Nonrigid autofocus motion correction for coronary MR angiography with a 3D cones trajectory

Authors

  • R. Reeve Ingle,

    Corresponding author
    1. Department of Electrical Engineering, Magnetic Resonance Systems Research Laboratory, Stanford University, Stanford, California, USA
    • Correspondence to: Reeve Ingle, M.S., Packard Electrical Engineering Bldg, Room 210, 350 Serra Mall, Stanford, CA 94305-9510. E-mail: ringle@stanford.edu

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  • Holden H. Wu,

    1. Department of Radiological Sciences, University of California, Los Angeles, California, USA
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  • Nii Okai Addy,

    1. Department of Electrical Engineering, Magnetic Resonance Systems Research Laboratory, Stanford University, Stanford, California, USA
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  • Joseph Y. Cheng,

    1. Department of Electrical Engineering, Magnetic Resonance Systems Research Laboratory, Stanford University, Stanford, California, USA
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  • Phillip C. Yang,

    1. Department of Medicine, Stanford University, Stanford, California, USA
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  • Bob S. Hu,

    1. Department of Electrical Engineering, Magnetic Resonance Systems Research Laboratory, Stanford University, Stanford, California, USA
    2. Palo Alto Medical Foundation, Palo Alto, California, USA.
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  • Dwight G. Nishimura

    1. Department of Electrical Engineering, Magnetic Resonance Systems Research Laboratory, Stanford University, Stanford, California, USA
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Abstract

Purpose

To implement a nonrigid autofocus motion correction technique to improve respiratory motion correction of free-breathing whole-heart coronary magnetic resonance angiography acquisitions using an image-navigated 3D cones sequence.

Methods

2D image navigators acquired every heartbeat are used to measure superior-inferior, anterior-posterior, and right-left translation of the heart during a free-breathing coronary magnetic resonance angiography scan using a 3D cones readout trajectory. Various tidal respiratory motion patterns are modeled by independently scaling the three measured displacement trajectories. These scaled motion trajectories are used for 3D translational compensation of the acquired data, and a bank of motion-compensated images is reconstructed. From this bank, a gradient entropy focusing metric is used to generate a nonrigid motion-corrected image on a pixel-by-pixel basis. The performance of the autofocus motion correction technique is compared with rigid-body translational correction and no correction in phantom, volunteer, and patient studies.

Results

Nonrigid autofocus motion correction yields improved image quality compared to rigid-body-corrected images and uncorrected images. Quantitative vessel sharpness measurements indicate superiority of the proposed technique in 14 out of 15 coronary segments from three patient and two volunteer studies.

Conclusion

The proposed technique corrects nonrigid motion artifacts in free-breathing 3D cones acquisitions, improving image quality compared to rigid-body motion correction. Magn Reson Med 72:347–361, 2014. © 2013 Wiley Periodicals, Inc.

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