Regional Distribution of Extracellular Volume Quantified by Cardiac CT in Aortic Stenosis: Insights Into Disease Mechanisms and Impact on Outcomes

BACKGROUND: Extracellular volume fraction (ECV) is a marker for myocardial fibrosis and infiltration, can be quantified using cardiac computed tomography (ECV CT ), and has prognostic utility in several diseases. This study aims to map out regional differences in ECV CT to obtain greater insights into the pathophysiological mechanisms of ECV expansion and its clinical implications. METHODS: Three prospective cohorts were included: patients with aortic stenosis (AS) and coexisting AS and transthyretin cardiac amyloidosis were referred for a transcatheter aortic valve replacement and had ECG-gated CT angiography and Technetium-99m-labelled 3,3-diphosphono-1,2-propanodicarboxylic acid scintigraphy to differentiate between the 2 cohorts. Controls had CT angiography and cardiac magnetic resonance demonstrating no significant coronary artery disease or infarction. Global and regional ECV CT was analyzed, and its association with mortality was assessed for patients with AS. RESULTS: In 199 patients, controls (n=65; 66% male), AS (n=115), and coexisting AS and transthyretin cardiac amyloidosis (n=19) had a global ECV CT of 26.1 (25.0–27.8%) versus 29.1 (27.5–31.1%) versus 37.4 (32.5–46.6%), respectively; P <0.001. Across cohorts, ECV CT was higher at the base (versus apex), the inferoseptum (versus anterolateral wall), and the subendocardium (versus subepicardium); P <0.05 for all. Among patients with AS, epicardial ECV CT , rather than any other regional value or global ECV CT , was the strongest predictor of mortality at a median of 3.9 (max 6.3) years (adjusted hazard ratio, 1.21 95% CI, 1.08–1.36; P =0.002). CONCLUSIONS: Regional differences in ECV CT suggest a predilection for fibrosis and amyloid infiltration at the base, subendocardium, inferior wall, and septum more than the anterior and lateral myocardium. ECV CT can predict long-term mortality with the subepicardium demonstrating the strongest discriminatory power. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifiers: NCT03029026 and NCT03094143.