Fully Automated 3D Segmentation and Diffeomorphic Medial Modeling of the Left Ventricle Mitral Valve Complex in Ischemic Mitral Regurgitation
•Ischemic mitral regurgitation is a ventricular disease that affects the mitral valve.•3D transesophageal echocardiography (TEE) is used for pre-surgical evaluation.•Medial preserving flows of diffeomorphisms prevent model self-intersection.•First left ventricle mitral valve segmentation and modelin...
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Veröffentlicht in: | Medical image analysis 2022-08, Vol.80, p.102513-102513, Article 102513 |
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Sprache: | eng |
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Zusammenfassung: | •Ischemic mitral regurgitation is a ventricular disease that affects the mitral valve.•3D transesophageal echocardiography (TEE) is used for pre-surgical evaluation.•Medial preserving flows of diffeomorphisms prevent model self-intersection.•First left ventricle mitral valve segmentation and modeling from 3D TEE algorithm.•This allows for more comprehensive and fully automated pre-surgical assessment.
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There is an urgent unmet need to develop a fully-automated image-based left ventricle mitral valve analysis tool to support surgical decision making for ischemic mitral regurgitation patients. This requires an automated tool for segmentation and modeling of the left ventricle and mitral valve from immediate pre-operative 3D transesophageal echocardiography. Previous works have presented methods for semi-automatically segmenting and modeling the mitral valve, but do not include the left ventricle and do not avoid self-intersection of the mitral valve leaflets during shape modeling. In this study, we develop and validate a fully automated algorithm for segmentation and shape modeling of the left ventricular mitral valve complex from pre-operative 3D transesophageal echocardiography. We performed a 3-fold nested cross validation study on two datasets from separate institutions to evaluate automated segmentations generated by nnU-net with the expert manual segmentation which yielded average overall Dice scores of 0.82±0.03 (set A), 0.87±0.08 (set B) respectively. A deformable medial template was subsequently fitted to the segmentation to generate shape models. Comparison of shape models to the manual and automatically generated segmentations resulted in an average Dice score of 0.93-0.94 and 0.75-0.81 for the left ventricle and mitral valve, respectively. This is a substantial step towards automatically analyzing the left ventricle mitral valve complex in the operating room. |
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ISSN: | 1361-8415 1361-8423 |
DOI: | 10.1016/j.media.2022.102513 |