Left Ventricular Entropy Is a Novel Predictor of Arrhythmic Events in Patients With Dilated Cardiomyopathy Receiving Defibrillators for Primary Prevention

Muthalaly, Rahul G.; Kwong, Raymond Y.; John, Roy M.; Geest, Rob J. van der; Tao, Qian; Schaeffer, Benjamin; Tanigawa, Shin‐ichi; Nakamura, Tomofumi; Kaneko, Kensuke; Tedrow, Usha B.; Stevenson, William G.; Epstein, Laurence M.; Kapur, Sunil; Zei, Paul C.; Koplan, Bruce A.

doi:10.1016/j.jcmg.2018.07.003

Cited by 45 publications

(29 citation statements)

References 22 publications

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“…These results are in agreement with [20], as Muthalaly et al concluded that high LV entropy is a predictor of forthcoming arrhythmias.…”

Section: The Effect Of Scar's Micro-structure On the Defibrillation Ssupporting

confidence: 89%

A Patient-based Model to Investigate the Effect of Micro-structure Scars on the Optogenetic Defibrillation Success: A Computational Modelling Approach

Zafarghandi

Bahrami

2020

Preprint

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This study investigates the role of the microstructure of real scars in the success of optogenetic defibrillation. To reduce the computational cost of high-order models (like Ten Tusscher Model, TTM) for a single cell as well as to take advantage of their ability to generate a more realistic output, we developed a low-order model of optogenetic cardiac tissue based on the modified Alieve-Panfilov single-cell model and estimated its parameters using a TTM. Two-dimensional electrophysiological cardiac tissue models were produced including different scar shapes that were extracted from Late Gadolinium-Enhanced (LGE) magnetic resonance imaging data set of 10 patients with non-ischemic dilated cardiomyopathy. The scar shapes were classified based on four criteria: transmurality, relative area, scar entropy, and interface length. Scar with the highest 25% of the relative area showed 25% of successful cases, this ratio is 27%, and 25% for a scar with the most top 25% of entropy, and transmurality, respectively. In comparison, the proportions are 61.54%, 44.44%, and 61.76%, for the lowest 25% of the area, entropy, and transmurality. We also investigated the efficacy of various methods for light-sensitive cells’ distribution within the cardiac tissue with scar. Four types of distributions were defined. Defibrillation within tissues with 0.1 light-sensitive out of all cells was 15 to 25% more successful than their counterparts with 0.05 light-sensitive cells. Lastly, we examined the effect of an earlier stimulation on the success probability of defibrillation. Our results indicated that inducing 0.5 msec earlier resulted in a roughly 15% rise in successful cases.

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“…These results are in agreement with [20], as Muthalaly et al concluded that high LV entropy is a predictor of forthcoming arrhythmias.…”

Section: The Effect Of Scar's Micro-structure On the Defibrillation Ssupporting

confidence: 89%

A Patient-based Model to Investigate the Effect of Micro-structure Scars on the Optogenetic Defibrillation Success: A Computational Modelling Approach

Zafarghandi

Bahrami

2020

Preprint

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“…Moreover, CMR-TA has potential use in identifying which patients remain at high risk of VA, which is of growing interest in prophylactic VT ablation in the ICM cohort, where it could play a role in patient selection. Its use in the NICM population is less clear given our findings significantly differ from the Harvard-Leiden groups, 18 albeit with different scar inclusion methods and therefore method refinement and further larger multi-centre studies are warranted.…”

Section: Predictors Of Appropriate Icd Therapy and Clinical Translationmentioning

confidence: 72%

“…All subjects were scanned on the same 1.5T scanner, therefore we do not know how filtered mean entropy values vary with 3T or indeed different manufacturers. Muthalaly et al (2018), noted a difference in unfiltered entropy values between 1.5T and 3T in their NICM cohort and therefore further assessment is required in future studies. 18 Furthermore, we do not know whether there is temporal variation in entropy values and also recognise that inversion times, timing of LGE acquisition and additional imaging factors are unknown and required assessment.…”

Section: Commented [20]mentioning

confidence: 94%

“…Muthalaly et al (2018), noted a difference in unfiltered entropy values between 1.5T and 3T in their NICM cohort and therefore further assessment is required in future studies. 18 Furthermore, we do not know whether there is temporal variation in entropy values and also recognise that inversion times, timing of LGE acquisition and additional imaging factors are unknown and required assessment. We used a standardised device therapy protocol mirroring our institutions guidelines when the study commenced in 2011.…”

