Brain shift modeling for use in neurosurgery

Abstract

Surgical navigation systems are used intraoperatively to help the surgeon to ascertain her or his position and to guide tools within the patient frame with respect to registered structures of interest in the preoperative images. However, these systems are subject to inaccuracy caused by intraoperative brain movement (brain shift) since they assume that the intracranial structures are rigid. Experiments show brain shifts of up to several millimeters, making it the cause of the dominant error in those systems. We propose a method for reducing this error based on a dynamic brain model. The initial model state is obtained from preoperative data. The brain tissue is modeled as a homogeneous linear visco-elastic material, although the model allows for setting the tissue properties locally. Gravity draws the brain downwards which in turn interacts with the skull and other surrounding structures. The simulation results are presented both for a 2D model (the mid-sagittal slice) and a 3D model. The results show the time evolution of the brain deformation. The complete 3D validation of the simulated brain deformation is a rather complicated task and is currently in progress within our laboratory, but a procedure is proposed for updating the model in time by one or more of several intraoperative measurements.