Gould, J;
Porter, B;
Claridge, S;
Chen, Z;
Sieniewicz, BJ;
Sidhu, BS;
Niederer, S;
... Rinaldi, CA; + view all
(2019)
Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity.
Heart Rhythm
, 16
(8)
pp. 1242-1250.
10.1016/j.hrthm.2019.03.001.
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Ganeshan_Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity_UnifiedAAM.pdf - Accepted Version Download (2MB) | Preview |
Abstract
BACKGROUND: Risk stratification of ventricular arrhythmia remains complex in both ischemic and nonischemic populations. OBJECTIVE: The purpose of this study was to determine whether scar heterogeneity, quantified by mean entropy, predicts appropriate implantable cardioverter-defibrillator (ICD) therapy. We hypothesized that higher mean entropy calculated from cardiac magnetic resonance texture analysis (CMR-TA) will predict appropriate ICD therapy. METHODS: Consecutive patients underwent CMR imaging before ICD implantation. Short-axis left ventricular scar was manually segmented. CMR-TA was performed using a Laplacian filter to extract and augment image features to create a scar texture from which histogram analysis of pixel intensity was used to calculate mean entropy. The primary end point was appropriate ICD therapy. RESULTS: A total of 114 patients underwent CMR-TA (ischemic cardiomyopathy [ICM]: n = 70; nonischemic cardiomyopathy [NICM]: n = 44) with a median follow-up of 955 days (interquartile range 691-1185 days). Mean entropy was significantly higher in the ICM group (5.7 ± 0.7 vs 5.5 ± 0.7; P= .045). Overall, 33 patients received appropriate ICD therapy. Using optimized cutoff values from receiver operating characteristic curves, Kaplan-Meier survival analysis demonstrated time until first appropriate therapy was significantly shorter in the high mean entropy group (P = .003). Multivariable analysis showed that mean entropy was the sole predictor of appropriate ICD therapy (hazard ratio 1.882; 95% confidence interval 1.083-3.271; P = .025). In the ICM group, mean entropy remained an independent predictor of appropriate ICD therapy, whereas in the NICM group, T1-native was the sole predictor. CONCLUSION: Scar heterogeneity, quantified by mean entropy using CMR-TA, was an independent predictor of appropriate ICD therapy in the mixed cardiomyopathy cohort and ICM-only group, suggesting a potential role for CMR-TA in predicting ventricular arrhythmia and risk-stratifying patients for ICD implantation.
| Type: | Article |
|---|---|
| Title: | Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.hrthm.2019.03.001 |
| Publisher version: | https://doi.org/10.1016/j.hrthm.2019.03.001 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Entropy, ICD risk stratification, Late gadolinium enhancement, Scar heterogeneity, Ventricular arrhythmia |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Department of Imaging |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10067610 |
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