Retrospective reconstruction of cardiac cine images from golden-ratio radial MRI using one-dimensional navigators

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Abstract

Purpose To demonstrate radial golden-ratio-based cardiac cine imaging by using interspersed one-dimensional (1D) navigators. Materials and Methods The 1D navigators were interspersed into the acquisition of radial spokes which were continuously rotated by an angle increment based on the golden-ratio. Performing correlation analysis between the 1D navigator projections, time points corresponding to the same cardiac motion phases were automatically identified and used to combine retrospectively golden-ratio rotated radial spokes from multiple data windows. Data windows were shifted consecutively for dynamic reconstruction of different cardiac motion frames. Experiments were performed during a single breathhold. By artificially reducing the amount of input data, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as artifact level was evaluated for different breathhold durations. Results Analysis of the 1D navigator data provided a detailed correlation function revealing cardiac motion over time. Imaging results were comparable to images reconstructed based on a timely synchronized ECG. Cardiac cine images with a low artifact level and good image quality in terms of SNR and CNR were reconstructed from volunteer data achieving a CNR between the myocardium and the left ventricular cavity of 50 for the longest breathhold duration of 26 s. CNR maintained a value higher than 30 for acquisition times as low as 10 s. Conclusion Combining radial golden-ratio-based imaging with an intrinsic navigator is a promising and robust method for performing high quality cardiac cine imaging. © 2013 Wiley Periodicals, Inc.

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APA

Krämer, M., Herrmann, K. H., Biermann, J., & Reichenbach, J. R. (2014). Retrospective reconstruction of cardiac cine images from golden-ratio radial MRI using one-dimensional navigators. Journal of Magnetic Resonance Imaging, 40(2), 413–422. https://doi.org/10.1002/jmri.24364

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