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Exploring the Potential of Artificial Intelligence in Pediatric Echocardiography—Preliminary Results from the First Pediatric Study Using AI Software Developed for Adults

(1) Background: Transthoracic echocardiography is the first-line non-invasive investigation for assessing pediatric patients’ cardiac anatomy, physiology, and hemodynamics, based on its accessibility and portability, but complete anatomic and hemodynamic assessment is time-consuming. (2) Aim: This s...

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Autores principales: Vasile, Corina Maria, Bouteiller, Xavier Paul, Avesani, Martina, Velly, Camille, Chan, Camille, Jalal, Zakaria, Thambo, Jean-Benoit, Iriart, Xavier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179538/
https://www.ncbi.nlm.nih.gov/pubmed/37176649
http://dx.doi.org/10.3390/jcm12093209
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author Vasile, Corina Maria
Bouteiller, Xavier Paul
Avesani, Martina
Velly, Camille
Chan, Camille
Jalal, Zakaria
Thambo, Jean-Benoit
Iriart, Xavier
author_facet Vasile, Corina Maria
Bouteiller, Xavier Paul
Avesani, Martina
Velly, Camille
Chan, Camille
Jalal, Zakaria
Thambo, Jean-Benoit
Iriart, Xavier
author_sort Vasile, Corina Maria
collection PubMed
description (1) Background: Transthoracic echocardiography is the first-line non-invasive investigation for assessing pediatric patients’ cardiac anatomy, physiology, and hemodynamics, based on its accessibility and portability, but complete anatomic and hemodynamic assessment is time-consuming. (2) Aim: This study aimed to determine whether an automated software developed for adults could be effectively used for the analysis of pediatric echocardiography studies without prior training. (3) Materials and Methods: The study was conducted at the University Hospital of Bordeaux between August and September 2022 and included 45 patients with normal or near normal heart architecture who underwent a 2D TTE. We performed Spearman correlation and Bland-Altman analysis. (4) Results: The mean age of our patients at the time of evaluation was 8.2 years ± 5.7, and the main reason for referral to our service was the presence of a heart murmur. Bland-Altman analysis showed good agreement between AI and the senior physician for two parameters (aortic annulus and E wave) regardless of the age of the children included in the study. A good agreement between AI and physicians was also achieved for two other features (STJ and EF) but only for patients older than 9 years. For other features, either a good agreement was found between physicians but not with the AI, or a poor agreement was established. In the first case, maybe proper training of the AI could improve the measurement, but in the latter case, for now, it seems unrealistic to expect to reach a satisfactory accuracy. (5) Conclusion: Based on this preliminary study on a small cohort group of pediatric patients, the AI soft originally developed for the adult population, had provided promising results in the evaluation of aortic annulus, STJ, and E wave.
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spelling pubmed-101795382023-05-13 Exploring the Potential of Artificial Intelligence in Pediatric Echocardiography—Preliminary Results from the First Pediatric Study Using AI Software Developed for Adults Vasile, Corina Maria Bouteiller, Xavier Paul Avesani, Martina Velly, Camille Chan, Camille Jalal, Zakaria Thambo, Jean-Benoit Iriart, Xavier J Clin Med Article (1) Background: Transthoracic echocardiography is the first-line non-invasive investigation for assessing pediatric patients’ cardiac anatomy, physiology, and hemodynamics, based on its accessibility and portability, but complete anatomic and hemodynamic assessment is time-consuming. (2) Aim: This study aimed to determine whether an automated software developed for adults could be effectively used for the analysis of pediatric echocardiography studies without prior training. (3) Materials and Methods: The study was conducted at the University Hospital of Bordeaux between August and September 2022 and included 45 patients with normal or near normal heart architecture who underwent a 2D TTE. We performed Spearman correlation and Bland-Altman analysis. (4) Results: The mean age of our patients at the time of evaluation was 8.2 years ± 5.7, and the main reason for referral to our service was the presence of a heart murmur. Bland-Altman analysis showed good agreement between AI and the senior physician for two parameters (aortic annulus and E wave) regardless of the age of the children included in the study. A good agreement between AI and physicians was also achieved for two other features (STJ and EF) but only for patients older than 9 years. For other features, either a good agreement was found between physicians but not with the AI, or a poor agreement was established. In the first case, maybe proper training of the AI could improve the measurement, but in the latter case, for now, it seems unrealistic to expect to reach a satisfactory accuracy. (5) Conclusion: Based on this preliminary study on a small cohort group of pediatric patients, the AI soft originally developed for the adult population, had provided promising results in the evaluation of aortic annulus, STJ, and E wave. MDPI 2023-04-29 /pmc/articles/PMC10179538/ /pubmed/37176649 http://dx.doi.org/10.3390/jcm12093209 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Vasile, Corina Maria
Bouteiller, Xavier Paul
Avesani, Martina
Velly, Camille
Chan, Camille
Jalal, Zakaria
Thambo, Jean-Benoit
Iriart, Xavier
Exploring the Potential of Artificial Intelligence in Pediatric Echocardiography—Preliminary Results from the First Pediatric Study Using AI Software Developed for Adults
title Exploring the Potential of Artificial Intelligence in Pediatric Echocardiography—Preliminary Results from the First Pediatric Study Using AI Software Developed for Adults
title_full Exploring the Potential of Artificial Intelligence in Pediatric Echocardiography—Preliminary Results from the First Pediatric Study Using AI Software Developed for Adults
title_fullStr Exploring the Potential of Artificial Intelligence in Pediatric Echocardiography—Preliminary Results from the First Pediatric Study Using AI Software Developed for Adults
title_full_unstemmed Exploring the Potential of Artificial Intelligence in Pediatric Echocardiography—Preliminary Results from the First Pediatric Study Using AI Software Developed for Adults
title_short Exploring the Potential of Artificial Intelligence in Pediatric Echocardiography—Preliminary Results from the First Pediatric Study Using AI Software Developed for Adults
title_sort exploring the potential of artificial intelligence in pediatric echocardiography—preliminary results from the first pediatric study using ai software developed for adults
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179538/
https://www.ncbi.nlm.nih.gov/pubmed/37176649
http://dx.doi.org/10.3390/jcm12093209
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