Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time; Application to non-rigid neuroimage registration

Abstract

Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using a NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer.

From Finite Element Meshes to Clouds of Points: A Review of Methods for Generation of Computational Biomechanics Models for Patient-Specific Applications

“…108 (b) Hexa-dominant mesh created using a multiblock technique for the patient specific geometry shown in (a). The mesh was applied for computing the brain deformations due to craniotomy induced brain shift.…”

“…The mesh was applied for computing the brain deformations due to craniotomy induced brain shift. 108 Poor quality hexahedral elements were replaced by tetrahedral elements. Because of irregular/complex geometry of ventricles and tumor, tetrahedral elements dominate the mesh of ventricles, tumor and parenchyma areas adjacent to the tumor and ventricles.…”

“…Because of irregular/complex geometry of ventricles and tumor, tetrahedral elements dominate the mesh of ventricles, tumor and parenchyma areas adjacent to the tumor and ventricles. Adapted from Wittek et al 108 tations. Alternative solutions have been proposed.…”

“…Therefore, it is possible to determine deformations of soft organs during surgery without knowledge of patient-specific properties of tissues. 64,79,108 The second type of problems has been identified in the field of biomechanics of intracranial aneurysms that can be approximately modeled as pressure vessels that are known to be statically determinate. If we formulate the boundary value problem inversely, we are able to determine the aneurysm wall stress distribution without knowledge of patientspecific mechanical properties of the tissues comprising the wall.…”

Efficient Inverse Isoparametric Mapping Algorithm for Whole-Body Computed Tomography Registration Using Deformations Predicted by Nonlinear Finite Element Modeling

“…The magnitude of displacements was 20% of the wedge height. Computation of the deformation field within the continuum was performed using a total Lagrangian explicit dynamic algorithm that we have previously developed and verified in numerous applications in image-guided surgery [13,27,28]. The predicted shape of the wedge due to the prescribed displacements is shown in Fig.…”