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Respiratory optimized data selection for more resilient self-navigated whole-heart coronary MR angiography

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Abstract

Objectives

Our objective was to test a data-exclusion strategy for respiratory motion suppression by retrospectively eliminating data acquired at extreme respiratory positions for improved coronary vessel sharpness (VS) of 1-D self-navigated 3-D radial whole-heart coronary angiography acquisitions.

Materials and methods

3-D radial self-navigated acquisitions were performed on a 1.5T scanner in volunteers during free-breathing (n = 8), in coached volunteers (n = 13) who were asked to breathe in a controlled manner to mimic cardiovascular patients presenting with Cheyne-Stokes breathing, and in free-breathing patients (n = 20). Data collected during large respiratory excursions were gradually excluded retrospectively from the reconstruction yielding 14 data sets per subject on average. The impact on VS, blood and myocardium signal-to-noise and contrast-to-noise was measured. From these results, two retrospective gating strategies were defined for the k-line elimination procedure and tested in all groups.

Results

Maximum right coronary artery VS improvement was +7.4 and +2.7% in coached volunteers and patients (P < 0.0001 for both), respectively, and 1.6% for the free-breathing volunteers (P = 0.13). The first gating strategy was defined as a fixed undersampling factor of 5 compared to a fully sampled 3-D radial acquisition, yielding significant VS improvement in coached volunteers and patients while myocardial signal-to-noise decreased in these. The second strategy was defined as a fixed gating window of 5.7 mm, leading to similar improvements.

Conclusion

The presented strategies improve image quality of self-navigated acquisitions by retrospectively excluding data collected during end-inspiration.

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Acknowledgements

This work was supported in part by the Grant No. 320030_143923 from the Swiss National Science Foundation (SNF).

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Authors and Affiliations

  1. Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland

    Jerome Chaptinel, Davide Piccini, Gabriele Bonanno, Simone Coppo & Matthias Stuber

  2. Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland

    Davide Piccini

  3. Division of Cardiology and Cardiac MR Center, University Hospital of Lausanne (CHUV), Lausanne, Switzerland

    Pierre Monney & Juerg Schwitter

  4. Center for Biomedical Imaging (CIBM), Lausanne, Switzerland

    Matthias Stuber

Authors
  1. Jerome Chaptinel
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  2. Davide Piccini
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  3. Gabriele Bonanno
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  4. Simone Coppo
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  5. Pierre Monney
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  6. Matthias Stuber
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  7. Juerg Schwitter
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Corresponding author

Correspondence to Juerg Schwitter.

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Conflict of interest

D. Piccini is an employee of Siemens Healthcare.

Ethical standard

All experiments performed were in accordance with the ethical standards of the local ethics committee. Informed consent was obtained from all individual participants included in the study.

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Chaptinel, J., Piccini, D., Bonanno, G. et al. Respiratory optimized data selection for more resilient self-navigated whole-heart coronary MR angiography. Magn Reson Mater Phy 30, 215–225 (2017). https://doi.org/10.1007/s10334-016-0598-4

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  • DOI: https://doi.org/10.1007/s10334-016-0598-4

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