Evidence map›Paper›PMID 41454943›Full record

ArticleAbdominal radiology (New York)2026

Use of artificial intelligence-assisted measurement of aortic diameter in clinical decision making about abdominal aortic aneurysm repair.

Chinmay Sharma, Mike Wu, Aditya Enjeti, Shivshankar Thanigaimani, Jason Jenkins, Frank Quigley, Jonathan Golledge

Abstract read
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Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Chinmay SharmaQueensland Research Centre for Peripheral Vascular Disease, College of Medicine and Dentistry, James Cook University, Townsville, Australia.
Mike WuDepartment of Vascular and Endovascular Surgery, Townsville University Hospital, Townsville, Australia.
Aditya EnjetiQueensland Research Centre for Peripheral Vascular Disease, College of Medicine and Dentistry, James Cook University, Townsville, Australia.
Shivshankar ThanigaimaniQueensland Research Centre for Peripheral Vascular Disease, College of Medicine and Dentistry, James Cook University, Townsville, Australia.
Jason JenkinsDepartment of Vascular and Endovascular Surgery, Royal Brisbane & Women's Hospital, Brisbane, Australia.
Frank QuigleyDepartment of Vascular and Endovascular Surgery, Townsville University Hospital, Townsville, Australia.
Jonathan GolledgeQueensland Research Centre for Peripheral Vascular Disease, College of Medicine and Dentistry, James Cook University, Townsville, Australia. jonathan.golledge@jcu.edu.au.

Funding

Australian National Health and Medical Research Council GNT1180736Medical Research Futures Fund MRF2015999National Health and Medical Research Council GNT2026319
6 · The paper itself

Abstract

objectivesDecisions to perform abdominal aortic aneurysm (AAA) repair are dependent on aneurysm size, but variation in size measurement leads to inconsistency in management. AI-assisted systems have potential to improve repeatability of measuring aortic dimensions. This study compared the repeatability and agreement in clinical decision-making between using artificial intelligence (AI)-automated and traditional semi-automated methods for measuring abdominal aortic aneurysm (AAA) size. MATERIALS AND

methodsComputed tomography angiogram scans from 142 patients who had scans at baseline (n = 142), 1 year (n = 100), 2 years (n = 56) and 3 years (n = 4) were analysed using semi-automated and AI-assisted automated systems. Three observers measured maximal AAA diameter and volume twice with each method. Intra- and inter-observer repeatability were assessed using reproducibility coefficients (RC). Measurements were used to decide if AAA repair was required according to clinical guidelines, and agreement was evaluated using Kappa coefficients (K). The ability of AI-assisted measurements to predict actual requirement for AAA repair was assessed using Cox proportional hazard analysis.

resultsAI-assisted measurements had perfect intra- and inter-observer repeatability (RC = 0) which were significantly superior to traditional measurements (RC for diameter: 1.9-5.6 mm; volume: 7.8-22.6 cm³, p < 0.001). Agreement about AAA repair was superior using AI-assisted (K = 1) than traditional (K = 0.55-0.70) measurements. Baseline AI-assisted measurements predicted actual requirement for AAA repair (Hazard ratio, HR, per mm diameter increase 1.12, 95% confidence intervals, CI, 1.03-1.22, HR per cm³ volume increase 1.02, 95% CI 1.01-1.02, p < 0.001).

conclusionThe findings suggest AI-assisted measurement of AAA size would enhance the consistency of decisions about AAA repair.

Indexed as

Aortic Aneurysm, AbdominalArtificial IntelligenceClinical Decision-MakingAgedAorta, AbdominalComputed Tomography AngiographyFemaleHumansIntelligent SystemsMaleMiddle AgedObserver VariationRadiographic Image Interpretation, Computer-AssistedReproducibility of ResultsAbdominal aortic aneurysmAgreementArtificial intelligenceDiameterRepeatabilitySegmentatioVolume

Identifiers

PMID41454943

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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.