Prognostic Value of Segmental Strain After ST-Elevation Myocardial Infarction: Insights From the EARLY Assessment of MYOcardial Tissue Characteristics by Cardiac Magnetic Resonance (EARLY-MYO-CMR) Study

Background: The prognostic value of left ventricular segmental strain (SS) in ST-elevation myocardial infarction (STEMI) remains unclear. Hypothesis: To assess the prognostic value and application of SS. Study type: Retrospective analysis of a prospective registry. Population: Five hundred and forty-four patients after STEMI (500 in Cohort 1, 44 in Cohort 2). Field strength/sequence: 3 T, balanced steady-state free precession, gradient echo, and gradient echo contrast-enhanced images. Assessment: Participants underwent cardiac MR during the acute phase after STEMI. Infarct-related artery (IRA) strain was determined based on SS obtained from cine images. The primary endpoint was the composite of major adverse cardiovascular events (MACEs) after 8 years of follow-up. In Cohort 2, SS stability was assessed by MR twice within 8 days. Contrast and non-contrast risk models based on SS were established, leading to the development of an algorithm. Statistical test: Student's t-test, Mann-Whitney U-test, Cox and logistic regression, Kaplan-Meier analysis, net reclassification index (NRI). P < 0.05 was considered significant. Results: During a median follow-up of 5.2 years, 83 patients from Cohort 1 experienced a MACE. Among SS, IRA peak circumferential strain (IRA-CS) was an independent factor for MACEs (adjusted hazard ratio 1.099), providing incremental prognostic value (NRI 0.180, P = 0.10). Patients with worse IRA-CS (>-8.64%) demonstrated a heightened susceptibility to MACE. Additionally, IRA-CS was significantly associated with microvascular obstruction (MVO) (adjusted odds ratio 1.084) and infarct size (r = 0.395). IRA-CS showed comparable prognostic effectiveness to global peak circumferential strain (NRI 0.100, P = 0.39), also counterbalancing contrast and non-contrast risk models (NRI 0.205, P = 0.05). In Cohort 2, IRA-CS demonstrated stability between two time points (P = 0.10). Based on risk models incorporating IRA-CS, algorithm "HJKL" was preliminarily proposed for stratification. Data conclusions: IRA-CS is an important prognostic factor, and an algorithm based on it is proposed for stratification.