Evidence map›Paper›PMID 42426486›Full record

ReviewCVIR endovascular2026

Application of radiomics in abdominal aortic aneurysm and endovascular aneurysm repair-related adverse events imaging: a systematic review.

Seyed Ali Forouzannia, Fattaneh Khalaj, Hamed Ghorani, Seyedeh Romina Rafiei Alavi, Nima Broomand Lomer, Niloofar Moradi, Seyed Amin Astani

Abstract readReview
In one paragraph

Review in CVIR endovascular, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Seyed Ali ForouzanniaSchool of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Fattaneh KhalajDigestive Diseases Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Hamed GhoraniAdvanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Science, Tehran, Iran.
Seyedeh Romina Rafiei AlaviSchool of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Nima Broomand LomerFaculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
Niloofar MoradiSchool of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Seyed Amin AstaniNorth Star Vascular and Interventional, Minneapolis, MN, USA. Astani.MD@northstarir.com.ORCID http://orcid.org/0000-0002-3077-0669

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAbdominal aortic aneurysm (AAA) carries high morbidity and mortality, while adverse events (AE) after endovascular aneurysm repair (EVAR) remain a major challenge. Accurate risk stratification is essential. Radiomics, by extracting quantitative imaging features, offers a noninvasive approach that may improve prediction of AAA outcomes and EVAR-related AE beyond conventional imaging. MAIN BODY: A search was conducted across Medline, Scopus, Embase, and Web of Science databases for articles published up to February 2024 to evaluate the application of radiomics in predicting the outcomes of AAA and diagnosing or predicting the AE related to EVAR. Inclusion criteria concentrated on observational studies that utilized a radiomics model based on the radiomic features extracted from imaging modalities to predict AAA outcomes and predict or diagnose EVAR-related AE. Eight studies involving 1729 observations met the inclusion criteria out of the 371 records yielded from the databases. Radiomics achieved a high area under the receiver operating characteristic (ROC) curve (AUROC) for predicting EVAR-related AE in three studies (up to 0.95), and it showed predictive value for AAA growth in three studies (AUROC 0.79-0.93) and rupture or repair in one study (AUROC 0.75). One study highlighted the diagnostic value of radiomics in post-EVAR endoleak detection using unenhanced computed tomography images (AUROC 0.91).

conclusionRadiomics showed promising but preliminary results in predicting AAA outcomes and EVAR-related AE, providing a noninvasive tool for risk assessment. However, further research with larger cohorts and external validation of the radiomics models is essential to confirm its clinical applicability.

Indexed as

Abdominal aortic aneurysmEndovascular aneurysm repairRadiomics

Identifiers

PMID42426486
PMCPMC13350606

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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.