基于AI的CT-FFR在胸痛胸闷疑似冠心病患者诊断中的应用价值
The value of AI-based CT-FFR in the diagnosis of patients with chest pain and chest tightness suspected coronary artery disease
朱先清 1刘云峰 1王宝春 1王怡 1胡茂能 1马天宇 2梁有峰3
作者信息
- 1. 安徽医科大学合肥第三临床学院(合肥市第三人民医院)影像中心,安徽合肥 230022
- 2. 安徽医科大学合肥第三临床学院(合肥市第三人民医院)心内科,安徽合肥 230022
- 3. 安徽医科大学第一附属医院心内科,安徽合肥 230032
- 折叠
摘要
目的:探究基于人工智能(AI)的 CT 血管造影血流储备分数(CT-FFR)在胸痛疑似冠心病患者诊断中的应用价值.方法:选取 2019 年 1 月至 2024 年 1 月我院 60 例疑似冠心病患者,以 ICA检测结果为金标准,分析基于AI的CT-FFR对胸痛胸闷疑似冠心病患者的诊断价值.结果:基于AI的CT-FFR诊断疑似冠心病患的准确度为 88.33%、灵敏度为 93.33%、特异度为 73.33%,AUC为 0.849(95%CI:0.714～0.985),具有较高的诊断价值.结论:基于AI的CT-FFR技术对胸痛胸闷疑似冠心病患者具有较高的诊断价值.
Abstract
Objective:To explore the value of artificial intelligence(AI)-based CT angiographic flow reserve fraction(CT-FFR)in the differential diagnosis of patients with chest pain and suspected coronary artery disease.Methods:Sixty patients with suspected coronary artery disease in our hospital were selected from January 2019 to January 2024 to analyze the diagnostic value of AI-based CT-FFR on patients with chest pain and chest tightness suspected coronary artery disease,using ICA test results as the gold standard.Results:The accuracy of AI-based CT-FFR for diagnosing suspected coronary artery disease patients was 88.33%,sensitivity was 93.33%,specificity was 73.33%,and AUC was 0.849(95%CI:0.714-0.985).Conclusion:AI-based CT-FFR technology has high diagnostic value for patients with chest pain and chest tightness suspected coronary artery disease.
关键词
冠心病/胸痛/人工智能/冠状动脉CT血管造影/血流储备分数Key words
Coronary artery disease/Chest pain/AI/CCTA/CT-FFR引用本文复制引用
基金项目
2021年度高校科学研究项目(KJ2021A0247)
出版年
2024
国家科技期刊平台
NSTL
万方数据