Cardiovascular magnetic resonance imaging characteristics and influence factors of aortic insufficiency patients with myocardial fibrosis

Abstract

Objective: To investigate the cardiovascular magnetic resonance (CMR) imaging characteristics and influence factors of aortic insufficiency (AI) patients with myocardial fibrosis. Method: This retrospective study included 59 AI patients who received CMR and transthoracic echocardiography (TTE) examinations from June 2011 to February 2015. AI patients were divided into 2 groups: bicuspid aortic valve (BAV) group (n=30) and non-BAV group (n=29). Patients were also divided into late gadolinium enhancement (LGE) group (n=27) and non-LGE group (n=32). The baseline clinical characteristics were collected through electronic medical records. Hemodynamic parameters such as grade of AI, cardiac functional parameters and LGE mass fraction (LGE%) were measured by CMR post-processing analysis. Kappa test was used to assess the consistency of AI severity between CMR and TTE, and the multivariate logistic regression analysis was performed to evaluate influence factors of myocardial fibrosis in AI patients. Results: (1) 56 (94.9%) patients were male, and the mean age was (44.2±11.0) years old. There was no significant difference in age and gender, hypertension, hyperlipidemia, alcoholic consumption between BAV and non-BAV group (all P>0.05). There were a higher proportion of smoking history (P=0.008), a lower body mass index (BMI) (P=0.020) in the LGE group than in the non-LGE group. (2) The accuracy of CMR in diagnosis of BAV was 96.7% (29/30) compared to the gold standard. In the BAV group, 20 patients (66.7%) were with fusion of left and right cusp (L-R), 5 patients (16.7%) were with fusion of right and noncoronary cusp (R-N), 5 patients (16.7%) were with fusion of left and noncoronary cusp (L-N); patients with BAV had larger left ventricular end diastolic volume index (LVEDVi), left ventricular end systolic volume index (LVESVi), higher proportion of LGE and lower left ventricular ejection fraction (LVEF) than those in non-BAV group (all P<0.05). There were 19 patients with BAV in the LGE group, the cases of L-R, R-N, L-N were 10 (52.6%), 5 (26.3%), and 4 (21.1%), respectively. In the non-LGE group, patients with BAV of L-R, R-N, L-N were 10 (90.9%), 0, and 1 (9.1%), respectively. Patients with LGE had lower body surface area (BSA), LVEF and larger LVEDVi, LVESVi, left ventricular mass index (LVMi) and higher proportion of BAV compared patients without LGE. In addition, the proportion of moderate and severe AI patients was significantly higher in BAV group than in non-BAV group (P=0.009). (3) The consistency of CMR and TTE in evaluating the severity of AI patients: the agreement between TTE and CMR regarding AI severity was satisfactory (kappa value was 0.624, 95%CI 0.402-0.831, P<0.001). (4) The linear regression analysis demonstrated a negative correlation between LVEF and LGE% in BAV and non-BAV group (P<0.001). The multivariate logistic regression analysis showed that the presence of BAV was an independent risk factor of left ventricucar fibrosis (OR=5.050, 95%CI 1.220-20.908, P=0.025) after adjustment for LVEF, hypertension, LVEDVi and LVMi. Conclusion: Multi-parametric CMR provides a satisfactory noninvasive tool for estimation of myocardial fibrosis and ventricular remodeling in patients with AI, and BAV is an independent risk factor for myocardial fibrosis in patients with AI.