Evaluation of clinical performance of artificial intelligence-assisted measurement of thoracic aortic diameter on non-contrast CT
This study aimed to evaluate the clinical performance of artificial intelligence (AI)-assisted measurement of thoracic aortic diameter on non-contrast computed tomography (NCCT). This single-center prospective study included 79 patients (mean age = 70 ± 13 standard deviation; 46 men) who underwent NCCT and arterial phase contrast-enhanced computed tomography (CECT) for evaluating aortic diseases between 2021 and 2022. Maximum diameters of 9 American Heart Association landmarks and the maximum ascending/descending aorta were measured. Upper limits of the 95% confidence interval (CI) for the absolute difference in aortic diameter between the AI-assisted/manual method on NCCT and the manual method on CECT (DiffAI-assisted/Diffmanual) were calculated and compared using a predefined cutoff of 1.5 mm. Evaluation times were also compared. No significant difference was found between per-patient DiffAI-assisted and Diffmanual (1.10 mm; 95% CI = 1.03-1.18 vs 1.03 mm; 95% CI = 0.95-1.11, P = .058); the upper limit of the 95% CI was <1.5 mm. The upper limit of the 95% CI of the geometric mean DiffAI-assisted and Diffmanual was also <1.5 mm at each landmark. The median evaluation time of the AI-assisted method was shorter than that of the manual method (expert radiologist = 272 seconds [interquartile range (IQR) = 229-313] vs 496 seconds [IQR = 438-550]; P < .001, training radiologist: 304 seconds [IQR = 257-404] vs 710 seconds [IQR = 563-855]; P < .001). AI-assisted thoracic aortic diameter measurement on NCCT was as accurate as manual measurement on CECT; its evaluation time was shorter than that of manual measurement on NCCT.
Authors
- Yuichi Morita
- Akihiko Wada (ORCID: https://orcid.org/0000-0003-3432-0267)
- Nobuo Tomizawa (ORCID: https://orcid.org/0000-0001-6305-1081)
- Satoshi Matsushita (ORCID: https://orcid.org/0000-0002-1686-6314)
- Minoru Tabata
- Mitsuo Nishizawa (ORCID: https://orcid.org/0000-0001-5486-3002)
- Toshiaki Akashi (ORCID: https://orcid.org/0000-0002-3056-0792)
- Shohei Fujita (ORCID: https://orcid.org/0000-0002-0099-0126)
- Daisuke Endo (ORCID: https://orcid.org/0000-0002-0929-3829)
- Katsuhiro Sano (ORCID: https://orcid.org/0000-0002-8388-3827)
- A Suzuki (ORCID: https://orcid.org/0000-0002-4457-3260)
- Kotaro Yamamoto
- Jonathan Sperl
- Kanako K. Kumamaru
- Keiichi Funaki
- Shigeki Aoki
- Kazuhiro Suzuki
Institutions
- Juntendo University (JP)
- Massachusetts General Hospital (US)
- Athinoula A. Martinos Center for Biomedical Imaging (US)
- Siemens Healthcare (United States) (US)
- Siemens Healthineers (Germany) (DE)
- Kokura Memorial Hospital (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Medicine
- Published
- 2026-09-18
- DOI
- https://doi.org/10.1097/md.0000000000050702
- Primary Topic
- Aortic Disease and Treatment Approaches
- Type
- article
- Field-Weighted Citation Impact
- 0.00