In vivo Exploration of the Connectivity between the Subthalamic Nucleus and the Globus Pallidus in the Human Brain Using Multi-Fiber Tractography

Linking profiles of pathway activation with clinical motor improvements - A retrospective computational study

BACKGROUND

Deep brain stimulation (DBS) is an established therapy for patients with Parkinson's disease. In silico computer models for DBS hold the potential to inform a selection of stimulation parameters. In recent years, the focus has shifted towards DBS-induced firing in myelinated axons, deemed particularly relevant for the external modulation of neural activity.

OBJECTIVE

The aim of this project was to investigate correlations between patient-specific pathway activation profiles and clinical motor improvement.

METHODS

We used the concept of pathway activation modeling, which incorporates advanced volume conductor models and anatomically authentic fiber trajectories to estimate DBS-induced action potential initiation in anatomically plausible pathways that traverse in close proximity to targeted nuclei. We applied the method on two retrospective datasets of DBS patients, whose clinical improvement had been evaluated according to the motor part of the Unified Parkinson's Disease Rating Scale. Based on differences in outcome and activation levels for intrapatient DBS protocols in a training cohort, we derived a pathway activation profile that theoretically induces a complete alleviation of symptoms described by UPDRS-III. The profile was further enhanced by analyzing the importance of matching activation levels for individual pathways.

RESULTS

The obtained profile emphasized the importance of activation in pathways descending from the motor-relevant cortical regions as well as the pallidothalamic pathways. The degree of similarity of patient-specific profiles to the optimal profile significantly correlated with clinical motor improvement in a test cohort.

CONCLUSION

Pathway activation modeling has a translational utility in the context of motor symptom alleviation in Parkinson's patients treated with 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.

A Scientometric Analysis of the 100 Most Cited Articles on Pallidotomy

BACKGROUND

Pallidotomy is the oldest stereotactically performed neurosurgical procedure for movement disorders. Consequently, there is a wealth of literature available on the topic.

OBJECTIVES

The aim of this analysis was to identify the top-cited articles on pallidotomy in order to discern the origins, spread, the current trends, and the future directions of this surgical procedure.

METHODS

We performed a search of the Web of Science database on 19 October 2020 using the keyword "pallidotomy." The top-100 cited articles found were arranged in descending order on the basis of citation count (CC) and citation per year (CY). Relevant conclusions were derived.

RESULTS

The 100 top-cited articles were published between 1961 and 2017, in 24 journals. The average CC and CY were 118.1 (range - 856-46) and 5.326 (range - 29.52-2.09), respectively. The 3 most prolific authors were Lang AE (Neurologist - Toronto), Lozano AM (Neurosurgeon - Toronto), and Vitek JL (Neurologist - Atlanta). The Journal of Neurosurgery published the highest number of top-cited articles [Neurology. 1960;10:61-9]. The maximum articles were from the USA. University of Toronto and Emory University were the most productive institutions.

CONCLUSIONS

Pallidotomy has gone through several ebbs and flows. Unilateral pallidotomy is currently recommended for the treatment of motor symptoms of Parkinson's disease and dystonia. The need for further research and improved technology to make the technique safer and prove its efficacy is highlighted, especially keeping in mind a large number of populations to which the prohibitively expensive deep brain stimulation is unavailable.

Resting-State Functional Connectivity Predicts STN DBS Clinical Response

BACKGROUND

Deep brain stimulation of the subthalamic nucleus is a widely used adjunctive therapy for motor symptoms of Parkinson's disease, but with variable motor response. Predicting motor response remains difficult, and novel approaches may improve surgical outcomes as well as the understanding of pathophysiological mechanisms. The objective of this study was to determine whether preoperative resting-state functional connectivity MRI predicts motor response from deep brain stimulation of the subthalamic nucleus.

METHODS

We collected preoperative resting-state functional MRI from 70 participants undergoing subthalamic nucleus deep brain stimulation. For this cohort, we analyzed the strength of STN functional connectivity with seeds determined by stimulation-induced (ON/OFF) 15 O H2 O PET regional cerebral blood flow differences in a partially overlapping group (n = 42). We correlated STN-seed functional connectivity strength with postoperative motor outcomes and applied linear regression to predict motor outcomes.

