Relationship of Myocardial Strain and Markers of Myocardial Injury to Predict Segmental Recovery After Acute ST-Segment–Elevation Myocardial Infarction

Author:

Khan Jamal N.1,Nazir Sheraz A.1,Singh Anvesha1,Shetye Abhishek1,Lai Florence Y.1,Peebles Charles1,Wong Joyce1,Greenwood John P.1,McCann Gerry P.1

Affiliation:

1. From the Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular BRU, Glenfield Hospital, United Kingdom (J.N.K., S.A.N., A.Singh, A.Shetye, F.Y.L., G.P.M.); Department of Cardiology, University Hospital Southampton NHS Trust, United Kingdom (C.P.); Department of Cardiology, Royal Brompton and Harefield NHS Trust, London, United Kingdom (J.W.); and The Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM), University of Leeds, United Kingdom ...

Abstract

Background— Late gadolinium-enhanced cardiovascular magnetic resonance imaging overestimates infarct size and underestimates recovery of dysfunctional segments acutely post ST-segment–elevation myocardial infarction. We assessed whether cardiovascular magnetic resonance imaging–derived segmental myocardial strain and markers of myocardial injury could improve the accuracy of late gadolinium-enhancement in predicting functional recovery after ST-segment–elevation myocardial infarction. Methods and Results— A total of 164 ST-segment–elevation myocardial infarction patients underwent acute (median 3 days) and follow-up (median 9.4 months) cardiovascular magnetic resonance imaging. Wall-motion scoring, feature tracking–derived circumferential strain ( Ecc ), segmental area of late gadolinium-enhancement (SEE), microvascular obstruction, intramyocardial hemorrhage, and salvage index (MSI) were assessed in 2624 segments. We used logistic regression analysis to identify markers that predict segmental recovery. At acute CMR 32% of segments were dysfunctional, and at follow-up CMR 19% were dysfunctional. Segmental function at acute imaging and odds ratio (OR) for functional recovery decreased with increasing SEE, although 33% of dysfunctional segments with SEE 76% to 100% improved. SEE was a strong predictor of functional improvement and normalization (area under the curve [AUC], 0.840 [95% confidence interval {CI}, 0.814–0.867]; OR, 0.97 [95% CI, 0.97–0.98] per +1% SEE for improvement and AUC, 0.887 [95% CI, 0.865–0.909]; OR, 0.95 [95% CI, 0.94–0.96] per +1% SEE for normalization). Its predictive accuracy for improvement, as assessed by areas under the receiver operator curves, was similar to that of MSI (AUC, 0.840 [95% CI, 0.809–0.872]; OR, 1.03 [95% CI, 1.02–1.03] per +1% MSI for improvement and AUC, 0.862 [0.832–0.891]; OR, 1.04 [95% CI, 1.03–1.04] per +1% SEE for normalization) and Ecc (AUC, 0.834 [95% CI, 0.807–0.862]; OR, 1.05 [95% CI, 1.03–1.07] per +1% MSI for improvement and AUC, 0.844 [95% CI, 0.818–0.871]; OR, 1.07 [95% CI, 1.05–1.10] per +1% SEE for normalization), and for normalization was greater than the other predictors. MSI and Ecc remained as significant after adjustment for SEE but provided no significant increase in predictive accuracy for improvement and normalization compared with SEE alone. MSI had similar predictive accuracy to SEE for functional recovery but was not assessable in 25% of patients. Microvascular obstruction provided no incremental predictive accuracy above SEE. Conclusions— This multicenter study confirms that SEE is a strong predictor of functional improvement post ST-segment–elevation myocardial infarction, but recovery occurs in a substantial proportion of dysfunctional segments with SEE >75%. Feature tracking–derived Ecc and MSI provide minimal incremental benefit to SEE in predicting segmental recovery. Clinical Trial Registration— URL: http://www.isrctn.com . Unique identifier: ISRCTN70913605.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine,Radiology, Nuclear Medicine and imaging

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3