Open-source graphical user interface for the creation of synthetic skeletons for medical image analysis.

Purpose: Deformable medial modeling is an inverse skeletonization approach to representing anatomy in medical images, which can be used for statistical shape analysis and assessment of patient-specific anatomical features such as locally varying thickness. It involves deforming a pre-defined synthetic skeleton, or template, to anatomical structures of the same class. The lack of software for creating such skeletons has been a limitation to more widespread use of deformable medial modeling. Therefore, the objective of this work is to present an open-source user interface (UI) for the creation of synthetic skeletons for a range of medial modeling applications in medical imaging. Approach: A UI for interactive design of synthetic skeletons was implemented in 3D Slicer, an open-source medical image analysis application. The steps in synthetic skeleton design include importation and skeletonization of a 3D segmentation, followed by interactive 3D point placement and triangulation of the medial surface such that the desired branching configuration of the anatomical structure's medial axis is achieved. Synthetic skeleton design was evaluated in five clinical applications. Compatibility of the synthetic skeletons with open-source software for deformable medial modeling was tested, and representational accuracy of the deformed medial models was evaluated. Results: Three users designed synthetic skeletons of anatomies with various topologies: the placenta, aortic root wall, mitral valve, cardiac ventricles, and the uterus. The skeletons were compatible with skeleton-first and boundary-first software for deformable medial modeling. The fitted medial models achieved good representational accuracy with respect to the 3D segmentations from which the synthetic skeletons were generated. Conclusions: Synthetic skeleton design has been a practical challenge in leveraging deformable medial modeling for new clinical applications. This work demonstrates an open-source UI for user-friendly design of synthetic skeletons for anatomies with a wide range of topologies.

Modeling the Myxomatous Mitral Valve With Three-Dimensional Echocardiography.

BACKGROUND: Degenerative mitral valve disease is associated with variable and complex defects in valve morphology. Three-dimensional echocardiography (3DE) has shown promise in aiding preoperative planning for patients with this disease but to date has not been as transformative as initially predicted. The clinical usefulness of 3DE has been limited by the laborious methods currently required to extract quantitative data from the images. METHODS: To maximize the utility of 3DE for preoperative valve evaluation, this work describes an automated 3DE image analysis method for generating models of the mitral valve that are well suited for both qualitative and quantitative assessment. The method is unique in that it captures detailed alterations in mitral leaflet and annular morphology and produces image-derived models with locally varying leaflet thickness. The method is evaluated on midsystolic transesophageal 3DE images acquired from 22 subjects with myxomatous degeneration and from 22 subjects with normal mitral valve morphology. RESULTS: Relative to manual image analysis, the automated method accurately represents both normal and complex leaflet geometries with a mean boundary displacement error on the order of one image voxel. A detailed quantitative analysis of the valves is presented and reveals statistically significant differences between normal and myxomatous valves with respect to numerous aspects of annular and leaflet geometry. CONCLUSIONS: This work demonstrates a successful methodology for the relatively rapid quantitative description of the complex mitral valve distortions associated with myxomatous degeneration. The methodology has the potential to significantly improve surgical planning for patients with complex mitral valve disease.

Segmentation of the Aortic Valve Apparatus in 3D Echocardiographic Images: Deformable Modeling of a Branching Medial Structure.

3D echocardiographic (3DE) imaging is a useful tool for assessing the complex geometry of the aortic valve apparatus. Segmentation of this structure in 3DE images is a challenging task that benefits from shape-guided deformable modeling methods, which enable inter-subject statistical shape comparison. Prior work demonstrates the efficacy of using continuous medial representation (cm-rep) as a shape descriptor for valve leaflets. However, its application to the entire aortic valve apparatus is limited since the structure has a branching medial geometry that cannot be explicitly parameterized in the original cm-rep framework. In this work, we show that the aortic valve apparatus can be accurately segmented using a new branching medial modeling paradigm. The segmentation method achieves a mean boundary displacement of 0.6 ± 0.1 mm (approximately one voxel) relative to manual segmentation on 11 3DE images of normal open aortic valves. This study demonstrates a promising approach for quantitative 3DE analysis of aortic valve morphology.

Medially constrained deformable modeling for segmentation of branching medial structures: Application to aortic valve segmentation and morphometry.

Deformable modeling with medial axis representation is a useful means of segmenting and parametrically describing the shape of anatomical structures in medical images. Continuous medial representation (cm-rep) is a "skeleton-first" approach to deformable medial modeling that explicitly parameterizes an object's medial axis and derives the object's boundary algorithmically. Although cm-rep has effectively been used to segment and model a number of anatomical structures with non-branching medial topologies, the framework is challenging to apply to objects with branching medial geometries since branch curves in the medial axis are difficult to parameterize. In this work, we demonstrate the first clinical application of a new "boundary-first" deformable medial modeling paradigm, wherein an object's boundary is explicitly described and constraints are imposed on boundary geometry to preserve the branching configuration of the medial axis during model deformation. This "boundary-first" framework is leveraged to segment and morphologically analyze the aortic valve apparatus in 3D echocardiographic images. Relative to manual tracing, segmentation with deformable medial modeling achieves a mean boundary error of 0.41 ± 0.10 mm (approximately one voxel) in 22 3DE images of normal aortic valves at systole. Deformable medial modeling is additionally demonstrated on pathological cases, including aortic stenosis, Marfan syndrome, and bicuspid aortic valve disease. This study demonstrates a promising approach for quantitative 3DE analysis of aortic valve morphology.