Prognostic Value of Cardiac-MRI Scar Heterogeneity Combined With Left Ventricular Strain in Patients With Myocardial Infarction.

BACKGROUND: Sudden cardiac death (SCD) after myocardial infarction (MI) is mostly caused by ventricular arrhythmias. As an arrhythmogenic substrate, infarct border zone (BZ) results in adverse electrophysiological properties. PURPOSE: To explore myocardial scar entropy (BZ, infarct core [IC], BZ + IC, expressed as IBZ) and to investigate their prognostic value combined with left ventricular (LV) strain parameters (global radial strain [GRS], global circumferential strain [GCS], global longitudinal strain [GLS]) in patients after MI. STUDY TYPE: Prospective. POPULATION: One hundred fifty-seven patients with previous MI, 26 in primary endpoint events group, 30 in secondary endpoint events group, and 43 in total endpoint events (primary + secondary). FIELD STRENGTH/SEQUENCE: 3.0 T/cine, late gadolinium enhancement (LGE). ASSESSMENT: Three-dimensional feature tracking analysis for three directions (radial, circumferential, and longitudinal), entropy and extent of infarct-related areas (BZ, IC, and IBZ), LV functional parameters. STATISTICAL TESTS: Student t-test, Mann-Whitney U, Spearman or Pearson rank correlation analysis, receiver operating characteristic curve, Kaplan-Meier event-free survival curve, and Cox proportional hazards regression were used. Results were considered statistically significant at P < 0.05. RESULTS: LGE extent and entropy of all infarct-related areas (BZ, IC, and IBZ) were significantly higher and GLS were lower in patients with endpoint events than those without. BZ and IBC entropy were further associated with LV strain in after-MI patients. In the univariable and multivariable Cox analysis, BZ entropy manifested independent association with primary endpoint events (hazard ratio: 3.859; 95% confidence interval: 2.136-6.974). Primary and secondary endpoint events prognostic value was improved by the addition of BZ entropy and GLS to the LVEF model (Delong test, Z = 2.729 for primary endpoint events; Z = 3.230 for secondary endpoint events). DATA CONCLUSION: Entropy of myocardial fibrosis was associated with LV strain. Assessment of BZ entropy and GLS improved prognostic value for endpoint events of LVEF. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 5.

Prognostic Value of Entropy Derived from Late Gadolinium Enhancement Images to Adverse Cardiac Events in Post-Myocardial Infarction Patients.

RATIONALE AND OBJECTIVES: To explore the prognostic value of entropy derived from late gadolinium enhancement images on cardiac magnetic resonance (CMR) for major adverse cardiac events (MACE) in post-myocardial infarction (MI) patients. MATERIALS AND METHODS: Participants with MI underwent 3.0T CMR were retrospectively enrolled. CMR parameters, including the entropy of infarct core (IC), peri-infarct border zone (BZ), and infarct core and peri-infarct border zone (IBZ) were analyzed. Patients were divided into the No-MACE group and the MACE group according to the absence or presence of MACE during the follow-up period. RESULTS: Eighty-four patients were included, among whom 51 patients without MACE and 33 patients with MACE. The MACE group showed higher IC mass, IBZ mass, IC entropy, BZ entropy, IBZ entropy, and LV entropy and lower LVEF than those of the NO-MACE group. LVEF, BZ entropy, and IBZ entropy were independent predictors of MACE (p < 0.05). Receiver operating characteristic curve revealed that the predictive values of BZ entropy with AUC of 0.860, IBZ entropy with AUC of 0.930, the combined model of LVEF and BZ entropy with AUC of 0.923, and the combined model of LVEF and IBZ entropy with AUC of 0.954 were higher than that of LVEF with AUC of 0.797. Delong test illustrated there was no significant difference in AUC among the three models with AUC > 0.900 (p > 0.05). CONCLUSION: BZ entropy and IBZ entropy were noninvasive parameters for better risk stratification of post-MI patients. MI Patients with MACE showed higher BZ entropy and IBZ entropy than patients without MACE.

Entropy of left ventricular late gadolinium enhancement and its prognostic value in hypertrophic cardiomyopathy a new CMR assessment method.

PURPOSE: As a novel metric, entropy generated from late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) can be utilized to assess tissue heterogeneity. However, it is unknown if it can be utilized for risk stratification in hypertrophic cardiomyopathy (HCM). In addition, it is unknown if LGE entropy correlates with LGE mass%, which is commonly utilized for fibrosis assessment. This research was done to investigate these issues. MATERIALS AND METHODS: Patients with HCM who underwent 3.0-T CMR between January 2015 and January 2020 were prospectively enrolled and classified into low- and high-risk groups according to the AHA/ACC risk stratification guideline for 2020. The LGE entropy was automatically estimated using a generic Python package algorithm. On CMR imaging, the LGE mass% was determined using the CVI 42 software. Endpoint events included sudden cardiac death (SCD), hospital readmission owing to heart failure, and implantable cardioverter defibrillator (ICD) treatment for ventricular arrhythmias. RESULTS: A total of 109 HCM participants (70 males) were included. During the follow-up (23 ± 7 months), the patients in the high-risk group had higher LGE entropy (p < 0.001) and LGE mass% (p < 0.001) than those in the low-risk group, and patients with endpoint events had higher LGE entropy (p < 0.001) and LGE mass% (p < 0.001) than those without endpoint events. In all participants, there was a link between LGE entropy and LGE mass%, according to the Spearman rank correlation analysis (p < 0.001; r = 0.667). In ROC analysis, the area under the curve (AUC) of LGE entropy was 0.893 (95% CI, 0.794-0.993; P<0.001), AUC of LGE mass% was 0.826 (95% CI, 0.737-0.914; P<0.001), AUC of LVEF was 0.610 (95% CI, 0.473-0.748; P = 0.117) and AUC of 2020 AHA/ACC guideline for risk stratification was 0.716 (95% CI, 0.617-0.815; P = 0.002). According to Kaplan-Meier curves, HCM with a higher LGE entropy (≥cutoff value (<5.873) or ≥ thied tertile (5.540)) were more likely to experience the endpoint events. Following adjustment for the 2020 AHA/ACC guideline for risk categorization, LGE mass%, or decreased LVEF, Cox analysis showed that LGE entropy was independently linked with endpoint events. CONCLUSIONS: The variability and extent of LGE pictures can be reflected by LGE entropy, which is a reliable, usable, and repeatable metric for risk classification in HCM. It is a prognostic indicator of endpoint events that is independent of other risk indicators.