Patient-Specific Electric Field Simulations and Acceleration Measurements for Objective Analysis of Intraoperative Stimulation Tests in the Thalamus

Objective clinical registration of tremor, bradykinesia, and rigidity during awake stereotactic neurosurgery: a scoping review

Tremor, bradykinesia, and rigidity are incapacitating motor symptoms that can be suppressed with stereotactic neurosurgical treatment like deep brain stimulation (DBS) and ablative surgery (e.g., thalamotomy, pallidotomy). Traditionally, clinicians rely on clinical rating scales for intraoperative evaluation of these motor symptoms during awake stereotactic neurosurgery. However, these clinical scales have a relatively high inter-rater variability and rely on experienced raters. Therefore, objective registration (e.g., using movement sensors) is a reasonable extension for intraoperative assessment of tremor, bradykinesia, and rigidity. The main goal of this scoping review is to provide an overview of electronic motor measurements during awake stereotactic neurosurgery. The protocol was based on the PRISMA extension for scoping reviews. After a systematic database search (PubMed, Embase, and Web of Science), articles were screened for relevance. Hundred-and-three articles were subject to detailed screening. Key clinical and technical information was extracted. The inclusion criteria encompassed use of electronic motor measurements during stereotactic neurosurgery performed under local anesthesia. Twenty-three articles were included. These studies had various objectives, including correlating sensor-based outcome measures to clinical scores, identifying optimal DBS electrode positions, and translating clinical assessments to objective assessments. The studies were highly heterogeneous in device choice, sensor location, measurement protocol, design, outcome measures, and data analysis. This review shows that intraoperative quantification of motor symptoms is still limited by variable signal analysis techniques and lacking standardized measurement protocols. However, electronic motor measurements can complement visual evaluations and provide objective confirmation of correct placement of the DBS electrode and/or lesioning. On the long term, this might benefit patient outcomes and provide reliable outcome measures in scientific research.

Thalamic Segmentation and Neural Activation Modeling Based on Individual Tissue Microstructure in Deep Brain Stimulation for Essential Tremor

OBJECTIVE

Thalamic deep brain stimulation (DBS) is the primary surgical therapy for essential tremor (ET). Thalamic DBS traditionally uses an atlas-based targeting approach, which, although nominally accurate, may obscure individual anatomic differences from population norms. The objective of this study was to compare this traditional atlas-based approach with a novel quantitative modeling methodology grounded in individual tissue microstructure (N-of-1 approach).

MATERIALS AND METHODS

The N-of-1 approach uses individual patient diffusion tensor imaging (DTI) data to perform thalamic segmentation and volume of tissue activation (VTA) modeling. For each patient, the thalamus was individually segmented into 13 nuclei using DTI-based k-means clustering. DBS-induced VTAs associated with tremor suppression and side effects were then computed for each patient with finite-element electric-field models incorporating DTI microstructural data. Results from N-of-1 and traditional atlas-based modeling were compared for a large cohort of patients with ET treated with thalamic DBS.

RESULTS

The size and shape of individual N-of-1 thalamic nuclei and VTAs varied considerably across patients (N = 22). For both methods, tremor-improving therapeutic VTAs showed similar overlap with motor thalamic nuclei and greater motor than sensory nucleus overlap. For VTAs producing undesirable sustained paresthesia, 94% of VTAs overlapped with N-of-1 sensory thalamus estimates, whereas 74% of atlas-based segmentations overlapped. For VTAs producing dysarthria/motor contraction, the N-of-1 approach predicted greater spread beyond the thalamus into the internal capsule and adjacent structures than the atlas-based method.

CONCLUSIONS

Thalamic segmentation and VTA modeling based on individual tissue microstructure explain therapeutic stimulation equally well and side effects better than a traditional atlas-based method in DBS for ET. The N-of-1 approach may be useful in DBS targeting and programming, particularly when patient neuroanatomy deviates from population norms.

Toward a cerebello-thalamo-cortical computational model of spinocerebellar ataxia

Computational neural network modelling is an emerging approach for optimization of drug treatment of neurological disorders and fine-tuning of rehabilitation strategies. In the current study, we constructed a cerebello-thalamo-cortical computational neural network model to simulate a mouse model of cerebellar ataxia (pcd^5J mice) by manipulating cerebellar bursts through reduction of GABAergic inhibitory input. Cerebellar output neurons were projected to the thalamus and bidirectionally connected with the cortical network. Our results showed that reduction of inhibitory input in the cerebellum orchestrated the cortical local field potential (LFP) dynamics to generate specific motor outputs of oscillations of the theta, alpha, and beta bands in the computational model as well as in mouse motor cortical neurons. The therapeutic potential of deep brain stimulation (DBS) was tested in the computational model by increasing the sensory input to restore cortical output. Ataxia mice showed normalization of the motor cortex LFP after cerebellum DBS. We provide a novel approach to computational modelling to investigate the effect of DBS by mimicking cerebellar ataxia involving degeneration of Purkinje cells. Simulated neural activity coincides with findings from neural recordings of ataxia mice. Our computational model could thus represent cerebellar pathologies and provide insight into how to improve disease symptoms by restoring neuronal electrophysiological properties using DBS.

Deep Brain Stimulation: Emerging Tools for Simulation, Data Analysis, and Visualization

Deep brain stimulation (DBS) is a well-established neurosurgical procedure for movement disorders that is also being explored for treatment-resistant psychiatric conditions. This review highlights important consideration for DBS simulation and data analysis. The literature on DBS has expanded considerably in recent years, and this article aims to identify important trends in the field. During DBS planning, surgery, and follow up sessions, several large data sets are created for each patient, and it becomes clear that any group analysis of such data is a big data analysis problem and has to be handled with care. The aim of this review is to provide an update and overview from a neuroengineering perspective of the current DBS techniques, technical aids, and emerging tools with the focus on patient-specific electric field (EF) simulations, group analysis, and visualization in the DBS domain. Examples are given from the state-of-the-art literature including our own research. This work reviews different analysis methods for EF simulations, tractography, deep brain anatomical templates, and group analysis. Our analysis highlights that group analysis in DBS is a complex multi-level problem and selected parameters will highly influence the result. DBS analysis can only provide clinically relevant information if the EF simulations, tractography results, and derived brain atlases are based on as much patient-specific data as possible. A trend in DBS research is creation of more advanced and intuitive visualization of the complex analysis results suitable for the clinical environment.

Distribution of electric field in patients with obsessive compulsive disorder treated with deep brain stimulation of the bed nucleus of stria terminalis

Background

Deep brain stimulation (DBS) is being investigated as a treatment for therapy-refractory obsessive compulsive disorder (OCD). Many different brain targets are being trialled. Several of these targets such as the ventral striatum (including the nucleus accumbens (NAc)), the ventral capsule, the inferior thalamic peduncle, and the bed nucleus of stria terminalis (BNST)) belong to the same network, are anatomically very close to one another, or even overlap. Data is still missing on how various stimulation parameters in a given target will affect surrounding anatomical areas and impact the clinical outcome of DBS.

Methods

In a pilot study of eleven participants with DBS of the BNST, we investigate through patient-specific simulation of electric field, which anatomical areas are affected by the electric field, and if this can be related to the clinical results. Our study combined individual patient’s stimulation parameters at 12- and 24-month follow-up with image data from the preoperative MRI and postoperative CT. These data were used to calculate the distribution of electric field and create individual anatomical models of the field of stimulation.

Results

The individual electric stimulation fields by stimulation in the BNST were similar at both the 12- and 24-month follow-up, involving mainly anterior limb of the internal capsule (ALIC), genu of the internal capsule (IC), BNST, fornix, anteromedial globus pallidus externa (GPe), and the anterior commissure. A statistical significant correlation (p < 0.05) between clinical effect measured by the Yale-Brown Obsessive Compulsive Scale and stimulation was found at the 12-month follow-up in the ventral ALIC and anteromedial GPe.

Conclusions

Many of the targets under investigation for OCD are in anatomical proximity. As seen in our study, off-target effects are overlapping. Therefore, DBS in the region of ALIC, NAc, and BNST may perhaps be considered to be stimulation of the same target.

Postoperative Lead Movement after Deep Brain Stimulation Surgery and the Change of Stimulation Volume

INTRODUCTION

Lead movement after deep brain stimulation may occur and influence the affected volume of stimulation. The aim of the study was to investigate differences in lead position between the day after surgery and approximately 1 month postoperatively and also simulate the electric field (EF) around the active contacts in order to investigate the impact of displacement on affected volume.

METHODS

Twenty-three patients with movement disorders underwent deep brain stimulation surgery (37 leads). Computed tomography at the 2 time points were co-fused respectively with the stereotactic images in Surgiplan. The coordinates (x, y, and z) of the lead tips were compared between the 2 dates. Eleven of these patients were selected for the EF simulation in Comsol Multiphysics. Postoperative changes of EF spread in the tissue due to conductivity changes in perielectrode space and due to displacement were evaluated by calculating the coverage coefficient and the Sørensen-Dice coefficient.

RESULTS

There was a significant displacement (mean ± SD) on the left lead: x (0.44 ± 0.72, p < 0.01), y (0.64 ± 0.54, p < 0.001), and z (0.62 ± 0.71, p < 0.001). On the right lead, corresponding values were: x (-0.11 ± 0.61, ns), y (0.71 ± 0.54, p < 0.001), and z (0.49 ± 0.81, p < 0.05). The anchoring technique was a statistically significant variable associated with displacement. No correlation was found between bilateral (n = 14) versus unilateral deep brain stimulation, gender (n = 17 male), age <60 years (n = 8), and calculated air volume. The simulated stimulation volume was reduced after 1 month because of the perielectrode space. When considering perielectrode space and displacement, the volumes calculated the day after surgery and approximately 1 month later were partly overlapped.

CONCLUSION

The left lead tip displayed a tendency to move lateral, anterior, and inferior and the right a tendency to move anterior and inferior. The anchoring technique was associated to displacement. New brain territory was affected due to the displacement despite considering the reduced stimulated volume after 1 month. Postoperative changes in perielectrode space and small lead movements are reasons for delaying programming to 4 weeks following surgery.

Improved Vim targeting for focused ultrasound ablation treatment of essential tremor: A probabilistic and patient-specific approach

Magnetic resonance-guided focused ultrasound (MRgFUS) ablation of the ventral intermediate (Vim) thalamic nucleus is an incisionless treatment for essential tremor (ET). The standard initial targeting method uses an approximate, atlas-based stereotactic approach. We developed a new patient-specific targeting method to identify an individual's Vim and the optimal MRgFUS target region therein for suppression of tremor. In this retrospective study of 14 ET patients treated with MRgFUS, we investigated the ability of WMnMPRAGE, a highly sensitive and robust sequence for imaging gray matter-white matter contrast, to identify the Vim, FUS ablation, and a clinically efficacious region within the Vim in individual patients. We found that WMnMPRAGE can directly visualize the Vim in ET patients, segmenting this nucleus using manual or automated segmentation capabilities developed by our group. WMnMPRAGE also delineated the ablation's core and penumbra, and showed that all patients' ablation cores lay primarily within their Vim segmentations. We found no significant correlations between standard ablation features (e.g., ablation volume, Vim-ablation overlap) and 1-month post-treatment clinical outcome. We then defined a group-based probabilistic target, which was nonlinearly warped to individual brains; this target was located within the Vim for all patients. The overlaps between this target and patient ablation cores correlated significantly with 1-month clinical outcome (r = -.57, p = .03), in contrast to the standard target (r = -.23, p = .44). We conclude that WMnMPRAGE is a highly sensitive sequence for segmenting Vim and ablation boundaries in individual patients, allowing us to find a novel tremor-associated center within Vim and potentially improving MRgFUS treatment for ET.

