Precise 3D modeling of the mitral valve has the potential to improve our understanding of valve morphology, particularly in the setting of mitral regurgitation (MR). Toward this goal, the authors have developed a user-initialized algorithm for reconstructing valve geometry from transesophageal 3D ultrasound (3D US)image data.Methods:
Semi-automated image analysis was performed on transesophageal 3D USimages obtained from 14 subjects with MR ranging from trace to severe. Image analysis of the mitral valve at midsystole had two stages: user-initialized segmentation and 3D deformable modeling with continuous medial representation (cm-rep). Semi-automated segmentation began with user-identification of valve location in 2D projection images generated from 3D US data. The mitral leaflets were then automatically segmented in 3D using the level set method. Second, a bileaflet deformable medial model was fitted to the binary valve segmentation by Bayesian optimization. The resulting cm-rep provided a visual reconstruction of the mitral valve, from which localized measurements of valve morphology were automatically derived. The features extracted from the fitted cm-rep included annular area, annular circumference, annular height, intercommissural width, septolateral length, total tenting volume, and percent anterior tenting volume. These measurements were compared to those obtained by expert manual tracing. Regurgitant orifice area (ROA) measurements were compared to qualitative assessments of MR severity. The accuracy of valve shape representation with cm-rep was evaluated in terms of the Dice overlap between the fitted cm-rep and its target segmentation.Results:
The morphological features and anatomic ROA derived from semi-automated image analysis were consistent with manual tracing of 3D USimage data and with qualitative assessments of MR severity made on clinical radiology. The fitted cm-reps accurately captured valve shape and demonstrated patient-specific differences in valve morphology among subjects with varying degrees of MR severity. Minimal variation in the Dice overlap and morphological measurements was observed when different cm-rep templates were used to initialize model fitting.Conclusions:
This study demonstrates the use of deformable medial modeling for semi-automated 3D reconstruction of mitral valve geometry using transesophageal 3D US. The proposed algorithm provides a parametric geometrical representation of the mitral leaflets, which can be used to evaluate valve morphology in clinical ultrasoundimages.
This research was supported by the National Institutes of Health T32 EB009384 from the NIBIB, an American Heart Association Great Rivers Affiliate predoctoral fellowship (10PRE3510014), and the National Institutes of Health HL63954 and HL73021 from the NHLBI. P. Yushkevich’s effort in this project was supported by the National Institutes of Health K25 AG027785 and R21 NS061111. A. Jassar was supported by a postdoctoral fellowship from the American Heart Association, and M. Vergnat was supported by a French Federation of Cardiology Research Grant.
II. MATERIALS AND METHODS
II.A. Image acquisition
II.B. Semi-automated valve morphometry
II.B.1. User-initialized segmentation
II.B.2. Deformable medial modeling
II.C. Manual valve delineation
II.D. Feature extraction
II.E. Comparison of manual and semi-automated valve delineation
II.F. Evaluation of valve shape approximation bias
II.G. ROA sensitivity analysis
III.A. Accuracy of semi-automated valve morphometry
III.B. Accuracy of valve shape approximation with cm-rep
III.C. Clinical relevance of automatically derived leaflet thickness and curvature measurements
- Medical imaging
- Image analysis
- Medical image segmentation
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