%0 Journal Article
%T Association between aortic valvular calcification and characteristics of the aortic valve in patients with bicuspid aortic valve stenosis
%A Bo Hwa Choi
%A Hyun Keun Chee
%A Jayoun Kim
%A Je Kyoun Shin
%A Jun Seok Kim
%A Sung Min Ko
%J Acta Radiologica
%@ 1600-0455
%D 2019
%R 10.1177/0284185118787359
%X Aortic valve calcification quantification using cardiac computed tomography (CCT) is a reliable marker for aortic stenosis (AS) in patients with bicuspid aortic valve (BAV) disease. To determine the association of Agatston aortic valve calcium score (AVCS) with morphological and hemodynamic characteristics of BAV and define cut-off AVCS for optimizing the grade of AS in patients with bicuspid AS. This study included 161 BAV patients with AS regardless of aortic regurgitation who underwent transthoracic echocardiography and CCT. BAVs were classified according to orientation of cusps and presence of raphe. Associations of AVCS with characteristics of BAV morphology and functional variables were determined by linear regression analysis. Area under the receiver operating characteristic curve (AUC) was used to determine the cut-off AVCS greater than which the diagnosis of severe AS was optimized. AVCS was significantly different according to sex (P£¿<£¿0.001), AS severity (P£¿<£¿0.001), type of valvular dysfunction (P£¿=£¿0.011), and orientation of cusps (P£¿=£¿0.028). Multiple linear regression showed that AVCS was significantly associated with sex (estimate£¿=£¿£¿0.583, P£¿<£¿0.001) and AS severity (estimate£¿=£¿0.817, P£¿<£¿0.001). AVCS was a predictor for severe AS with AUC of 0.80 in both women (P£¿=£¿0.002) and men (P£¿<£¿0.001). Its cut-off value was 1423 Agatston unit (AU) in women and 2573 AU in men. In patients with bicuspid AS, AVCS was significantly higher in men and those with severe AS. However, AVCS was not significantly associated with morphological characteristics of BAV or the type of valvular dysfunction
%K Aortic valve
%K aortic valve stenosis
%K calcium
%K echocardiography
%K multidetector computed tomography
%U https://journals.sagepub.com/doi/full/10.1177/0284185118787359