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 inter‐observer 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.

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. 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). 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). 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.

Background: In patients with non-ischemic dilated cardiomyopathy (NIDCM), myocardial fibrosis (MF) is related to adverse cardiovascular outcomes. The purpose of this study was to evaluate the potential relationship between the myocardial mechanics of different chambers of the heart and the presence of MF and to determine the accuracy of the whole-heart myocardial strain parameters to predict MF in patients with NIDCM. Methods: We studied 101 patients (64% male; 50 ± 11 years) with a first-time diagnosis of NIDCM who were referred for a clinical cardiovascular magnetic resonance (CMR) and speckle tracking 2D echocardiography examination. We analyzed MF by late gadolinium enhancement (LGE), and the whole-heart myocardial mechanics were assessed by speckle tracking. The presence of MF was related to worse strain parameters in both ventricles and atria. The strongest correlations were found between MF and left ventricle (LV) global longitudinal strain (GLS) (r = −0.586, p < 0.001), global circumferential strain (GCS) (r = −0.609, p < 0.001), LV ejection fraction (LVEF) (r = 0.662, p < 0.001), and left atrial strain during the reservoir phase (LASr) (r = 0.588, p < 0.001). However, the binary logistic regression analysis revealed that only LV GLS, GCS, and LASr were independently associated with the presence of MF (area under the curves of 0.84, 0.85, and 0.64, respectively). None of the echocardiographic parameters correlated with fibrosis localization. Conclusions: In NIDCM patients, MF is correlated with reduced mechanical parameters in both ventricles and atria. LV GLS, LASr, and LV GCS are the most accurate 2D echocardiography predictive factors for the presence of MF.

Introduction: Hematopoietic stem cell transplantation (HSCT) recipients are at increased risk of cardiovascular diseases. In our study, we aimed to find subclinical changes in myocardial tissue after HSCT with the help of cardiovascular magnetic resonance (CMR) tissue imaging techniques. Methods: The data of 44 patients undergoing autologous and allogeneic HSCT in the Hospital of Lithuanian University of Health Sciences Kaunas Clinics from October 2021 to February 2023 were analyzed. Bioethics approval for the prospective study was obtained (No BE-2-96). CMR was performed two times: before enrolling for the HSCT procedure (before starting mobilization chemotherapy for autologous HSCT and before starting the conditioning regimen for allogeneic HSCT) and 12 ± 1 months after HSCT. LV end-diastolic volume, LV end-systolic volume, LV mass and values indexed to body surface area (BSA), and LV ejection fraction were calculated. T1 and T2 mapping values were measured. Results: There was a statistically significant change in T1 mapping values. Before HSCT, mean T1 mapping was 1226.13 ± 39.74 ms, and after HSCT, it was 1248.70 ± 41.07 ms (p = 0.01). The other parameters did not differ significantly. Conclusions: Increases in T1 mapping values following HSCT can show the progress of diffuse myocardial fibrosis and may reflect subclinical injury. T2 mapping values remain the same and do not show edema and active inflammation processes at 12 months after HSCT.

Background/Objectives: Cardiac magnetic resonance (CMR) imaging provides a comprehensive assessment of myocardial injury after ST-segment elevation myocardial infarction (STEMI), yet the relative prognostic value of segmental infarct zone parameters compared with global indices for predicting left ventricular (LV) functional recovery remains incompletely defined. This study aimed to determine whether segmental infarct zone functional and structural CMR parameters provide prognostic information for LV functional recovery after a first STEMI treated with primary percutaneous coronary intervention (PCI). Methods: In this prospective single-center study, 93 patients with a first STEMI (median age 61 years; 77% male) underwent CMR at baseline (median 3 days post-PCI) and at a 6-month follow-up. The comprehensive CMR assessment included cine imaging for volumetric and feature-tracking strain analysis, T1 and T2 mapping, and late gadolinium enhancement (LGE) for infarct size (IS) and microvascular obstruction (MVO) quantification. The myocardial segments were classified as infarcted, adjacent, or remote based on the LGE distribution. The primary outcome was unfavorable LV functional recovery, defined as failure to achieve an absolute increase of >10 percentage points in the LV ejection fraction (LVEF) or a follow-up LVEF ≤ 50%. Results: At the 6-month follow-up, significant reverse remodeling was observed: the LVEF improved from 49.0% [40.7–52.4] to 55.8% [47.9–59.9] (p < 0.001), the LV end-systolic volume decreased from 91.8 mL [75.1–113.8] to 80.8 mL [61.9–108.3] (p = 0.005), and the relative IS decreased from 30.9% [18.9–45.5] to 19.0% [11.1–31.3] of LV mass (p < 0.001). At the follow-up, MVO was no longer detectable in any patient. Unfavorable functional recovery occurred in 17 patients (18.3%). In the multivariable analysis, the infarct zone circumferential strain (CS) was the strongest independent predictor of unfavorable recovery (OR 8.81; 95% CI 1.98–39.28; p = 0.004), followed by the relative IS (OR 4.02; 95% CI 1.03–15.73; p = 0.045) and a lower infarct zone post-contrast T1 (OR 4.40; 95% CI 1.12–17.36; p = 0.034). Conclusions: Segmental infarct zone characteristics—particularly circumferential strain, post-contrast T1, and infarct size—provide clinically relevant prognostic information for LV functional recovery after STEMI. The infarct zone CS offers incremental predictive value beyond its structural parameters, reflecting the residual contractile reserve and myocardial viability.