Retrospective respiratory motion correction for navigated cine velocity mapping.
In general, high spatial and temporal resolutions in cine cardiac imaging require long scan times, making breath-hold acquisition impossible in many cases. To enable free-breathing cardiac imaging, methods such as navigator gating were developed to reduce image artifacts due to respiratory motion. Nevertheless, residual image blurring is seen in images acquired late in the cardiac cycle. Image blurring itself hampers accurate blood flow quantification, especially in vessels exhibiting high flows during diastole. In the present work, the navigator gating and slice tracking method was extended by using navigator information to correct for in-slice motion components throughout the cardiac cycle. For this purpose, a standard two-dimensional (2D) cine phase contrast sequence with navigator gating and slice position correction was used, and navigator information was recorded along with the raw k-space data. In postprocessing, in-plane motion components arising from respiration during the actual data acquisition were estimated and corrected according to the Fourier shift theorem. In phantom experiments, the performance of the correction algorithm for different slice angulations with respect to the navigator orientation was validated. In vivo, coronary flow measurements were performed in 9 healthy volunteers. The correction algorithm led to considerably improved vessel sharpness throughout the cardiac cycle in all measured subjects [increase in vessel sharpness: 16+/-11% (mean+/-SD)]. Furthermore, these improvements resulted in increased volume flow rates [16+/-13% (mean+/-SD)] after retrospective correction indicating the impact of the method. It is concluded that retrospective respiratory motion corrections for navigated cine two-dimensional (2D) velocity mapping can correct for in-plane motion components, providing better image quality for phases acquired late in the cardiac cycle. Therefore, this method holds promise in particular for free-breathing coronary flow quantification.
Baltes
Christof
C
Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
Kozerke
Sebastian
S
Atkinson
David
D
Boesiger
Peter
P
D001783:Blood Flow Velocity / Q000502:physiology; D003326:Coronary Circulation / Q000502:physiology; D003331:Coronary Vessels / Q000502:physiology; D005240:Feasibility Studies; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods; D019047:Phantoms, Imaging; D012137:Respiratory System / Q000098:blood supply*; D012189:Retrospective Studies