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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
  • , David J. Williams
  • , Sylvie De Raedt
  • , Francisco Purroy
  • , Geert Vanhooren
  • , George Pope
  • , Peter Vanacker
  • , Tim Cassidy
  • , Cathal Walsh
  • , Daniel Bos
  • , Peter Kelly
  • Robin Lemmens
  • KU Leuven
  • Université Paris Cité
  • Centre Hospitalier Sainte-Anne
  • Erasmus University Rotterdam
  • Groupe santé CHC
  • AZ Damiaan
  • Trinity College Dublin
  • Health Research Board Ireland
  • Tallaght Hospital
  • University College Cork
  • Royal College of Surgeons in Ireland
  • Vrije Universiteit Brussel
  • Hospitalt Universitari Arnau de Vilanova de Lleida
  • IRBLleida
  • AZ Sint-Jan
  • Mid-Western Regional Hospital Limerick
  • AZ Groeninge
  • University of Antwerp
  • University College Dublin

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: In 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 methods: We 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. Results: We 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]. Conclusion: Different 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.

Original languageEnglish
Pages (from-to)1463-1473
Number of pages11
JournalEuropean Radiology
Volume36
Issue number2
DOIs
Publication statusPublished - Feb 2026
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Atherosclerosis
  • Carotid artery (Internal)
  • Carotid stenosis
  • Computed tomography angiography
  • Diagnostic imaging

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