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

Justin Gould; Bradley Porter; Simon Claridge; Zhong Chen; Benjamin J Sieniewicz; Baldeep S Sidhu; Steven Niederer; Martin J Bishop; Francis Murgatroyd; Balaji Ganeshan; Gerald Carr-White; Reza Razavi; Amedeo Chiribiri; Christopher A Rinaldi

doi:10.1016/j.hrthm.2019.03.001

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

Justin Gould^*, Bradley Porter, Simon Claridge, Zhong Chen, Benjamin J Sieniewicz, Baldeep S Sidhu, Steven Niederer, Martin J Bishop, Francis Murgatroyd, Balaji Ganeshan, Gerald Carr-White, Reza Razavi, Amedeo Chiribiri, Christopher A Rinaldi

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

26 Citations (Scopus)

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.

Original language	English
Pages (from-to)	1242-1250
Number of pages	9
Journal	Heart Rhythm
Volume	16
Issue number	8
Early online date	5 Mar 2019
DOIs	https://doi.org/10.1016/j.hrthm.2019.03.001
Publication status	Published - 1 Aug 2019

Keywords

Entropy
Late gadolinium enhancement
Risk stratification of ventricular arrhythmia
Scar heterogeneity
Ventricular arrhythmia

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10.1016/j.hrthm.2019.03.001

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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

@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",

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publisher = "Elsevier",

number = "8",

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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

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

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U2 - 10.1016/j.hrthm.2019.03.001

DO - 10.1016/j.hrthm.2019.03.001

M3 - Article

C2 - 30849532

SN - 1547-5271

VL - 16

SP - 1242

EP - 1250

JO - Heart Rhythm

JF - Heart Rhythm

IS - 8

ER -

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

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Keywords

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