Echocardiographic Differentiation of Pericardial Constriction and Left Ventricular Restriction

被引:5
作者
Grewal, Hardeep Kaur [1 ]
Bansal, Manish [1 ]
机构
[1] Medanta Medicity, Medanta Heart Inst, Gurgaon 122001, Haryana, India
关键词
Ventricular interdependence; Annulus paradoxus; Annulus reversus; Strain reversus; Myocardial deformation imaging; Machine learning; MITRAL ANNULAR VELOCITY; SPECKLE-TRACKING ECHOCARDIOGRAPHY; RESPIRATORY VARIATION; MAGNETIC-RESONANCE; CARDIAC MECHANICS; AMERICAN SOCIETY; TISSUE TRACKING; CARDIOMYOPATHY; DIAGNOSIS; DISEASE;
D O I
10.1007/s11886-022-01774-6
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Purpose of Review Overlapping hemodynamics in constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM) often pose difficulties in establishing accurate diagnosis. Echocardiography is the first-line imaging modality used for this purpose, but no single echocardiographic parameter is sufficiently robust for distinguishing between the two conditions. The newer developments may improve the diagnostic accuracy of echocardiography in this setting. Recent Findings Recent studies have validated multiparametric algorithms, based on conventional echocardiographic parameters, which enable high sensitivity and specificity for distinguishing between CP and RCM. In addition, myocardial deformation analysis using speckle-tracking echocardiography has revealed distinct pattern of abnormalities in the two conditions. CP is characterized by impaired left ventricular apical rotation with relatively preserved longitudinal strain, esp. of ventricular and atrial septum. In contrast, RCM results in global and marked impairment of left ventricular longitudinal strain with initially preserved circumferential mechanics. Combining multiple echocardiographic parameters into step-wise algorithms and incorporation of myocardial deformation analysis help improve the diagnostic accuracy of echocardiography for distinguishing between CP and RCM. The use of machine-learning may allow easy integration of a wide range of echocardiographic and clinical parameters to permit accurate, automated diagnosis, with less dependence on the user expertise.
引用
收藏
页码:1599 / 1610
页数:12
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