Currently, the intra-operative visualization of vessels during endovascular aneurysm repair (EVAR) relies on contrast-based imaging modalities. Moreover, traditional image fusion techniques lack a continuous and automatic update of the vessel configuration, which changes due to the insertion of stiff guidewires. The purpose of this work is to develop and evaluate a novel approach to improve image fusion, that takes into account the deformations, combining electromagnetic (EM) tracking technology and finite element modeling (FEM). To assess whether EM tracking can improve the prediction of the numerical simulations, a patient-specific model of abdominal aorta was segmented and manufactured. A database of simulations with different insertion angles was created. Then, an ad hoc sensorized tool with three embedded EM sensors was designed, enabling tracking of the sensors' positions during the insertion phase. Finally, the corresponding cone beam computed tomography (CBCT) images were acquired and processed to obtain the ground truth aortic deformations of the manufactured model. Among the simulations in the database, the one minimizing the in silico versus in vitro discrepancy in terms of sensors' positions gave the most accurate aortic displacement results. The proposed approach suggests that the EM tracking technology could be used not only to follow the tool, but also to minimize the error in the predicted aortic roadmap, thus paving the way for a safer EVAR navigation.
Read full abstract