Tuesday, April 1, 2025
4/1/2025
Secondary Analysis of 3D Echo Images of the Right Ventricle to Compute 3D Surface Strain - PROJECT SUMMARY Right Ventricular (RV) dysfunction is the primary cause of acute RV failure in pulmonary arterial hypertension (PAH). RV failure in turn is the cause of at least 70% of deaths in PAH patients and is almost universally correlated to poor prognosis. RV function is routinely assessed with echocardiography, which allows for dynamic visualization of RV motion as well as assessment of major cardiac structures. As part of a routine clinical exam, echo-derived global longitudinal strain (GLS) is measured from a two-dimensional echo (2DE) image; strain is a mechanical measure of cardiac deformation during RV contraction. GLS has been incorporated into recent echo guidelines, is emerging as a useful measure of RV systolic and diastolic function and has prognostic significance. GLS tends to be an earlier measure of ventricular dysfunction, with reduced values showing up before global function (as measured by ejection fraction, EF) is significantly reduced. However, the 2DE modality by which GLS is obtained is, by definition, confined to a 2D plane, and thus cannot fully visualize contractions over the asymmetrically shaped RV. We have recently developed an analysis of three-dimensional echo (3DE) image data that overcomes these limitations and provides 3D surface (3DS) strain values upon the entire RV surface. We have shown that these 3DS strains are in reasonable agreement with 2D GLS and further 1) provide additional deformational parameters such as shear strains and two normal principal strains (PS); 2) shown the PS have stronger correlation with EF compared to GLS and display disease-specific changes in direction on the ventricular surface. Below, we demonstrate preliminary evidence that these 3DS parameters have strong associations to one-year composite outcomes. We believe the 3DS strains add truly novel detail regarding how the RV deforms in three dimensions; although this work focuses on pediatric patients, initial work with our adult PAH collaborators suggests this holds true there as well. Overall, 3DS strain should allow for earlier bedside detection of ventricular dysfunction and in turn, earlier management changes for PAH patients. We now have a functional computational pipeline for the processing of strain data from clinical imaging; our secondary analysis goals for this proposal are to further enhance this pipeline to enable the routine spatial and temporal examination of 3D strains via machine learning and the comparison of these strain parameters to disease outcomes. Upon completion of these goals, we will be well-prepared to extend these studies into larger prospective populations, and even potentially transfer these concepts towards better characterization of LV function.
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