A computational model for tracking subsurface tissue deformation during stereotactic neurosurgery

Recent advances in the field of sterotactic neurosurgery have made it possi ble to coregister preoperative computed tomography (CT) and magnetic resona nce (MR) images with instrument locations in the operating field. However, accounting for intraoperative movement of brain tissue remains a challengin g problem. While intraoperative CT and MR scanners record concurrent tissue motion, there is motivation to develop methodologies which would be signif icantly lower in cost and more widely available. The approach we present is a computational model of brain tissue deformation that could be used in co njunction with a limited amount of concurrently obtained operative data to estimate subsurface tissue motion. Specifically, we report on the initial d evelopment of a finite element model of brain tissue adapted from consolida tion theory. Validations of the computational mathematics in two and three dimensions are shown with errors of 1%-2% for the discretizations used. Exp erience with the computational strategy for estimating surgically induced b rain tissue motion in vivo is also presented. While the predicted tissue di splacements differ from measured values by about 15%, they suggest that exp loiting a physics-based computational framework for updating preoperative i maging databases during the course of surgery has considerable merit. Howev er, additional model and computational developments are needed before this approach can become a clinical reality.