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Updated: Apr 1, 2026

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
Published on: February 12, 2011
Assessment of cardiac dyssynchrony by cardiac MR: A comparison of velocity encoding and feature tracking analysis
Daniel L R Kuetting1, Alois M Sprinkart1, Darius Dabir1
1Department of Radiology, University of Bonn, Bonn, Germany.
Purpose:
To investigate whether cardiac magnetic resonance (cardiac MR)-based feature tracking (FT) may be used for robust and rapid quantification of dyssynchrony by measurement of the septal to lateral delay (SLD).
Materials And Methods:
Healthy volunteers (n = 18) and patients with mechanical dyssynchrony (n = 17) were investigated. Velocity encoding cardiac MR (VENC) and steady-state free precession (SSFP)-cine sequences were acquired in identical horizontal long axis (HLA) positions using a 1.5T MR scanner. Using FT and VENC cardiac MR software, myocardial velocity curves were calculated for the basal segment of the septal and lateral wall. Based on the quantity of dyssynchrony, the patients were classified into three subgroups (minimal, intermediate, extensive). SLD and patient classification were compared and intra- as well as interobserver variability assessed.
Results:
VENC and FT SLD measurements showed strong correlation (r = 0.94) and good agreement (mean 1.33 msec; limits of agreement [LoA] -2.96 to 5.63). Dyssynchrony subclassification based on FT was identical to VENC in 83% of the cases. While FT correctly classified all healthy subjects, three patients with mechanical dyssynchrony were misclassified. Compared to VENC, FT showed higher intra- and interobserver variability. VENC: intraobserver: mean 2.5 msec, LoA -17.5 to 22.5; interobserver: mean 1.5 msec, LoA -17.2 to 21.9. FT: intraobserver: mean 2.1 msec, LoA 27.6 to 31.8; interobserver: mean 2.4 msec LoA -31.4 to 34.5.
Conclusion:
Cardiac MR-based FT analysis may be used for rapid appraisal of left ventricle cardiac dyssynchrony from SSFP images. However, FT results are less accurate and reproducible compared to VENC-based assessment of SLD.
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