A methodology for guidewire simulation on patient specific data during vascular intervention
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Minimally-invasive surgery (MIS) has radically transformed traditional surgical techniques. However, with the currently available tools, the interventionalist has to rely solely on his/her past experiences to place guidewire and stents at the desired location. While various valuable decision-making metrics have been developed to aid the interventionalist, recognition of the behavior of guidewires, catheters, stents, etc., inside patient-specific vessel data would enhance the reliability of his/her decisions. Such interventions are hard to simulate using analytical methods but may be modeled accurately by numerical techniques such as finite element methods (FEM). The goal of this thesis is to simulate the tool-vessel interaction on patient-specific vascular models extracted in near real-time and not just to provide an example of a model surgical procedure on standard anatomy. The proposed framework was implemented using C++ and OpenInventor. The validity of the methodology was demonstrated using both clinical and synthetic data. We see this system as an important step to providing valuable information to the interventionalist to make his decisions more reliable.