Surgical decision making for deep brain stimulation should not be based on aggregated normative data mining

Comparison of structural connectomes for modeling deep brain stimulation pathway activation

INTRODUCTION

Structural connectivity models of the brain are commonly employed to identify pathways that are directly activated during deep brain stimulation (DBS). However, various connectomes differ in the technical parameters, parcellation schemes, and methodological approaches used in their construction.

OBJECTIVE

The goal of this study was to compare and quantify variability in DBS pathway activation predictions when using different structural connectomes, while using identical electrode placements and stimulation volumes in the brain.

APPROACH

We analyzed four example structural connectomes: 1) Horn normative connectome (whole brain), 2) Yeh population-averaged tract-to-region pathway atlas (whole brain), 3) Petersen histology-based pathway atlas (subthalamic focused), and 4) Majtanik histology-based pathway atlas (anterior thalamus focused). DBS simulations were performed with each connectome, at four generalized locations for DBS electrode placement: 1) subthalamic nucleus, 2) anterior nucleus of thalamus, 3) ventral capsule, and 4) ventral intermediate nucleus of thalamus.

RESULTS

The choice of connectome used in the simulations resulted in notably distinct pathway activation predictions, and quantitative analysis indicated little congruence in the predicted patterns of brain network connectivity. The Horn and Yeh tractography-based connectomes provided estimates of DBS connectivity for any stimulation location in the brain, but have limitations in their anatomical validity. The Petersen and Majtanik histology-based connectomes are more anatomically realistic, but are only applicable to specific DBS targets because of their limited representation of pathways.

SIGNIFICANCE

The widely varying and inconsistent inferences of DBS network connectivity raises substantial concern regarding the general reliability of connectomic DBS studies, especially those that lack anatomical and/or electrophysiological validation in their analyses.

Emerging Techniques for the Personalization of Deep Brain Stimulation Programming

The success of deep brain stimulation (DBS) relies on applying carefully titrated therapeutic stimulation at specific targets. Once implanted, the electrical stimulation parameters at each electrode contact can be modified. Iteratively adjusting the stimulation parameters enables testing for the optimal stimulation settings. Due to the large parameter space, the currently employed empirical testing of individual parameters based on acute clinical response is not sustainable. Within the constraints of short clinical visits, optimization is particularly challenging when clinical features lack immediate feedback, as seen in DBS for dystonia and depression and with the cognitive and axial side effects of DBS for Parkinson's disease. A personalized approach to stimulation parameter selection is desirable as the increasing complexity of modern DBS devices also expands the number of available parameters. This review describes three emerging imaging and electrophysiological methods of personalizing DBS programming. Normative connectome-base stimulation utilizes large datasets of normal or disease-matched connectivity imaging. The stimulation location for an individual patient can then be varied to engage regions associated with optimal connectivity. Electrophysiology-guided open- and closed-loop stimulation capitalizes on the electrophysiological recording capabilities of modern implanted devices to individualize stimulation parameters based on biomarkers of success or symptom onset. Finally, individual functional MRI (fMRI)-based approaches use fMRI during active stimulation to identify parameters resulting in characteristic patterns of functional engagement associated with long-term treatment response. Each method provides different but complementary information, and maximizing treatment efficacy likely requires a combined approach.

Advancing Neuropsychological Rehabilitation in Primary Progressive Aphasia Based on Principles of Cognitive Neuroscience: A Scoping Review and Systematic Analysis of the Data

Background/Objectives: This systematic review of neuropsychological rehabilitation strategies for primary progressive aphasia will consider recent developments in cognitive neuroscience, especially neuroimaging techniques such as EEG and fMRI, to outline how these tools might be integrated into clinical practice to maximize treatment outcomes. Methods: A systematic search of peer-reviewed literature from the last decade was performed following the PRISMA guidelines across multiple databases. A total of 63 studies were included, guided by predefined inclusion and exclusion criteria, with a focus on cognitive and language rehabilitation in PPA, interventions guided by neuroimaging, and mechanisms of neuroplasticity. Results: Integration of neuroimaging techniques contributes to the increase in the efficacy of interventions with critical information about the neural mechanisms underlying language deficits in the aphasias. Traditional rehabilitation strategies, technology-assisted interventions, and non-invasive brain stimulation techniques hold considerable promise for language improvement. Neuroimaging was also found to be necessary in subtype-specific differentiation toward tailoring therapeutic intervention. Evidence also shows that directed and sustained interventions using neuroplasticity can have long-term effects in managing the symptoms of PPA. Conclusions: The present review underlines the necessity of including cognitive neuroscience techniques within neuropsychological rehabilitation to enhance therapeutic outcomes in PPA. In addition, neuroimaging modalities such as EEG and fMRI are also of great importance in understanding the underlying neurobiology of language disturbances and guiding tailored interventions. Long-term benefits of these approaches should be evaluated, including their applicability in routine clinical practice.

