Literature DB >> 31000102

Entropy as a Novel Measure of Myocardial Tissue Heterogeneity for Prediction of Ventricular Arrhythmias and Mortality in Post-Infarct Patients.

Alexander F A Androulakis1, Katja Zeppenfeld2, Elisabeth H M Paiman3, Sebastiaan R D Piers1, Adrianus P Wijnmaalen1, Hans-Marc J Siebelink1, Marek Sramko1, Hildo J Lamb3, Rob J van der Geest4, Marta de Riva1, Qian Tao5.   

Abstract

OBJECTIVES: This study proposed entropy as a new late gadolinium enhanced cardiac magnetic resonance-derived parameter to evaluate tissue inhomogeneity, independent of signal intensity thresholds. This study hypothesized that entropy within the scar is associated with ventricular arrhythmias (VAs), whereas entropy of the entire left ventricular (LV) myocardium is associated with mortality.
BACKGROUND: In patients after myocardial infarction, the heterogeneity of fibrosis determines the substrate for VA. Fibrosis in remote areas has been associated with heart failure and mortality. Late gadolinium-enhanced cardiac magnetic resonance has been used to delineate fibrosis, but available methods depend on signal intensity thresholds and results have been inconsistent.
METHODS: Consecutive post-myocardial infarction patients undergoing late gadolinium enhanced cardiac magnetic resonance prior to implantable cardioverter-defibrillator implantation were included. From cardiac magnetic resonance imaging, total scar size, scar gray zone, scar transmurality, and tissue entropy were derived. Patients were followed for appropriate implantable cardioverter-defibrillator therapy and mortality.
RESULTS: A total of 154 patients (age 64 ± 10 years, 84% male, LV ejection fraction 29 ± 10%, 47% acute revascularization) were included. During a median follow-up of 56 (interquartile range: 40 to 73) months, appropriate implantable cardioverter-defibrillator therapy occurred in 46 patients (30%), and 41 patients (27%) died. From multivariable analysis, higher entropy of the scar (hazard ratio [HR]: 1.9; 95% confidence interval [CI]: 1.0 to 3.5; p = 0.042) was independently associated with VA, after adjusting for multivessel disease, acute revascularization, LV ejection fraction, scar gray zone, and transmurality. Entropy of the entire LV was independently associated with mortality (HR: 3.2; 95% CI: 1.1 to 9.9; p = 0.038).
CONCLUSIONS: High entropy within the scar was associated with VA and may indicate an arrhythmogenic scar. High entropy of the entire LV was associated with mortality and may reflect a fibrosis pattern associated with adverse remodeling.
Copyright © 2019 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  cardiac magnetic resonance; diffuse fibrosis; entropy; late gadolinium enhancement; magnetic resonance imaging; sudden death; ventricular arrhythmia

Mesh:

Substances:

Year:  2019        PMID: 31000102     DOI: 10.1016/j.jacep.2018.12.005

Source DB:  PubMed          Journal:  JACC Clin Electrophysiol        ISSN: 2405-500X


  9 in total

1.  Spatial dispersion analysis of LGE-CMR for prediction of ventricular arrhythmias in patients with cardiac sarcoidosis.

Authors:  Konstantinos N Aronis; David R Okada; Eric Xie; Usama A Daimee; Adityo Prakosa; Nisha A Gilotra; Katherine C Wu; Natalia Trayanova; Jonathan Chrispin
Journal:  Pacing Clin Electrophysiol       Date:  2021-11-26       Impact factor: 1.976

2.  Substrate Spatial Complexity Analysis for the Prediction of Ventricular Arrhythmias in Patients With Ischemic Cardiomyopathy.

Authors:  David R Okada; Jason Miller; Jonathan Chrispin; Adityo Prakosa; Natalia Trayanova; Steven Jones; Mauro Maggioni; Katherine C Wu
Journal:  Circ Arrhythm Electrophysiol       Date:  2020-03-18

Review 3.  Cardiac fibrosis.

Authors:  Nikolaos G Frangogiannis
Journal:  Cardiovasc Res       Date:  2021-05-25       Impact factor: 10.787

4.  More Than Meets the Eye: Cardiac Magnetic Resonance Image Entropy and Ventricular Arrhythmia Risk Prediction.

Authors:  Katherine C Wu; Jonathan Chrispin
Journal:  JACC Cardiovasc Imaging       Date:  2022-03-16

Review 5.  Role of Cardiac Magnetic Resonance to Improve Risk Prediction Following Acute ST-Elevation Myocardial Infarction.

Authors:  Martin Reindl; Ingo Eitel; Sebastian Johannes Reinstadler
Journal:  J Clin Med       Date:  2020-04-07       Impact factor: 4.241

Review 6.  Advanced imaging for risk stratification for ventricular arrhythmias and sudden cardiac death.

Authors:  Eric Xie; Eric Sung; Elie Saad; Natalia Trayanova; Katherine C Wu; Jonathan Chrispin
Journal:  Front Cardiovasc Med       Date:  2022-08-22

7.  Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data.

Authors:  Divneet Mandair; Premanand Tiwari; Steven Simon; Kathryn L Colborn; Michael A Rosenberg
Journal:  BMC Med Inform Decis Mak       Date:  2020-10-02       Impact factor: 2.796

Review 8.  Heart failure with recovered ejection fraction and the utility of defibrillator therapy: a review.

Authors:  Jasneet K Devgun; Samuel Kennedy; Jeremy Slivnick; Zachary Garrett; Katherine Dodd; Mohamed H Derbala; Cristina Ortiz; Sakima A Smith
Journal:  ESC Heart Fail       Date:  2021-12-24

9.  Predicting risk of sudden cardiac death in patients with cardiac sarcoidosis using multimodality imaging and personalized heart modeling in a multivariable classifier.

Authors:  Julie K Shade; Adityo Prakosa; Dan M Popescu; Rebecca Yu; David R Okada; Jonathan Chrispin; Natalia A Trayanova
Journal:  Sci Adv       Date:  2021-07-28       Impact factor: 14.136

  9 in total

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