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Left ventricular myocardial deformation measurements by magnetic resonance Tissue Tracking agrees with tagging (HARP) in healthy volunteers
© Mukai et al. 2016
- Published: 27 January 2016
- Congenital Heart Disease
- Cardiovascular Magnetic Resonance
- Steady State Free Precession
- Short Axis Image
- Cardiovascular Magnetic Resonance Image
Left ventricular myocardial strain has been described as a potentially useful technique for evaluation and risk stratification of a range of acquired and congenital heart diseases. Tagged acquisition by cardiac MRI has been considered the reference standard for determining myocardial strain; however, this method can be time consuming and the tagged lines may not be visible throughout the cardiac cycle. Tissue Tracking software (Circle Cardiovascular Imaging®) is a post-processing method which allows measurements of myocardial strain based on cine cardiovascular magnetic resonance images without the need for additional sequences. Augustine et al. (JCMR 2013) have previously reported reasonable agreement between Feature Tracking (Tom Tec®) measurements for circumferential strain and tagging. We aimed to perform a similar comparison between Tissue Tracking software and tagging on a small cohort of normal volunteers.
Cardiac MRI studies were performed with a 1.5 T unit (Achieva, Philips Medical Systems) on 7 normal volunteers. Short-axis tagged MR images of the left ventricle were analyzed using HARP software (Diagnosoft, Cary, NC) by the same observer, blinded to results of the alternate method. Steady state free precession (SSFP) cine images were analyzed with Tissue Tracking software (Circle Cardiovascular Imaging®) by two observers in consensus. The 2D peak circumferential strain (%) obtained by both techniques were compared using Bland Altman analysis for each of the 16 cardiac segments based on the American Heart Association classification for short axis images.
Tissue Tracking software provides a good surrogate for calculating 2D peak circumferential strain (%). A larger cohort is needed to further validate this new capability.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.