A new imaging era aided by artificial intelligence to enhance cardio-oncology care. Tun-AI Enhance Study

IF 2.3 3区医学 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS

Archives of Cardiovascular Diseases Pub Date : 2025-05-30 DOI:10.1016/j.acvd.2025.04.030

D. Aouadi, F. Mghaeith, F. Daly, M. Chedly, A. Ben Salem, Z. Jebberi, S. Boudiche, M.S. Mourali

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引用次数: 0

Abstract

Background

3D echocardiography is recommended as the preferred echocardiographic modality to measure left ventricular ejection fraction (LVEF). This technique needs an experimented operators and expensive machines. Artificial Intelligence (AI) based systems were reported to be of clinical interest.

Objectives

This study aims to compare performances and variability of echocardiographic measures between a 3D-equipped ultrasound system and an AI equipped one for cancer patients while assessing inter-oberver variability between different expertise level operators.

Methods

This was a prospective study done between May 2023 and February 2024 in the cardiology departement of Rabta hospital. It included patients > 18 years with a malignant tumor and candidates for cardiotoxic chemotherapy. We excluded patients who had started chemotherapy and who had an irregular rythm. TTE were performed by a senior operator, using a Philips EPIC7 ultrasound system to measure the 3D LVEF. An Echonous Kosmos system equipped with an US2-AI software was used for automatic LVEF measurement by a senior operator and a junior one.

Results

This study included 47 patients (mean age 50 ± 12 years, 68% female). There was no statistically significant difference in LVEF measurments when performed by the senior operator using the 3D echocradiography or the AI systems (P = 0.16). When using the AI system, there was no statiscally significant difference between the results found by the senior and the junior doctor (P = 0.918). There was a correlation between 3D measured LVEF and AI-measured LVEF when done by the senior operator (r = 0.43, P = 0.003). A correlation between AI-measured LVEF by the senior operator and the junior operator was found (r = 0.571, P < 10⁻³).

Conclusion

The AI echocardiography system demonstrates potential to reduce inter-observer variability, minimize expertise-related errors and improve test performance in the assessment of left ventricular function.

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人工智能辅助下的新成像时代，增强心脏肿瘤护理。tunai增强学习

背景：三维超声心动图被推荐为测量左心室射血分数（LVEF）的首选超声心动图方式。这项技术需要经验丰富的操作人员和昂贵的机器。据报道，基于人工智能（AI）的系统具有临床意义。本研究旨在比较3d超声系统和人工智能超声系统在癌症患者超声心动图测量中的性能和可变性，同时评估不同专业水平操作员之间的观察者之间的可变性。方法该前瞻性研究于2023年5月至2024年2月在Rabta医院心内科完成。它包括患者>；患有恶性肿瘤18年，需要心脏毒性化疗。我们排除了已经开始化疗和节律不规律的患者。TTE由一名高级操作员进行，使用飞利浦EPIC7超声系统测量3D LVEF。一名高级操作员和一名初级操作员使用配备US2-AI软件的Echonous Kosmos系统进行LVEF自动测量。结果47例患者（平均年龄50±12岁，女性68%）。当高级操作员使用3D超声心动图或人工智能系统进行LVEF测量时，差异无统计学意义（P = 0.16）。使用人工智能系统时，高级医生与初级医生的结果差异无统计学意义（P = 0.918）。当由高级操作员完成时，3D测量的LVEF与ai测量的LVEF之间存在相关性（r = 0.43, P = 0.003）。高级操作员与初级操作员人工智能测量的LVEF之间存在相关性(r = 0.571, P <；10−3)。结论人工智能超声心动图系统在左心室功能评估中具有降低观察者间差异、减少专业知识相关错误和提高测试性能的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Archives of Cardiovascular Diseases 医学-心血管系统

CiteScore

4.40

自引率

6.70%

发文量

审稿时长

34 days

期刊介绍： The Journal publishes original peer-reviewed clinical and research articles, epidemiological studies, new methodological clinical approaches, review articles and editorials. 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. 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.