Brain shift modeling for use in neurosurgery

Abstract

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. IntroductionThe use of surgical navigation systems is a standard way to assist the neurosurgeon in navigating within the intraoperative environment, allowing her or him to "see" through the body and relate the position of the surgical instruments to the features in preoperative images. It is important that these systems be as precise as possible. Ideally, they should provide a 3D display of the neuroanatomical structures of interest and include visualization of surgical instruments within the same frame. Furthermore, if 3D acquisition systems were fast enough, brain shift would not cause an error. Thus, the ideal goal would be to sense 3D intraoperative volumetric information in real time. Since the brain deforms rather slowly even a slower acquisition rate would be acceptable. However, hardware for obtaining true 3D data is limited probably to MR or CT and is typically bulky and expensive, restricting surgical access and therefore is not currently widely used in the OR 1.1 There exists a system using intraoperative MRI (see [5] and [6]) but it does not provide a complete 3D dataset of the head at a fast enough rate, but rather single slices at lower fields.

Model-Updated Image Guidance: A Statistical Approach to Gravity-Induced Brain Shift

“…Various computational models based on different physical and biomechanical principles have been developed [6,7]. The biphasic model used by Miga et al has been shown to compensate for 70-80% of the intraoperative brain shift.…”

A New Biomechanical Model Based Approach on Brain Shift Compensation

“…Without intraoperative 3D imaging, as in Ferrant et al [1], we can only access displacement of open brain surfaces, which is not sufficient to estimate deeper structures' displacement. To deal with such problems, challenging approaches have been conducted by Miga et al who modeled buoyancy change due to the loss of CSF [4], and by Skrinjar et al who incorporated brain-skull contact model into their analysis [7]. Both attempts have included the interaction between the brain and its surroundings into their biomechanical models.…”

Registration of 3D Intraoperative MR Images of the Brain Using a Finite Element Biomechanical Model

“…Skrinjar et al [15,7] have proposed a model consisting of mass nodes interconnected by Kelvin models to simulate the behavior of brain tissue under gravity, with boundary conditions to model the interaction of the brain with the skull. Miga et al [3,5,6] proposed a Finite Element (FE) model based on consolidation theory where the brain is modeled as an elastic body with an intersticial fluid.…”