Left ventricular radial tagging acquisition using gradient-recalled-echo techniques: sequence optimization.
Myocardial tagging with magnetic resonance (MR) imaging offers unique possibilities for noninvasive left ventricular (LV) strain analysis. True three-dimensional strain analysis can be achieved with tags implemented in cardiac short axis and long axis images. Spin-echo (SE) techniques have been used for these studies. However, this approach is time-consuming: images at different phases of the cardiac cycle have to be obtained in successive measurements and hence the total number of measurements equals the number of time frames. Moreover, the images are often degraded by flow and motion artifacts. The purpose of this study was to optimize a faster and more robust MR tagging sequence for use on a clinical whole-body 1 T MR system with optimal persistence of the tags during the entire cardiac cycle. The tagging pulses were implemented in gradient-recalled-echo (GRE) sequences and compared to SE-based acquisitions. The effects of the use of flow-compensating gradients, the excitation angles, and the angles of the saturation pulses have been studied with MR signal simulations and in comparative measurements in volunteers. GRE acquisitions with flow-compensating gradients are robust techniques for myocardial tagging acquisitions. Use of optimized flip angles and saturation pulses can significantly improve delineation of the tag and can be used up to at least 700 ms after the R-wave. Therefore, LV tagging with GRE acquisitions using optimized MR parameters is a robust and promising technique.
Bosmans
H
H
Department of Radiology, University Hospitals, Leuven, Belgium.
Bogaert
J
J
Rademakers
F
F
Marchal
G
G
Laub
G
G
Verschakelen
J
J
Baert
A L
AL
D006321:Heart / Q000033:anatomy & histology* / Q000502:physiology; D006352:Heart Ventricles / Q000033:anatomy & histology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D016276:Ventricular Function