Assessing the Role of an Artificial Intelligence Assessment Tool for Thoracic Aorta Diameter on Routine Chest CT

Overview

Journal Br J Radiol

Publisher Oxford University Press

Specialty Radiology

Date 2023 Jun 19

PMID 37335231

Authors

John Graby

Maredudd Harris

Calum Jones

Harry Waring

Stephen Lyen

Benjamin J Hudson

Jonathan Carl Luis Rodrigues

Affiliations

Soon will be listed here.

Abstract

Objective: To assess the diagnostic accuracy and clinical impact of automated artificial intelligence (AI) measurement of thoracic aorta diameter on routine chest CT.

Methods: A single-centre retrospective study involving three cohorts. 210 consecutive ECG-gated CT aorta scans (mean age 75 ± 13) underwent automated analysis (AI-Rad Companion Chest CT, Siemens) and were compared to a reference standard of specialist cardiothoracic radiologists for accuracy measuring aortic diameter. A repeated measures analysis tested reporting consistency in a second cohort (29 patients, mean age 61 ± 17) of immediate sequential pre-contrast and contrast CT aorta acquisitions. Potential clinical impact was assessed in a third cohort of 197 routine CT chests (mean age 66 ± 15) to document potential clinical impact.

Results: AI analysis produced a full report in 387/436 (89%) and a partial report in 421/436 (97%). Manual AI agreement was good to excellent (ICC 0.76-0.92). Repeated measures analysis of expert and AI reports for the ascending aorta were moderate to good (ICC 0.57-0.88). AI diagnostic performance crossed the threshold for maximally accepted limits of agreement (>5 mm) at the aortic root on ECG-gated CTs. AI newly identified aortic dilatation in 27% of patients on routine thoracic imaging with a specificity of 99% and sensitivity of 77%.

Conclusion: AI has good agreement with expert readers at the mid-ascending aorta and has high specificity, but low sensitivity, at detecting dilated aortas on non-dedicated chest CTs.

Advances In Knowledge: An AI tool may improve the detection of previously unknown thoracic aorta dilatation on chest CTs current routine reporting.

Citing Articles

Artificial intelligence-powered solutions for automated aortic diameter measurement in computed tomography: a narrative review.

Lo E, Chen S, Ng K, Wong R Ann Transl Med. 2025; 12(6):116.

PMID: 39817238 PMC: 11729799. DOI: 10.21037/atm-24-171.

Repeatability of AI-based, automatic measurement of vertebral and cardiovascular imaging biomarkers in low-dose chest CT: the ImaLife cohort.

Hamelink I, van Tuinen M, Kwee T, van Ooijen P, Vliegenthart R Eur Radiol. 2025; .

PMID: 39779514 DOI: 10.1007/s00330-024-11328-9.

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