Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year
survival rate of high-grade glioma is poor. Magnetic resonance imaging (MRI) is essential for …

Radiomics is an emerging discipline that aims to make intelligent predictions and derive
medical insights based on quantitative features extracted from medical images as a means …

Radiomics seeks to apply classical methods of image processing to obtain quantitative
parameters from imaging. Derived features are subsequently fed into algorithmic models to …

Gliomas are neurologically devastating tumors with generally poor outcomes. Traditionally,
survival prediction in glioma is studied from clinical features using statistical approaches …

In the central nervous system, gliomas are the most common, but complex primary tumors.
Genome-based molecular and clinical studies have revealed different classifications and …

Diffuse gliomas are incurable brain tumors, yet there is significant heterogeneity in patient
survival. Advanced computational techniques such as radiomics show potential for …

Purpose To establish an individualized predictive model to identify patients with brainstem
gliomas (BSGs) at high risk of H3K27M mutation, with the inclusion of brain structural …

Introduction Like other forms of neuropathology, gliomas appear to spread along neural
pathways. Accordingly, our group and others have previously shown that brain network …

Simple Summary Early characterization of the isocitrate dehydrogenase (IDHIDH) gene
mutation status of glioma is crucial for personalized decision making and prognosis in …

Diffuse gliomas are the most common malignant primary brain tumors. Identification of
isocitrate dehydrogenase 1 (IDH1) mutations aids the diagnostic classification of these …