Purpose of review: Echocardiography is the mainstay in the diagnostic evaluation of constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM), but no single echocardiographic parameter is sufficiently robust to accurately distinguish between the two conditions. The present review summarizes the recent advances in echocardiography that promise to improve its diagnostic performance for this purpose. The role of other imaging modalities such as cardiac computed tomography, magnetic resonance imaging, and invasive hemodynamic assessment in the overall diagnostic approach is also discussed briefly.
Recent findings: A recent study has demonstrated improved diagnostic accuracy of echocardiography with integration of multiple conventional echocardiographic parameters in to a step-wise algorithm. Concurrently, the studies using speckle-tracking echocardiography have revealed distinct and disparate patterns of myocardial mechanical abnormalities in CP and RCM with their ability to distinguish between the two conditions. The incorporation of machine-learning algorithms into echocardiography workflow permits easy integration of the wealth of the diagnostic data available and promises to further enhance the diagnostic accuracy of echocardiography. New imaging algorithms are continuously being evolved to permit accurate distinction between CP and RCM. Further research is needed to validate the accuracy of these newer algorithms and to define their place in the overall diagnostic approach for this purpose.
Keywords: Machine-learning; Myocardial deformation imaging; Speckle tracking echocardiography.