Assessment of left ventricular mechanical dyssynchrony in LBBB canine model: a comparison between cine and tagged MRI

S. Saporito, H.C. van Assen, P. Houthuizen, J.-P. Aben, M. Strik, L. van Middendorp, F. Prinzen, M. Mischi

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To compare cine and tagged magnetic resonance imaging (MRI) for left ventricular dyssynchrony assessment in left bundle branch block (LBBB), using the time-to-peak contraction timing, and a novel approach based on cross-correlation.

Materials and Methods
We evaluated a canine model dataset (n = 10) before (pre-LBBB) and after induction of isolated LBBB (post-LBBB). Multislice short-axis tagged and cine MRI images were acquired using a 1.5 T scanner. We computed contraction time maps by cross-correlation, based on the timing of radial wall motion and of circumferential strain. Finally, we estimated dyssynchrony as the standard deviation of the contraction time over the different regions of the myocardium.

Induction of LBBB resulted in a significant increase in dyssynchrony (cine: 13.0 ± 3.9 msec for pre-LBBB, and 26.4 ± 5.0 msec for post-LBBB, P = 0.005; tagged: 17.1 ± 5.0 msec at for pre-LBBB, and 27.9 ± 9.8 msec for post-LBBB, P = 0.007). Dyssynchrony assessed by cine and tagged MRI were in agreement (r = 0.73, P = 0.0003); differences were in the order of time difference between successive frames of 20 msec (bias: –2.9 msec; limit of agreement: 10.1 msec). Contraction time maps were derived; agreement was found in the contraction patterns derived from cine and tagged MRI (mean difference in contraction time per segment: 3.6 ± 13.7 msec).

This study shows that the proposed method is able to quantify dyssynchrony after induced LBBB in an animal model. Cine-assessed dyssynchrony agreed with tagged-derived dyssynchrony, in terms of magnitude and spatial direction.
Original languageEnglish
Pages (from-to)956-963
Number of pages8
JournalJournal of Magnetic Resonance Imaging
Issue number4
Publication statusPublished - Oct 2016


  • MR tagging
  • LBBB
  • cardiac dyssynchrony
  • dogs
  • cine-MRI
  • image analysis


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