A novel cardiac magnetic resonance–based personalized risk stratification model in dilated cardiomyopathy: a prospective study

Objectives: To explore individual weight of cardiac magnetic resonance (CMR) metrics to predict mid-term outcomes in patients with dilated cardiomyopathy (DCM), and develop a risk algorithm for mid-term outcome based on CMR biomarkers. Materials and methods: Patients with DCM who underwent CMR imaging were prospectively enrolled in this study. The primary endpoint was a composite of heart failure (HF) death, sudden cardiac death (SCD), aborted SCD, and heart transplantation. Results: A total of 407 patients (age 48.1 ± 13.8 years, 331 men) were included in the final analysis. During a median follow-up of 21.7 months, 63 patients reached the primary endpoint. NYHA class III/IV (HR = 2.347 [1.073–5.133], p = 0.033), left ventricular ejection fraction (HR = 0.940 [0.909–0.973], p < 0.001), late gadolinium enhancement (LGE) > 0.9% and ≤ 6.6% (HR = 3.559 [1.020–12.412], p = 0.046), LGE > 6.6% (HR = 6.028 [1.814–20.038], p = 0.003), and mean extracellular volume (ECV) fraction ≥ 32.8% (HR = 5.922 [2.566–13.665], p < 0.001) had a significant prognostic association with the primary endpoints (C-statistic: 0.853 [0.810–0.896]). Competing risk regression analyses showed that patients with mean ECV fraction ≥ 32.8%, LGE ≥ 5.9%, global circumferential strain ≥ − 5.6%, or global longitudinal strain ≥ − 7.3% had significantly shorter event-free survival due to HF death and heart transplantation. Patients with mean ECV fraction ≥ 32.8% and LGE ≥ 5.9% had significantly shorter event-free survival due to SCD or aborted SCD. Conclusion: ECV fraction may be the best independently risk factor for the mid-term outcomes in patients with DCM, surpassing LVEF and LGE. LGE has a better prognostic value than other CMR metrics for SCD and aborted SCD. The risk stratification model we developed may be a promising non-invasive tool for decision-making and prognosis. Clinical relevance statement: “One-stop” assessment of cardiac function and myocardial characterization using cardiac magnetic resonance might improve risk stratification of patients with DCM. In this prospective study, we propose a novel risk algorithm in DCM including NYHA functional class, LVEF, LGE, and ECV. Key Points: • The present study explores individual weight of CMR metrics for predicting mid-term outcomes in dilated cardiomyopathy. • We have developed a novel risk algorithm for dilated cardiomyopathy that includes cardiac functional class, ejection fraction, late gadolinium enhancement, and extracellular volume fraction. • Personalized risk model derived by CMR contributes to clinical assessment and individual decision-making.