Abstract
It has been demonstrated that 3D anatomical models can be used effectively as roadmaps in image guided interventions. However, besides the anatomical information also the integrated display of functional information is desirable. In particular, a number of procedures such as the treatment of coro nary artery disease by revascularization and myocardial repair by targeted cell delivery require information about myocardial viability. In this paper we show how we can determine myocardial viability and integrate the information into a patient-specific cardiac 3D model. In contrast to other work we associate the viability information directly with the 3D patient anatomy. Thus we ensure that the functional information can be visualized in a way suitable for interventional guidance. Furthermore we propose a workflow that allows the nearly automatic generation of the patient-specific model. Our work is based on a previously published cardiac model that can be automatically adapted to images from different modalities like CT and MR. To enable integration of myocardial viability we first define a new myocardium surface model that encloses the left ventricular cavity in a way that suits robust viability measurements. We modify the model-based segmentation method to allow accurate adaptation of this new model. Second, we extend the model and the segmentation method to incorporate volumetric tissue properties. We validate the accuracy of the segmentation of the left ventricular cavity systematically using clinical data and illustrate the complete method for integrating myocardial viability by an example.
The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 224495 (euHeart project).
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Lehmann, H. et al. (2009). Integrating Viability Information into a Cardiac Model for Interventional Guidance. In: Ayache, N., Delingette, H., Sermesant, M. (eds) Functional Imaging and Modeling of the Heart. FIMH 2009. Lecture Notes in Computer Science, vol 5528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01932-6_34
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DOI: https://doi.org/10.1007/978-3-642-01932-6_34
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