Anatomical brain structures normalization for deep brain stimulation in movement disorders

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Non-linear iterative structural normalization method focused on the deep brain.

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Multi-modality image data from deep brain stimulation patients.

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Comparison of ANTS, FNIRT and DRAMMS for the non-linear registrations using different settings for each.

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Evaluation of the registration tools based on the analysis of 58 structures of the deep brain segmented manually by a single expert.

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ANTS was identified as the best performing non-linear registration tool.

Deep brain stimulation (DBS) therapy requires extensive patient-specific planning prior to implantation to achieve optimal clinical outcomes. Collective analysis of patient’s brain images is promising in order to provide more systematic planning assistance. In this paper the design of a normalization pipeline using a group specific multi-modality iterative template creation process is presented. The focus was to compare the performance of a selection of freely available registration tools and select the best combination. The workflow was applied on 19 DBS patients with T1 and WAIR modality images available. Non-linear registrations were computed with ANTS, FNIRT and DRAMMS, using several settings from the literature. Registration accuracy was measured using single-expert labels of thalamic and subthalamic structures and their agreement across the group. The best performance was provided by ANTS using the High Variance settings published elsewhere. Neither FNIRT nor DRAMMS reached the level of performance of ANTS. The resulting normalized definition of anatomical structures were used to propose an atlas of the diencephalon region defining 58 structures using data from 19 patients.

Stimulation maps: visualization of results of quantitative intraoperative testing for deep brain stimulation surgery

Deep brain stimulation (DBS) is an established therapy for movement disorders such as essential tremor (ET). Positioning of the DBS lead in the patient's brain is crucial for effective treatment. Extensive evaluations of improvement and adverse effects of stimulation at different positions for various current amplitudes are performed intraoperatively. However, to choose the optimal position of the lead, the information has to be "mentally" visualized and analyzed. This paper introduces a new technique called "stimulation maps," which summarizes and visualizes the high amount of relevant data with the aim to assist in identifying the optimal DBS lead position. It combines three methods: outlines of the relevant anatomical structures, quantitative symptom evaluation, and patient-specific electric field simulations. Through this combination, each voxel in the stimulation region is assigned one value of symptom improvement, resulting in the division of stimulation region into areas with different improvement levels. This technique was applied retrospectively to five ET patients in the University Hospital in Clermont-Ferrand, France. Apart from identifying the optimal implant position, the resultant nine maps show that the highest improvement region is frequently in the posterior subthalamic area. The results demonstrate the utility of the stimulation maps in identifying the optimal implant position. Graphical abstract.

White matter tracing combined with electric field simulation - A patient-specific approach for deep brain stimulation

OBJECTIVE

Deep brain stimulation (DBS) in zona incerta (Zi) is used for symptom alleviation in essential tremor (ET). Zi is positioned along the dentato-rubro-thalamic tract (DRT). Electric field simulations with the finite element method (FEM) can be used for estimation of a volume where the stimulation affects the tissue by applying a fixed isolevel (VDBS). This work aims to develop a workflow for combined patient-specific electric field simulation and white matter tracing of the DRT, and to investigate the influence on the VDBS from different brain tissue models, lead design and stimulation modes. The novelty of this work lies in the combination of all these components.

METHOD

Patients with ET were implanted in Zi (lead 3389, n = 3, voltage mode; directional lead 6172, n = 1, current mode). Probabilistic reconstruction from diffusion MRI (dMRI) of the DRT (n = 8) was computed with FSL Toolbox. Brain tissue models were created for each patient (two homogenous, one heterogenous isotropic, one heterogenous anisotropic) and the respective VDBS (n = 48) calculated from the Comsol Multiphysics FEM simulations. The DRT and VDBS were visualized with 3DSlicer and superimposed on the preoperative T2 MRI, and the common volumes calculated. Dice Coefficient (DC) and level of anisotropy were used to evaluate and compare the brain models.

