On Extended Finite Element Method (XFEM) for Modelling of Organ Deformations Associated with Surgical Cuts

2D XFEM-based modeling of retraction and successive resections for preoperative image update

This paper considers an approach to improving outcomes for neurosurgery patients by enhancing intraoperative navigation and guidance. Currently, intraoperative navigation systems do not accurately account for brain shift or tissue resection. We describe how preoperative images can be incrementally updated to take into account any type of brain tissue deformation that may occur during surgery, and thus to improve the accuracy of image-guided navigation systems. For this purpose, we have developed a non-rigid image registration technique using a biomechanical model, which deforms based on the Finite Element Method (FEM). While the FEM has been used successfully for dealing with deformations such as brain shift, it has difficulty with tissue discontinuities. Here, we describe a novel application of the eXtended Finite Element Method (XFEM) in the field of image-guided surgery in order to model brain deformations that imply tissue discontinuities. In particular, this paper presents a detailed account of the use of XFEM for dealing with retraction and successive resections, and demonstrates the feasibility of the approach by considering 2D examples based on intraoperative MR images. To evaluate our results, we compute the modified Hausdorff distance between Canny edges extracted from images before and after registration. We show that this distance decreases after registration, and thus demonstrate that our approach improves alignment of intraoperative images.

Application of soft tissue modelling to image-guided surgery

The deformation of soft tissue compromises the accuracy of image-guided surgery based on preoperative images, and restricts its applicability to surgery on or near bony structures. One way to overcome these limitations is to combine biomechanical models with sparse intraoperative data, in order to realistically warp the preoperative image to match the surgical situation. We detail the process of biomechanical modelling in the context of image-guided surgery. We focus in particular on the finite element method, which is shown to be a promising approach, and review the constitutive relationships which have been suggested for representing tissue during surgery. Appropriate intraoperative measurements are required to constrain the deformation, and we discuss the potential of the modalities which have been applied to this task. This technology is on the verge of transition into clinical practice, where it promises to increase the guidance accuracy and facilitate less invasive interventions. We describe here how soft tissue modelling techniques have been applied to image-guided surgery applications.