Dynamic Model-Driven Quantitative and Visual Evaluation of the Aortic Valve from 4D CT

Authors:
Razvan Ioan Ionasec;Bogdan Georgescu;Eva Gassner;Sebastian Vogt;Oliver Kutter;Michael Scheuering;Nassir Navab;Dorin Comaniciu
Affiliations:
Integrated Data Systems, Siemens Corporate Research, , Princeton, USA and Computer Aided Medical Procedures, , Technical University Munich, Germany;Integrated Data Systems, Siemens Corporate Research, , Princeton, USA;Department of Radiology, Medical University of South Carolina, Charleston, USA;Siemens Medical Solutions, Computed Tomography, Forchheim, Germany;Computer Aided Medical Procedures, , Technical University Munich, Germany;Siemens Medical Solutions, Computed Tomography, Forchheim, Germany;Computer Aided Medical Procedures, , Technical University Munich, Germany;Integrated Data Systems, Siemens Corporate Research, , Princeton, USA
Venue:
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Year:
2008

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Abstract

Aortic valve disease is an important cardio-vascular disorder, which affects 2.5% of the global population and often requires elaborate clinical management. Experts agree that visual and quantitative evaluation of the valve, crucial throughout the clinical workflow, is currently limited to 2D imaging which can potentially yield inaccurate measurements. In this paper, we propose a novel approach for morphological and functional quantification of the aortic valve based on a 4D model estimated from computed tomography data. A physiological model of the aortic valve, capable to express large shape variations, is generated using parametric splines together with anatomically-driven topological and geometrical constraints. Recent advances in discriminative learning and incremental searching methods allow rapid estimation of the model parameters from 4D Cardiac CT specifically for each patient. The proposed approach enables precise valve evaluation with model-based dynamic measurements and advanced visualization. Extensive experiments and initial clinical validation demonstrate the efficiency and accuracy of the proposed approach. To the best of our knowledge this is the first time such a patient specific 4D aortic valve model is proposed.