Murphy I G, Collins J, Powell A, Markl M, McCarthy P, Malaisrie S C, Carr J C, Barker A J
Department of Radiology, Feinberg School of Medicine, Northwestern University, 737 N. Michigan Ave, Suite 1600, Chicago, IL, 60611, USA.
Department Biomedical Engineering, McCormick School of Engineering, Northwestern University, Chicago, IL, USA.
Int J Cardiovasc Imaging. 2017 Aug;33(8):1213-1221. doi: 10.1007/s10554-017-1107-1. Epub 2017 Mar 15.
Bicuspid aortic valve (BAV) disease is heterogeneous and related to valve dysfunction and aortopathy. Appropriate follow up and surveillance of patients with BAV may depend on correct phenotypic categorization. There are multiple classification schemes, however a need exists to comprehensively capture commissure fusion, leaflet asymmetry, and valve orifice orientation. Our aim was to develop a BAV classification scheme for use at MRI to ascertain the frequency of different phenotypes and the consistency of BAV classification. The BAV classification scheme builds on the Sievers surgical BAV classification, adding valve orifice orientation, partial leaflet fusion and leaflet asymmetry. A single observer successfully applied this classification to 386 of 398 Cardiac MRI studies. Repeatability of categorization was ascertained with intraobserver and interobserver kappa scores. Sensitivity and specificity of MRI findings was determined from operative reports, where available. Fusion of the right and left leaflets accounted for over half of all cases. Partial leaflet fusion was seen in 46% of patients. Good interobserver agreement was seen for orientation of the valve opening (κ = 0.90), type (κ = 0.72) and presence of partial fusion (κ = 0.83, p < 0.0001). Retrospective review of operative notes showed sensitivity and specificity for orientation (90, 93%) and for Sievers type (73, 87%). The proposed BAV classification schema was assessed by MRI for its reliability to classify valve morphology in addition to illustrating the wide heterogeneity of leaflet size, orifice orientation, and commissural fusion. The classification may be helpful in further understanding the relationship between valve morphology, flow derangement and aortopathy.
二叶式主动脉瓣(BAV)疾病具有异质性,与瓣膜功能障碍和主动脉病变相关。对BAV患者进行适当的随访和监测可能取决于正确的表型分类。目前有多种分类方案,但需要全面考虑瓣叶融合、瓣叶不对称以及瓣口方向。我们的目的是开发一种用于MRI的BAV分类方案,以确定不同表型的频率以及BAV分类的一致性。该BAV分类方案基于西弗斯(Sievers)手术BAV分类,增加了瓣口方向、部分瓣叶融合和瓣叶不对称的内容。一名观察者成功地将此分类应用于398项心脏MRI研究中的386项。通过观察者内和观察者间的kappa评分确定分类的可重复性。MRI检查结果的敏感性和特异性根据可用的手术报告来确定。左右瓣叶融合占所有病例的一半以上。46%的患者可见部分瓣叶融合。观察者间在瓣口方向(κ = 0.90)、类型(κ = 0.72)和部分融合的存在(κ = 0.83,p < 0.0001)方面具有良好的一致性。对手术记录的回顾性分析显示,瓣口方向的敏感性和特异性分别为90%和93%,西弗斯类型的敏感性和特异性分别为73%和87%。除了说明瓣叶大小、瓣口方向和瓣叶融合的广泛异质性外,还通过MRI评估了所提出的BAV分类模式对瓣膜形态分类的可靠性。该分类可能有助于进一步理解瓣膜形态、血流紊乱和主动脉病变之间的关系。