Systolic Global Longitudinal Strain: A Novel Predictor of Myocardial Fibrosis Extent in Patients with Hypertrophic Cardiomyopathy - Wanichsetakul, Punchanit; Arunakul, Ing-orn; Buakhamsri, Adisai (Asian Medical Journal and Alternative Medicine, 2023)
Introduction: Myocardial fibrosis is a marker of adverse prognosis in hypertrophic cardiomyopathy (HCM). It can be assessed with cardiac magnetic resonance (CMR) using late gadolinium enhancement (LGE) as a gold standard. New echocardiographic parameters have ability to determine degree of myocardial fibrosis in patients with coronary heart disease. However, the relationship between these two imaging methods in identifying myocardial fibrosis in patient with HCM is still limited Objectives: To evaluate the correlation of peak systolic global longitudinal strain (GLS) using 2D-speckle tracking echocardiogram (2D-STE) and the extent of LGE by CMR. Methods: Adult patients with diagnosis of HCM at Thammasat University Hospital during January 2011 to December 2020 were identified if both comprehensive echocardiogram and CMR studies were performed less than 1 year apart. Standard echocardiographic parameters including GLS by 2D-STE were retrospectively measured. %LGE by CMR ≥15% was defined as extensive LGE. Results: Ninety-six patients with HCM were included (age = 67 ± 14, female 54%, GLS -14.2 ± 3.7%, extensive LGE 37.5%). GLS and maximal LV wall thickness were significantly correlated with %LGE in univariate analysis (r = 0.526, P ≤ .001 and r = 0.431, P ≤ .001, respectively). In multivariate linear regression analysis, both were independent predictors of %LGE (standard coefficient 0.418, P = .002 and standard coefficient 0.309, P = .017, respectively). GLS was an independent predictor of extensive LGE [(OR 1.2 (95% CI 1.04 - 1.46)), P = .013]. ROC analysis of GLS had demonstrated a best cutoff of -15% for prediction of extensive LGE (AUC of 0.68, sensitivity 74%, specificity 53%) Conclusions: GLS was independently correlated with extent of LGE. 2D-STE strain analysis may be a potential tool for initial risk stratification in HCM.