SynthesisEuropean radiology2026
CT and MRI radiomics in cardiovascular risk prediction: a systematic review and meta-analysis by the EuSoMII Radiomics Auditing Group.
Synthesis in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Why Radiomics Rarely Reaches the Clinic: Reproducibility, Validation, and Evidence Gap-A Critical Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Methodological quality of cardiac CT and MRI radiomics studies assessed using METRICS and RQS by human readers and ChatGPT 5.1 Thinking.European radiology experimental · 2026Article
- Radiomic Assessment of Epicardial Adipose Tissue for the Prediction of Non-Calcified Coronary Atherosclerotic Plaques.Journal of cardiovascular development and disease · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo conduct a comprehensive systematic review of the studies applying radiomics to CT and MRI for the evaluation of cardiac disease, and to perform a meta-analysis of their diagnostic accuracy, focused on cardiovascular events prediction. A secondary aim was to assess the methodological quality of cardiac imaging radiomics studies using the METRICS score. MATERIALS AND
methodsFour investigators searched multiple medical literature archives (Scopus, Web of Science, and PubMed). The search was conducted from February 7th, 2021, to March 10th, 2025. Papers were also screened to identify studies for the prediction of cardiovascular events, defined as the occurrence of major cardiovascular events or myocardial ischemia. Methodological quality was assessed by using the METRICS tool. Diagnostic accuracy was estimated with pooled area under the curve (AUC).
resultsA total of 202 studies were included in the final analysis. Seventeen papers were identified for the meta-analysis, of which 9 were considered eligible for analysis. 111 papers (55%) had CT as the imaging modality, and 91 (45%) papers had MRI. Overall, the average METRICS total score was 54.52% ± 15.89%. Meta-analysis showed pooled AUC of 0.81 (95% CI: 0.75-0.87), with a high level of heterogeneity (I² = 83.4%, τ² = 0.0068). Egger's test for funnel plot asymmetry was statistically significant (z = -2.39, p = 0.017), suggesting potential publication bias.
conclusionRadiomics in cardiac imaging holds potential, showing moderate quality and relatively high cumulative performance for the prediction of cardiovascular events. KEY POINTS: Question What is the current methodological quality and pooled diagnostic performance of cardiovascular radiomics for predicting clinical events, based on a meta-analysis? Findings The average METRICS quality score was 54.52%. A meta-analysis showed a pooled AUC of 0.81 for event prediction, but with high heterogeneity and publication bias. Clinical relevance Assessing radiomics research methodological quality is crucial to enhance reproducibility and clinical applicability of radiomics pipelines. The evaluation of cumulative evidence for cardiovascular events prediction may guide clinical translation and future study design.
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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.