Biophysical Principles and Computational Modeling of Deep Brain Stimulation

BACKGROUND

Deep brain stimulation (DBS) has revolutionized the treatment of neurological disorders, yet the mechanisms of DBS are still under investigation. Computational models are important in silico tools for elucidating these underlying principles and potentially for personalizing DBS therapy to individual patients. The basic principles underlying neurostimulation computational models, however, are not well known in the clinical neuromodulation community.

OBJECTIVE

In this study, we present a tutorial on the derivation of computational models of DBS and outline the biophysical contributions of electrodes, stimulation parameters, and tissue substrates to the effects of DBS.

RESULTS

Given that many aspects of DBS are difficult to characterize experimentally, computational models have played an important role in understanding how material, size, shape, and contact segmentation influence device biocompatibility, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Neural activation is dictated by stimulation parameters including frequency, current vs voltage control, amplitude, pulse width, polarity configurations, and waveform. These parameters also affect the potential for tissue damage, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Activation of the neural substrate also is influenced by the encapsulation layer surrounding the electrode, the conductivity of the surrounding tissue, and the size and orientation of white matter fibers. These properties modulate the effects of the electric field and determine the ultimate therapeutic response.

CONCLUSION

This article describes biophysical principles that are useful for understanding the mechanisms of neurostimulation.

Mediation of Tremor Control by the Decussating and Nondecussating Part of the Dentato-Rubro-Thalamic Tract in Deep Brain Stimulation in Essential Tremor: Which Part Should Be Stimulated?

OBJECTIVES

The dentato-rubro-thalamic tract (DRTT) has been found to play a major role in the mechanisms of tremor alleviation by deep brain stimulation (DBS) in essential tremor (ET). Still, the influence of the two different parts of the DRTT, consisting of crossing and nondecussating fibers, is not yet clear with respect to tremor reduction. The aim of this study was to assess the influence of the crossing and the nondecussating part of the DRTT on tremor control in ET.

MATERIALS AND METHODS

We investigated 80 electrode contacts in ten patients with ET who received bilateral DBS of the Nucleus ventralis intermedius of the thalamus (VIM). Preoperatively and with patients under general anesthesia, 3T magnetic resonance imaging scans were performed, including Diffusion Tensor Imaging scans with 64 gradient directions. We calculated the course of the two parts of the DRTT based on a workflow for probabilistic fiber tracking including protocols for correction of susceptibility- and eddy current-induced distortions. Distances of electrode contacts were correlated with clinical data from neurologic single pole testing.

RESULTS

Voltage- and current-steered systems were analyzed separately. Regarding postural tremor, effective contacts showed significantly lower distances to both parts of the DRTT (crossing p < 0.001, nondecussating p < 0.05) in voltage-steered systems. Regarding intentional tremor, significant results were only found for the crossing part (p < 0.01). Regarding both tremor types, effective contacts were closer to the crossing part, unlike less effective contacts. Nonlinear regression analyses using a logistic model showed higher coefficients for the crossing part of the DRTT. Multivariate regression models including distances to both parts of the DRTT showed a significant influence of only the crossing part. Analysis of current-steered systems showed unstable data, probably because of the small number of analyzed patients.

CONCLUSIONS

Our data suggest an involvement of both parts of the DRTT in tremor reduction, indicating mediation of DBS effects by both fiber bundles, although the crossing part showed stronger correlations with good clinical responses. Nevertheless, special attention should be paid to methodologic aspects when using probabilistic tractography for patient-specific targeting to avoid uncertain and inaccurate results.

Tomographic tract tracing and data driven approaches to unravel complex 3D fiber anatomy of DBS relevant prefrontal projections to the diencephalic-mesencephalic junction in the marmoset

BACKGROUND

Understanding prefrontal cortex projections to diencephalic-mesencephalic junction (DMJ), especially to subthalamic nucleus (STN) and ventral mesencephalic tegmentum (VMT) helps our comprehension of Deep Brain Stimulation (DBS) in major depression (MD) and obsessive-compulsive disorder (OCD). Fiber routes are complex and tract tracing studies in non-human primate species (NHP) have yielded conflicting results. The superolateral medial forebrain bundle (slMFB) is a promising target for DBS in MD and OCD. It has become a focus of criticism owing to its name and its diffusion weighted-imaging based primary description.

