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      Four-Dimensional Respiratory Motion-Resolved Whole Heart Coronary MR Angiography

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          Abstract

          Purpose

          Free-breathing whole-heart coronary MR angiography (MRA) commonly uses navigators to gate respiratory motion, resulting in lengthy and unpredictable acquisition times. Conversely, self-navigation has 100% scan efficiency, but requires motion correction over a broad range of respiratory displacements, which may introduce image artifacts. We propose replacing navigators and self-navigation with a respiratory motion-resolved reconstruction approach.

          Methods

          Using a respiratory signal extracted directly from the imaging data, individual signal-readouts are binned according to their respiratory states. The resultant series of undersampled images are reconstructed using an extradimensional golden-angle radial sparse parallel imaging (XD-GRASP) algorithm, which exploits sparsity along the respiratory dimension. Whole-heart coronary MRA was performed in 11 volunteers and four patients with the proposed methodology. Image quality was compared with that obtained with one-dimensional respiratory self-navigation.

          Results

          Respiratory-resolved reconstruction effectively suppressed respiratory motion artifacts. The quality score for XD-GRASP reconstructions was greater than or equal to self-navigation in 80/88 coronary segments, reaching diagnostic quality in 61/88 segments versus 41/88. Coronary sharpness and length were always superior for the respiratory-resolved datasets, reaching statistical significance ( P < 0.05) in most cases.

          Conclusion

          XD-GRASP represents an attractive alternative for handling respiratory motion in free-breathing whole heart MRI and provides an effective alternative to self-navigation.

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          Author and article information

          Journal
          8505245
          5733
          Magn Reson Med
          Magn Reson Med
          Magnetic resonance in medicine
          0740-3194
          1522-2594
          7 June 2016
          28 March 2016
          April 2017
          01 April 2017
          : 77
          : 4
          : 1473-1484
          Affiliations
          [1 ]Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
          [2 ]Department of Radiology, University Hospital and University of Lausanne, Lausanne, Switzerland
          [3 ]Center for Advanced Imaging Innovation and Research, and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
          [4 ]Center for Biomedical Imaging, Lausanne, Switzerland
          [5 ]Department of Radiology, Austin Health and The University of Melbourne, Melbourne, Victoria, Australia
          [6 ]Division of Cardiology and Cardiac MR Center, University Hospital of Lausanne, Lausanne, Switzerland
          Author notes
          [* ]Correspondence to: Davide Piccini Ph.D., Center for BioMedical Imaging, Centre Hospitalier Universitaire Vaudois, Rue de Bugnon 46, BH 7.84, 1011 Lausanne, Switzerland. piccinidavide@ 123456gmail.com ; Twitter: @CVMR_Lausanne
          [†]

          Davide Piccini and Li Feng contributed equally to this study.

          Article
          PMC5040623 PMC5040623 5040623 nihpa790954
          10.1002/mrm.26221
          5040623
          27052418
          1c7cf218-4406-4213-a1d8-626be3cbd97f
          Categories
          Article

          sparse reconstruction,coronary MRA,free breathing,compressed sensing,motion correction,self-navigation

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