- Poster presentation
- Open Access
Improved prediction of adverse events in hypertrophic cardiomyopathy with quantitative late gadolinium enhancement and myocardial strain
© Brahmanandam et al. 2016
- Published: 27 January 2016
- Late Gadolinium Enhancement
- Radial Strain
- Peak Systolic Strain
- Maximum Wall Thickness
- SSFP Cine
Risk prediction for sudden death remains imperfect in HCM. We compared CMR-derived LV fibrosis and strain measures to outcomes in a cohort of HCM patients.
Consecutive patients undergoing CMR on identical 1.5 Tesla scanners to evaluate HCM were identified at a tertiary referral center. LV fibrosis was measured using a previously validated iterative technique (cmr42, Circle Cardiovascular Imaging) from LGE images acquired using standard inversion recovery techniques. LV volume, mass and EF were assessed from contiguous short axis SSFP cines. LV circumferential and radial strain were measured from a single mid-SAX SSFP cine (Trufi Strain, Siemens). Sustained VT/VF, ICD placement, appropriate ICD therapy, CHF admission, septal reduction and/or death comprised the Event Group, n = 13 and those without the No Event Group, n = 34. Baseline characteristics were reported as mean ± SD for continuous variables and frequencies for categorical variables with group differences examined by t and χ2 tests. A Shapiro-Wilk test was used to evaluate normality and a Wilcoxon-Kruskal-Wallis test was used for non normal distributions. Linear regression analysis evaluated the independent association of predictive variables and receiver operator curves were generated (JMP, SAS).
LV strain, fibrosis burden and wall thickness contribute to risk stratification in HCM beyond clinical predictors. These findings support further studies to develop multivariable prediction models that incorporate multiple CMR measures.
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.