SynthesisAJNR. American journal of neuroradiology2024
Ten Years of VASARI Glioma Features: Systematic Review and Meta-Analysis of Their Impact and Performance.
Synthesis in AJNR. American journal of neuroradiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
8 citing papers in PubMed.
- Glioblastoma radiomics can delineate systemic immune activity states like blood abundance of T cell populations or transcription factors.Journal of neuroinflammation · 2026Article
- Visual versus region-of-interest based diffusion evaluation and their diagnostic impact in adult-type diffuse gliomas.Neuroradiology · 2026Article
- MRI-based prediction of DNA methylation grade in IDH-mutant astrocytomas using qualitative imaging features and tumor volumetrics.Neuroradiology · 2025Article
- Opportunities and challenges in application of VASARI features in neuro-oncology.Neuro-oncology practice · 2025Review
- Improving diagnostic accuracy in preoperative glioma classification: performance of knowledge-enhanced large language models compared with radiologists.NPJ precision oncology · 2025Article
- Assessing inter-rater reliability of MRI features in glioma: a multi-radiologist agreement study.BMC medical imaging · 2025Article
- Towards integrating imaging and immunology in glioblastoma: mapping blood immune system metrics to tumor magnetic resonance image data.Acta neuropathologica communications · 2024Article
- VASARI Glioma Features: Insights into Their Impact and Performance.Radiology. Imaging cancer · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVisually Accessible Rembrandt (Repository for Molecular Brain Neoplasia Data) Images (VASARI) features, a vocabulary to establish reproducible terminology for glioma reporting, have been applied for a decade, but a systematic performance evaluation is lacking. PURPOSE: Our aim was to conduct a systematic review and meta-analysis of the performance of the VASARI features set for glioma assessment. DATA SOURCES: MEDLINE, Web of Science, EMBASE, and the Cochrane Library were systematically searched until September 26, 2023. STUDY SELECTION: Original articles predicting diagnosis, progression, and survival in patients with glioma were included. DATA ANALYSIS: The modified Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was applied to evaluate the risk-of-bias. The meta-analysis used a random effects model and forest plot visualizations, if ≥5 comparable studies with a low or medium risk of bias were provided. DATA SYNTHESIS: Thirty-five studies (3304 patients) were included. Risk-of-bias scores were medium ( LIMITATIONS: Studies were heterogeneously designed and often with a small sample size. Several studies used The Cancer Imaging Archive database, with likely overlapping cohorts. The meta-analysis for
conclusionsSome VASARI features perform well in predicting overall survival and
Indexed as
Identifiers
What OpenQuestion holds
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.