SynthesisEuropean radiology2025
Radiomics for differentiating radiation-induced brain injury from recurrence in gliomas: systematic review, meta-analysis, and methodological quality evaluation using METRICS and RQS.
Synthesis in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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, 1 synthesis or guideline pooled it.
- Radiomics for differentiating ruptured intracranial aneurysms: overview, methodological quality evaluation using METRICS and RQS, and feature transportability validation using independent multi-center dataset.European radiology · 2026Pooled it
- Practical applications of photon-counting CT in oncology: an organ-based pictorial review.Insights into imaging · 2026Article
- Predicting early response to ablative radiotherapy in oligometastatic disease: a scoping review of radiomics-based machine learning and deep learning models.European radiology · 2026Article
- Why Radiomics Rarely Reaches the Clinic: Reproducibility, Validation, and Evidence Gap-A Critical Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Calibrated and explainable multiparametric MRI radiomics for differentiating tumor positive disease from treatment-related changes in glioblastoma.Frontiers in oncology · 2026Article
- Imaging in Neuro-oncology.Seminars in neurology · 2025Review
- Explanation and Elaboration with Examples for METRICS (METRICS-E3): an initiative from the EuSoMII Radiomics Auditing Group.Insights into imaging · 2025Article
- Postsurgical detection of glioma recurrence using MRI radiomics.Neuro-oncology advancesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo systematically evaluate glioma radiomics literature on differentiating between radiation-induced brain injury and tumor recurrence.
methodsLiterature was searched on PubMed and Web of Science (end date: May 7, 2024). Quality of eligible papers was assessed using METhodological RadiomICs Score (METRICS) and Radiomics Quality Score (RQS). Reliability of quality scoring tools were analyzed. Meta-analysis, meta-regression, and subgroup analysis were performed.
resultsTwenty-seven papers were included in the qualitative assessment. Mean average METRICS score and RQS percentage score across three readers was 57% (SD, 14%) and 16% (SD, 12%), respectively. Score-wise inter-rater agreement for METRICS ranged from poor to excellent, while RQS demonstrated moderate to excellent agreement. Item-wise agreement was moderate for both tools. Meta-analysis of 11 eligible studies yielded an estimated area under the receiver operating characteristic curve of 0.832 (95% CI, 0.757-0.908), with significant heterogeneity (I
conclusionWhile a good performance was noted for radiomics, results should be interpreted cautiously due to heterogeneity, publication bias, and quality issues thoroughly examined in this study. KEY POINTS: Question Radiomic literature on distinguishing radiation-induced brain injury from glioma recurrence lacks systematic reviews and meta-analyses that assess methodological quality using radiomics-specific tools. Findings While the results are encouraging, there was substantial heterogeneity, publication bias toward positive findings, and notable concerns regarding methodological quality. Clinical relevance Meta-analysis results need cautious interpretation due to significant problems detected during the analysis (e.g., suboptimal quality, heterogeneity, bias), which may help explain why radiomics has not yet been translated into clinical practice.
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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 Socratic graph.