Author
Listed:
- Johannes T Kowallick
- Pablo Lamata
- Shazia T Hussain
- Shelby Kutty
- Michael Steinmetz
- Jan M Sohns
- Martin Fasshauer
- Wieland Staab
- Christina Unterberg-Buchwald
- Boris Bigalke
- Joachim Lotz
- Gerd Hasenfuß
- Andreas Schuster
Abstract
Objectives: Cardiovascular magnetic resonance feature tracking (CMR-FT) offers quantification of myocardial deformation from routine cine images. However, data using CMR-FT to quantify left ventricular (LV) torsion and diastolic recoil are not yet available. We therefore sought to evaluate the feasibility and reproducibility of CMR-FT to quantify LV torsion and peak recoil rate using an optimal anatomical approach. Methods: Short-axis cine stacks were acquired at rest and during dobutamine stimulation (10 and 20 µg·kg−1·min−1) in 10 healthy volunteers. Rotational displacement was analysed for all slices. A complete 3D-LV rotational model was developed using linear interpolation between adjacent slices. Torsion was defined as the difference between apical and basal rotation, divided by slice distance. Depending on the distance between the most apical (defined as 0% LV distance) and basal (defined as 100% LV distance) slices, four different models for the calculation of torsion were examined: Model-1 (25–75%), Model-2 (0–100%), Model-3 (25–100%) and Model-4 (0–75%). Analysis included subendocardial, subepicardial and global torsion and recoil rate (mean of subendocardial and subepicardial values). Results: Quantification of torsion and recoil rate was feasible in all subjects. There was no significant difference between the different models at rest. However, only Model-1 (25–75%) discriminated between rest and stress (Global Torsion: 2.7±1.5°cm−1, 3.6±2.0°cm−1, 5.1±2.2°cm−1, p
Suggested Citation
Johannes T Kowallick & Pablo Lamata & Shazia T Hussain & Shelby Kutty & Michael Steinmetz & Jan M Sohns & Martin Fasshauer & Wieland Staab & Christina Unterberg-Buchwald & Boris Bigalke & Joachim Lotz, 2014.
"Quantification of Left Ventricular Torsion and Diastolic Recoil Using Cardiovascular Magnetic Resonance Myocardial Feature Tracking,"
PLOS ONE, Public Library of Science, vol. 9(10), pages 1-11, October.
Handle:
RePEc:plo:pone00:0109164
DOI: 10.1371/journal.pone.0109164
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