Objectives: The aim of this study was to investigate whether cluster analysis of left atrial and left ventricular (LV) mechanical deformation parameters provide sufficient information for Doppler-independent assessment of LV diastolic function.
Background: Medical imaging produces substantial phenotyping data, and superior computational analyses could allow automated classification of repetitive patterns into patient groups with similar behavior.
Methods: The authors performed a cluster analysis and developed a model of LV diastolic function from an initial exploratory cohort of 130 patients that was subsequently tested in a prospective cohort of 44 patients undergoing cardiac catheterization. Patients in both study groups had standard echocardiographic examination with Doppler-derived assessment of diastolic function. Both the left ventricle and the left atrium were tracked simultaneously using speckle-tracking echocardiography (STE) for measuring simultaneous changes in left atrial and ventricular volumes, volume rates, longitudinal strains, and strain rates. Patients in the validation group also underwent invasive measurements of pulmonary capillary wedge pressure and LV end diastolic pressure immediately after echocardiography. The similarity between STE and conventional 2-dimensional and Doppler methods of diastolic function was investigated in both the exploratory and validation cohorts.
Results: STE demonstrated strong correlations with the conventional indices and independently clustered the patients into 3 groups with conventional measurements verifying increasing severity of diastolic dysfunction and LV filling pressures. A multivariable linear regression model also allowed estimation of E/e' and pulmonary capillary wedge pressure by STE in the validation cohort.
Conclusions: Tracking deformation of the left-sided cardiac chambers from routine cardiac ultrasound images provides accurate information for Doppler-independent phenotypic characterization of LV diastolic function and noninvasive assessment of LV filling pressures.
Keywords: big-data analytics; diastolic dysfunction; left ventricular filling pressures; speckle-tracking echocardiography.
Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.