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Related Experiment Video

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Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
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Arrhythmic Risk Stratification by Cardiovascular Magnetic Resonance Imaging in Patients With Nonischemic

Daniel J Hammersley1, Abbasin Zegard2, Emmanuel Androulakis3

  • 1National Heart and Lung Institute, Imperial College London, London, United Kingdom; Royal Brompton & Harefield Clinical Group, part of Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom; Kings College Hospital NHS Foundation Trust, London, United Kingdom.

Journal of the American College of Cardiology
|September 1, 2024
PubMed
Summary

Myocardial fibrosis (MF) is a strong predictor of sudden cardiac death and ventricular arrhythmias (VAs) in nonischemic cardiomyopathy (NICM). Quantified fibrosis measures, unlike LVEF, effectively stratify patient risk.

Keywords:
arrythmiafibrosisnonischemic cardiomyopathyrisk stratificationsudden cardiac death

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Area of Science:

  • Cardiology
  • Medical Imaging
  • Biomarkers

Background:

  • Myocardial fibrosis (MF) contributes to the substrate for ventricular arrhythmias (VAs).
  • Nonischemic cardiomyopathy (NICM) patients are at risk for life-threatening arrhythmias.

Purpose of the Study:

  • To compare the predictive power of total myocardial fibrosis (TF) and gray zone fibrosis (GZF) assessed by cardiovascular magnetic resonance (CMR) against left ventricular ejection fraction (LVEF) for predicting VAs in NICM patients.
  • To evaluate the utility of CMR-derived fibrosis quantification in risk stratification.

Main Methods:

  • Quantification of TF and GZF using CMR in two cohorts of NICM patients (derivation n=866, validation n=848).
  • Assessment of the primary composite endpoint: sudden cardiac death or VAs.
  • Competing-risks analyses to determine predictive values of MF measures and LVEF.

Main Results:

  • Myocardial fibrosis on visual assessment (MFVA) significantly predicted the primary endpoint (HR: 5.83).
  • Quantified TF categorized patients into low, intermediate, and high-risk groups for the primary endpoint, outperforming LVEF (<35%) which was a poor predictor (validation HR: 1.99).
  • TF and GZF, individually or combined, provided incremental value for risk stratification.

Conclusions:

  • MFVA is a robust predictor of sudden cardiac death and VAs in NICM.
  • Quantified TF and GZF offer superior risk stratification compared to LVEF in NICM patients.
  • CMR-derived fibrosis assessment is crucial for identifying patients at high risk for arrhythmic events.