Non-contrast coronary magnetic resonance angiography: current frontiers and future horizons
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REVIEW
Non‑contrast coronary magnetic resonance angiography: current frontiers and future horizons Yoko Kato1 · Bharath Ambale‑Venkatesh2 · Yoshimori Kassai3 · Larry Kasuboski4 · Joanne Schuijf4 · Karan Kapoor1 · Shelton Caruthers4 · Joao A. C. Lima1 Received: 4 October 2019 / Revised: 22 January 2020 / Accepted: 29 January 2020 © The Author(s) 2020
Abstract Coronary magnetic resonance angiography (coronary MRA) is advantageous in its ability to assess coronary artery morphology and function without ionizing radiation or contrast media. However, technical limitations including reduced spatial resolution, long acquisition times, and low signal-to-noise ratios prevent it from clinical routine utilization. Nonetheless, each of these limitations can be specifically addressed by a combination of novel technologies including super-resolution imaging, compressed sensing, and deep-learning reconstruction. In this paper, we first review the current clinical use and motivations for non-contrast coronary MRA, discuss currently available coronary MRA techniques, and highlight current technical developments that hold unique potential to optimize coronary MRA image acquisition and post-processing. In the final section, we examine the various research-based coronary MRA methods and metrics that can be leveraged to assess coronary stenosis severity, physiological function, and atherosclerotic plaque characterization. We specifically discuss how such technologies may contribute to the clinical translation of coronary MRA into a robust modality for routine clinical use. Keywords Magnetic resonance coronary angiography · Image acceleration technique · Image denoising · Review article Abbreviations MRA Magnetic resonance angiography CAD Coronary artery disease CTA Computed tomography angiography CAG Coronary angiography LGE Late gadolinium enhancement ECG Electrocardiography SSFP Steady-state free precession RCA Right coronary artery SNR Signal-to-noise ratio CNR Contrast-to-noise ratio bSSFP Balanced steady-state free precession imaging
* Joao A. C. Lima [email protected] 1
Division of Cardiology, Johns Hopkins University School of Medicine, 600 N Wolfe St, Blalock 524, Baltimore, MD 21287‑0409, USA
2
Division of Radiology, Johns Hopkins University, Baltimore, MD, USA
3
Canon Medical Systems Corporation, Otawara, Japan
4
Canon Medical Research USA, Inc., Cleveland, OH, USA
FLASH Fast low angle shots MRI Magnetic resonance imaging SR Super-resolution BM3D Block matching and 3-D filtering TNRD Trainable nonlinear reaction diffusion DnCNNs Denoising convolutional neural networks PI Parallel imaging CS Compressed sensing SENSE Sensitivity encoding iGRASP Iterative golden-angle radial sparse parallel MRI SPIRiT Self-consistent parallel imaging reconstruction ESPIRiT Eigenvector maps self-consistent parallel imaging reconstruction tGA Tiny golden radial DLR Deep learning reconstruction XD-GRASP Extra-dimensional GRASP PC Phase contrast CBF Coronary blood flow LAD Left anterior descending L
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