Psychology

Philosophy

Artificial intelligence

Pedagogy

Feature (linguistics)

Pattern recognition (psychology)

Feature tracking

Cardiology

Computer science

Tracking (education)

Linguistics

Internal medicine

Heart failure

Strain (injury)

Medicine

ESC Heart Failure

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. 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. 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.

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