A simplified approach to discriminate between healthy subjects and patients with heart failure using cardiac magnetic resonance myocardial deformation imaging.

European heart journal. Imaging methods and practice Pub Date : 2024-09-12 eCollection Date: 2024-07-01 DOI:10.1093/ehjimp/qyae093
Undine Ella Witt, Maximilian Leo Müller, Rebecca Elisabeth Beyer, Johannes Wieditz, Susanna Salem, Djawid Hashemi, Wensu Chen, Mina Cvetkovic, Anna Clara Nolden, Patrick Doeblin, Moritz Blum, Gisela Thiede, Alexander Huppertz, Henning Steen, Bjoern Andrew Remppis, Volkmar Falk, Tim Friede, Sebastian Kelle
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Abstract

Aims: Left ventricular global longitudinal strain (LV-GLS) shows promise as a marker to detect early heart failure (HF). This study sought to (i) establish cardiac magnetic resonance imaging (CMR)-derived LV-GLS cut-offs to differentiate healthy from HF for both acquisition-based and post-processing techniques, (ii) assess agreement, and (iii) provide a method to convert LV-GLS between both techniques.

Methods and results: A secondary analysis of a prospective study enrolling healthy subjects (n = 19) and HF patients (n = 56) was conducted. LV-GLS was measured using fast strain-encoded imaging (fSENC) and feature tracking (FT). Receiver operating characteristic (ROC) analyses were performed to derive and evaluate LV-GLS cut-offs discriminating between healthy, HF with mild deformation impairment (DI), and HF with severe DI. Linear regression and Bland-Altman analyses assessed agreement. Cut-offs discriminating between healthy and HF were identified at -19.3% and -15.1% for fSENC and FT, respectively. Cut-offs of -15.8% (fSENC) and -10.8% (FT) further distinguished mild from severe DI. No significant differences in area under ROC curve were identified between fSENC and FT. Bland-Altman analysis revealed a bias of -4.01%, 95% CI -4.42, -3.50 for FT, considering fSENC as reference. Linear regression suggested a factor of 0.76 to rescale fSENC-derived LV-GLS to FT. Using this factor on fSENC-derived cut-offs yielded rescaled FT LV-GLS cut-offs of -14.7% (healthy vs. HF) and -12% (mild vs. severe DI).

Conclusion: LV-GLS distinguishes healthy from HF with high accuracy. Each measurement technique requires distinct cut-offs, but rescaling factors facilitate conversion. An FT-based LV-GLS ≥ -15% simplifies HF detection in clinical routine.

利用心脏磁共振心肌变形成像区分健康受试者和心力衰竭患者的简化方法。
目的:左心室整体纵向应变(LV-GLS)有望成为检测早期心力衰竭(HF)的标志物。本研究旨在:(i) 建立心脏磁共振成像(CMR)得出的 LV-GLS 临界值,以区分基于采集和后处理技术的健康和 HF;(ii) 评估一致性;(iii) 提供在两种技术之间转换 LV-GLS 的方法:对一项前瞻性研究中的健康受试者(19 人)和心房颤动患者(56 人)进行了二次分析。使用快速应变编码成像(fSENC)和特征追踪(FT)测量了左心室-GLS。通过接收者操作特征(ROC)分析,得出并评估了区分健康人、轻度变形障碍(DI)的心房颤动患者和重度变形障碍(DI)的心房颤动患者的 LV-GLS 临界值。线性回归和 Bland-Altman 分析评估了一致性。fSENC和FT区分健康和HF的临界值分别为-19.3%和-15.1%。-15.8%(fSENC)和-10.8%(FT)的临界值进一步区分了轻度和重度DI。fSENC 和 FT 的 ROC 曲线下面积无明显差异。将 fSENC 作为参考,Bland-Altman 分析显示 FT 的偏差为 -4.01%,95% CI -4.42,-3.50。线性回归结果表明,将 fSENC 导出的 LV-GLS 与 FT 进行比例调整的因子为 0.76。将这一因子用于 fSENC 导出的临界值,得到的 FT LV-GLS 临界值的重定标分别为-14.7%(健康 vs. HF)和-12%(轻度 vs. 重度 DI):结论:LV-GLS 能高度准确地区分健康与 HF。每种测量技术都需要不同的临界值,但重定向因子有助于转换。基于 FT 的 LV-GLS ≥ -15% 简化了临床常规中的心房颤动检测。
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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