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Updated: Feb 10, 2026

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging
Published on: May 24, 2021
Head-to-head comparison of left ventricular strain assessed by CMR post-processing tools and fast strain-ENCoded
Andreas Ochs1,2, Marc Zahlten1, Janek Salatzki1,2
1Department of Cardiology, Angiology, and Pneumology, University Hospital Heidelberg, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany.
Aims:
Cardiovascular magnetic resonance (CMR) strain imaging allows early detection of subclinical myocardial dysfunction and provides incremental diagnostic and prognostic information. Strain can be derived from dedicated sequences such as fast Strain-ENCoded imaging (fSENC) or from post-processing of cine images using feature tracking (FT) and tissue tracking (TT). However, it remains unclear whether strain values from different approaches are directly comparable, making the definition of universal reference values difficult. This study compared left ventricular (LV) strain assessed by FT, TT, and fSENC.
Methods And Results:
We studied 240 individuals (183 patients recovered from coronavirus disease 2019 [COVID-19] and 57 age- and sex-matched healthy controls), who underwent standardized CMR including cine imaging and fSENC. LV global longitudinal (GLS), circumferential (GCS), and radial strain (GRS) were analysed using FT and TT; fSENC provided GLS and GCS. Global strain values differed significantly between all methods (P < 0.001). Agreement between FT and TT was high for GLS (bias -0.8%, r = 0.77) and moderate for GCS (bias -1.2%, r = 0.63), but poor for GRS (bias -6.0%, r = 0.37). Compared with fSENC, GLS showed moderate agreement for FT (bias 2.3%, r = 0.57) and TT (bias 3.0%, r = 0.59), while agreement for GCS was weaker. All approaches demonstrated excellent reproducibility. Post-COVID-19 patients showed a consistent but mild reduction in GLS compared with controls across all techniques (all P < 0.05).
Conclusion:
CMR strain imaging provides fast, reliable, and reproducible measurements. However, strain values are not directly interchangeable even between similar post-processing methods or when compared with dedicated sequences, highlighting the need for standardization and method-specific reference values.
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