Literature DB >> 28566200

Performance of new automated transthoracic three-dimensional echocardiographic software for left ventricular volumes and function assessment in routine clinical practice: Comparison with 3 Tesla cardiac magnetic resonance.

Franck Levy1, Elie Dan Schouver2, Laura Iacuzio2, Filippo Civaia2, Stephane Rusek2, Carinne Dommerc2, Sylvestre Marechaux3, Vincent Dor2, Christophe Tribouilloy4, Gilles Dreyfus2.   

Abstract

BACKGROUND: Three-dimensional (3D) transthoracic echocardiography (TTE) is superior to two-dimensional Simpson's method for assessment of left ventricular (LV) volumes and LV ejection fraction (LVEF). Nevertheless, 3D TTE is not incorporated into everyday practice, as current LV chamber quantification software products are time-consuming. AIMS: To evaluate the feasibility, accuracy and reproducibility of new fully automated fast 3D TTE software (HeartModelA.I.; Philips Healthcare, Andover, MA, USA) for quantification of LV volumes and LVEF in routine practice; to compare the 3D LV volumes and LVEF obtained with a cardiac magnetic resonance (CMR) reference; and to optimize automated default border settings with CMR as reference.
METHODS: Sixty-three consecutive patients, who had comprehensive 3D TTE and CMR examinations within 24hours, were eligible for inclusion. Nine patients (14%) were excluded because of insufficient echogenicity in the 3D TTE. Thus, 54 patients (40 men; mean age 63±13 years) were prospectively included into the study.
RESULTS: The inter- and intraobserver reproducibilities of 3D TTE were excellent (coefficient of variation<10%) for end-diastolic volume (EDV), end-systolic volume (ESV) and LVEF. Despite a slight underestimation of EDV using 3D TTE compared with CMR (bias=-22±34mL; P<0.0001), a significant correlation was found between the two measurements (r=0.93; P=0.0001). Enlarging default border detection settings leads to frequent volume overestimation in the general population, but improved agreement with CMR in patients with LVEF≤50%. Correlations between 3D TTE and CMR for ESV and LVEF were excellent (r=0.93 and r=0.91, respectively; P<0.0001).
CONCLUSION: 3D TTE using new-generation fully automated software is a feasible, fast, reproducible and accurate imaging modality for LV volumetric quantification in routine practice. Optimization of border detection settings may increase agreement with CMR for EDV assessment in dilated ventricles.
Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  3 tesla cardiac magnetic resonance; 3D echocardiography; Echocardiographie tridimensionnelle; HeartModel(A.I.); Heartmodel; IRM cardiaque 3 tesla

Mesh:

Year:  2017        PMID: 28566200     DOI: 10.1016/j.acvd.2016.12.015

Source DB:  PubMed          Journal:  Arch Cardiovasc Dis        ISSN: 1875-2128            Impact factor:   2.340


  11 in total

1.  Machine learning based automated dynamic quantification of left heart chamber volumes.

Authors:  Akhil Narang; Victor Mor-Avi; Aldo Prado; Valentina Volpato; David Prater; Gloria Tamborini; Laura Fusini; Mauro Pepi; Neha Goyal; Karima Addetia; Alexandra Gonçalves; Amit R Patel; Roberto M Lang
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2019-05-01       Impact factor: 6.875

2.  The Role of Automated 3D Echocardiography for Left Ventricular Ejection Fraction Assessment.

Authors:  Ernest Spitzer; Ben Ren; Felix Zijlstra; Nicolas M Van Mieghem; Marcel L Geleijnse
Journal:  Card Fail Rev       Date:  2017-11

3.  Three-dimensional echocardiography of the athlete's heart: a comparison with cardiac magnetic resonance imaging.

Authors:  Ruben De Bosscher; Mathias Claeys; Christophe Dausin; Kaatje Goetschalckx; Piet Claus; Lieven Herbots; Olivier Ghekiere; Caroline Van De Heyning; Bernard P Paelinck; Kristel Janssens; Leah Wright; Michael Darragh Flannery; André La Gerche; Rik Willems; Hein Heidbuchel; Jan Bogaert; Guido Claessen
Journal:  Int J Cardiovasc Imaging       Date:  2022-09-23       Impact factor: 2.316

4.  Three-dimensional echocardiographic assessment of left ventricular volume in different heart diseases using a fully automated quantification software.

Authors:  Chen-Ke Pan; Bo-Wen Zhao; Xuan-Xuan Zhang; Mei Pan; Yan-Kai Mao; Yuan Yang
Journal:  World J Clin Cases       Date:  2022-05-06       Impact factor: 1.534

5.  Automated Echocardiographic Quantification of Left Ventricular Ejection Fraction Without Volume Measurements Using a Machine Learning Algorithm Mimicking a Human Expert.

Authors:  Federico M Asch; Nicolas Poilvert; Theodore Abraham; Madeline Jankowski; Jayne Cleve; Michael Adams; Nathanael Romano; Ha Hong; Victor Mor-Avi; Randolph P Martin; Roberto M Lang
Journal:  Circ Cardiovasc Imaging       Date:  2019-09-16       Impact factor: 7.792

6.  Realization of fully automated quantification of left ventricular volumes and systolic function using transthoracic 3D echocardiography.

Authors:  Lina Sun; Haiyan Feng; Lujia Ni; Hui Wang; Dongmei Gao
Journal:  Cardiovasc Ultrasound       Date:  2018-01-23       Impact factor: 2.062

Review 7.  Artificial intelligence and echocardiography.

Authors:  M Alsharqi; W J Woodward; J A Mumith; D C Markham; R Upton; P Leeson
Journal:  Echo Res Pract       Date:  2018-12-01

8.  Heart Model A.I. Three-Dimensional Echocardiographic Evaluation of Left Ventricular Function and Parameter Setting.

Authors:  Yuan-Yuan Xing; Hong-Yuan Xue; Yu-Quan Ye
Journal:  Int J Gen Med       Date:  2021-11-09

9.  Optimal threshold of three-dimensional echocardiographic fully automated software for quantification of left ventricular volumes and ejection fraction: Comparison with cardiac magnetic resonance disk-area summation method and feature tracking method.

Authors:  Victor Chien-Chia Wu; Tetuji Kitano; Yosuke Nabeshima; Kyoko Otani; Pao-Hsien Chu; Masaaki Takeuchi
Journal:  PLoS One       Date:  2019-01-28       Impact factor: 3.240

Review 10.  AI and the cardiologist: when mind, heart and machine unite.

Authors:  Antonio D'Costa; Aishwarya Zatale
Journal:  Open Heart       Date:  2021-12
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