The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …

Objective The main aim of the present systematic review was a comprehensive overview of
the Radiomics Quality Score (RQS)–based systematic reviews to highlight common issues …

Molecular classification has transformed the management of brain tumors by enabling more
accurate prognostication and personalized treatment. However, timely molecular diagnostic …

The central role of MRI in neuro-oncology is undisputed. The technique is used, both in
clinical practice and in clinical trials, to diagnose and monitor disease activity, support …

Objectives Radiomic features have demonstrated encouraging results for non-invasive
detection of molecular biomarkers, but the lack of guidelines for pre-processing MRI-data …

Texture-based convolutional neural networks (CNNs) have shown great promise in
predicting various types of cancer, including lower grade glioma (LGG) through radiomics …

Purpose Molecular biomarkers are important for classifying intracranial gliomas, prompting
research into correlating imaging with genotype (“radiogenomics”). A limitation of the …

Simple Summary Significant efforts have been put toward developing MRI-based
radiogenomics for IDH status subtyping predictions; however, in the vast majority of these …

Background IDH mutation and 1p/19q codeletion status are important prognostic markers for
glioma that are currently determined using invasive procedures. Our goal was to develop …

Background Advances in molecular diagnostics accomplished the discovery of two
malignant glioma entities harboring alterations in the H3 histone: diffuse midline glioma, H3 …