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Direct Myocardial Strain Assessment from Frequency Estimation in Tagging MRI

  • Hanne B. Kause
  • Olena G. Filatova
  • Remco Duits
  • L. C. Mark Bruurmijn
  • Andrea Fuster
  • Jos J. M. Westenberg
  • Luc M. J. Florack
  • Hans C. van Assen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8330)

Abstract

We propose a new method to analyse deformation of the cardiac left ventricular wall from tagging magnetic resonance images. The method exploits the fact that the time-dependent frequency covector field representing the tag pattern is tightly coupled to the myocardial deformation and not affected by tag fading. Deformation and strain tensor fields can be retrieved from local frequency estimates given at least n (independent) tagging sequences, where n denotes spatial dimension. Our method does not require knowledge of material motion or tag line extraction. We consider the conventional case of two tag directions, as well as the overdetermined case of four tag directions, which improves robustness. Additional scan time can be prevented by using one or two grid patterns consisting of multiple, simultaneously acquired tag directions. This concept is demonstrated on patient data. Tracking errors obtained for phantom data are smaller than those obtained by HARP, 0.32±0.14 px versus 0.53±0.07 px. Strain results for volunteers are compared with corresponding linearised strain fields derived from HARP.

Keywords

Tagging Magnetic Resonance Imaging Myocardial Deformation Myocardial Strain Gabor Transform Frequency Analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Hanne B. Kause
    • 1
  • Olena G. Filatova
    • 1
  • Remco Duits
    • 2
    • 3
  • L. C. Mark Bruurmijn
    • 2
  • Andrea Fuster
    • 2
    • 3
  • Jos J. M. Westenberg
    • 4
  • Luc M. J. Florack
    • 2
    • 3
  • Hans C. van Assen
    • 1
  1. 1.Department of Electrical EngineeringEindhoven University of TechnologyThe Netherlands
  2. 2.Department of Biomedical EngineeringEindhoven University of TechnologyThe Netherlands
  3. 3.Department of Mathematics & Computer ScienceEindhoven University of TechnologyThe Netherlands
  4. 4.Department of RadiologyLeiden University Medical CenterThe Netherlands

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