Literature DB >> 28637807

Sudden Cardiac Death Substrate Imaged by Magnetic Resonance Imaging: From Investigational Tool to Clinical Applications.

Katherine C Wu1.   

Abstract

Sudden cardiac death (SCD) is a devastating event afflicting 350 000 Americans annually despite the availability of life-saving preventive therapy, the implantable cardioverter defibrillator. SCD prevention strategies are hampered by over-reliance on global left ventricular ejection fraction <35% as the most important criterion to determine implantable cardioverter defibrillator candidacy. Annually in the United States alone, this results in ≈130 000 implantable cardioverter defibrillator placements at a cost of >$3 billion but only a 5% incidence per year of appropriate firings. This approach further fails to identify individuals who experience the majority, as many as 80%, of SCD events, which occur in the setting of more preserved left ventricular ejection fraction. Better risk stratification is needed to improve care and should be guided by direct pathophysiologic markers of arrhythmic substrate, such as specific left ventricular structural abnormalities. There is an increasing body of literature to support the prognostic value of cardiac magnetic resonance imaging with late gadolinium enhancement in phenotyping the left ventricular to identify those at highest risk for SCD. Cardiac magnetic resonance has unparalleled tissue characterization ability and provides exquisite detail about myocardial structure and composition, abnormalities of which form the direct, pathophysiologic substrate for SCD. Here, we review the evolution and the current state of cardiac magnetic resonance for imaging the arrhythmic substrate, both as a research tool and for clinical applications.
© 2017 American Heart Association, Inc.

Entities:  

Keywords:  arrhythmias, cardiac; cardiomyopathies; death, sudden, cardiac; fibrosis; magnetic resonance imaging; tachycardia, ventricular; ventricular dysfunction, left

Mesh:

Year:  2017        PMID: 28637807      PMCID: PMC5507445          DOI: 10.1161/CIRCIMAGING.116.005461

Source DB:  PubMed          Journal:  Circ Cardiovasc Imaging        ISSN: 1941-9651            Impact factor:   7.792


  83 in total

1.  Image-based left ventricular shape analysis for sudden cardiac death risk stratification.

Authors:  Fijoy Vadakkumpadan; Natalia Trayanova; Katherine C Wu
Journal:  Heart Rhythm       Date:  2014-05-20       Impact factor: 6.343

2.  Infarct tissue heterogeneity assessed with contrast-enhanced MRI predicts spontaneous ventricular arrhythmia in patients with ischemic cardiomyopathy and implantable cardioverter-defibrillator.

Authors:  Stijntje D Roes; C Jan Willem Borleffs; Rob J van der Geest; Jos J M Westenberg; Nina Ajmone Marsan; Theodorus A M Kaandorp; Johan H C Reiber; Katja Zeppenfeld; Hildo J Lamb; Albert de Roos; Martin J Schalij; Jeroen J Bax
Journal:  Circ Cardiovasc Imaging       Date:  2009-03-23       Impact factor: 7.792

3.  Relationship Between Infarct Size and Outcomes Following Primary PCI: Patient-Level Analysis From 10 Randomized Trials.

Authors:  Gregg W Stone; Harry P Selker; Holger Thiele; Manesh R Patel; James E Udelson; E Magnus Ohman; Akiko Maehara; Ingo Eitel; Christopher B Granger; Paul L Jenkins; Melissa Nichols; Ori Ben-Yehuda
Journal:  J Am Coll Cardiol       Date:  2016-04-12       Impact factor: 24.094

Review 4.  Sudden cardiac death early after myocardial infarction: pathogenesis, risk stratification, and primary prevention.

Authors:  Sarah Zaman; Pramesh Kovoor
Journal:  Circulation       Date:  2014-06-10       Impact factor: 29.690

5.  Relationship of MRI delayed contrast enhancement to irreversible injury, infarct age, and contractile function.

Authors:  R J Kim; D S Fieno; T B Parrish; K Harris; E L Chen; O Simonetti; J Bundy; J P Finn; F J Klocke; R M Judd
Journal:  Circulation       Date:  1999-11-09       Impact factor: 29.690

6.  Cardiovascular magnetic resonance-GUIDEd management of mild to moderate left ventricular systolic dysfunction (CMR GUIDE): Study protocol for a randomized controlled trial.

