Image-guided neurosurgery relies on accurate registration of the patient, the preoperative image series, and the surgical instruments in the same coordinate space. Recent clinical reports have documented the magnitude of gravity-induced brain deformation in the operating room and suggest these levels of tissue motion may compromise the integrity of such systems. We are investigating a model-based strategy which exploits the wealth of readily-available preoperative information in conjunction with intraoperatively acquired data to construct and drive a three dimensional (3-D) computational model which estimates volumetric displacements in order to update the neuronavigational image set. Using model calculations, the preoperative image database can be deformed to generate a more accurate representation of the surgical focus during an operation. In this paper, we present a preliminary study of four patients that experienced substantial brain deformation from gravity and correlate cortical shift measurements with model predictions. Additionally, we illustrate our image deforming algorithm and demonstrate that preoperative image resolution is maintained. Results over the four cases show that the brain shifted, on average, 5.7 mm in the direction of gravity and that model predictions could reduce this misregistration error to an average of 1.2 mm.

A strategy by which intraoperative brain deformation may be accounted for has been developed, validated in an animal model, and demonstrated clinically.

A strategy to update preoperative imaging for image-guided surgery using readily available intraoperative information has been developed and implemented. A patient-specific three-dimensional finite element model of the brain is generated from preoperative MRI and used to simulate deformation resulting from multiple surgical processes. Intraoperatively obtained sparse imaging data, such as from digital cameras or ultrasonography, is then used to prescribe the displacement of selected points within the model. Interpolation to the resolution of preoperative imaging may then be performed based upon the model. The algorithms for generation of the finite element model and for its subsequent deformation have been successfully validated using a pig brain model, and preliminary clinical application in the operating room has demonstrated feasibility.