Literature DB >> 31351874

Artificial Intelligence for the Measurement of the Aortic Valve Annulus.

Richard Thalappillil1, Pranav Datta2, Saurabh Datta2, Yong Zhan3, Sophie Wells4, Feroze Mahmood5, Frederick C Cobey2.   

Abstract

OBJECTIVE: The authors aim to evaluate an automated echocardiography software as compared with computed tomography in measurement of the aortic valve annulus in patients with aortic stenosis. The authors hypothesize that aortic annular measurements by this software and computed tomography will show acceptable correlation.
DESIGN: This study is an Institutional Review Board-approved, retrospective data collection of patients with aortic stenosis who underwent implantation of a transcatheter heart valve with intraprocedural transesophageal echocardiography, multidetector computed tomography, and use of the Siemens eSie Valves automated aortic valve software.
SETTING: Intraprocedural in a single hospital institution. PARTICIPANTS: The participants are 47 patients who underwent implantation of an Edwards SAPIEN 3 transcatheter heart valve.
INTERVENTIONS: The authors compared aortic valve annulus measurements by two-dimensional transesophageal echocardiography, computed tomography, and the automated software.
MEASUREMENTS AND MAIN RESULTS: Aortic annulus measurements by the software correlated more closely to the computed tomography measurements than two-dimensional measurements. Bland-Altman analysis showed qualitative comparability of measurements performed by the automated software to computed tomography (95% limits of agreement between -4.62 mm and 1.26 mm for area-derived and -4.51 mm and 1.45 mm for perimeter-derived methods). Similarly, there was significant linear correlation with automated software use (r = 0.84, p < 0.0001 and r = 0.85, p < 0.0001).
CONCLUSIONS: Periprocedural aortic valve measurement by automated echocardiographic software correlates with computed tomography in patients with severe aortic stenosis. This technology is helpful and accurate, but has limitations.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  aortic valve three-dimensional modeling; artificial intelligence; automated software; machine learning

Mesh:

Year:  2019        PMID: 31351874     DOI: 10.1053/j.jvca.2019.06.017

Source DB:  PubMed          Journal:  J Cardiothorac Vasc Anesth        ISSN: 1053-0770            Impact factor:   2.628


  5 in total

1.  Artificial Intelligence in Echocardiography.

Authors:  Stephanie A Coulter; Karla Campos
Journal:  Tex Heart Inst J       Date:  2022-03-01

2.  Precision medicine in anesthesiology.

Authors:  Laleh Jalilian; Maxime Cannesson
Journal:  Int Anesthesiol Clin       Date:  2020

Review 3.  Aortic Annular Sizing Using Novel Software in Three-Dimensional Transesophageal Echocardiography for Transcatheter Aortic Valve Replacement: A Systematic Review and Meta-Analysis.

Authors:  Chanrith Mork; Minjie Wei; Weixi Jiang; Jianli Ren; Haitao Ran
Journal:  Diagnostics (Basel)       Date:  2021-04-22

Review 4.  Artificial intelligence for the echocardiographic assessment of valvular heart disease.

Authors:  Rashmi Nedadur; Bo Wang; Wendy Tsang
Journal:  Heart       Date:  2022-09-26       Impact factor: 7.365

Review 5.  Artificial intelligence and cardiovascular imaging: A win-win combination.

Authors:  Luigi P Badano; Daria M Keller; Denisa Muraru; Camilla Torlasco; Gianfranco Parati
Journal:  Anatol J Cardiol       Date:  2020-10       Impact factor: 1.596

  5 in total

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