In vivo quantification of a homogeneous brain deformation model for updating preoperative images during surgery

Clinicians using image-guidance for neurosurgical procedures have recently recognized that intraoperative deformation from surgical loading can compro mise the accuracy of patient registration in the operating room. While whol e brain intraoperative imaging is conceptually appealing it presents signif icant practical limitations, Alternatively, a promising approach may be to combine incomplete intraoperatively acquired data with a computational mode l of brain deformation to update high resolution preoperative images during surgery, The success of such an approach is critically dependent on identi fying a valid model of brain deformation physics. Towards this end, we eval uate a three-dimensional finite element consolidation theory model for pred icting brain deformation in vivo through a series of controlled repeat-expe riments. This database is used to construct an interstitial pressure bounda ry condition calibration curve which is prospectively tested in a fourth va lidation experiment, The computational model is found to recover 75%-85% of brain motion occurring under loads comparable to clinical conditions. Addi tionally, the updating of preoperative images using the model calculations is presented and demonstrates that model-updated image-guided neurosurgery may be a viable option for addressing registration errors related to intrao perative tissue motion.