Cardiac MRI to Predict Sudden Cardiac Death Risk in Dilated Cardiomyopathy
Yangjie Li1, Yuanwei Xu1, Weihao Li1
1From the Departments of Cardiology (Y.L., Y.X., W.L., J.G., J.W., Z.X., Y.C.), Geriatrics (K.W.), and Radiology (J.S.), West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China; and Wexner Medical Center, College of Medicine, The Ohio State University, Columbus, Ohio (Y.H.).
Insights
Cardiac MRI tissue characteristics like native T1 and late gadolinium enhancement (LGE) predict sudden cardiac death (SCD) in nonischemic dilated cardiomyopathy (DCM). A new algorithm using these markers stratifies SCD risk effectively.
Area of Science:
- Cardiology
- Radiology
- Biomedical Imaging
Background:
- Sudden cardiac death (SCD) is a major cause of mortality in nonischemic dilated cardiomyopathy (DCM).
- Risk stratification for SCD in DCM patients remains clinically challenging.
- Cardiac magnetic resonance (CMR) imaging offers potential for myocardial tissue characterization.
Purpose of the Study:
- To assess the predictive value of myocardial tissue characteristics from CMR for SCD events in nonischemic DCM.
- To develop and validate an SCD risk stratification algorithm using CMR findings in this population.
Main Methods:
- Prospective single-center study of 858 adults with nonischemic DCM undergoing CMR.
- Enrollment period: June 2012 to August 2020.
- SCD-related events included SCD, appropriate ICD shock, and resuscitation; analyzed using competing risk regression and Kaplan-Meier methods.
Main Results:
- Late gadolinium enhancement (LGE), native T1, and extracellular volume fraction were independent predictors of SCD-related events.
- An SCD risk stratification algorithm combining native T1 and LGE demonstrated good predictive ability (C-statistic = 0.74).
- Highest annual SCD event rate (9.3%) observed in patients with native T1 ≥ 4 SDs above mean; lowest rate (0.6%) in those with native T1 ≤ 2 SDs below mean and negative LGE.
Conclusions:
- Myocardial tissue characteristics derived from CMR are independent predictors of SCD in nonischemic DCM.
- CMR-derived parameters can effectively stratify patients into different SCD risk categories.
- This approach aids in identifying high-risk individuals for targeted interventions.
Abstract:
Background Sudden cardiac death (SCD) is one of the leading causes of death in individuals with nonischemic dilated cardiomyopathy (DCM). However, the risk stratification of SCD events remains challenging in clinical practice. Purpose To determine whether myocardial tissue characterization with cardiac MRI could be used to predict SCD events and to explore a SCD stratification algorithm in nonischemic DCM. Materials and Methods In this prospective single-center study, adults with nonischemic DCM who underwent cardiac MRI between June 2012 and August 2020 were enrolled. SCD-related events included SCD, appropriate implantable cardioverter-defibrillator shock, and resuscitation after cardiac arrest. Competing risk regression analysis and Kaplan-Meier analysis were performed to identify the association of myocardial tissue characterization with outcomes. Results Among the 858 participants (mean age, 48 years; age range, 18-83 years; 603 men), 70 (8%) participants experienced SCD-related events during a median follow-up of 33.0 months. In multivariable competing risk analysis, late gadolinium enhancement (LGE) (hazard ratio [HR], 1.87; 95% CI: 1.07, 3.27; P = .03), native T1 (per 10-msec increase: HR, 1.07; 95% CI: 1.04, 1.11; P < .001), and extracellular volume fraction (per 3% increase: HR, 1.26; 95% CI: 1.11, 1.44; P < .001) were independent predictors of SCD-related events after adjustment of systolic blood pressure, atrial fibrillation, and left ventricular ejection fraction. An SCD risk stratification category was developed with a combination of native T1 and LGE. Participants with a native T1 value 4 or more SDs above the mean (1382 msec) had the highest annual SCD-related events rate of 9.3%, and participants with a native T1 value 2 SDs below the mean (1292 msec) and negative LGE had the lowest rate of 0.6%. This category showed good prediction ability (C statistic = 0.74) and could be used to discriminate SCD risk and competing heart failure risk. Conclusion Myocardial tissue characteristics derived from cardiac MRI were independent predictors of sudden cardiac death (SCD)-related events in individuals with nonischemic dilated cardiomyopathy and could be used to stratify participants according to different SCD risk categories. Clinical trial registration no. ChiCTR1800017058 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sakuma in this issue.
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