医学
肥厚性心肌病
外显率
自然史
心源性猝死
病理生理学
磁共振成像
心脏病学
心力衰竭
内科学
心肌病
表型
放射科
遗传学
生物
基因
作者
Ameya Baxi,Carlos S. Restrepo,Daniel Vargas,Alejandro Marmol-Velez,Daniel Ocazionez,Horacio Murillo
出处
期刊:Radiographics
[Radiological Society of North America]
日期:2016-03-01
卷期号:36 (2): 335-354
被引量:104
标识
DOI:10.1148/rg.2016150137
摘要
Hypertrophic cardiomyopathy (HCM) is a heterogeneous group of diseases related to sarcomere gene mutations exhibiting heterogeneous phenotypes with an autosomal dominant mendelian pattern of inheritance. The disorder is characterized by diverse phenotypic expressions and variable natural progression, which may range from dyspnea and/or syncope to sudden cardiac death. It is found across all racial groups and is associated with left ventricular hypertrophy in the absence of another systemic or cardiac disease. The management of HCM is based on a thorough understanding of the underlying morphology, pathophysiology, and clinical course. Imaging findings of HCM mirror the variable expressivity and penetrance heterogeneity, with the added advantage of diagnosis even in cases where a specific mutation may not yet be found. The diagnostic information obtained from imaging varies depending on the specific stage of HCM-phenotype manifestation, including the prehypertrophic, hypertrophic, and later stages of adverse remodeling into the burned-out phase of overt heart failure. However, subtle or obvious, these imaging findings become critical components in diagnosis, management, and follow-up of HCM patients. Although diagnosis of HCM traditionally relies on clinical assessment and transthoracic echocardiography, recent studies have demonstrated increased utility of multidetector computed tomography (CT) and particularly cardiac magnetic resonance (MR) imaging in diagnosis, phenotype differentiation, therapeutic planning, and prognostication. In this article, we provide an overview of the genetics, pathophysiology, and clinical manifestations of HCM, with the spectrum of imaging findings at MR imaging and CT and their contribution in diagnosis, risk stratification, and therapy. ©RSNA, 2016
科研通智能强力驱动
Strongly Powered by AbleSci AI