Novel cardiovascular magnetic resonance strain heterogeneity phenotypes predict cardiovascular events: A prospective...

Global longitudinal (GLS), circumferential (GCS) and radial (GRS) strains may be insufficiently sensitive to early regional pathological cardiac remodeling on cardiovascular magnetic resonance imaging (CMR). Corresponding strain coefficients of variation, CoV_LS, CoV_CS and CoV_RS, may facilitate improved prognostication by quantifying contractile heterogeneity.

To compare CoV_LS, CoV_CS, CoV_RS, to GLS, GCS, GRS, to predict incident cardiovascular (CV) events at population level, respectively.

CMR feature tracking-derived strain biomarkers from 60,746 UK Biobank participants were calculated. Kaplan-Meier survival analysis and Cox proportional hazards regression analyzed unadjusted and adjusted associations between strain biomarkers and CV outcomes, respectively. Covariables included age, sex, CV risk factors, left ventricular mass, end-diastolic volume, ejection fraction (LVEF) and pre-existent regional strain abnormalities. Logrank test for trend, hazard ratios (HR) and Uno's C-Index compared relative performances of CoV and global strain.

Over a median follow-up 5.1 years, higher CoV_CS, CoV_RS and lower GLS predicted greater risk of all-cause death (HR 1.10 [1.02-1.19]; HR 1.08 [1.01-1.16]; HR 0.84 [0.77-0.93], respectively) and a composite CV endpoint of myocardial infarction (MI), heart failure (HF) and arrhythmia (HR 1.10 [1.04-1.16]; HR 1.06 [1.01-1.12]; HR 0.77 [0.71-0.82], respectively). Model discrimination of HF and arrhythmia were significantly improved by CoV_CS (△C-index 0.004 [P<0.001], 0.002 [P=0.001], respectively) and CoV_RS (△C-index 0.004 [P<0.001], 0.001 [P=0.004], respectively). When LVEF ≥50% and ≥3 of age >65 years, obesity, hypertension, diabetes, atrial fibrillation and chronic kidney disease, CoV_CS and CoV_RS were more predictive of incident HF than GLS (HR 1.37 [1.14-1.65]; HR 1.35 [1.14-1.60]; HR 0.68 [0.53-0.86], respectively). When LVEF <50%, CoV_CS and CoV_RS were superior to GLS in predicting the composite CV endpoint, HF and arrhythmia (logrank test for trend, P<0.001 for all with CoV_CS and CoV_RS vs P=0.022, P=0.15, P=0.030 for GLS respectively).

Heterogeneity biomarkers are sensitive to early pathological signals by measuring disease regionality. CoV_CS and CoV_RS are significant, consistent, additive and sometimes superior predictors of HF, arrhythmia and all-cause death than established risk markers, particularly in cohorts with multiple co-morbidities or LVEF <50%. Expansion of machine learning-guided image analysis makes strain CoV imminently translatable into routine clinical practice.