Early Deformation of Deep Brain Stimulation Electrodes Following Surgical Implantation: Intracranial, Brain, and Electrode Mechanics

IntroductionAlthough deep brain stimulation is nowadays performed worldwide, the biomechanical aspects of electrode implantation received little attention, mainly as physicians focused on the medical aspects, such as the optimal indication of the surgical procedure, the positive and adverse effects, and the long-term follow-up. We aimed to describe electrode deformations and brain shift immediately after implantation, as it may highlight our comprehension of intracranial and intracerebral mechanics.Materials and MethodsSixty electrodes of 30 patients suffering from severe symptoms of Parkinson’s disease and essential tremor were studied. They consisted of 30 non-directional electrodes and 30 directional electrodes, implanted 42 times in the subthalamus and 18 times in the ventrolateral thalamus. We computed the x (transversal), y (anteroposterior), z (depth), torsion, and curvature deformations, along the electrodes from the entrance point in the braincase. The electrodes were modelized from the immediate postoperative CT scan using automatic voxel thresholding segmentation, manual subtraction of artifacts, and automatic skeletonization. The deformation parameters were computed from the curve of electrodes using a third-order polynomial regression. We studied these deformations according to the type of electrodes, the clinical parameters, the surgical-related accuracy, the brain shift, the hemisphere and three tissue layers, the gyration layer, the white matter stem layer, and the deep brain layer (type I error set at 5%).ResultsWe found that the implanted first hemisphere coupled to the brain shift and the stiffness of the type of electrode impacted on the electrode deformations. The deformations were also different according to the tissue layers, to the electrode type, and to the first-hemisphere-brain-shift effect.ConclusionOur findings provide information on the intracranial and brain biomechanics and should help further developments on intracerebral electrode design and surgical issues

METHODS FOR HIGH-PRECISION AND MINIMALLY INVASIVE MICRO-ELECTRODE INSERTION IN DEEP BRAIN STIMULATION

Ph.DDOCTOR OF PHILOSOPH

Computational modelling of brain shift in stereotactic neurosurgery

Navigation in stereotactic neurosurgery relies solely on preoperative images, with the location of anatomical targets defined relative to the skull. Displacement of the anatomical target from its expected position is a common complication during surgery; however, the magnitude of this deviation is currently unpredictable. One potential source of this error occurs with reorientation of the head alone and is known as positional brain shift (PBS). PBS is the focus of this thesis, which aims to better understand the phenomenon through computational methods. A finite element (FE) model was generated in FEBio, incorporating a novel spring element/fluid structure-interaction representation of the pia-arachnoid complex (PAC). The model was loaded to represent gravity in the prone and supine positions. Material parameter identification and sensitivity analysis were performed using statistical software, comparing the FE results to human in-vivo measurements. Results for the brain Ogden parameters

Analysis of electrode deformations in deep brain stimulation surgery.

International audiencePURPOSE : 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