Evidence map›Paper›PMID 40753328›Full record

Trial reportEuropean radiology2026

Agreement across different measurements for internal carotid artery stenosis in patients with TIA or stroke in the CONVINCE trial.

Louise Maes, Jo P Peluso, Joseph Benzakoun, Jelle Demeestere, Ching Fawad Khan, Philippe Desfontaines, Adinda De Pauw, Ronan Collins, Dominick J H McCabe, Simon Cronin and 11 more

Abstract readRandomized Controlled Trial
PubMed Publisher
In one paragraph

Trial report in European radiology, 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
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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

21 authors.

Louise MaesDepartment of Neurology, University Hospitals Leuven, Leuven, Belgium.
Jo P PelusoDivision of Neuroradiology, Department of Radiology, University Hospitals Leuven, Leuven, Belgium.
Joseph BenzakounInstitute of Psychiatry and Neuroscience of Paris (IPNP), Université Paris Cité, INSERM U1266, Paris, France.
Jelle DemeestereDepartment of Neurology, University Hospitals Leuven, Leuven, Belgium.
Ching Fawad KhanDepartment of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Philippe DesfontainesDepartment of Neurology, Stroke Unit, CHC Groupe Santé, Liège, Belgium.
Adinda De PauwDepartment of Neurology, AZ Damiaan, Oostende, Belgium.
Ronan CollinsDepartment of Neurology and Department of Geriatric and Stroke Medicine, Tallaght University Hospital-The Adelaide and Meath Hospital, Dublin, Ireland, incorporating the National Children's Hospital and Academic Unit of Neurology, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Dominick J H McCabeHealth Research Board (HRB) Stroke Clinical Trials Network Ireland (SCTNI), Dublin, Ireland.
Simon CroninHealth Research Board (HRB) Stroke Clinical Trials Network Ireland (SCTNI), Dublin, Ireland.
David J WilliamsHealth Research Board (HRB) Stroke Clinical Trials Network Ireland (SCTNI), Dublin, Ireland.
Sylvie De RaedtDepartment of Neurology, Universitair Ziekenhuis Brussel, NEUR Research group, Vrije Universiteit Brussel, Brussels, Belgium.
Francisco PurroyStroke Unit, Department of Neurology, Hospitalt Universitari Arnau de Vilanova de Lleida, Lleida, Spain.
Geert VanhoorenDepartment of Neurology, AZ Sint-Jan, Brugge, Belgium.
George PopeDepartment of Medicine for the Elderly, University Hospital Waterford, Waterford, Ireland.
Peter VanackerDepartment of Neurology, AZ Groeninge, Kortrijk, Belgium.
Tim CassidyDepartment of Geriatric Medicine, St. Vincent's University Hospital, Dublin, Ireland.
Cathal WalshTCD Biostatistics Unit, Discipline of Public Health and Primary Care, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Daniel BosDepartment of Neurosciences, Experimental Neurology, KU Leuven-University of Leuven, Leuven, Belgium.
Peter KellyHealth Research Board (HRB) Stroke Clinical Trials Network Ireland (SCTNI), Dublin, Ireland.
Robin LemmensDepartment of Neurology, University Hospitals Leuven, Leuven, Belgium. robin.lemmens@uzleuven.be.ORCID http://orcid.org/0000-0002-4948-5956

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesIn patients with atherosclerosis of the internal carotid artery (ICA), stenosis grading is commonly performed using the NASCET (North American Symptomatic Carotid Endarterectomy Trial) method. Semi-automated software techniques for computed tomography angiography (CTA) offer alternative methods. We compared the NASCET method (based on the absolute minimal diameter) with three different stenosis measurements. MATERIALS AND

methodsWe analysed 519 baseline CTA scans from patients in the CONVINCE (Colchicine for prevention of vascular inflammation in Non-CardioEmbolic stroke) trial. For each ICA, we calculated stenosis with semi-automated imaging software using four methods: absolute minimal diameter (NASCET method, dia[min]), area, effective diameter from area (dia[area]), and effective diameter from perimeter (dia[perim]). We assessed agreement using a weighted kappa statistic (κ), intraclass correlation coefficient (ICC) and Bland-Altman analysis.

resultsWe identified 579 atherosclerotic arteries in 360 patients. Within the clinically relevant 30-99% stenosis subgroup (195/579, 33.7%), absolute agreement between dia[min] and other methods was good (ICC values of 0.82, 0.87, and 0.72 for area, dia[area], and dia[perim]). Kappa's were 0.68 (95% CI 0.63-0.73), 0.66 (95% CI 0.60-0.73), and 0.49 (95% CI 0.40-0.58) for dia[min] vs. area, dia[area], and dia[perim]. Dia[min] underestimated stenosis by 6.4% (95% CI 4.7%-8.2%) compared to area and overestimated by 12.4% (95% CI 11.0%-13.7%) and 17.8% (95% CI 15.8%-19.9%) compared to dia[area] and dia[perim].

conclusionDifferent semi-automated methods for stenosis measurement showed fair to moderate agreement with both systematic over- and underestimation affecting stenosis grading. The observed variation underscores the importance of consistently reporting the exact method used for stenosis assessment. KEY POINTS: Question Advances in CT angiography acquisition and semi-automated software introduce new methods for stenosis assessment. How do these methods compare to the traditional minimal diameter-based NASCET approach? Findings Stenosis classification varies substantially across methods, with both systematic over- and underestimation depending on the measurement method used. Clinical relevance Different methods for stenosis measurements showed fair to moderate agreement affecting stenosis grading. Clearly reporting the measurement method is crucial for patient follow-up and clinical studies.

Indexed as

Carotid Artery, InternalCarotid StenosisComputed Tomography AngiographyIschemic Attack, TransientStrokeAgedFemaleHumansMaleMiddle AgedReproducibility of ResultsAtherosclerosisCarotid artery (Internal)Carotid stenosisComputed tomography angiographyDiagnostic imaging

Identifiers

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Registered trials

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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 Socratic graph.