REPRODUCIBLE COMPUTER-ASSISTED QUANTIFICATION OF MYOCARDIAL PERFUSION WITH CONTRAST-ENHANCED ULTRASOUND

被引:8
作者
Li, Yuanwei [1 ]
Chahal, Navtej [2 ,3 ]
Senior, Roxy [2 ,3 ]
Tang, Meng-Xing [1 ]
机构
[1] Imperial Coll London, Dept Bioengn, Exhibit Rd, London SW7 2AZ, England
[2] Royal Brompton Hosp, Dept Echocardiog, London, England
[3] Imperial Coll, Natl Heart & Lung Inst, Biomed Res Unit, London, England
基金
英国工程与自然科学研究理事会;
关键词
Myocardial contrast echocardiography; Myocardial perfusion; Computer-assisted quantification; Coronary artery disease; Reproducibility; CORONARY-ARTERY-DISEASE; BLOOD-FLOW RESERVE; STRESS ECHOCARDIOGRAPHY; TOMOGRAPHY; INFARCTION; VARIABILITY; ANGIOGRAPHY;
D O I
10.1016/j.ultrasmedbio.2017.05.001
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Myocardial perfusion can be quantified by myocardial contrast echocardiography (MCE) and is used for the diagnosis of coronary artery disease (CAD). However, existing MCE quantification software is highly operator dependent and has poor reproducibility and ease of usage. The aim of this study was to develop robust and easy-to-use software that can perform MCE quantification accurately, reproducibly and rapidly. The developed software has the following features: (i) semi-automatic segmentation of the myocardium; (ii) automatic rejection of MCE data with poor image quality; (iii) automatic computation of perfusion parameters such as myocardial blood flow (MBF). MCE sequences of 18 individuals (9 normal, 9 with CAD) undergoing vasodilator stress with dipyridamole were analysed quantitatively using the software. When evaluated against coronary angiography, the software achieved a sensitivity of 71% and a specificity of 91% for hyperemic MBF. With the automatic rejection algorithm, the sensitivity and specificity further improved to 77% and 94%, respectively. For MBF reproducibility, the percentage agreement is 85% (k = 0.65) for inter-observer variability and 88% (k = 0.72) for intra-observer variability. The intra-class correlation coefficients are 0.94 (inter-observer) and 0.96 (intra-observer). The time taken to analyse one MCE sequence using the software is about 3 min on a PC. The software has exhibited good diagnostic performance and reproducibility for CAD detection and is rapid and user-friendly. (E-mail: mengxing.tang@imperial.ac.uk) (C) 2017 The Authors. Published by Elsevier Inc. on behalf of World Federation for Ultrasound in Medicine & Biology.
引用
收藏
页码:2235 / 2246
页数:12
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