Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to
their infiltrative properties, still rely on conventional structural MRI, which does not deliver …

Objectives To evaluate the methodological quality and diagnostic accuracy of MRI-based
radiomic studies predicting O6-methylguanine-DNA methyltransferase (MGMT) promoter …

Purpose This study evaluated the performance of multiparametric magnetic resonance
imaging (MRI)–based fusion radiomics models (MMFRs) to predict telomerase reverse …

Imaging is central to the clinical surveillance of brain tumors yet it provides limited insight
into a tumor's underlying biology. Machine learning and other mathematical modeling …

The methylation of the O6-methylguanine-DNA methyltransferase (MGMT) promoter is a
molecular marker associated with a better response to chemotherapy in patients with …

Purpose To develop and validate a dynamic contrast-enhanced (DCE) MRI-based radiomics
model to predict epidermal growth factor receptor (EGFR) amplification in patients with …

In high-grade gliomas, pseudoprogression after radiation treatment might dramatically
impact patient's management. We searched for perioperative imaging predictors of …

Abstract Purpose Artificial Intelligence (AI) has become increasingly integrated clinically
within neurosurgical oncology. This report reviews the cutting-edge technologies impacting …

Background: Glioblastoma (GBM) is the most common primary malignant brain tumor in
adults, with an aggressive disease course that requires accurate prognosis for …

Objective This study aims to evaluate the effectiveness of deep learning features derived
from multi-sequence magnetic resonance imaging (MRI) in determining the O6 …