Comparison of feature tracking, fast-SENC, and myocardial tagging for global and segmental left ventricular strain

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.

Strain-encoded magnetic resonance: a method for the assessment of myocardial deformation

This study aims to assess the usefulness of strain‐encoded magnetic resonance (SENC) for the quantification of myocardial deformation (‘strain’) in healthy volunteers and for the diagnostic workup of patients with different cardiovascular pathologies. SENC was initially described in the year 2001. Since then, the SENC sequence has undergone several technical developments, aiming at the detection of strain during single‐heartbeat acquisitions (fast‐SENC). Experimental and clinical studies that used SENC and fast‐SENC or compared SENC with conventional cine or tagged magnetic resonance in phantoms, animals, healthy volunteers, or patients were systematically searched for in PubMed. Using ‘strain‐encoded magnetic resonance and SENC’ as keywords, three phantom and three animal studies were identified, along with 27 further clinical studies, involving 185 healthy subjects and 904 patients. SENC (i) enabled reproducible assessment of myocardial deformation in vitro, in animals and in healthy volunteers, (ii) showed high reproducibility and substantially lower time spent compared with conventional tagging, (iii) exhibited incremental value to standard cine imaging for the detection of inducible ischaemia and for the risk stratification of patients with ischaemic heart disease, and (iv) enabled the diagnostic classification of patients with transplant vasculopathy, cardiomyopathies, pulmonary hypertension, and diabetic heart disease. SENC has the potential to detect a wide range of myocardial diseases early, accurately, and without the need of contrast agent injection, possibly enabling the initiation of specific cardiac therapies during earlier disease stages. Its one‐heartbeat acquisition mode during free breathing results in shorter cardiovascular magnetic resonance protocols, making its implementation in the clinical realm promising.

MRI-Derived Myocardial Strain Measures in Normal Subjects

OBJECTIVES

The aim of this study was to perform a systematic review and meta-analysis to estimate the normal ranges of magnetic resonance imaging (MRI)-based feature tracking (FT) and to identify sources of variations. Similar analyses were also performed for strain encoding, displacement encoding with stimulated echoes, and myocardial tagging.

BACKGROUND

MRI-FT is a novel technique for quantification of myocardial deformation using MRI cine images. However, the reported 95% confidence intervals (CIs) from the 2 largest studies have no overlaps.

METHODS

Four databases (EMBASE, SCOPUS, PUBMED, and Web of Science) were systematically searched for MRI strains of the left (LV) and right (RV) ventricles. The key terms for MRI-FT were "tissue tracking," "feature tracking," "cardiac magnetic resonance," "cardiac MRI," "CMR," and "strain." A random effects model was used to pool LV global longitudinal strain (GLS), global circumferential strain (GCS), global radial strain (GRS), and RVGLS. Meta-regressions were used to identify the sources of variations.

RESULTS

659 healthy subjects were included from 18 papers for MRI-FT. Pooled mean of LVGLS was -20.1% (95% CI: -20.9% to -19.3%), LVGCS -23% (95% CI: -24.3% to -21.7%), LVGRS 34.1% (95% CI: 28.5% to 39.7%), and RVGLS -21.8% (95% CI: -23.3% to -20.2%). Although there were no publication biases except for LVGCS, significant heterogeneities were found. Meta-regression showed that variation of LVGCS was associated with field strength (β = 3.2; p = 0.041). Variations of LVGLS, LVGRS, and RVGLS were not associated with any of age, sex, software, field strength, sequence, LV ejection fraction, or LV size. LVGCS seems the most robust in MRI-FT. Among the MRI-derived strain techniques, the normal ranges were mostly concordant in LVGLS and LVGCS but varied substantially in LVGRS and RVGLS.

CONCLUSIONS

The pooled means of 4 MRI-derived myocardial strain methods in normal subjects are demonstrated. Differences in field strength were attributed to variations of LVGCS.

Assessment of liver fibrosis using fast strain-encoded MRI driven by inherent cardiac motion

PURPOSE

An external driver-free MRI method for assessment of liver fibrosis offers a promising noninvasive tool for diagnosis and monitoring of liver disease. Lately, the heart's intrinsic motion and MR tagging have been utilized for the quantification of liver strain. However, MR tagging requires multiple breath-hold acquisitions and substantial postprocessing. In this study, we propose the use of a fast strain-encoded (FSENC) MRI method to measure the peak strain (Sp ) in the liver's left lobe, which is in close proximity and caudal to the heart. Additionally, we introduce a new method of measuring heart-induced shear wave velocity (SWV) inside the liver.

METHODS

Phantom and in vivo experiments (11 healthy subjects and 11 patients with liver fibrosis) were conducted. Reproducibility experiments were performed in seven healthy subjects.

RESULTS

Peak liver strain, Sp , decreased significantly in fibrotic liver compared with healthy liver (6.46% ± 2.27% vs 12.49% ± 1.76%; P < 0.05). Heart-induced SWV increased significantly in patients compared with healthy subjects (0.15 ± 0.04 m/s vs 0.63 ± 0.32 m/s; P < 0.05). Reproducibility analysis yielded no significant difference in Sp (P = 0.47) or SWV (P = 0.56).

CONCLUSION

Accelerated external driver-free noninvasive assessment of left liver lobe strain and SWV is feasible using strain-encoded MRI. The two measures significantly separate healthy subjects from patients with fibrotic liver. Magn Reson Med 74:106-114, 2015. © 2014 Wiley Periodicals, Inc.