Evidence map›Paper›PMID 41441995›Full record

SynthesisEuropean radiology2026

CT and MRI radiomics in cardiovascular risk prediction: a systematic review and meta-analysis by the EuSoMII Radiomics Auditing Group.

Armando Ugo Cavallo, Andrea Ponsiglione, Bernardo Pereira, Carlo Di Donna, Emmanouil Koltsakis, Federica Vernuccio, Mario Laudazi, Roberto Cannella, Salvatore Claudio Fanni, Tugba Akinci D'Antonoli and 1 more

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Armando Ugo CavalloDivision of Radiology, Istituto Dermopatico dell'Immacolata (IDI), IRCCS, Rome, Italy.
Andrea PonsiglioneDepartment of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy. Andrea.ponsiglione@unina.it.ORCID http://orcid.org/0000-0002-0105-935X
Bernardo PereiraQuantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain.
Carlo Di DonnaDivision of Radiology, Sant'Andrea University Hospital, Rome, Italy.
Emmanouil KoltsakisDepartment of Nuclear Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden.
Federica VernuccioDepartment of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo, Italy.
Mario LaudaziDivision of Radiology, Policlinico Tor Vergata, Rome, Italy.
Roberto CannellaDepartment of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo, Italy.
Salvatore Claudio FanniDepartment of Translational Research, Academic Radiology, University of Pisa, Pisa, Italy.
Tugba Akinci D'AntonoliDepartment of Pediatric Radiology, University Children's Hospital Basel, Basel, Switzerland.
Renato CuocoloDepartment of Medicine, Surgery, and Dentistry, University of Salerno, Baronissi, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Cardiovascular DiseasesMagnetic Resonance ImagingTomography, X-Ray ComputedHumansRadiomicsRisk AssessmentCardiovascular systemComputed tomographyMagnetic resonance imagingMeta-analysisRadiomics

Identifiers

PMID41441995
PMCPMC13086800

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.