Global Longitudinal Strain Analysis Using Cardiac MRI in Aortic Stenosis: Comparison with Left Ventricular Remodeling, Myocardial Fibrosis, and 2-year Clinical Outcomes.

PURPOSE: To use global longitudinal strain (GLS) as a marker of left ventricular decompensation in aortic stenosis and to investigate the relationship of GLS measured with cardiac MRI with markers of myocardial fibrosis, symptom development, remodeling, and clinical outcomes. MATERIALS AND METHODS: Patients with aortic stenosis and healthy control subjects were assessed. GLS was assessed by using cardiac MRI feature tracking, diffuse fibrosis by T1 mapping, and replacement fibrosis using late gadolinium enhancement. Follow-up was prospective for the primary endpoint of all-cause mortality. RESULTS: GLS was reduced in aortic stenosis (n = 159) compared with control subjects (n = 41) (-17.6% ± 3.1 [standard deviation] vs -18.9% ± 2.6, P = .02). GLS demonstrated weak associations with aortic stenosis severity (Vmax; r = 0.24, P = .0005) but showed moderate correlation with T1 mapping measures of myocardial fibrosis (eg, indexed extracellular volume [iECV]; r = 0.43, P < .0001). Moreover, GLS was reduced in patients with midwall fibrosis compared with control subjects (P < .001), although values were similar to those of patients with myocardial infarction (P = .25). In adjusted analyses, GLS was associated with total myocardial fibrosis burden (iECV) and ejection fraction (both P < .001). GLS offered poor discrimination between disease states, inability to distinguish between control subjects and patients (area under the curve [AUC], 0.60), presence or absence of fibrosis (AUC, 0.63), or symptomatic severity (left ventricular decompensation AUC, 0.64). At follow-up (median, 1466 days), 21 patients died. GLS did not independently predict clinical outcomes. CONCLUSION: GLS correlates with established markers of myocardial fibrosis. However, widespread utility of single GLS measurements may be limited by overlap between disease states and its inability to predict clinical outcomes beyond current established markers.© RSNA, 2019Supplemental material is available for this article.