RESULTS

Preoperative functional connectivity between the left subthalamic nucleus and the ipsilateral internal globus pallidus correlated with postsurgical motor outcomes (r = -0.39, P = 0.0007), with stronger preoperative functional connectivity relating to greater improvement. Left pallidal-subthalamic nucleus connectivity also predicted motor response to DBS after controlling for covariates.

DISCUSSION

Preoperative pallidal-subthalamic nucleus resting-state functional connectivity predicts motor benefit from deep brain stimulation, although this should be validated prospectively before clinical application. These observations suggest that integrity of pallidal-subthalamic nucleus circuits may be critical to motor benefits from deep brain stimulation. © 2020 International Parkinson and Movement Disorder Society.

Anatomy and Connectivity of the Subthalamic Nucleus in Humans and Non-human Primates

The Subthalamic Nucleus (STh) is an oval-shaped diencephalic structure located ventrally to the thalamus, playing a fundamental role in the circuitry of the basal ganglia. In addition to being involved in the pathophysiology of several neurodegenerative disorders, such as Huntington’s and Parkinson’s disease, the STh is one of the target nuclei for deep brain stimulation. However, most of the anatomical evidence available derives from non-human primate studies. In this review, we will present the topographical and morphological organization of the nucleus and its connections to structurally and functionally related regions of the basal ganglia circuitry. We will also highlight the importance of additional research in humans focused on validating STh connectivity, cytoarchitectural organization, and its functional subdivision.

Mapping tracts in the human subthalamic area by 11.7T ex vivo diffusion tensor imaging

The cortico-basal ganglia-thalamo-cortical feedback loops that consist of distinct white matter pathways are important for understanding in vivo imaging studies of functional and anatomical connectivity, and for localizing subthalamic white matter structures in surgical approaches for movement disorders, such as Parkinson's disease. Connectomic analysis in animals has identified fiber connections between the basal ganglia and thalamus, which pass through the fields of Forel, where other fiber pathways related to motor, sensory, and cognitive functions co-exist. We now report these pathways in the human brain on ex vivo mesoscopic (250 μm) diffusion tensor imaging and on tractography. The locations of the tracts were identified relative to the adjacent gray matter structures, such as the internal and external segments of the globus pallidus; the zona incerta; the subthalamic nucleus; the substantia nigra pars reticulata and compacta; and the thalamus. The connectome atlas of the human subthalamic region may serve as a resource for imaging studies and for neurosurgical planning.

A Comprehensive Review of Brain Connectomics and Imaging to Improve Deep Brain Stimulation Outcomes

DBS is an effective neuromodulatory therapy that has been applied in various conditions, including PD, essential tremor, dystonia, Tourette syndrome, and other movement disorders. There have also been recent examples of applications in epilepsy, chronic pain, and neuropsychiatric conditions. Innovations in neuroimaging technology have been driving connectomics, an emerging whole-brain network approach to neuroscience. Two rising techniques are functional connectivity profiling and structural connectivity profiling. Functional connectivity profiling explores the operational relationships between multiple regions of the brain with respect to time and stimuli. Structural connectivity profiling approximates physical connections between different brain regions through reconstruction of axonal fibers. Through these techniques, complex relationships can be described in various disease states, such as PD, as well as in response to therapy, such as DBS. These advances have expanded our understanding of human brain function and have provided a partial in vivo glimpse into the underlying brain circuits underpinning movement and other disorders. This comprehensive review will highlight the contemporary concepts in brain connectivity as applied to DBS, as well as introduce emerging considerations in movement disorders. © 2020 International Parkinson and Movement Disorder Society.

