological behavior. Currently, the assessment of tumor grade follows surgical resection and histopathologic review. Reliable techniques for pre-operative determination of tumor grade may enhance clinical decision-making.
Using machine-learning algorithms gained from pre-operative MRI scans, this study aims to determine the diagnostic accuracy of a neural network in segmentating and discriminating between benign and atypical/anaplastic meningiomas.