Similarity-driven multi-dimensional binning algorithm (SIMBA) for free-running motion-suppressed whole-heart MRA

John Heerfordt; Kevin K Whitehead; Jessica A M Bastiaansen; Lorenzo Di Sopra; Christopher W Roy; Jérôme Yerly; Bastien Milani; Mark A Fogel; Matthias Stuber; Davide Piccini

doi:10.1002/mrm.28713

Similarity-driven multi-dimensional binning algorithm (SIMBA) for free-running motion-suppressed whole-heart MRA

Magn Reson Med. 2021 Jul;86(1):213-229. doi: 10.1002/mrm.28713. Epub 2021 Feb 24.

Authors

John Heerfordt^{1

2}, Kevin K Whitehead³, Jessica A M Bastiaansen¹, Lorenzo Di Sopra¹, Christopher W Roy¹, Jérôme Yerly^{1

4}, Bastien Milani¹, Mark A Fogel³, Matthias Stuber^{1

4}, Davide Piccini^{1

2}

Affiliations

¹ Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
² Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.
³ Division of Cardiology, Department of Pediatrics, The Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
⁴ Center for Biomedical Imaging, Lausanne, Switzerland.

PMID: 33624348
DOI: 10.1002/mrm.28713

Abstract

Purpose: Whole-heart MRA techniques typically target predetermined motion states, address cardiac and respiratory dynamics independently, and require either complex planning or computationally demanding reconstructions. In contrast, we developed a fast data-driven reconstruction algorithm with minimal physiological assumptions and compatibility with ungated free-running sequences.

Theory and methods: We propose a similarity-driven multi-dimensional binning algorithm (SIMBA) that clusters continuously acquired k-space data to find a motion-consistent subset for whole-heart MRA reconstruction. Free-running 3D radial data sets from 12 non-contrast-enhanced scans of healthy volunteers and six ferumoxytol-enhanced scans of pediatric cardiac patients were reconstructed with non-motion-suppressed regridding of all the acquired data ("All Data"), with SIMBA, and with a previously published free-running framework (FRF) that uses cardiac and respiratory self-gating and compressed sensing. Images were compared for blood-myocardium sharpness and contrast ratio, visibility of coronary artery ostia, and right coronary artery sharpness.

Results: Both the 20-second SIMBA reconstruction and FRF provided significantly higher blood-myocardium sharpness than All Data in both patients and volunteers (P < .05). The SIMBA reconstruction provided significantly sharper blood-myocardium interfaces than FRF in volunteers (P < .001) and higher blood-myocardium contrast ratio than All Data and FRF, both in volunteers and patients (P < .05). Significantly more ostia could be visualized with both SIMBA (31 of 36) and FRF (34 of 36) than with All Data (4 of 36) (P < .001). Inferior right coronary artery sharpness using SIMBA versus FRF was observed (volunteers: SIMBA 36.1 ± 8.1%, FRF 40.4 ± 8.9%; patients: SIMBA 35.9 ± 7.7%, FRF 40.3 ± 6.1%, P = not significant).

Conclusion: The SIMBA technique enabled a fast, data-driven reconstruction of free-running whole-heart MRA with image quality superior to All Data and similar to the more time-consuming FRF reconstruction.

Keywords: 3D radial; clustering; ferumoxytol; free-running; noncontrast MRA; whole heart.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Child
Coronary Vessels / diagnostic imaging
Humans
Imaging, Three-Dimensional*
Magnetic Resonance Angiography*
Motion