Dataset Information

Segmentation of Tricuspid Valve Leaflets From Transthoracic 3D Echocardiograms of Children With Hypoplastic Left Heart Syndrome Using Deep Learning.

ABSTRACT: Hypoplastic left heart syndrome (HLHS) is a severe congenital heart defect in which the right ventricle and associated tricuspid valve (TV) alone support the circulation. TV failure is thus associated with heart failure, and the outcome of TV valve repair are currently poor. 3D echocardiography (3DE) can generate high-quality images of the valve, but segmentation is necessary for precise modeling and quantification. There is currently no robust methodology for rapid TV segmentation, limiting the clinical application of these technologies to this challenging population. We utilized a Fully Convolutional Network (FCN) to segment tricuspid valves from transthoracic 3DE. We trained on 133 3DE image-segmentation pairs and validated on 28 images. We then assessed the effect of varying inputs to the FCN using Mean Boundary Distance (MBD) and Dice Similarity Coefficient (DSC). The FCN with the input of an annular curve achieved a median DSC of 0.86 [IQR: 0.81-0.88] and MBD of 0.35 [0.23-0.4] mm for the merged segmentation and an average DSC of 0.77 [0.73-0.81] and MBD of 0.6 [0.44-0.74] mm for individual TV leaflet segmentation. The addition of commissural landmarks improved individual leaflet segmentation accuracy to an MBD of 0.38 [0.3-0.46] mm. FCN-based segmentation of the tricuspid valve from transthoracic 3DE is feasible and accurate. The addition of an annular curve and commissural landmarks improved the quality of the segmentations with MBD and DSC within the range of human inter-user variability. Fast and accurate FCN-based segmentation of the tricuspid valve in HLHS may enable rapid modeling and quantification, which in the future may inform surgical planning. We are now working to deploy this network for public use.

SUBMITTER: Herz C

PROVIDER: S-EPMC8696083 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The tricuspid valve ensures unidirectional blood flow from the right atrium to the right ventricle. The three tricuspid leaflets operate within a dynamic stress environment of shear, bending, tensile, and compressive forces, which is cyclically repeated nearly three billion times in a lifetime. Ostensibly, the microstructural and mechanical properties of the tricuspid leaflets have mechanobiologically evolved to optimally support their function under those forces. Yet, how the tricuspid leaflet microstructure determines its mechanical properties and whether this relationship differs between the three leaflets is unknown. Here we perform a microstructural and mechanical analysis in matched ovine tricuspid leaflet samples. We found that the microstructure and mechanical properties vary among the three tricuspid leaflets in sheep. Specifically, we found that tricuspid leaflet composition, collagen orientation, and valve cell nuclear morphology are spatially heterogeneous and vary across leaflet type. Furthermore, under biaxial tension, the leaflets' mechanical behaviors exhibited unequal degrees of mechanical anisotropy. Most importantly, we found that the septal leaflet was stiffer in the radial direction and not the circumferential direction as with the other two leaflets. The differences we observed in leaflet microstructure coincide with the varying biaxial mechanics among leaflets. Our results demonstrate the structure-function relationship for each leaflet in the tricuspid valve. We anticipate our results to be vital toward developing more accurate, leaflet-specific tricuspid valve computational models. Furthermore, our results may be clinically important, informing differential surgical treatments of the tricuspid valve leaflets. Finally, the identified structure-function relationships may provide insight into the homeostatic and remodeling potential of valvular cells in altered mechanical environments, such as in diseased or repaired tricuspid valves. STATEMENT OF SIGNIFICANCE: Our work is significant as we investigated the structure-function relationship of ovine tricuspid valve leaflets. This is important as tricuspid valves fail frequently and our current approach to repairing them is suboptimal. Specifically, we related the distribution of structural and cellular elements, such as collagen, glycosaminoglycans, and cell nuclei, to each leaflet's mechanical properties. We found that leaflets have different structures and that their mechanics differ. This may, in the future, inform leaflet-specific treatment strategies and help optimize surgical outcomes.

Dataset Information

Segmentation of Tricuspid Valve Leaflets From Transthoracic 3D Echocardiograms of Children With Hypoplastic Left Heart Syndrome Using Deep Learning.

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