Key result
Feature-tracking CMR showed significantly lower RV global longitudinal strain in ARVC patients (-17±5%) compared to RV outflow tract arrhythmia patients (-26±6%) and controls (-29±6%; P<0.001).
Why the study?
Does feature-tracking CMR analysis of RV strain and dyssynchrony improve the identification and quantification of RV dysfunction in patients with ARVC compared to conventional cine CMR?
Case-Control (n=96)
Does feature-tracking CMR analysis of RV strain and dyssynchrony improve the identification and quantification of RV dysfunction in patients with ARVC compared to conventional cine CMR?
Absolute Event Rate: -17% vs -29%
p-value: p=<0.001
Feature-tracking CMR strain analysis provides incremental diagnostic value over conventional cine CMR by objectively quantifying RV dysfunction and identifying ARVC patients who lack major conventional imaging criteria.
RV strain by feature-tracking CMR may aid ARVC detection beyond conventional imaging; leaves open whether it improves outcomes or risk stratification.
BACKGROUND: Analysis of right ventricular (RV) regional dysfunction by cardiac magnetic resonance (CMR) imaging in arrhythmogenic RV cardiomyopathy (ARVC) may be inadequate because of the complex contraction pattern of the RV. Aim of this study was to determine the use of RV strain and dyssynchrony assessment in ARVC using feature-tracking CMR analysis. METHODS AND RESULTS: Thirty-two consecutive patients with ARVC referred to CMR imaging were included. Thirty-two patients with idiopathic RV outflow tract arrhythmias and 32 control subjects, matched for age and sex to the ARVC group, were included for comparison purpose. CMR imaging was performed to assess biventricular function; feature-tracking analysis was applied to the cine CMR images to assess regional and global longitudinal, circumferential, and radial RV strains and RV dyssynchrony (defined as the SD of the time-to-peak strain of the RV segments). RV global longitudinal strain (-17±5% versus -26±6% versus -29±6%; P<0.001), global circumferential strain (-9±4% versus -12±4% versus -13±5%; P=0.001), and global radial strain (18 [12-26]% versus 22 [15-32]% versus 27 [20-39]%; P=0.015) were significantly lower and SD of the time-to-peak RV strain in all 3 directions were significantly higher among patients with ARVC compared with patients with RV outflow tract arrhythmias and controls. RV global longitudinal strain >-23.2%, SD of the time-to-peak RV longitudinal strain >113.1 ms, and SD of the time-to-peak RV circumferential strain >177.1 ms allowed correct identification of 88%, 75%, and 63% of ARVC patients with no or only minor CMR criteria for ARVC diagnosis. CONCLUSIONS: Strain analysis by feature-tracking CMR helps to objectively quantify global and regional RV dysfunction and RV dyssynchrony in patients with ARVC and provides incremental value over conventional cine CMR imaging.
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Prati et al. (2015) conducted a case-control in Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) (n=96). Feature-tracking CMR analysis vs. RV outflow tract arrhythmias and healthy controls was evaluated on RV global longitudinal strain (p=<0.001). Feature-tracking CMR showed significantly lower RV global longitudinal strain in ARVC patients (-17±5%) compared to RV outflow tract arrhythmia patients (-26±6%) and controls (-29±6%; P<0.001).
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