OBJECTIVE

To investigate DMJ connectivity in NHP with a special focus on slMFB and the limbic hyperdirect pathway utilizing three-dimensional and data driven techniques.

METHODS

We performed left prefrontal adeno-associated virus - tracer based injections in the common marmoset monkey (n = 52). Histology and two-photon microscopy were integrated into a common space. Manual and data driven cluster analyses of DMJ, subthalamic nucleus and VMT together, followed by anterior tract tracing streamline (ATTS) tractography were deployed.

RESULTS

Typical pre- and supplementary motor hyperdirect connectivity was confirmed. The advanced tract tracing unraveled the complex connectivity to the DMJ. Limbic prefrontal territories directly projected to the VMT but not STN.

DISCUSSION

Intricate results of tract tracing studies warrant the application of advanced three-dimensional analyses to understand complex fiber-anatomical routes. The applied three-dimensional techniques can enhance anatomical understanding also in other regions with complex fiber anatomy.

CONCLUSION

Our work confirms slMFB anatomy and enfeebles previous misconceptions. The rigorous NHP approach strengthens the role of the slMFB as a target structure for DBS predominantly in psychiatric indications like MD and OCD.

Patient specific intracranial neural signatures of obsessions and compulsions in the ventral striatum

Objective. Deep brain stimulation is a treatment option for patients with refractory obsessive-compulsive disorder. A new generation of stimulators hold promise for closed loop stimulation, with adaptive stimulation in response to biologic signals. Here we aimed to discover a suitable biomarker in the ventral striatum in patients with obsessive compulsive disorder using local field potentials.Approach.We induced obsessions and compulsions in 11 patients undergoing deep brain stimulation treatment using a symptom provocation task. Then we trained machine learning models to predict symptoms using the recorded intracranial signal from the deep brain stimulation electrodes.Main results.Average areas under the receiver operating characteristics curve were 62.1% for obsessions and 78.2% for compulsions for patient specific models. For obsessions it reached over 85% in one patient, whereas performance was near chance level when the model was trained across patients. Optimal performances for obsessions and compulsions was obtained at different recording sites.Significance. The results from this study suggest that closed loop stimulation may be a viable option for obsessive-compulsive disorder, but that intracranial biomarkers are patient and not disorder specific.Clinical Trial:Netherlands trial registry NL7486.

Deep brain stimulation for extreme behaviors associated with autism spectrum disorder converges on a common pathway: a systematic review and connectomic analysis

OBJECTIVE

Individuals with autism spectrum disorder (ASD) may display extreme behaviors such as self-injury or aggression that often become refractory to psychopharmacology or behavioral intervention. Deep brain stimulation (DBS) is a surgical alternative that modulates brain circuits that have yet to be clearly elucidated. In the current study the authors performed a connectomic analysis to identify brain circuitry engaged by DBS for extreme behaviors associated with ASD.

METHODS

A systematic review was performed to identify prior reports of DBS as a treatment for extreme behaviors in patients with ASD. Individual patients' perioperative imaging was collected from corresponding authors. DBS electrode localization and volume of tissue activated modeling were performed. Volumes of tissue activated were used as seed points in high-resolution normative functional and structural imaging templates. The resulting individual functional and structural connectivity maps were pooled to identify networks and pathways that are commonly engaged by all targets.

RESULTS

Nine patients with ASD who were receiving DBS for symptoms of aggression or self-injurious behavior were identified. All patients had some clinical improvement with DBS. Connectomic analysis of 8 patients (from the systematic review and unpublished clinical data) demonstrated a common anatomical area of shared circuitry within the anterior limb of the internal capsule. Functional analysis of 4 patients identified a common network of distant brain areas including the amygdala, insula, and anterior cingulate engaged by DBS.

CONCLUSIONS

This study presents a comprehensive synopsis of the evidence for DBS in the treatment of extreme behaviors associated with ASD. Using network mapping, the authors identified key circuitry common to DBS targets.

