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Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity

Research output: Contribution to journalArticlepeer-review

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Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity. / Gould, Justin; Porter, Bradley; Claridge, Simon et al.

In: Heart Rhythm, Vol. 16, No. 8, 01.08.2019, p. 1242-1250.

Research output: Contribution to journalArticlepeer-review

Harvard

Gould, J, Porter, B, Claridge, S, Chen, Z, Sieniewicz, BJ, Sidhu, BS, Niederer, S, Bishop, MJ, Murgatroyd, F, Ganeshan, B, Carr-White, G, Razavi, R, Chiribiri, A & Rinaldi, CA 2019, 'Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity', Heart Rhythm, vol. 16, no. 8, pp. 1242-1250. https://doi.org/10.1016/j.hrthm.2019.03.001

APA

Gould, J., Porter, B., Claridge, S., Chen, Z., Sieniewicz, B. J., Sidhu, B. S., Niederer, S., Bishop, M. J., Murgatroyd, F., Ganeshan, B., Carr-White, G., Razavi, R., Chiribiri, A., & Rinaldi, C. A. (2019). Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity. Heart Rhythm, 16(8), 1242-1250. https://doi.org/10.1016/j.hrthm.2019.03.001

Vancouver

Gould J, Porter B, Claridge S, Chen Z, Sieniewicz BJ, Sidhu BS et al. Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity. Heart Rhythm. 2019 Aug 1;16(8):1242-1250. https://doi.org/10.1016/j.hrthm.2019.03.001

Author

Gould, Justin ; Porter, Bradley ; Claridge, Simon et al. / Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity. In: Heart Rhythm. 2019 ; Vol. 16, No. 8. pp. 1242-1250.

Bibtex Download

@article{aad5f9e83e1b4dea9af8161594a78362,
title = "Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity",
abstract = "BACKGROUND: Risk stratification of ventricular arrhythmia (VA) remains complex in both ischemic and non-ischemic populations.OBJECTIVE: To determine whether scar heterogeneity, quantified by mean entropy, predicts appropriate ICD therapy. We hypothesize that higher mean entropy calculated from cardiac magnetic resonance texture analysis (CMR-TA) will predict appropriate ICD therapy.METHODS: Consecutive patients underwent CMR imaging prior to 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 endpoint was appropriate ICD therapy.RESULTS: 114 patients underwent CMR-TA (ICM n=70, NICM n=44) with median follow-up of 955 [IQR 691-1185] days. Mean entropy was significantly higher in the ICM group (5.7±0.7 vs. 5.5±0.7, P=0.045). Overall, 33 patients received appropriate ICD therapy. Using optimized cut-offs from ROC curves, Kaplan-Meier survival analysis demonstrated time until first appropriate therapy was significantly shorter in the high mean entropy group (P=0.003). Multivariable analysis showed mean entropy was the sole predictor of appropriate ICD therapy (HR 1.882, 95% CI 1.083-3.271, P=0.025). 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 VA and risk-stratifying patients for ICD implantation.",
keywords = "Entropy, Late gadolinium enhancement, Risk stratification of ventricular arrhythmia, Scar heterogeneity, Ventricular arrhythmia",
author = "Justin Gould and Bradley Porter and Simon Claridge and Zhong Chen and Sieniewicz, {Benjamin J} and Sidhu, {Baldeep S} and Steven Niederer and Bishop, {Martin J} and Francis Murgatroyd and Balaji Ganeshan and Gerald Carr-White and Reza Razavi and Amedeo Chiribiri and Rinaldi, {Christopher A}",
year = "2019",
month = aug,
day = "1",
doi = "10.1016/j.hrthm.2019.03.001",
language = "English",
volume = "16",
pages = "1242--1250",
journal = "Heart rhythm : the official journal of the Heart Rhythm Society",
issn = "1547-5271",
publisher = "Elsevier",
number = "8",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity

AU - Gould, Justin

AU - Porter, Bradley

AU - Claridge, Simon

AU - Chen, Zhong

AU - Sieniewicz, Benjamin J

AU - Sidhu, Baldeep S

AU - Niederer, Steven

AU - Bishop, Martin J

AU - Murgatroyd, Francis

AU - Ganeshan, Balaji

AU - Carr-White, Gerald

AU - Razavi, Reza

AU - Chiribiri, Amedeo

AU - Rinaldi, Christopher A

PY - 2019/8/1

Y1 - 2019/8/1

N2 - BACKGROUND: Risk stratification of ventricular arrhythmia (VA) remains complex in both ischemic and non-ischemic populations.OBJECTIVE: To determine whether scar heterogeneity, quantified by mean entropy, predicts appropriate ICD therapy. We hypothesize that higher mean entropy calculated from cardiac magnetic resonance texture analysis (CMR-TA) will predict appropriate ICD therapy.METHODS: Consecutive patients underwent CMR imaging prior to 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 endpoint was appropriate ICD therapy.RESULTS: 114 patients underwent CMR-TA (ICM n=70, NICM n=44) with median follow-up of 955 [IQR 691-1185] days. Mean entropy was significantly higher in the ICM group (5.7±0.7 vs. 5.5±0.7, P=0.045). Overall, 33 patients received appropriate ICD therapy. Using optimized cut-offs from ROC curves, Kaplan-Meier survival analysis demonstrated time until first appropriate therapy was significantly shorter in the high mean entropy group (P=0.003). Multivariable analysis showed mean entropy was the sole predictor of appropriate ICD therapy (HR 1.882, 95% CI 1.083-3.271, P=0.025). 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 VA and risk-stratifying patients for ICD implantation.

AB - BACKGROUND: Risk stratification of ventricular arrhythmia (VA) remains complex in both ischemic and non-ischemic populations.OBJECTIVE: To determine whether scar heterogeneity, quantified by mean entropy, predicts appropriate ICD therapy. We hypothesize that higher mean entropy calculated from cardiac magnetic resonance texture analysis (CMR-TA) will predict appropriate ICD therapy.METHODS: Consecutive patients underwent CMR imaging prior to 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 endpoint was appropriate ICD therapy.RESULTS: 114 patients underwent CMR-TA (ICM n=70, NICM n=44) with median follow-up of 955 [IQR 691-1185] days. Mean entropy was significantly higher in the ICM group (5.7±0.7 vs. 5.5±0.7, P=0.045). Overall, 33 patients received appropriate ICD therapy. Using optimized cut-offs from ROC curves, Kaplan-Meier survival analysis demonstrated time until first appropriate therapy was significantly shorter in the high mean entropy group (P=0.003). Multivariable analysis showed mean entropy was the sole predictor of appropriate ICD therapy (HR 1.882, 95% CI 1.083-3.271, P=0.025). 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 VA and risk-stratifying patients for ICD implantation.

KW - Entropy

KW - Late gadolinium enhancement

KW - Risk stratification of ventricular arrhythmia

KW - Scar heterogeneity

KW - Ventricular arrhythmia

UR - http://www.scopus.com/inward/record.url?scp=85068991978&partnerID=8YFLogxK

U2 - 10.1016/j.hrthm.2019.03.001

DO - 10.1016/j.hrthm.2019.03.001

M3 - Article

C2 - 30849532

VL - 16

SP - 1242

EP - 1250

JO - Heart rhythm : the official journal of the Heart Rhythm Society

JF - Heart rhythm : the official journal of the Heart Rhythm Society

SN - 1547-5271

IS - 8

ER -

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