TOWARDS PATIENT-SPECIFIC SURGICAL PLANNING FOR BICUSPID AORTIC VALVE REPAIR: FULLY AUTOMATED SEGMENTATION OF THE AORTIC VALVE IN 4D CT.
Publication/Presentation Date
4-1-2025
Abstract
The bicuspid aortic valve (BAV) is the most prevalent congenital heart defect and may require surgery for complications such as stenosis, regurgitation, and aortopathy. BAV repair surgery is effective but challenging due to the heterogeneity of BAV morphology. Multiple imaging modalities can be employed to assist the quantitative assessment of BAVs for surgical planning. Contrast-enhanced 4D computed tomography (CT) produces volumetric temporal sequences with excellent contrast and spatial resolution. Segmentation of the aortic cusps and root in these images is an essential step in creating patient-specific models for visualization and quantification. While deep learning-based methods are capable of fully automated segmentation, no BAV-specific model exists. Among valve segmentation studies, there has been limited quantitative assessment of the clinical usability of the segmentation results. In this work, we developed a fully automated multi-label BAV segmentation pipeline based on nnU-Net. The predicted segmentations were used to carry out surgically relevant morphological measurements including geometric cusp height, commissural angle and annulus diameter, and the results were compared against manual segmentation. Automated segmentation achieved average Dice scores of over 0.7 and symmetric mean distance below 0.7 mm for all three aortic cusps and the root wall. Clinically relevant benchmarks showed good consistency between manual and predicted segmentations. Overall, fully automated BAV segmentation of 3D frames in 4D CT can produce clinically usable measurements for surgical risk stratification, but the temporal consistency of segmentations needs to be improved.
Volume
2025
ISSN
1945-7928
Published In/Presented At
Guo, Z., Dong, N. J., Litt, H., Yushkevich, N., Freas, M., Nunez, J., Ferrari, V., Hao, J., Goldfinger, S., Jolley, M. A., Bavaria, J., Desai, N., & Pouch, A. M. (2025). TOWARDS PATIENT-SPECIFIC SURGICAL PLANNING FOR BICUSPID AORTIC VALVE REPAIR: FULLY AUTOMATED SEGMENTATION OF THE AORTIC VALVE IN 4D CT. Proceedings. IEEE International Symposium on Biomedical Imaging, 2025, 10.1109/ISBI60581.2025.10981269. https://doi.org/10.1109/ISBI60581.2025.10981269
Disciplines
Medicine and Health Sciences
PubMedID
40630832
Department(s)
Department of Surgery
Document Type
Article