A Systematic Review of Treatment Outcome Predictors in Deep Brain Stimulation for Refractory Obsessive-Compulsive Disorder

Obsessive-compulsive disorder (OCD) is a chronic and debilitating mental disorder. Deep brain stimulation (DBS) is a promising approach for refractory OCD patients. Research aiming at treatment outcome prediction is vital to provide optimized treatments for different patients. The primary purpose of this systematic review was to collect and synthesize studies on outcome prediction of OCD patients with DBS implantations in recent years. This systematic review (PROSPERO registration number: CRD42022335585) followed the PRISMA (Preferred Reporting Items for Systematic Review and Meta-analysis) guidelines. The search was conducted using three different databases with the following search terms related to OCD and DBS. We identified a total of 3814 articles, and 17 studies were included in our review. A specific tract confirmed by magnetic resonance imaging (MRI) was predictable for DBS outcome regardless of implant targets, but inconsistencies still exist. Current studies showed various ways of successful treatment prediction. However, considering the heterogeneous results, we hope that future studies will use larger cohorts and more precise approaches for predictors and establish more personalized ways of DBS surgeries.

Connectomic Deep Brain Stimulation for Obsessive-Compulsive Disorder

Obsessive-compulsive disorder is among the most disabling psychiatric disorders. Although deep brain stimulation is considered an effective treatment, its use in clinical practice is not fully established. This is, at least in part, due to ambiguity about the best suited target and insufficient knowledge about underlying mechanisms. Recent advances suggest that changes in broader brain networks are responsible for improvement of obsessions and compulsions, rather than local impact at the stimulation site. These findings were fueled by innovative methodological approaches using brain connectivity analyses in combination with neuromodulatory interventions. Such a connectomic approach for neuromodulation constitutes an integrative account that aims to characterize optimal target networks. In this critical review, we integrate findings from connectomic studies and deep brain stimulation interventions to characterize a neural network presumably effective in reducing obsessions and compulsions. To this end, we scrutinize methodologies and seemingly conflicting findings with the aim to merge observations to identify common and diverse pathways for treating obsessive-compulsive disorder. Ultimately, we propose a unified network that-when modulated by means of cortical or subcortical interventions-alleviates obsessive-compulsive symptoms.

A randomised, double-blind, sham-controlled trial of deep brain stimulation of the bed nucleus of the stria terminalis for treatment-resistant obsessive-compulsive disorder

Deep brain stimulation (DBS) is a promising treatment for severe, treatment-resistant obsessive-compulsive disorder (OCD). Here, nine participants (four females, mean age 47.9 ± 10.7 years) were implanted with DBS electrodes bilaterally in the bed nucleus of the stria terminalis (BNST). Following a one-month postoperative recovery phase, participants entered a three-month randomised, double-blind, sham-controlled phase before a twelve-month period of open-label stimulation incorporating a course of cognitive behavioural therapy (CBT). The primary outcome measure was OCD symptoms as rated with the Yale-Brown Obsessive-Compulsive Scale (YBOCS). In the blinded phase, there was a significant benefit of active stimulation over sham (p = 0.025, mean difference 4.9 points). After the open phase, the mean reduction in YBOCS was 16.6 ± 1.9 points (χ² (11) = 39.8, p = 3.8 × 10^-5), with seven participants classified as responders. CBT resulted in an additive YBOCS reduction of 4.8 ± 3.9 points (p = 0.011). There were two serious adverse events related to the DBS device, the most severe of which was an infection during the open phase necessitating device explantation. There were no serious psychiatric adverse events related to stimulation. An analysis of the structural connectivity of each participant's individualised stimulation field isolated right-hemispheric fibres associated with YBOCS reduction. These included subcortical tracts incorporating the amygdala, hippocampus and stria terminalis, in addition to cortical regions in the ventrolateral and ventromedial prefrontal cortex, parahippocampal, parietal and extrastriate visual cortex. In conclusion, this study provides further evidence supporting the efficacy and tolerability of DBS in the region of the BNST for individuals with otherwise treatment-refractory OCD and identifies a connectivity fingerprint associated with clinical benefit.

Image-based biophysical modeling predicts cortical potentials evoked with subthalamic deep brain stimulation

BACKGROUND

Subthalamic deep brain stimulation (DBS) is an effective surgical treatment for Parkinson's disease and continues to advance technologically with an enormous parameter space. As such, in-silico DBS modeling systems have become common tools for research and development, but their underlying methods have yet to be standardized and validated.

