Abstract
Hypoplastic left heart syndrome (HLHS) is a congenital heart disease characterized by incomplete development of the left heart. Children with HLHS undergo a series of operations which result in the tricuspid valve (TV) becoming the only functional atrioventricular valve. Some of those patients develop tricuspid regurgitation which is associated with heart failure and death and necessitates further surgical intervention. Repair of the regurgitant TV, and understanding the connections between structure and function of this valve remains extremely challenging. Adult cardiac populations have used 3D echocardiography (3DE) combined with computational modeling to better understand cardiac conditions affecting the TV. However, these structure-function analyses rely on simplistic point-based techniques that do not capture the leaflet surface in detail, nor do they allow robust comparison of shapes across groups. We propose using statistical shape modeling and analysis of the TV using Spherical Harmonic Representation Point Distribution Models (SPHARM-PDM) in order to generate a reproducible representation, which in turn enables high dimensional low sample size statistical analysis techniques such as principal component analysis and distance weighted discrimination. Our initial results suggest that visualization of the differences in regurgitant vs. non-regurgitant valves can precisely locate populational structural differences as well as how an individual regurgitant valve differs from the mean shape of functional valves. We believe that these results will support the creation of modern image-based modeling tools, and ultimately increase the understanding of the relationship between valve structure and function needed to inform and improve surgical planning in HLHS.
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Acknowledgements
Research reported in this publication was supported by the National Institute of Biomedical Imaging and Bioengineering from the National Institutes of Health under Award Number R01HL153166 as well as the National Institute of Biomedical Imaging and Bioengineering under award number R01EB021391. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The methods presented in this work are distributed as part of SlicerSALT [14], an open-source, free, comprehensive software that will allow biomedical scientists to precisely locate shape changes in their imaging studies, and SlicerHeart [2, 3], a 3DSlicer extension containing tools for cardiac image import (3D/4D ultrasound, CT, MRI), quantification, and implant placement planning and assessment.
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Vicory, J. et al. (2022). Statistical Shape Analysis of the Tricuspid Valve in Hypoplastic Left Heart Syndrome. In: Puyol Antón, E., et al. Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. STACOM 2021. Lecture Notes in Computer Science(), vol 13131. Springer, Cham. https://doi.org/10.1007/978-3-030-93722-5_15
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