Machine-learning phenotypic classification of bicuspid aortopathy

The Journal of Thoracic and Cardiovascular Surgery

Eric E. Roselli¹  Jay J. Idrees²  Theresa A. Carnes³  Yuanjia Zhu⁴  Charles M. Wojnarski⁵ 

[1] Aortic Center, Miller Family Heart and Vascular Institute, Cleveland, Ohio;Cleveland Clinic Lerner College of Medicine, Cleveland, Ohio;Department of Cardiovascular Medicine, Miller Family Heart and Vascular Institute, Cleveland, Ohio;Department of Quantitative Health Sciences, Research Institute, Cleveland Clinic, Cleveland, Ohio;Department of Thoracic and Cardiovascular Surgery, Miller Family Heart and Vascular Institute, Cleveland, Ohio

关键词: aneurysm;    aorta;    valves;   

DOI  :  10.1016/j.jtcvs.2017.08.123

学科分类：心脏病和心血管学

来源: Mosby, Inc.

【 摘 要 】

BackgroundBicuspid aortic valves (BAV) are associated with incompletely characterized aortopathy. Our objectives were to identify distinct patterns of aortopathy using machine-learning methods and characterize their association with valve morphology and patient characteristics.MethodsWe analyzed preoperative 3-dimensional computed tomography reconstructions for 656 patients with BAV undergoing ascending aorta surgery between January 2002 and January 2014. Unsupervised partitioning around medoids was used to cluster aortic dimensions. Group differences were identified using polytomous random forest analysis.ResultsThree distinct aneurysm phenotypes were identified: root (n = 83; 13%), with predominant dilatation at sinuses of Valsalva; ascending (n = 364; 55%), with supracoronary enlargement rarely extending past the brachiocephalic artery; and arch (n = 209; 32%), with aortic arch dilatation. The arch phenotype had the greatest association with right–noncoronary cusp fusion: 29%, versus 13% for ascending and 15% for root phenotypes (P P P P P ConclusionsThree distinct phenotypes of bicuspid valve–associated aortopathy were identified using machine-learning methodology. Patient characteristics and valvular dysfunction vary by phenotype, suggesting that the location of aortic pathology may be related to the underlying pathophysiology of this disease.

【 授权许可】

Unknown