Variable phenotypes of bicuspid aortic valve disease: classification by cardiovascular magnetic resonance

Buchner, Stefan and Huelsmann, Marion and Poschenrieder, Florian and Hamer, Okka W. and Fellner, Claudia and Kobuch, Reinhard and Feuerbach, Stefan and Riegger, Guenter A. J. and Djavidani, Behrus and Luchner, Andreas and Debl, Kurt (2010) Variable phenotypes of bicuspid aortic valve disease: classification by cardiovascular magnetic resonance. HEART, 96 (15). pp. 1233-1240. ISSN 1355-6037, 1468-201X

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Abstract

Background Recently, cardiovascular magnetic resonance (CMR) has been shown to allow accurate visualisation and quantification of aortic valve disease. Although bicuspid aortic valve (BAV) disease is relatively rare in the general population, the frequency is high in patients requiring valve surgery. The aim of the current study was to characterise the different phenotypes of BAV disease by CMR. Methods CMR studies were performed on a 1.5 T scanner in 105 patients with BAV. Results The pattern of BAV phenotypes was as follows: a raphe was identified in 90 patients (86%). Among patients with raphe, 76 patients had fusion between the right and left cusps (RL) and 14 patients had fusion between the right and the non-coronary cusps (RN). There were no significant differences in the aortic dimensions in the different BAV phenotypes. Conclusion CMR allows excellent characterisation of valve phenotype in patients with BAV. The present data demonstrate that a raphe is present in the vast majority of cases and RL fusion is the predominant phenotype of BAV. No significant differences in the aortic dimensions were observed.

Item Type: Article
Uncontrolled Keywords: CONGENITAL HEART-DISEASE; STATE FREE-PRECESSION; ASCENDING AORTA; STENOSIS; MORPHOLOGY; QUANTIFICATION; ECHOCARDIOGRAPHY; REPLACEMENT; AUTOPSY; REPAIR;
Subjects: 600 Technology > 610 Medical sciences Medicine
Divisions: Medicine > Lehrstuhl für Herz-, Thorax- und herznahe Gefäßchirurgie
Medicine > Lehrstuhl für Innere Medizin II
Medicine > Lehrstuhl für Röntgendiagnostik
Depositing User: Dr. Gernot Deinzer
Date Deposited: 20 Jul 2020 08:56
Last Modified: 20 Jul 2020 08:56
URI: https://pred.uni-regensburg.de/id/eprint/24388

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