Currently, most CNS tumors require tissue sampling to discern their molecular/genomic
landscape. However, growing research has shown the powerful role imaging can play in …

Based on artificial intelligence (AI), computer-assisted medical diagnosis can scientifically
and efficiently deal with a large quantity of medical imaging data. AI technologies including …

Purpose MYCN amplification plays a critical role in defining high-risk subgroup of patients
with neuroblastoma. We aimed to develop and validate the CT-based machine learning …

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

Purpose Magnetic resonance spectroscopy (MRS) provides a non-invasive means of
determining isocitrate dehydrogenase (IDH) status. Determination of 2-hydroxyglutarate (2 …

Abstract Purpose The Checklist for Artificial Intelligence in Medical Imaging (CLAIM) is a
recently released guideline designed for the optimal reporting methodology of artificial …

Introduction Chemotherapy and radiotherapy can produce treatment‐related effects, which
may mimic tumour progression. Advances in Artificial Intelligence (AI) offer the potential to …

Purpose The increasing importance of molecular markers for classification and
prognostication of diffuse gliomas has prompted the use of imaging features to predict …

Simple Summary The T2-FLAIR mismatch sign has shown promise in determining IDH
mutant 1p/19q non-co-deleted diffuse gliomas with a high specificity and modest sensitivity …

Molecular biomarkers are becoming increasingly important in the classification of
intracranial gliomas. While tissue sampling remains the gold standard, there is growing …