Abstract
Mitral valve (MV) is often involved in cardiac diseases, with various pathological patterns that require a systemic view of the entire MV apparatus. Due to its complex shape and dynamics, patient-specific modeling of the MV constitutes a particular challenge. We propose a novel approach for personalized modeling of the dynamic MV and its subvalvular apparatus that ensures temporal consistency over the cardiac sequence and provides realistic deformations. The idea is to detect the anatomical MV components under constraints derived from the biomechanical properties of the leaflets. This is achieved by a robust two-step alternate algorithm that combines discriminative learning and leaflet biomechanics. Extensive evaluation on 200 transesophageal echochardiographic sequences showed an average Hausdorff error of 5.1mm at a speed of 9sec, which constitutes an improvement of up to 11.5% compared to purely data driven approaches. Clinical evaluation on 42 subjects showed, that the proposed fully-automatic approach could provide discriminant biomarkers to detect and quantify remodeling of annulus and leaflets in functional mitral regurgitation.
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References
Borger, M., Alam, A., Murphy, P., Doenst, T., David, T.: Chronic ischemic mitral regurgitation: Repair, replace or rethink? Ann. Thorac. Surg. (81), 1153–1161 (2006)
Votta, E., Caiani, E., Veronesi, F., Soncini, M., Montevecchi, F., Redaelli, A.: Mitral valve finite-element modelling from ultrasound data: a pilot study for a new approach to understand mitral function and clinical scenarios. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 366(1879), 3411 (2008)
Ionasec, R., Voigt, I., Georgescu, B., Wang, Y., Houle, H., Vega-Higuera, F., Navab, N., Comaniciu, D.: Patient-Specific Modeling and Quantification of the Aortic and Mitral Valves From 4-D Cardiac CT and TEE. IEEE Transactions on Medical Imaging 29(9), 1636–1651 (2010)
Heimann, T., Meinzer, H.P.: Statistical shape models for 3d medical image segmentation: A review. Medical Image Analysis 13(4), 543–563 (2009)
Papademetris, X., Sinusas, A.J., Dione, D.P., Duncan, J.S.: Estimation of 3D left ventricular deformation from echocardiography. Med. Image Anal. 5, 17–28 (2001)
Sermesant, M., Delingette, H., Ayache, N.: An electromechanical model of the heart for image analysis and simulation. IEEE Transactions in Medical Imaging 5(25), 612–625 (2006)
Zheng, Y., Barbu, A., Georgescu, B., Scheuering, M., Comaniciu, D.: Four-chamber heart modeling and automatic segmentation for 3-d cardiac ct volumes using marginal space learning and steerable features. IEEE Transactions on Medical Imaging 27(11), 1668–1681 (2008)
Schievano, S., Kunzelman, K., Nicosia, M., Cochran, R., Einstein, D., Khambadkone, S., Bonhoeffer, P.: Percutaneous mitral valve dilatation: Single balloon ver-sus double balloon. a finite element study. Journal of Heart Valve Disease 18(1), 28–34 (2009)
Nesme, M., Payan, Y., Faure, F.: Efficient, physically plausible finite elements. Eurographics (short papers), 77–80 (2005)
Calleja, A., Stiver, K., Thavendiranathan, P., Liu, S., Ionasec, R., Voigt, I., Houle, H., Michelis, N.D., Ryan, T., Vannan, M.: Automated Quantitative 3-D Echocardiography of The Surgical Mitral Valve Anatomy in Functional Mitral Regurgitation to Guide Mitral Valve Repair. In: Proceedings of the 22nd Annual Scientific Sessions of the American Society of Echocardiography (2011)
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Voigt, I. et al. (2011). Robust Physically-Constrained Modeling of the Mitral Valve and Subvalvular Apparatus. In: Fichtinger, G., Martel, A., Peters, T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6893. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23626-6_62
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DOI: https://doi.org/10.1007/978-3-642-23626-6_62
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