Enhanced Bidirectional Connectivity of the Subthalamo-pallidal Pathway in 6-OHDA-mouse Model of Parkinson's Disease Revealed by Probabilistic Tractography of Diffusion-weighted MRI at 9.4T

An important challenge in Parkinson’s disease (PD) based neuroscience and neuroimaging is mapping the neuronal connectivity of the basal ganglia to understand how the disease affects brain circuitry. However, a majority of diffusion tractography studies have shown difficulties in revealing connections between distant anatomic brain regions and visualizing basal ganglia connectome. In this current study, we investigated the differences in basal ganglia connectivity between 6-OHDA induced ex-vivo PD mouse model and normal ex-vivo mouse model by using diffusion tensor imaging tractography from diffusion-weighted images obtained with a high resolution 9.4 T MR scanner. Connectivity pattern of the basal ganglia were compared between five 6-OHDA and five control ex-vivo mouse brains using results of probabilistic tractography generated with PROBTRACKX. When compared with control mouse, 6-OHDA mouse showed significant enhancements to motor territory-related subthalamo-pallidal and pallido-subthalamic connectivity. Multi-fiber tractography combined with diffusion MRI data has the potential to help recognize the abnormalities found in connectivity of psychiatric and neurologic disease models.

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.

Post mortem high resolution diffusion MRI for large specimen imaging at 11.7 T with 3D segmented echo-planar imaging

BACKGROUND

Diffusion weighted imaging (DWI) is the only in vivo technique allowing for the mapping of tissue fiber architecture. Post mortem DWI is an increasingly popular method, since longer acquisition times (compared to in vivo) allow higher spatial and angular resolutions to be achieved. However, DWI protocols must be adapted to post mortem tissue (e.g., tuning acquisition parameters to account for changes in T1/T2). New method: In this work, we developed a framework to obtain high quality diffusion weighted images on post mortem large samples by using a combination of fast imaging with 3D diffusion-weighted segmented EPI (3D-DW seg-EPI), Gadolinium soaking and data denoising. Analyses including tractography were used to check the quality of the acquired data, including a comparison with 3D-DW SE acquisitions. Comparison with existing method: Effects on diffusion data of each of the components of the framework were tested: 3D-DW seg-EPI versus 3D-DW SE EPI; with and without data denoising; with and without Gd-soaking.

CONCLUSIONS

Our study demonstrated the feasibility of analysing anatomical connectivity using diffusion imaging of a post mortem macaque brain with a 3D-DW seg-EPI sequence acquired at ultra-high field. The combination of high angular and spatial resolution DWI with Gd-soaking and denoising provided data allowing us to perform diffusion tractography with results very similar to those obtained with a 3D-DW SE acquisition (with shorter acquisition times: 222 h versus 37 h for 3D-DW seg-EPI).

Diffusion tensor imaging in Parkinson's disease: Review and meta-analysis

BACKGROUND

Neuroimaging studies help us better understand the pathophysiology and symptoms of Parkinson's disease (PD). In several of these studies, diffusion tensor imaging (DTI) was used to investigate structural changes in cerebral tissue. Although data have been provided as regards to specific brain areas, a whole brain meta-analysis is still missing.

METHODS

We compiled 39 studies in this meta-analysis: 14 used fractional anisotropy (FA), 1 used mean diffusivity (MD), and 24 used both indicators. These studies comprised 1855 individuals, 1087 with PD and 768 healthy controls. Regions of interest were classified anatomically (subcortical structures; white matter; cortical areas; cerebellum). Our statistical analysis considered the disease effect size (DES) as the main variable; the heterogeneity index (I2) and Pearson's correlations between the DES and co-variables (demographic, clinical and MRI parameters) were also calculated.

RESULTS

Our results showed that FA-DES and MD-DES were able to distinguish between patients and healthy controls. Significant differences, indicating degenerations, were observed within the substantia nigra, the corpus callosum, and the cingulate and temporal cortices. Moreover, some findings (particularly in the corticospinal tract) suggested opposite brain changes associated with PD. In addition, our results demonstrated that MD-DES was particularly sensitive to clinical and MRI parameters, such as the number of DTI directions and the echo time within white matter.

CONCLUSIONS

Despite some limitations, DTI appears as a sensitive method to study PD pathophysiology and severity. The association of DTI with other MRI methods should also be considered and could benefit the study of brain degenerations in PD.