Abstract

Doc number: 94

Abstract

Background: Cardiovascular magnetic resonance using displacement encoding with stimulated echoes (DENSE) is capable of assessing advanced measures of cardiac mechanics such as strain and torsion. A potential hurdle to widespread clinical adoption of DENSE is the time required to manually segment the myocardium during post-processing of the images. To overcome this hurdle, we proposed a radical approach in which only three contours per image slice are required for post-processing (instead of the typical 30-40 contours per image slice). We hypothesized that peak left ventricular circumferential, longitudinal and radial strains and torsion could be accurately quantified using this simplified analysis.

Methods and Results: We tested our hypothesis on a large multi-institutional dataset consisting of 541 DENSE image slices from 135 mice and 234 DENSE image slices from 62 humans. We compared measures of cardiac mechanics derived from the simplified post-processing to those derived from original post-processing utilizing the full set of 30-40 manually-defined contours per image slice. Accuracy was assessed with Bland-Altman limits of agreement and summarized with a modified coefficient of variation. The simplified technique showed high accuracy with all coefficients of variation less than 10% in humans and 6% in mice. The accuracy of the simplified technique was also superior to two previously published semi-automated analysis techniques for DENSE post-processing.

Conclusions: Accurate measures of cardiac mechanics can be derived from DENSE cardiac magnetic resonance in both humans and mice using a simplified technique to reduce post-processing time by approximately 94%. These findings demonstrate that quantifying cardiac mechanics from DENSE data is simple enough to be integrated into the clinical workflow.

Details

Title
Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics
Author
Suever, Jonathan D; Wehner, Gregory J; Haggerty, Christopher M; Jing, Linyuan; Hamlet, Sean M; Binkley, Cassi M; Kramer, Sage P; Mattingly, Andrea C; Powell, David K; Bilchick, Kenneth C; Epstein, Frederick H; Fornwalt, Brandon K
Pages
94
Publication year
2014
Publication date
2014
Publisher
BioMed Central
ISSN
10976647
e-ISSN
1532429X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1628575126
Copyright
© 2014 Suever et al.; licensee 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 credited. 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.