ReviewInsights into imaging2022
A systematic review and meta-analysis on the differentiation of glioma grade and mutational status by use of perfusion-based magnetic resonance imaging.
Review in Insights into imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis 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.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.
- The role of DSC MR perfusion in predicting IDH mutation and 1p19q codeletion status in gliomas: meta-analysis and technical considerations.Neuroradiology · 2023Pooled it
- RCBVmax from DSC Perfusion MRI as a Supportive Imaging Biomarker for Differentiating IDH-Mutant Astrocytomas and Oligodendroglioma.Clinical neuroradiology · 2026Article
- Vascular permeability mediates contralateral glymphatic dysfunction across glioma grades and IDH status.Neuroradiology · 2026Article
- Imaging biomarkers for detecting IDH mutations and monitoring response to novel targeted therapies: Current insights and future perspectives.Neuro-oncology · 2026Review
- Differentiation of Molecular Glioblastomas and Lower-grade Diffuse Astrocytomas Using MRI Perfusion and Diffusion Parameters.Clinical neuroradiology · 2026Article
- Comparative evaluation of dynamic susceptibility contrast MRI techniques for brain imaging at 3T and 5T magnetic field strengths.Frontiers in human neuroscience · 2026Article
- The utility of multi-b-value diffusion and arterial spin labelling magnetic resonance imaging in gliomas grading and prediction of isocitrate dehydrogenase status.Quantitative imaging in medicine and surgery · 2025Article
- Predicting glioma histo-molecular diagnosis and prognosis: preoperative dynamic contrast-enhanced magnetic resonance imaging insights.Quantitative imaging in medicine and surgery · 2025Article
- An optimized tissue sampling scheme guided by MRI features reveals intratumoral heterogeneity in glioblastoma.Scientific reports · 2025Article
- Evaluation of [Journal of clinical medicine · 2025Article
- Does arterial spin labelling represent a valid alternative to other MR perfusion techniques in neuro-oncology?La Radiologia medica · 2025Review
- Role of dynamic contrast-enhanced and dynamic susceptibility contrast imaging in evaluating the biological features of glioma.Quantitative imaging in medicine and surgery · 2025Article
- The Value of Cerebral Blood Volume Derived from Dynamic Susceptibility Contrast Perfusion MRI in Predicting IDH Mutation Status of Brain Gliomas-A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2025Review
- Integrating quantitative DCE-MRI parameters and radiomic features for improved IDH mutation prediction in gliomas.Frontiers in oncology · 2025Article
- Customized SAM-Med3D with multi-view adapter and T2-FLAIR mismatch features for glioma IDH genotyping and grading.Frontiers in behavioral neuroscience · 2025Article
- Research Progress on Glioma Microenvironment and Invasiveness Utilizing Advanced Multi-Parametric Quantitative MRI.Cancers · 2024Review
- Impact of Sex Hormones on Glioblastoma: Sex-Related Differences and Neuroradiological Insights.Life (Basel, Switzerland) · 2024Review
- Statistical plots in oncologic imaging, a primer for neuroradiologists.The neuroradiology journal · 2024Review
- The diagnostic efficiency of integration of 2HG MRS and IVIM versus individual parameters for predicting IDH mutation status in gliomas in clinical scenarios: A retrospective study.Journal of neuro-oncology · 2024Article
- Probing the glioma microvasculature: a case series of the comparison between perfusion MRI and intraoperative high-frame-rate ultrafast Doppler ultrasound.European radiology experimental · 2024Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMolecular characterization plays a crucial role in glioma classification which impacts treatment strategy and patient outcome. Dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) perfusion imaging have been suggested as methods to help characterize glioma in a non-invasive fashion. This study set out to review and meta-analyze the evidence on the accuracy of DSC and/or DCE perfusion MRI in predicting IDH genotype and 1p/19q integrity status.
methodsAfter systematic literature search on Medline, EMBASE, Web of Science and the Cochrane Library, a qualitative meta-synthesis and quantitative meta-analysis were conducted. Meta-analysis was carried out on aggregated AUC data for different perfusion metrics.
resultsOf 680 papers, twelve were included for the qualitative meta-synthesis, totaling 1384 patients. It was observed that CBV, ktrans, Ve and Vp values were, in general, significantly higher in IDH wildtype compared to IDH mutated glioma. Meta-analysis comprising of five papers (totaling 316 patients) showed that the AUC of CBV, ktrans, Ve and Vp were 0.85 (95%-CI 0.75-0.93), 0.81 (95%-CI 0.74-0.89), 0.84 (95%-CI 0.71-0.97) and 0.76 (95%-CI 0.61-0.90), respectively. No conclusive data on the prediction of 1p/19q integrity was available from these studies.
conclusionsFuture research should aim to predict 1p/19q integrity based on perfusion MRI data. Additionally, correlations with other clinically relevant outcomes should be further investigated, including patient stratification for treatment and overall survival.
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Registered trials
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.