Novel cardiovascular magnetic resonance imaging heterogeneity biomarkers to diagnose and predict cardiovascular disease: a UK Biobank CMR strain study

Abstract Background Myocardial strain evaluation on cardiovascular magnetic resonance imaging (CMR) shows significant promise to investigate cardiac function in vivo. There is concern that derived global longitudinal strain (GLS) and global circumferential strain (GCS) are less sensitive to early pathological cardiac remodelling, especially when regional. By quantifying contractile variability across the myocardium, the absolute longitudinal and circumferential strain coefficients of variation, |CoVLS| and |CoVCS| may facilitate earlier diagnosis and improved prognostication. Purpose We compared experimental heterogeneity biomarkers, |CoVLS| and |CoVCS|, to established global strain markers, GLS and GCS, to discriminate prevalent cardiovascular disease (CVD) and predict major adverse cardiovascular events (MACE). Methods Prevalent and incident CVD were defined among 44,955 participants from the UK Biobank (UKBB), who had feature-tracking (FT-CMR) derived strain markers. Prevalent CVD was the sum of established cardiovascular diagnoses at the time of baseline CMR, including hypertension, diabetes, atrial fibrillation, coronary artery disease, stroke and heart failure (HF). Incident CVD was newly identified MACE, including death from any cause, myocardial infarction, HF and stroke. Biomarkers were separately regressed against said endpoints, using ordinal logistic and Cox proportional hazards regression respectively. Statistical adjustment was performed for important baseline co-variables, including age, sex, ethnicity, smoking status, body mass index (BMI), low-density lipoprotein (LDL), left atrial volume, left ventricular mass and ejection fraction. Results Overall, 30,289 (67.4%) participants had no prevalent CVD, 10,362 (23.0%) had 1 CVD and 29 (0.06%) had ≥5 CVD. |CoVLS|, GLS, |CoVCS| and GCS were associated with a higher odds of prevalent CVD diagnoses (Figure 1). GLS had the greatest strength of association (OR 1.25, 95% CI 1.20-1.29), followed by |CoVCS| (OR 1.14, 95% CI 1.10-1.17). Over median 2.7 years (Q1-Q3 1.9-4.1 years), 966 (2.1%) participants experienced MACE, including 379 (0.8%) deaths, 263 (0.6%) MI, 246 (0.5%) HF, 237 (0.5%) stroke. |CoVLS|, |CoVCS| and GLS were comparable risk markers for MACE (Figure 2). The largest and smallest effect sizes were in predicting HF and death from any cause respectively. Conclusion Subclinical cardiac disease is often patchy, diffuse and regional; measures of heterogeneity may be more sensitive to these early pathological signals. We demonstrated that |CoVLS| and |CoVCS| are comparable to GLS and better than GCS in discriminating prevalent cardiac disease and predicting future cardiovascular events. These findings need to be replicated in other population studies and diseased cohorts.