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July 1, 2024European Heart Journal - Imaging Methods and Practice4 citationsOpen Access

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

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UWUndine Ella WittMMMaximilian MüllerRBRebecca Beyer

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Abstract

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.

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Cite This Study

Witt et al. (2024) studied this question.

synapsesocial.com/papers/68e61deab6db6435875afddbhttps://doi.org/10.1093/ehjimp/qyae093
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Also Consider

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