Moving Particle Semi-Implicit and Finite Element Method Coupled Analysis for Brain Shift Estimation

Neuronavigation is a computer-assisted technique for presenting three-dimensional images of a patient’s brain to facilitate immediate and precise lesion localization by surgeons. Neuronavigation systems use preoperative medical images of patients. In neurosurgery, when the dura mater and arachnoid membrane are incised and the cerebrospinal fluid (CSF) drains out, the brain loses the CSF buoyancy and deforms in the direction of gravity, which is referred to as brain shift. This brain shift yields inaccurate neuronavigation. To reduce this inaccuracy, an intraoperative brain shift should be estimated. This paper proposes a dynamic simulation method for brain-shift estimation combining the moving-particle semi-implicit (MPS) method and the finite element method (FEM). The CSF was modeled using fluid particles, whereas the brain parenchyma was modeled using finite elements (FEs). Node particles were attached to the surface nodes of the brain parenchyma in the FE model. The interaction between the CSF and brain parenchyma was simulated using the repulsive force between the fluid particles and node particles. Validation experiments were performed using a gelatin block. The gelatin block was dipped into silicone oil, which was then gradually removed; the block deformation owing to the buoyancy loss was measured. The experimental deformation data were compared with the results of the MPS-FEM coupled analysis. The mean absolute error (MAE) between the simulated deformation and the average across the four experiments was 0.26 mm, while the mean absolute percentage error (MAPE) was 27.7%. Brain-shift simulations were performed using the MPS-FEM coupled analysis, and the computational cost was evaluated.

Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery

Intraoperative brain shift during neurosurgical procedures is a well-known phenomenon caused by gravity, tissue manipulation, tumor size, loss of cerebrospinal fluid (CSF), and use of medication. For the use of image-guided systems, this phenomenon greatly affects the accuracy of the guidance. During the last several decades, researchers have investigated how to overcome this problem. The purpose of this paper is to present a review of publications concerning different aspects of intraoperative brain shift especially in a tumor resection surgery such as intraoperative imaging systems, quantification, measurement, modeling, and registration techniques. Clinical experience of using intraoperative imaging modalities, details about registration, and modeling methods in connection with brain shift in tumor resection surgery are the focuses of this review. In total, 126 papers regarding this topic are analyzed in a comprehensive summary and are categorized according to fourteen criteria. The result of the categorization is presented in an interactive web tool. The consequences from the categorization and trends in the future are discussed at the end of this work.

Analysis of electrode deformations in deep brain stimulation surgery

PURPOSE

Deep brain stimulation (DBS) surgery is used to reduce motor symptoms when movement disorders are refractory to medical treatment. Post-operative brain morphology can induce electrode deformations as the brain recovers from an intervention. The inverse brain shift has a direct impact on accuracy of the targeting stage, so analysis of electrode deformations is needed to predict final positions.

METHODS

DBS electrode curvature was evaluated in 76 adults with movement disorders who underwent bilateral stimulation, and the key variables that affect electrode deformations were identified. Non-linear modelling of the electrode axis was performed using post-operative computed tomography (CT) images. A mean curvature index was estimated for each patient electrode. Multivariate analysis was performed using a regression decision tree to create a hierarchy of predictive variables. The identification and classification of key variables that determine electrode curvature were validated with statistical analysis.

RESULTS

The principal variables affecting electrode deformations were found to be the date of the post-operative CT scan and the stimulation target location. The main pathology, patient's gender, and disease duration had a smaller although important impact on brain shift.

CONCLUSIONS

The principal determinants of electrode location accuracy during DBS procedures were identified and validated. These results may be useful for improved electrode targeting with the help of mathematical models.

Biomechanical simulation of electrode migration for deep brain stimulation

Deep Brain Stimulation is a modern surgical technique for treating patients who suffer from affective or motion disorders such as Parkinson's disease. The efficiency of the procedure relies heavily on the accuracy of the placement of a micro-electrode which sends electrical pulses to a specific part of the brain that controls motion and affective symptoms. However, targeting this small anatomical structure is rendered difficult due to a series of brain shifts that take place during and after the procedure. This paper introduces a biomechanical simulation of the intra and postoperative stages of the procedure in order to determine lead deformation and electrode migration due to brain shift. To achieve this goal, we propose a global approach, which accounts for brain deformation but also for the numerous interactions that take place during the procedure (contacts between the brain and the inner part of the skull and falx cerebri, effect of the cerebro-spinal fluid, and biomechanical interactions between the brain and the electrodes and cannula used during the procedure). Preliminary results show a good correlation between our simulations and various results reported in the literature.

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.

A light sterilizable pipette device for the in vivo estimation of human soft tissues constitutive laws

This paper introduces a new light device for the in vivo estimation of human soft tissues constitutive laws. It consists of an aspiration pipette able to meet the very severe sterilization and handling issues imposed during surgery. The simplicity of the device, free of any electronic circuitry, allows using it as an ancillary instrument. The deformation of the aspired tissue is imaged via a mirror using an external camera. The paper describes the experimental setup as well as the protocol that should be used during surgery. First feasibility measurements are shown for human tongue and forearm skin.