Aims A multitude of cardiac magnetic resonance (CMR) techniques are used for myocardial strain assessment; however, studies comparing them are limited. We sought to compare global longitudinal (GLS), circumferential (GCS), segmental longitudinal (SLS), and segmental circumferential (SCS) strain values, as well as reproducibility between CMR feature tracking (FT), tagging (TAG), and fast-strain-encoded (fast-SENC) CMR techniques. Methods and results Eighteen subjects (11 healthy volunteers and seven patients with heart failure) underwent two CMR scans (1.5T, Philips) with identical parameters. Global and segmental strain values were measured using FT (Medis), TAG (Medviso), and fast-SENC (Myocardial Solutions). Friedman's test, linear regression, Pearson's correlation coefficient, and Bland-Altman analyses were used to assess differences and correlation in measured GLS and GCS between the techniques. Two-way mixed intra-class correlation coefficient (ICC), coefficient of variance (COV), and Bland-Altman analysis were used for reproducibility assessment. All techniques correlated closely for GLS (Pearson's r: 0.86-0.92) and GCS (Pearson's r: 0.85-0.94). Intra-observer and interobserver reproducibility was excellent in all techniques for both GLS (ICC 0.92-0.99, CoV 2.6-10.1%) and GCS (ICC 0.89-0.99, CoV 4.3-10.1%). Inter-study reproducibility was similar for all techniques for GLS (ICC 0.91-0.96, CoV 9.1-10.8%) and GCS (ICC 0.95-0.97, CoV 7.6-10.4%). Combined segmental intra-observer reproducibility was good in all techniques for SLS (ICC 0.914-0.953, CoV 12.35-24.73%) and SCS (ICC 0.885-0.978, CoV 10.76-19.66%). Combined inter-study SLS reproducibility was the worst in FT (ICC 0.329, CoV 42.99%), while fast-SENC performed the best (ICC 0.844, CoV 21.92%). TAG had the best reproducibility for combined inter-study SCS (ICC 0.902, CoV 19.08%), while FT performed the worst (ICC 0.766, CoV 32.35%). Bland-Altman analysis revealed considerable inter-technique biases for GLS (FT vs. fast-SENC 3.71%; FT vs. TAG 8.35%; and TAG vs. fast-SENC 4.54%) and GCS (FT vs. fast-SENC 2.15%; FT vs. TAG 6.92%; and TAG vs. fast-SENC 2.15%). Limits of agreement for GLS ranged from ±3.1 (TAG vs. fast-SENC) to ±4.85 (FT vs. TAG) for GLS and ±2.98 (TAG vs. fast-SENC) to ±5.85 (FT vs. TAG) for GCS. Conclusions We found significant differences in measured GLS and GCS between FT, TAG, and fast-SENC. Global strain reproducibility was excellent for all techniques. Acquisition-based techniques had better reproducibility than FT for segmental strain.

Background Right ventricular (RV) strain is a useful predictor of prognosis in various cardiovascular diseases, including those traditionally believed to impact only the left ventricle. We aimed to determine inter-modality and inter-technique agreement in RV longitudinal strain (LS) measurements between currently available cardiovascular magnetic resonance (CMR) and echocardiographic techniques, as well as their reproducibility and the impact of layer-specific strain measurements. Methods RV-LS was determined in 62 patients using 2D speckle tracking echocardiography (STE, Epsilon) and two CMR techniques: feature tracking (FT) and strain-encoding (SENC), and in 17 healthy subjects using FT and SENC only. Measurements included global and free-wall LS (GLS, FWLS). Inter-technique agreement was assessed using linear regression and Bland-Altman analysis. Reproducibility was quantified using intraclass correlation (ICC) and coefficients of variation (CoV). Results We found similar moderate agreement between both CMR techniques and STE in patients: r = 0.57–0.63 for SENC; r = 0.50–0.62 for FT. The correlation between SENC and STE was better for GLS (r = 0.63) than for FWLS (r = 0.57). Conversely, the correlation between FT and STE was higher for FWLS (r = 0.60–0.62) than GLS (r = 0.50–0.54). FT-midmyocardial strain correlated better with SENC and STE than FT-subendocardial strain. The agreement between SENC and FT was fair (r = 0.36–0.41, bias: − 6.4 to − 10.4%) in the entire study group. All techniques except FT showed excellent reproducibility (ICC: 0.62–0.96, CoV: 0.04–0.30). Conclusions We found only moderate inter-modality agreement with STE in RV-LS for both FT and SENC and poor agreement when comparing between the CMR techniques. Different modalities and techniques should not be used interchangeably to determine and monitor RV strain.

In this study, we used a single commercially available software solution to assess global longitudinal (GLS) and global circumferential strain (GCS) using cardiac computed tomography (CT) and cardiac magnetic resonance (CMR) feature tracking (FT). We compared agreement and reproducibility between these two methods and the reference standard, CMR tagging (TAG). Twenty-seven patients with severe aortic stenosis underwent CMR and cardiac CT examinations. FT analysis was performed using Medis suite version 3.0 (Leiden, The Netherlands) software. Segment (Medviso) software was used for GCS assessment from tagged images. There was a trend towards the underestimation of GLS by CT-FT when compared to CMR-FT (19.4 ± 5.04 vs. 22.40 ± 5.69, respectively; p = 0.065). GCS values between TAG, CT-FT, and CMR-FT were similar (p = 0.233). CMR-FT and CT-FT correlated closely for GLS (r = 0.686, p < 0.001) and GCS (r = 0.707, p < 0.001), while both of these methods correlated moderately with TAG for GCS (r = 0.479, p < 0.001 for CMR-FT vs. TAG; r = 0.548 for CT-FT vs. TAG). Intraobserver and interobserver agreement was excellent in all techniques. Our findings show that, in elderly patients with severe aortic stenosis (AS), the FT algorithm performs equally well in CMR and cardiac CT datasets for the assessment of GLS and GCS, both in terms of reproducibility and agreement with the gold standard, TAG.