Enhancement of subsurface brain shift model accuracy: a preliminary study

Biomechanical models that describe soft-tissue deformations provide a relatively inexpensive way to correct registration errors in image guided neurosurgical systems caused by non-rigid brain shifts. Quantifying the factors that cause this deformation to sufficient precision is a challenging task. To circumvent this difficulty, atlas-based method have been developed recently which allow for uncertainty yet still capture the first order effects associated with brain deformations. More specifically, the technique involves building an atlas of solutions to account for the statistical uncertainty in factors that control the direction and magnitude of brain shift. The inverse solution is driven by a sparse intraoperative surface measurement. Since this subset of data only provides surface information, it could bias the reconstruction and affect the subsurface accuracy of the model prediction. Studies in intraoperative MR have shown that the deformation in the midline, tentorium, and contralateral hemisphere is relatively small. The falx cerebri and tentorium cerebelli, two of the important dural septa, act as rigid membranes supporting the brain parenchyma and compartmentalizing the brain. Accounting for these structures in models may be an important key to improving subsurface shift accuracy. The goals of this paper are to describe a novel method developed to segment the tentorium cerebelli, develop the procedure for modeling the dural septa and study the effect of those membranes on subsurface brain shift.