Predicting ventricular tachyarrhythmia in patients with systolic heart failure based on texture features of the gray zone from contrast-enhanced magnetic resonance imaging

Abstract

BackgroundPrevious research showed that gray zone detected by late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) imaging could help identify high-risk patients. In this study, we investigated whether LGE-CMR gray zone heterogeneity measured by image texture features could predict cardiovascular events in patients with heart failure (HF). MethodThis is a retrospective cohort study. Patients with systolic HF undergoing CMR imaging were enrolled. Cine and LGE images were analyzed to derive left ventricular (LV) function and scar characteristics. Entropy and uniformity of gray zones were derived by texture analysis. ResultsA total of 82 systolic HF patients were enrolled. After a median 1021 (25%–75% quartiles, 205–2066) days of follow-up, the entropy (0.60 ± 0.260 vs. 0.87 ± 0.28, p = 0.013) was significantly increased while the uniformity (0.68 ± 0.14 vs. 0.53±0.15, p = 0.016) was significantly decreased in patients with ventricular tachycardia or ventricular fibrillation (VT/VF). The percentage of core scar (21.9 ± 10.6 vs. 30.6 ± 10.4, p = 0.029) was higher in cardiac mortality group than survival group while the uniformity (0.55 ± 0.17 vs. 0.67 ± 0.14, p = 0.018) was lower in cardiac mortality group than survival group. A multivariate Cox regression model showed that higher percentage of gray zone area (HR = 8.805, 1.620−47.84, p = 0.045), higher entropy (>0.85) (HR = 1.391, 1.092−1.772, p = 0.024) and lower uniformity (≦0.54) (HR = 0.535, 0.340−0.842, p = 0.022) were associated with VT/VF attacks. Also, higher percentage of gray zone area (HR = 5.716, 1.379−23.68, p = 0.017), core scar zone (HR = 1.939, 1.056−3.561, p = 0.025), entropy (>0.85) (HR = 1.434, 1.076−1.911, p = 0.008) and lower uniformity (≦0.54) (HR = 0.513, 0.296−0.888, p = 0.009) were associated with cardiac mortality during follow-up. ConclusionsGray zone heterogeneity by texture analysis method could provide additional prognostic value to traditional LGE-CMR substrate analysis method.