Real time 3D brain shift compensation

Abstract

Surgical navigation systems are used intraoperatively to provide the surgeon with a display of preoperative and intraoperative data in the same coordinate system and help her or him guide the surgery. However, these systems are subject to inaccuracy caused by intraoperative brain movement (brain shift) since commercial systems in use today typically assume that the intracranial structures are rigid. Experiments show brain shifts up to several millimeters, making it the cause of the dominant error in the system. We propose an image-based brain shift compensation system based on an intraoperatively guided deformable model. We have recorded a set of brain surface points during the surgery and used them to guide and/or validate the model predictions. Initial results show that this system limits the error between its brain surface prediction and real brain surfaces to within 0.5 mm, which is a significant improvement over the systems that are based on the rigid brain assumption, that in this case would have an error of 3 mm or greater.