Special Issue "Trends and Prospects in Cardiac MRI"
Deadline for manuscript submissions: 18 March 2024 | Viewed by 1331
Over the last 15 years, cardiovascular magnetic resonance (CMR) imaging has progressively evolved to become an indispensable tool in cardiology. It is the gold standard for assessing myocardial function, volumes, and scarring, and has become an indispensable tool in the evaluation of congenital heart disease, heart failure, cardiac masses, pericardial disease, and coronary artery disease. Additionally, CMR imaging is unique in its comprehensive tissue characterization, including the assessment of myocardial edema, myocardial siderosis, myocardial perfusion, and diffuse myocardial fibrosis. Recent innovations in CMR scanner technology and parallel imaging techniques have facilitated the generation of T1 and T2 parametric mapping in order to explore tissue characteristics. In addition, the emergence of strain imaging has enabled cardiologists to evaluate cardiac function beyond conventional metrics and progress in computer processing capabilities, and cloud infrastructure has supported the growth of artificial intelligence in CMR imaging. Accordingly, this Special Issue encourages scientists to present their new findings (from well-established clinical indications to new scenarios), discuss future roles and potential controversies, and identify challenges and questions for future research. We encourage researchers to submit their contributions, either in the form of original research, review articles, or meta-analysis.
Dr. Paola Gargiulo
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- cardiac magnetic resonance
- heart failure
- myocardial fibrosis
- tissue composition
- hybrid imaging
- artificial intelligence