Real-time prediction of brain shift using nonlinear finite element algorithms.
Patient-specific biomechanical models implemented using specialized nonlinear (i.e., taking into account material and geometric nonlinearities) finite element procedures were applied to predict the deformation field within the brain for five cases of craniotomy-induced brain shift. The procedures utilize the Total Lagrangian formulation with explicit time stepping. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register the preoperative images with the intraoperative ones indicated that the models very accurately predict the intraoperative positions and deformations of the brain anatomical structures for limited information about the brain surface deformations. For each case, it took less than 40 s to compute the deformation field using a standard personal computer, and less than 4 s using a Graphics Processing Unit (GPU). The results suggest that nonlinear biomechanical models can be regarded as one possible method of complementing medical image processing techniques when conducting non-rigid registration within the real-time constraints of neurosurgery.
Joldes
Grand Roman
GR
Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, 6009 Crawley/Perth, Western Australia, Australia. grandj@mech.uwa.edu.au
Wittek
Adam
A
Couton
Mathieu
M
Warfield
Simon K
SK
Miller
Karol
K
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology*; D003198:Computer Simulation; D003199:Computer Systems; D054459:Elasticity Imaging Techniques / Q000379:methods*; D020342:Finite Element Analysis; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008959:Models, Neurological; D017711:Nonlinear Dynamics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity