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World J Cardiol. Nov 26, 2018; 10(11): 210-221
Published online Nov 26, 2018. doi: 10.4330/wjc.v10.i11.210
Clinical applications of feature-tracking cardiac magnetic resonance imaging
Daniele Muser, Simon A Castro, Pasquale Santangeli, Gaetano Nucifora
Daniele Muser, Simon A Castro, Pasquale Santangeli, Cardiovascular Division, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, United States
Daniele Muser, Cardiothoracic Department, University Hospital of Udine, Udine 33100, Italy
Gaetano Nucifora, NorthWest Cardiac Imaging Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester M23 9LT, United Kingdom
Gaetano Nucifora, Flinders University, Bedford Park, Adelaide 5042, South Australia, Australia
Author contributions: All the authors have contributed significantly to the submitted work.
Conflict-of-interest statement: None.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author to: Gaetano Nucifora, MD, PhD, Associate Professor, Doctor, NorthWest Cardiac Imaging Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester M23 9LT, United Kingdom. gaetano.nucifora@flinders.edu.au
Telephone: +44-73-93633651 Fax: +44-73-93633638
Received: July 16, 2018
Peer-review started: July 17, 2018
First decision: July 31, 2018
Revised: September 4, 2018
Accepted: October 9, 2018
Article in press: October 9, 2018
Published online: November 26, 2018
Processing time: 133 Days and 14.8 Hours
Abstract

Cardiovascular diseases represent the leading cause of mortality and morbidity in the western world. Assessment of cardiac function is pivotal for early diagnosis of primitive myocardial disorders, identification of cardiac involvement in systemic diseases, detection of drug-related cardiac toxicity as well as risk stratification and monitor of treatment effects in patients with heart failure of various etiology. Determination of ejection fraction with different imaging modalities currently represents the gold standard for evaluation of cardiac function. However, in the last few years, cardiovascular magnetic resonance feature tracking techniques has emerged as a more accurate tool for quantitative evaluation of cardiovascular function with several parameters including strain, strain-rate, torsion and mechanical dispersion. This imaging modality allows precise quantification of ventricular and atrial mechanics by directly evaluating myocardial fiber deformation. The purpose of this article is to review the basic principles, current clinical applications and future perspectives of cardiovascular magnetic resonance myocardial feature tracking, highlighting its prognostic implications.

Keywords: Left ventricular ejection fraction; Cardiac magnetic resonance; Cardiovascular disease; Strain; Feature-tracking

Core tip: Cardiac magnetic resonance feature tracking analysis is progressively establishing its role as an accurate tool to for quantitative evaluation of cardiovascular function by directly evaluating myocardial fiber deformation. Feature-tracking derived strain parameters are able to identify subtle myocardial abnormalities before overt clinical manifestation thus allowing early diagnosis of primitive cardiomyopathies, identification of cardiac involvement in systemic diseases, detection of drug-related cardiac toxicity as well as risk stratification and monitor of treatment effects in patients with heart failure of various etiology. The present article summarizes the basic principles, current applications and future perspectives of cardiovascular magnetic resonance myocardial feature tracking.