Background Analysis of regional wall motion of the right ventricle (RV) is primarily qualitative with large interobserver variation in clinical practice. Thus, the purpose of this study was to use feature tracking to analyze regional wall motion abnormalities in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC). Methods We enrolled 110 subjects (39 overt ARVC [mutation+/phenotype+] (35.5%), 40 preclinical ARVC [mutation+/phenotype-] (36.3%), and 31 control subjects (28.2%)). Cine steady state free precession cardiac MR was performed with temporal resolution ≤40 ms in the horizontal long axis (HLA), axial, and short axis directions. Regional strain was analyzed using feature tracking software and reproducibility was assessed by means of intraclass correlation coefficient. Dunnett's test was used in univariate analysis for comparisons to control subjects; cumulative odds logistic regression was used for minimally and fully adjusted multivariate models. Results Strain was significantly impaired in overt ARVC compared with control subjects both globally (P < 0.01) and regionally (all segments of HLA view, P < 0.01). In the HLA view, regional reproducibility was excellent within (intraclass correlation coefficient [ICC] = 0.81) and moderate between (ICC = 0.62) observers. Using a threshold of -31% subtricuspid strain in the HLA view, the sensitivity and specificity for overt ARVC were 75.0% and 78.2%, respectively. In multivariable analysis involving all three groups, subtricuspid strain less than -31% (beta = 1.38; P = 0.014) and RV end diastolic volume index (beta = 0.06; P = 0.001) were significant predictors of disease presence. Conclusion RV strain can be reproducibly assessed with MR feature tracking, and regional strain is abnormal in overt ARVC compared with control subjects. J. Magn. Reson.
- cardiac magnetic resonance (MR)
- magnetic resonance imaging (MRI)
- strain, feature tracking, arrhythmogenic right ventricular cardiomyopathy (ARVC)
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging