Capturing Brain Deformation

A critical challenge for the neurosurgeon during surgery is to be able to preserve healthy tissue and minimize the disruption of critical anatomical structures while at the same time removing as much tumor tissue as possible. Over the past several years we have developed intraoperative image processing algorithms with the goal of augmenting the surgeon's capacity to achieve maximal tumor resection while minimizing the disruption to normal tissue. The brain of the patient often changes shape in a nonrigid fashion over the course of a surgery, due to loss of cerebrospinal fluid, concomitant pressure changes, the impact of anaesthetics and the surgical resection itself. This further increases the challenge of visualizing and navigating critical brain structures. The primary concept of our approach is to exploit intraoperative image acquisition to directly visualize the morphology of brain as it changes over the course of the surgery, and to enhance the surgeon's capacity to visualize critical structures by projecting extensive preoperative data into the intraoperative configuration of the patient's brain. Our approach to tracking brain changes during neurosurgery has been previously described. We identify key structures in volumetric preoperative and intraoperative scans, and use the constraints provided by the matching of these key surfaces to compute a biomechanical simulation of the volumetric brain deformation. The recovered volumetric deformation field can then be applied to preoperative data sets, such as functional MRI (fMRI) or diffusion tensor MRI (DT-MRI) in order to warp this data into the new configuration of the patient's brain. In recent work we have constructed visualizations of preoperative fMRI and DT-MRI, and intraoperative MRI showing a close correspondence between the matched data. A further challenge of intraoperative image processing is that augmented visualizations must be presented to the neurosurgeon at a rate compatible with surgical decision making. We have previously demonstrated our biomechanical simulation of brain deformation can be executed entirely during neurosurgery. We used a generic atlas to provide surrogate information regarding the expected location of critical anatomical structures, and were able to project this data to match the patient and to display the matched data to the neurosurgeon during the surgical procedure. The use of patient-specific DTI and fMRI preoperative data significantly improves the localization of critical structures. The augmented visualization of intraoperative data with relevant preoperative data can significantly enhance the information available to the neurosurgeon.