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Free-running SIMilarity-Based Angiography (SIMBA) for simplified anatomical MR imaging of the heart (2007.06544v1)

Published 13 Jul 2020 in eess.IV, cs.CV, and physics.med-ph

Abstract: Purpose: Whole-heart MRA techniques typically target pre-determined motion states and address cardiac and respiratory dynamics independently. We propose a novel fast reconstruction algorithm, applicable to ungated free-running sequences, that leverages inherent similarities in the acquired data to avoid such physiological constraints. Theory and Methods: The proposed SIMilarity-Based Angiography (SIMBA) method clusters the continuously acquired k-space data in order to find a motion-consistent subset that can be reconstructed into a motion-suppressed whole-heart MRA. Free-running 3D radial datasets from six ferumoxytol-enhanced scans of pediatric cardiac patients and twelve non-contrast scans of healthy volunteers were reconstructed with a non-motion-suppressed regridding of all the acquired data (All Data), our proposed SIMBA method, and a previously published free-running framework (FRF) that uses cardiac and respiratory self-gating and compressed sensing. Images were compared for blood-myocardium interface sharpness, contrast ratio, and visibility of coronary artery ostia. Results: Both the fast SIMBA reconstruction (~20s) and the FRF provided significantly higher blood-myocardium sharpness than All Data (P<0.001). No significant difference was observed among the former two. Significantly higher blood-myocardium contrast ratio was obtained with SIMBA compared to All Data and FRF (P<0.01). More coronary ostia could be visualized with both SIMBA and FRF than with All Data (All Data: 4/36, SIMBA: 30/36, FRF: 33/36, both P<0.001) but no significant difference was found between the first two. Conclusion: The combination of free-running sequences and the fast SIMBA reconstruction, which operates without a priori assumptions related to physiological motion, forms a simple workflow for obtaining whole-heart MRA with sharp anatomical structures.

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Authors (10)
  1. John Heerfordt (2 papers)
  2. Kevin K. Whitehead (1 paper)
  3. Jessica A. M. Bastiaansen (5 papers)
  4. Lorenzo Di Sopra (2 papers)
  5. Christopher W. Roy (5 papers)
  6. Bastien Milani (3 papers)
  7. Mark A. Fogel (2 papers)
  8. Matthias Stuber (15 papers)
  9. Davide Piccini (9 papers)
  10. Jérôme Yerly (5 papers)

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