SynthesisNeuroradiology2021
Conventional MRI features of adult diffuse glioma molecular subtypes: a systematic review.
Synthesis in Neuroradiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed, 4 syntheses or guidelines pooled it, 55 citations in OpenAlex.
- High-grade gliomas with autoimmune encephalitis-like presentation: case report and systematic review of the literature.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Pooled it
- MRI-derived deep learning models for predicting 1p/19q codeletion status in glioma patients: a systematic review and meta-analysis of diagnostic test accuracy studies.Neuroradiology · 2025Pooled it
- Imaging features associated with H3 K27-altered and H3 G34-mutant gliomas: a narrative systematic review.Cancer imaging : the official publication of the International Cancer Imaging Society · 2022Pooled it
- Pooled it
- Robust deep learning for incomplete MRI sequences in glioma grading and IDH mutation status prediction: a large-scale multicenter study.European radiology · 2026Article
- Conventional MRI/CT for differentiation of IDH-mutant adult-type diffuse gliomas: revisited with a new imaging feature "scFLAIR-D".Japanese journal of radiology · 2026Article
- Management of Adult Patients With Isocitrate Dehydrogenase-Mutant Gliomas in Australia: An Expert Position Statement From the Cooperative Trials Group for Neuro-Oncology.Asia-Pacific journal of clinical oncology · 2026Review
- IDH status shapes glioma oncotopy: voxel-wise mapping of 644 adult diffuse gliomas.Neuroradiology · 2026Article
- Presenting clinical and radiographic features of diffuse glioma molecular subtypes in accordance with the 2021 CNS5 WHO classification.Neuro-oncology practice · 2025Article
- The Diagnostic Value of Susceptibility-Weighted Imaging in Preoperative Grading of Glial Tumors.Cureus · 2025Article
- Structured reporting of gliomas based on VASARI criteria to improve report content and consistency.BMC medical imaging · 2025Article
- Preoperative prediction of diffuse glioma type and grade in adults: a gadolinium-free MRI-based decision tree.European radiology · 2025Article
- Radiomics for predicting grades, isocitrate dehydrogenase mutation, and oxygen 6-methylguanine-DNA methyltransferase promoter methylation of adult diffuse gliomas: combination of structural MRI, apparent diffusion coefficient, and susceptibility-weighted imaging.Quantitative imaging in medicine and surgery · 2024Article
- Magnetic resonance relaxometry in quantitative imaging of brain gliomas: A literature review.The neuroradiology journal · 2024Review
- Rethinking extent of resection of contrast-enhancing and non-enhancing tumor: different survival impacts on adult-type diffuse gliomas in 2021 World Health Organization classification.European radiology · 2024Article
- Radiogenomics Provides Insights into Gliomas Demonstrating Single-Arm 1p or 19q Deletion.AJNR. American journal of neuroradiology · 2023Article
- Radiogenomics of adult intracranial gliomas after the 2021 World Health Organisation classification: a review of changes, challenges and opportunities.Quantitative imaging in medicine and surgery · 2023Review
- Correlating MRI features with additional genetic markers and patient survival in histological grade 2-3 IDH-mutant astrocytomas.Neuroradiology · 2023Article
- Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas.Cancers · 2023Article
- Cyclin-Dependent Kinase Inhibitor 2A/B Homozygous Deletion Prediction and Survival Analysis.Brain sciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeMolecular parameters have become integral to glioma diagnosis. Much of radiogenomics research has focused on the use of advanced MRI techniques, but conventional MRI sequences remain the mainstay of clinical assessments. The aim of this research was to synthesize the current published data on the accuracy of standard clinical MRI for diffuse glioma genotyping, specifically targeting IDH and 1p19q status.
methodsA systematic search was performed in September 2019 using PubMed and the Cochrane Library, identifying studies on the diagnostic value of T1 pre-/post-contrast, T2, FLAIR, T2*/SWI and/or 3-directional diffusion-weighted imaging sequences for the prediction of IDH and/or 1p19q status in WHO grade II-IV diffuse astrocytic and oligodendroglial tumours as defined in the WHO 2016 Classification of CNS Tumours.
resultsForty-four studies including a total of 5286 patients fulfilled the inclusion criteria. Correlations between key glioma molecular markers, namely IDH and 1p19q, and distinctive MRI findings have been established, including tumour location, signal composition (including the T2-FLAIR mismatch sign) and apparent diffusion coefficient values.
conclusionConsistent trends have emerged indicating that conventional MRI is valuable for glioma genotyping, particularly in presumed lower grade glioma. However, due to limited interobserver testing, the reproducibility of qualitatively assessed visual features remains an area of uncertainty.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.