Authors:  Joseph B Selvanayagam; Trent Hartshorne; Laurent Billot; Suchi Grover; Graham S Hillis; Werner Jung; Henry Krum; Sanjay Prasad; Andrew D McGavigan
Journal:  Ann Noninvasive Electrocardiol       Date:  2017-01-24       Impact factor: 1.468

7.  Cardiac resynchronization therapy-induced proarrhythmia: understanding preferential conduction within myocardial scars.

Authors:  Jason S Bradfield; Kalyanam Shivkumar
Journal:  Circ Arrhythm Electrophysiol       Date:  2014-12

8.  Defibrillator Implantation in Patients with Nonischemic Systolic Heart Failure.

Authors:  Lars Køber; Jens J Thune; Jens C Nielsen; Jens Haarbo; Lars Videbæk; Eva Korup; Gunnar Jensen; Per Hildebrandt; Flemming H Steffensen; Niels E Bruun; Hans Eiskjær; Axel Brandes; Anna M Thøgersen; Finn Gustafsson; Kenneth Egstrup; Regitze Videbæk; Christian Hassager; Jesper H Svendsen; Dan E Høfsten; Christian Torp-Pedersen; Steen Pehrson
Journal:  N Engl J Med       Date:  2016-08-27       Impact factor: 91.245

9.  Delayed-enhanced magnetic resonance imaging in nonischemic cardiomyopathy: utility for identifying the ventricular arrhythmia substrate.

Authors:  Frank M Bogun; Benoit Desjardins; Eric Good; Sanjaya Gupta; Thomas Crawford; Hakan Oral; Matthew Ebinger; Frank Pelosi; Aman Chugh; Krit Jongnarangsin; Fred Morady
Journal:  J Am Coll Cardiol       Date:  2009-03-31       Impact factor: 24.094

Review 10.  State of the Art: Clinical Applications of Cardiac T1 Mapping.

Authors:  Erik B Schelbert; Daniel R Messroghli
Journal:  Radiology       Date:  2016-03       Impact factor: 11.105

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  20 in total

1.  LGE-CMR-derived texture features reflect poor prognosis in hypertrophic cardiomyopathy patients with systolic dysfunction: preliminary results.

Authors:  Sainan Cheng; Mengjie Fang; Chen Cui; Xiuyu Chen; Gang Yin; Sanjay K Prasad; Di Dong; Jie Tian; Shihua Zhao
Journal:  Eur Radiol       Date:  2018-05-04       Impact factor: 5.315

2.  American perspective: Comparing the AHA/ACC and ESC guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death.

Authors:  Saurabh Malhotra; John M Canty
Journal:  J Nucl Cardiol       Date:  2017-08-22       Impact factor: 5.952

3.  Myocardial Fibrosis as a Predictor of Ventricular Arrhythmias in Patients With Non-ischemic Cardiomyopathy.

Authors:  Călin Schiau; Daniel-Corneliu Leucuța; Sorin Marian Dudea; Simona Manole
Journal:  In Vivo       Date:  2021 May-Jun       Impact factor: 2.155

4.  Preliminary Study: Learning the Impact of Simulation Time on Reentry Location and Morphology Induced by Personalized Cardiac Modeling.

Authors:  Lv Tong; Caiming Zhao; Zhenyin Fu; Ruiqing Dong; Zhenghong Wu; Zefeng Wang; Nan Zhang; Xinlu Wang; Boyang Cao; Yutong Sun; Dingchang Zheng; Ling Xia; Dongdong Deng
Journal:  Front Physiol       Date:  2021-12-24       Impact factor: 4.566

5.  Plasma big endothelin-1 is an effective predictor for ventricular arrythmias and end-stage events in primary prevention implantable cardioverter- defibrillator indication patients.

Authors:  Xiao-Yao Li; Shuang Zhao; Xiao-Han Fan; Ke-Ping Chen; Wei Hua; Zhi-Min Liu; Xiao-Di Xue; Bin Zhou; Shu Zhang
Journal:  J Geriatr Cardiol       Date:  2020-07-28       Impact factor: 3.327

6.  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

7.  Bringing Order to Disorder: Is Image Entropy the Answer?

Authors:  Katherine C Wu
Journal:  JACC Cardiovasc Imaging       Date:  2018-08-15

8.  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

9.  Learning for Prevention of Sudden Cardiac Death.

Authors:  Natalia A Trayanova
Journal:  Circ Res       Date:  2021-01-21       Impact factor: 17.367

10.  Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation.

Authors:  Shannon Wongvibulsin; Katherine C Wu; Scott L Zeger
Journal:  JMIR Med Inform       Date:  2020-06-09
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