ArticleStatistical atlases and computational models of the heart. STACOM (Workshop)2022
Statistical shape analysis of the tricuspid valve in hypoplastic left heart sydrome.
Article in Statistical atlases and computational models of the heart. STACOM (Workshop), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Euclidean and Shape-Based Analysis of the Dynamic Mitral Annulus in Children using a Novel Open-Source Framework.Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography · 2024Article
- Mesh2SSM: From Surface Meshes to Statistical Shape Models of Anatomy.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
- Tricuspid Valve Regurgitation in Hypoplastic Left Heart Syndrome: Current Insights and Future Perspectives.Journal of cardiovascular development and disease · 2023Review
- Visualization and Quantification of the Unrepaired Complete Atrioventricular Canal Valve Using Open-Source Software.Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography · 2022Article
- Skeletal model-based analysis of the tricuspid valve in hypoplastic left heart syndrome.Statistical atlases and computational models of the heart. STACOM (Workshop) · 2022Article
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
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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