C. Vasile , X. Bouteiller , M. Avesani , C. Velly , C. Chan , J.B. Thambo , X. Iriart
{"title":"探索人工智能在儿童超声心动图中的潜力。这是首个使用为成人开发的人工智能软件的儿科研究的初步结果","authors":"C. Vasile , X. Bouteiller , M. Avesani , C. Velly , C. Chan , J.B. Thambo , X. Iriart","doi":"10.1016/j.acvdsp.2023.07.038","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><p>Transthoracic echocardiography<span> is the first-line non-invasive investigation for assessing pediatric patients. Sometimes performing echocardiography in pediatric patients can be challenging for physicians and sonographers due to factors such as patient cooperation and time constraints.</span></p></div><div><h3>Objective</h3><p>Our primary purpose was to establish whether the Ligence Heart software validated for analyzing adult echocardiography could be transposed to pediatric patients.</p></div><div><h3>Methods</h3><p>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. The ultrasound scans were performed manually by two medical practitioners, a senior, a junior and the AI software provided by Ligence Heart Company. Twenty-three features were assessed through echocardiography for each patient. We compared the agreement between methods and observers.</p></div><div><h3>Results/Expected results</h3><p>The mean age of our patients at the time of evaluation was 8.2 years<!--> <!-->±<!--> <span>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, 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.</span></p></div><div><h3>Conclusion/Perspectives</h3><p>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 evaluating aortic annulus, STJ, and E wave.</p></div>","PeriodicalId":8140,"journal":{"name":"Archives of Cardiovascular Diseases Supplements","volume":"15 4","pages":"Pages 290-291"},"PeriodicalIF":18.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring the potential of artificial intelligence in pediatric echocardiography. Preliminary results from the first pediatric study using AI software developed for adults\",\"authors\":\"C. Vasile , X. Bouteiller , M. Avesani , C. Velly , C. Chan , J.B. Thambo , X. Iriart\",\"doi\":\"10.1016/j.acvdsp.2023.07.038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Introduction</h3><p>Transthoracic echocardiography<span> is the first-line non-invasive investigation for assessing pediatric patients. Sometimes performing echocardiography in pediatric patients can be challenging for physicians and sonographers due to factors such as patient cooperation and time constraints.</span></p></div><div><h3>Objective</h3><p>Our primary purpose was to establish whether the Ligence Heart software validated for analyzing adult echocardiography could be transposed to pediatric patients.</p></div><div><h3>Methods</h3><p>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. The ultrasound scans were performed manually by two medical practitioners, a senior, a junior and the AI software provided by Ligence Heart Company. Twenty-three features were assessed through echocardiography for each patient. We compared the agreement between methods and observers.</p></div><div><h3>Results/Expected results</h3><p>The mean age of our patients at the time of evaluation was 8.2 years<!--> <!-->±<!--> <span>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, 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.</span></p></div><div><h3>Conclusion/Perspectives</h3><p>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 evaluating aortic annulus, STJ, and E wave.</p></div>\",\"PeriodicalId\":8140,\"journal\":{\"name\":\"Archives of Cardiovascular Diseases Supplements\",\"volume\":\"15 4\",\"pages\":\"Pages 290-291\"},\"PeriodicalIF\":18.0000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of Cardiovascular Diseases Supplements\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1878648023002598\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Cardiovascular Diseases Supplements","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1878648023002598","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
Exploring the potential of artificial intelligence in pediatric echocardiography. Preliminary results from the first pediatric study using AI software developed for adults
Introduction
Transthoracic echocardiography is the first-line non-invasive investigation for assessing pediatric patients. Sometimes performing echocardiography in pediatric patients can be challenging for physicians and sonographers due to factors such as patient cooperation and time constraints.
Objective
Our primary purpose was to establish whether the Ligence Heart software validated for analyzing adult echocardiography could be transposed to pediatric patients.
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. The ultrasound scans were performed manually by two medical practitioners, a senior, a junior and the AI software provided by Ligence Heart Company. Twenty-three features were assessed through echocardiography for each patient. We compared the agreement between methods and observers.
Results/Expected 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, 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.
Conclusion/Perspectives
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 evaluating aortic annulus, STJ, and E wave.
期刊介绍：
Archives of Cardiovascular Diseases Supplements is the official journal of the French Society of Cardiology. The journal publishes original peer-reviewed clinical and research articles, epidemiological studies, new methodological clinical approaches, review articles, editorials, and Images in cardiovascular medicine. The topics covered include coronary artery and valve diseases, interventional and pediatric cardiology, cardiovascular surgery, cardiomyopathy and heart failure, arrhythmias and stimulation, cardiovascular imaging, vascular medicine and hypertension, epidemiology and risk factors, and large multicenter studies. Additionally, Archives of Cardiovascular Diseases also publishes abstracts of papers presented at the annual sessions of the Journées Européennes de la Société Française de Cardiologie and the guidelines edited by the French Society of Cardiology.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
