Diagnostic Cardiovascular Magnetic Resonance Imaging Criteria in Noncompaction Cardiomyopathy and the Yield of Genetic Testing

非致密性心肌病诊断性心血管磁共振成像标准及基因检测的诊断价值

阅读:1

Abstract

BACKGROUND: Noncompaction cardiomyopathy (NCCM) is characterized by a thickened myocardial wall with excessive trabeculations of the left ventricle, and ∼30% is explained by a (likely) pathogenic variant [(L)PV] in a cardiomyopathy gene. Diagnosing an (L)PV is important because it allows accurate identification of which relatives are at risk and helps predicting prognosis. The goal of this study was to assess which specific clinical and morphologic characteristics of the myocardium may predict an (L)PV and which of the cardiovascular magnetic resonance (CMR) diagnostic criteria for NCCM can best be used for that purpose. METHODS: Sixty-two patients with NCCM, diagnosed by means of echocardiographic Jenni criteria, underwent CMR imaging that was evaluated according the Petersen, Stacey, Jacquier, Captur, and Choi diagnostic CMR criteria for NCCM. Patients also underwent DNA testing and were stratified according to having an (L)PV. RESULTS: Thirty-three patients (53%) with NCCM had an (L)PV. The apical and mid-lateral segments were the dominant locations for meeting Petersen and/or Stacey criteria. Correlation between different CMR criteria varied from moderate to very strong. In multivariate binary logistic regression analysis with CMR and non-CMR parameters, independent positive predictors for an (L)PV were familial cardiomyopathy, trabecular mass, and meeting Petersen criteria in ≥ 2 out of 3 long-axis views, whereas left bundle branch block and hypertension were negative predictors. The receiver operating characteristic curve of this multivariate model had an area under the curve of 0.89 (95% confidence interval 0.82-0.97). CONCLUSIONS: CMR criteria together with family history help to distinguish those patients in whom an (L)PV can be identified, consequently leading to referral for genetic diagnostics and cascade screening.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。