Cardiovascular magnetic resonance imaging: Principles and advanced techniques
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Date
2025
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Abstract
Cardiovascular magnetic resonance (CMR) imaging is an established non-invasive tool for the assessment of cardiovascular diseases, which are the leading cause of death globally. CMR provides dynamic and static multi-contrast and multi-parametric images, including cine for functional evaluation, contrast-enhanced imaging and parametric mapping for tissue characterization, and MR angiography for the assessment of the aortic, coronary and pulmonary circulation. However, clinical CMR imaging sequences still have some limitations such as the requirement for multiple breath-holds, incomplete spatial coverage, complex planning and acquisition, low scan efficiency and long scan times. To address these challenges, novel techniques have been developed during the last two decades, focusing on automated planning and acquisition timing, improved respiratory and cardiac motion handling strategies, image acceleration algorithms employing undersampled reconstruction, all-in-one imaging techniques that can acquire multiple contrast/parameters in a single scan, deep learning based methods applied along the entire CMR imaging pipeline, as well as imaging at high- and low-field strengths. In this article, we aim to provide a comprehensive review of CMR imaging, covering both established and emerging techniques, to give an overview of the present and future applications of CMR.
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Keywords
All-in-one imaging, Cardiovascular magnetic resonance, Deep learning, High-field and low-field, Image acceleration, Motion correction