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Verfasst von:Hatzl, Johannes [VerfasserIn]   i
 Uhl, Christian [VerfasserIn]   i
 Barb, Alexandru [VerfasserIn]   i
 Henning, Daniel [VerfasserIn]   i
 Fiering, Jonathan [VerfasserIn]   i
 El-Sanosy, Edris [VerfasserIn]   i
 Cuypers, Philippe W.M. [VerfasserIn]   i
 Böckler, Dittmar [VerfasserIn]   i
Titel:External validation of fully-automated infrarenal maximum aortic aneurysm diameter measurements in computed tomography angiography scans using artificial intelligence (PRAEVAorta 2)
Verf.angabe:Johannes Hatzl, MD, Christian Uhl, MD,Alexandru Barb, MD, Daniel Henning, Jonathan Fiering, Edris El-Sanosy, MD, Philippe W.M. Cuypers, MD, PhD, and Dittmar Böckler, MD on behalf of the Zephyr Study Group collaborators
Ausgabe:Online first
Jahr:2024
Umfang:8 S.
Fussnoten:Online veröffentlicht: 13. November 2024 ; Gesehen am 18.06.2025
Titel Quelle:Enthalten in: Journal of endovascular therapy
Ort Quelle:Thousand Oaks, Calif. : Sage, 2000
Jahr Quelle:2024
Band/Heft Quelle:(2024), online first, Seite 1-8
ISSN Quelle:1545-1550
Abstract:Purpose: This study investigates the accuracy of fully-automated maximum aortic diameter measurements in abdominal aortic aneurysm (AAA) patients using artificial intelligence software (PRAEVAorta 2, Nurea, Bordeaux, France). - Materials and Methods: This is a multicenter, retrospective validation study using prospectively collected data from the Zenith alpha for aneurysm Repair Registry (ZEPHYR). Automated measurements of PRAEVAorta 2 are compared with measurements of an internationally recognized core laboratory (Syntactx, New York, New York State). The reviewers at the core laboratory were measurement technologists trained to and utilizing established measurement standards, overseen by vascular surgeons and radiologists. The data set comprised 871 computed tomography angiography scans from the ZEPHYR registry with 347 patients who underwent endovascular aneurysm repair (EVAR) with the Zenith Alpha Endovascular Abdominal Graft (Cook Medical, Bloomington, Indiana) in Germany, Belgium, and The Netherlands between 2016 and 2019. - Results: The analysis demonstrated excellent correlation of the measurements (r=0.97) with an intraclass correlation (ICC) of 0.972 (95% confidence interval [CI]=0.968-0.976) across all scans. For preoperative computed tomography (CT) scans, ICC was 0.953 (95% CI=0.941-0.963), and for postoperative scans, ICC was 0.979 (95% CI=0.975-0,983), respectively. In total, 95.4% of measurements were within the clinically acceptable range of 5 mm in absolute difference. In total, 10% of scans demonstrated obvious segmentation errors, mainly due to failure in detecting vessel segments (renal arteries, aortic bifurcation) or due to mis-detecting the outer border of the AAA (duodenum, inferior vena cava, aortic branches) and were excluded from the analysis. - Conclusion: In this study, the maximum AAA diameter could be accurately measured fully-automatically by PRAEVAorta 2 (Nurea) in most cases demonstrating that artificial intelligence (AI) software could serve as an important adjunct for research and clinical practice. However, critical review of the generated reports by an experienced observer and cautious use is warranted to identify flawed segmentations. - Clinical Impact - This multicenter, retrospective validation study assessed the accuracy of fully-automated maximum infrarenal aortic aneurysm diameter measurements. It was demonstrated, that 95.4% of measurements were within the clinically acceptable range of 5 mm in absolute difference, positioning the software as a potential adjunct for clinical practice and research. It is also highlighted however, that critical review of the measurements is obligatory, due to a 10% segmentation error rate.
DOI:doi:10.1177/15266028241295563
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

kostenfrei: Volltext: https://doi.org/10.1177/15266028241295563
 DOI: https://doi.org/10.1177/15266028241295563
Datenträger:Online-Ressource
Sprache:eng
K10plus-PPN:1928556493
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