RESULT

Combined patient-specific tractography and electric field simulation was designed and evaluated, and all patients showed benefit from DBS. All VDBS overlapped the reconstructed DRT. Current stimulation showed prominent difference between the tissue models, where the homogenous grey matter deviated most (67 < DC < 69). Result from heterogenous isotropic and anisotropic models were similar (DC > 0.95), however the anisotropic model consistently generated larger volumes related to a greater extension of the electric field along the DBS lead. Independent of tissue model, the steering effect of the directional lead was evident and consistent.

CONCLUSION

A workflow for patient-specific electric field simulations in combination with reconstruction of DRT was successfully implemented. Accurate tissue classification is essential for electric field simulations, especially when using the current control stimulation. With an accurate targeting and tractography reconstruction, directional leads have the potential to tailor the electric field into the desired region.

Patient-Specific Simulations of Deep Brain Stimulation Electric Field with Aid of In-house Software ELMA

Deep brain stimulation (DBS) is an established technique for reduction of symptoms in movement disorders. Finite element method (FEM) simulations of the electric field magnitude (EF) are useful for estimating the affected tissue around the DBS lead and this can help optimize the therapy. This paper describes how patient-specific FEM models can be set up with the aid of the Matlab-based in-house software tool ELMA. Electrode placement is determined from two coordinates in postoperative medical imaging and electric conductivity is assigned from preoperative magnetic resonance imaging (MRI) and patient-specific DBS data. Simulations are performed using the equation for steady currents in Comsol Multiphysics (CM). The simulated EF is superimposed on the preoperative MRI for evaluation of affected structures. The method is demonstrated with patient-specific simulations in the zona incerta and a globus pallidus example containing cysts with higher conductive which causes considerable distortion of the EF. The improved software modules and precise lead positioning simplifies and reduces the time for DBS EF modelling and simulation.

Electric Field Comparison between Microelectrode Recording and Deep Brain Stimulation Systems-A Simulation Study

The success of deep brain stimulation (DBS) relies primarily on the localization of the implanted electrode. Its final position can be chosen based on the results of intraoperative microelectrode recording (MER) and stimulation tests. The optimal position often differs from the final one selected for chronic stimulation with the DBS electrode. The aim of the study was to investigate, using finite element method (FEM) modeling and simulations, whether lead design, electrical setup, and operating modes induce differences in electric field (EF) distribution and in consequence, the clinical outcome. Finite element models of a MER system and a chronic DBS lead were developed. Simulations of the EF were performed for homogenous and patient-specific brain models to evaluate the influence of grounding (guide tube vs. stimulator case), parallel MER leads, and non-active DBS contacts. Results showed that the EF is deformed depending on the distance between the guide tube and stimulating contact. Several parallel MER leads and the presence of the non-active DBS contacts influence the EF distribution. The DBS EF volume can cover the intraoperatively produced EF, but can also extend to other anatomical areas. In conclusion, EF deformations between stimulation tests and DBS should be taken into consideration as they can alter the clinical outcome.

Predicting irreversible electroporation-induced tissue damage by means of magnetic resonance electrical impedance tomography

Irreversible electroporation (IRE) is gaining importance in routine clinical practice for nonthermal ablation of solid tumors. For its success, it is extremely important that the coverage and exposure time of the treated tumor to the electric field is within the specified range. Measurement of electric field distribution during the electroporation treatment can be achieved using magnetic resonance electrical impedance tomography (MREIT). Here, we show improved MREIT-enabled electroporation monitoring of IRE-treated tumors by predicting IRE-ablated tumor areas during IRE of mouse tumors in vivo. The in situ prediction is enabled by coupling MREIT with a corresponding Peleg-Fermi mathematical model to obtain more informative monitoring of IRE tissue ablation by providing cell death probability in the IRE-treated tumors. This technique can potentially be used in electroporation-based clinical applications, such as IRE tissue ablation and electrochemotherapy, to improve and assure the desired treatment outcome.