Brain shift computation using a fully nonlinear biomechanical model

Authors:
Adam Wittek;Ron Kikinis;Simon K. Warfield;Karol Miller
Affiliations:
Intelligent Systems for Medicine Laboratory, School of Mechanical Engineering, The University of Western Australia, Crawley/Perth WA Australia;Surgical Planning Laboratory, Brigham and Women's Hospital, Children's Hospital and Harvard Medical School, Boston, MA;Computational Radiology Laboratory, Brigham and Women's Hospital, Children's Hospital and Harvard Medical School, Boston, MA;Intelligent Systems for Medicine Laboratory, School of Mechanical Engineering, The University of Western Australia, Crawley/Perth WA Australia
Venue:
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Year:
2005

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Abstract

In the present study, fully nonlinear (i.e. accounting for both geometric and material nonlinearities) patient specific finite element brain model was applied to predict deformation field within the brain during the craniotomyinduced brain shift. Deformation of brain surface was used as displacement boundary conditions. Application of the computed deformation field to align (i.e. register) the preoperative images with the intraoperative ones indicated that the model very accurately predicts the displacements of gravity centers of the lateral ventricles and tumor even for very limited information about the brain surface deformation. These results are sufficient to suggest that nonlinear biomechanical models can be regarded as one possible way of complementing medical image processing techniques when conducting nonrigid registration. Important advantage of such models over the linear ones is that they do not require unrealistic assumptions that brain deformations are infinitesimally small and brain tissue stress-strain relationship is linear.