Real-time exercise stress cardiac MRI with Fourier-series reconstruction from golden-angle radial data
Magnetic resonance imaging (MRI) can measure cardiac response to exercise stress for evaluating and managing heart patients in the practice of clinical cardiology. However, exercise stress cardiac MRI have been clinically limited by the ability of available MRI techniques to quantitatively measure f...
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Published in | Magnetic resonance imaging Vol. 75; pp. 89 - 99 |
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Main Authors | , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier Inc
01.01.2021
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Subjects | |
Online Access | Get full text |
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Summary: | Magnetic resonance imaging (MRI) can measure cardiac response to exercise stress for evaluating and managing heart patients in the practice of clinical cardiology. However, exercise stress cardiac MRI have been clinically limited by the ability of available MRI techniques to quantitatively measure fast and unstable cardiac dynamics during exercise. The presented work is to develop a new real-time MRI technique for improved quantitative performance of exercise stress cardiac MRI. This technique seeks to represent real-time cardiac images as a sparse Fourier-series along the time. With golden-angle radial acquisition, parallel imaging and compressed sensing can be integrated into a linear system of equations for resolving Fourier coefficients that are in turn used to generate real-time cardiac images from the Fourier-series representation. Fourier-series reconstruction from golden-angle radial data can effectively address data insufficiency due to MRI speed limitation, providing a real-time approach to exercise stress cardiac MRI. To demonstrate the feasibility, an exercise stress cardiac MRI experiment was run to investigate biventricular response to in-scanner biking exercise in a cohort of sixteen healthy volunteers. It was found that Fourier-series reconstruction from golden-angle radial data effectively detected exercise-induced increase in stroke volume and ejection fraction in a healthy heart. The presented work will improve the applications of exercise stress cardiac MRI in the practice of clinical cardiology. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Pengyue Zhang, Shams Rashid, Wenhui Li: Investigation, Data curation, Software, Writing-Original draft preparation. Elizabeth Haag: Project administration. Maries Grgas: Resources. J. Jane Cao: Writing- Reviewing and Editing, Resources, Project administration. Yang J. Cheng, William Schapiro, Kathleen Gliganic, Ann-Marie Yamashita: Investigation, Visualization. Yu Y. Li: Conceptualization, Methodology, Validation, Software, Investigation, Formal analysis, Writing-Original draft, Data Curation, Visualization, Supervision, Funding acquisition |
ISSN: | 0730-725X 1873-5894 |
DOI: | 10.1016/j.mri.2020.10.010 |