Section: Commented [20]mentioning

confidence: 94%

“…This is in contrast to the recent findings of the Harvard-Leiden collaboration who used a different software platform in a cohort of 130 NICM patients, with visible scar in 56.9% of patients. 18 This may also be explained by several methodological differences between the studies. Muthalaly et al segmented the entire myocardium using unfiltered LGE images to derive entropy compared to our method of total scar segmentation with the application of spatial scale filters to generate scar textures from which entropy was calculated.…”

Section: Comparison With Previous Studiesmentioning

confidence: 99%

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

et al. 2019

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Risk Stratification in Nonischemic Dilated Cardiomyopathy Using CMR Imaging

Eichhorn,

Koeckerling,

Reddy

et al. 2024

JAMA

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ImportanceAccurate risk stratification of nonischemic dilated cardiomyopathy (NIDCM) remains challenging.ObjectiveTo evaluate the association of cardiac magnetic resonance (CMR) imaging–derived measurements with clinical outcomes in NIDCM.Data SourcesMEDLINE, Embase, Cochrane Library, and Web of Science Core Collection databases were systematically searched for articles from January 2005 to April 2023.Study SelectionProspective and retrospective nonrandomized diagnostic studies reporting on the association between CMR imaging–derived measurements and adverse clinical outcomes in NIDCM were deemed eligible.Data Extraction and SynthesisPrespecified items related to patient population, CMR imaging measurements, and clinical outcomes were extracted at the study level by 2 independent reviewers. Random-effects models were fitted using restricted maximum likelihood estimation and the method of Hartung, Knapp, Sidik, and Jonkman.Main Outcomes and MeasuresAll-cause mortality, cardiovascular mortality, arrhythmic events, heart failure events, and major adverse cardiac events (MACE).ResultsA total of 103 studies including 29 687 patients with NIDCM were analyzed. Late gadolinium enhancement (LGE) presence and extent (per 1%) were associated with higher all-cause mortality (hazard ratio [HR], 1.81 [95% CI, 1.60-2.04]; P &lt; .001 and HR, 1.07 [95% CI, 1.02-1.12]; P = .02, respectively), cardiovascular mortality (HR, 2.43 [95% CI, 2.13-2.78]; P &lt; .001 and HR, 1.15 [95% CI, 1.07-1.24]; P = .01), arrhythmic events (HR, 2.69 [95% CI, 2.20-3.30]; P &lt; .001 and HR, 1.07 [95% CI, 1.03-1.12]; P = .004) and heart failure events (HR, 1.98 [95% CI, 1.73-2.27]; P &lt; .001 and HR, 1.06 [95% CI, 1.01-1.10]; P = .02). Left ventricular ejection fraction (LVEF) (per 1%) was not associated with all-cause mortality (HR, 0.99 [95% CI, 0.97-1.02]; P = .47), cardiovascular mortality (HR, 0.97 [95% CI, 0.94-1.00]; P = .05), or arrhythmic outcomes (HR, 0.99 [95% CI, 0.97-1.01]; P = .34). Lower risks for heart failure events (HR, 0.97 [95% CI, 0.95-0.98]; P = .002) and MACE (HR, 0.98 [95% CI, 0.96-0.99]; P &lt; .001) were observed with higher LVEF. Higher native T1 relaxation times (per 10 ms) were associated with arrhythmic events (HR, 1.07 [95% CI, 1.01-1.14]; P = .04) and MACE (HR, 1.06 [95% CI, 1.01-1.11]; P = .03). Global longitudinal strain (GLS) (per 1%) was not associated with heart failure events (HR, 1.06 [95% CI, 0.95-1.18]; P = .15) or MACE (HR, 1.03 [95% CI, 0.94-1.14]; P = .43). Limited data precluded definitive analysis for native T1 relaxation times, GLS, and extracellular volume fraction (ECV) with respect to mortality outcomes.ConclusionThe presence and extent of LGE were associated with various adverse clinical outcomes, whereas LVEF was not significantly associated with mortality and arrhythmic end points in NIDCM. Risk stratification using native T1 relaxation times, extracellular volume fraction, and global longitudinal strain requires further evaluation.

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Left Ventricular Entropy Is a Novel Predictor of Arrhythmic Events in Patients With Dilated Cardiomyopathy Receiving Defibrillators for Primary Prevention

Abstract: Automated LV entropy measurement is a novel marker for risk stratification toward ventricular arrhythmia in patients with DCM.

Cited by 45 publications

References 22 publications

A Patient-based Model to Investigate the Effect of Micro-structure Scars on the Optogenetic Defibrillation Success: A Computational Modelling Approach

A Patient-based Model to Investigate the Effect of Micro-structure Scars on the Optogenetic Defibrillation Success: A Computational Modelling Approach

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

Risk Stratification in Nonischemic Dilated Cardiomyopathy Using CMR Imaging

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