Abstract Introduction Extra-cellular volume (ECV) fraction on magnetic resonance imaging (MRI) can evaluate the degree of myocardial fibrosis and has been reported to help diagnose and evaluate the prognosis of cardiomyopathy. In hypertrophic cardiomyopathy (HCM), ECV analysis on MRI is reported to help predict ventricular arrhythmias. However, the performance of cardiac MRI takes time, and there are also several contraindications. Cardiac computed tomography (CT) is more versatile than cardiac MRI and is also useful in screening coronary artery disease. ECV analysis on CT is now available, and a good correlation with ECV on MRI has been reported. We hypothesized that ECV on CT, a new fibrosis indicator, would be useful in predicting prognosis in HCM patients. Purpose To determine the utility of ECV analysis on CT to predict the prognosis in patients with HCM. Methods One hundred and three HCM patients (68 males, 66 ± 11 years old) who underwent cardiac CT using 320-row detector CT or 256-row detector CT, from 2008 to 2021 at our two hospitals were analyzed. We measured left ventricular (LV) ECV (LV-ECV) on CT and collected patient characteristics, transthoracic echocardiographic, and other CT findings. We investigated the relationship between these findings and the major adverse cardiac events (MACEs) (cardiac death, fatal arrhythmia, and heart failure hospitalization) after CT. Results All patients were followed for 64 ± 54 months after cardiac CT, and 15 patients (14.6%) had MACEs (ten heart failure hospitalization cases, two ventricular fibrillation cases, two sustained ventricular tachycardia cases, and one sudden cardiac death case). The patients with MACEs had a significantly higher LV-ECV, sudden cardiac death (SCD) risk score and lower LV ejection fraction (LVEF) than those without MACEs(42.0 ± 8.3% vs. 33.7 ± 6.1%, P < 0.001, 2.4 ± 0.39 vs 1.95 ± 0.16, P= 0.047, and 57.7 ± 11.9% vs. 66.7 ± 6.9%, P = 0.004). The percentage of dilated phase HCM was significantly higher in the patients with MACEs than those without MACEs (21% vs 0%, p=0.002). LV-ECV was the only significant predictor of MACEs based on the multivariate analysis by Cox proportional hazard model (hazard ratio 1.23, 95% confidence interval 1.09-1.41, P<0.001). The optimal threshold of LV-ECV to predict MACEs was 37.6% based on the receiver operating characteristic analysis. The sensitivity and specificity of LV-ECV to predict MACEs were 73% and 78% at the best cut-off, and the area under the curve was 0.79 (Figure A). The patients with LV-ECV ≥ 37.6% (30 patients) had significantly higher MACEs than those with LV-ECV < 37.6% during the follow-up periods (P < 0.001) (Figure B). Conclusion LV-ECV on CT of 37.6% is a good prognostic indicator in HCM cases. ECV analysis on CT helped predict MACEs in HCM cases.
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