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Updated: May 28, 2026
Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
Published on: February 12, 2011
Cardiovascular magnetic resonance myocardial feature tracking detects quantitative wall motion during dobutamine
Andreas Schuster1, Shelby Kutty, Asif Padiyath
1King's College London British Heart Foundation Centre of Excellence, London, UK. andreas_schuster@gmx.net
Background:
Dobutamine stress cardiovascular magnetic resonance (DS-CMR) is an established tool to assess hibernating myocardium and ischemia. Analysis is typically based on visual assessment with considerable operator dependency. CMR myocardial feature tracking (CMR-FT) is a recently introduced technique for tissue voxel motion tracking on standard steady-state free precession (SSFP) images to derive circumferential and radial myocardial mechanics.We sought to determine the feasibility and reproducibility of CMR-FT for quantitative wall motion assessment during intermediate dose DS-CMR.
Methods:
10 healthy subjects were studied at 1.5 Tesla. Myocardial strain parameters were derived from SSFP cine images using dedicated CMR-FT software (Diogenes MRI prototype; Tomtec; Germany). Right ventricular (RV) and left ventricular (LV) longitudinal strain (EllRV and EllLV) and LV long-axis radial strain (ErrLAX) were derived from a 4-chamber view at rest. LV short-axis circumferential strain (EccSAX) and ErrSAX; LV ejection fraction (EF) and volumes were analyzed at rest and during dobutamine stress (10 and 20 μg · kg⁻¹· min⁻¹).
Results:
In all volunteers strain parameters could be derived from the SSFP images at rest and stress. EccSAX values showed significantly increased contraction with DSMR (rest: -24.1 ± 6.7; 10 μg: -32.7 ± 11.4; 20 μg: -39.2 ± 15.2; p < 0.05). ErrSAX increased significantly with dobutamine (rest: 19.6 ± 14.6; 10 μg: 31.8 ± 20.9; 20 μg: 42.4 ± 25.5; p < 0.05). In parallel with these changes; EF increased significantly with dobutamine (rest: 56.9 ± 4.4%; 10 μg: 70.7 ± 8.1; 20 μg: 76.8 ± 4.6; p < 0.05). Observer variability was best for LV circumferential strain (EccSAX ) and worst for RV longitudinal strain (EllRV) as determined by 95% confidence intervals of the difference.
Conclusions:
CMR-FT reliably detects quantitative wall motion and strain derived from SSFP cine imaging that corresponds to inotropic stimulation. The current implementation may need improvement to reduce observer-induced variance. Within a given CMR lab; this novel technique holds promise of easy and fast quantification of wall mechanics and strain.