OBJECTIVE

Evaluate the accuracy of patient-specific estimates of neural pathway activations in the subthalamic region against intracranial, cortical evoked potential (EP) recordings.

METHODS

Pathway activations were modeled in eleven patients using the latest advances in connectomic modeling of subthalamic DBS, focusing on the hyperdirect pathway (HDP) and corticospinal/bulbar tract (CSBT) for their relevance in human research studies. Correlations between pathway activations and respective EP amplitudes were quantified.

RESULTS

Good model performance required accurate lead localization and image fusions, as well as appropriate selection of fiber diameter in the biophysical model. While optimal model parameters varied across patients, good performance could be achieved using a global set of parameters that explained 60% and 73% of electrophysiologic activations of CSBT and HDP, respectively. Moreover, restricted models fit to only EP amplitudes of eight standard (monopolar and bipolar) electrode configurations were able to extrapolate variation in EP amplitudes across other directional electrode configurations and stimulation parameters, with no significant reduction in model performance across the cohort.

CONCLUSIONS

Our findings demonstrate that connectomic models of DBS with sufficient anatomical and electrical details can predict recruitment dynamics of white matter. These results will help to define connectomic modeling standards for preoperative surgical targeting and postoperative patient programming applications.

Subthalamic Stimulation for Camptocormia in Parkinson's Disease: Association of Volume of Tissue Activated and Structural Connectivity with Clinical Effectiveness

BACKGROUND

Deep brain stimulation of the subthalamic nucleus (STN-DBS) has been reported to be effective for camptocormia in Parkinson's disease (PD). However, the association between clinical effectiveness and the stimulated volumes or structural connectivity remains unexplored.

OBJECTIVE

To investigate the effectiveness of STN-DBS for treating camptocormia in PD and its association with volumes of tissue activated (VTA) and structural connectivity.

METHODS

We reviewed video recordings of patients who had undergone STN-DBS. The total and upper camptocormia (TCC and UCC) angles were measured to quantify changes in camptocormia. The Movement Disorders Society Unified Parkinson's Disease Rating Scale III (MDS-UPDRS III) was used to assess motor symptoms. Pre- and postoperative brain images were collected for modeling volume of VTA and structural connectivity using Lead-DBS software.

RESULTS

Participants included 36 patients with PD (8 with TCC-camptocormia and 2 with UCC-camptocormia) treated with bilateral STN-DBS. After surgery, patients showed a significant improvement in postural alignment at follow-up (mean follow-up duration: 6.0±2.2 months). In the entire sample, higher structural connectivity to the right supplementary motor area (SMA) and right lateral premotor cortex along the dorsal plane (PMd) was associated with larger postsurgical improvements in axial signs and TCC angles after stimulation was turned on. In patients diagnosed with camptocormia, larger improvement in camptocormia angles after STN-DBS was associated with a larger VTA overlap with STN (R = 0.75, p = 0.032).

CONCLUSION

This study suggests that both VTA overlap with STN and structural connectivity to cortical motor regions are associated with the effectiveness of STN-DBS for managing camptocormia in PD.

Long-Term Outcome and Neuroimaging of Deep Brain Stimulation in Holmes Tremor: A Case Series

BACKGROUND

Different deep brain stimulation (DBS) targets have been suggested as treatment for patients with pharmacologically refractory Holmes tremor (HT). We report the clinical and quality of life (QoL) long-term (up to nine years) outcome in four patients with HT treated with DBS (in thalamic ventral intermediate nucleus-VIM or in dentato-rubro-thalamic tract-DRTT).

MATERIALS AND METHODS

The patients underwent routine clinical evaluations before and after DBS (typically annually). Tremor severity and activities of daily living (ADL) were quantified by the Fahn-Tolosa-Marin Tremor-Rating-Scale (FTMTRS). QoL was assessed using the RAND SF-36-item Health Survey (RAND SF-36). In addition, we computed, in all four patients, the VTA based on the best stimulation settings using heuristic approaches included in the open source toolbox LEAD-DBS.

RESULTS

In all patients, tremor and ADL improved significantly at one-year post-DBS follow-up (34-61% improvement in FTMTRS total score compared to baseline). In three out of four patients, the improvement of tremor was sustained no longer than two to three years and only in one patient was sustained up to nine years. In this patient, the largest intersection between VTA and DBS target has been observed. Scores for ADL deteriorated over the course of time, reaching worse levels compared to baseline already during the three-year post-DBS follow-up, in three out of four patients. Physical and mental health component scores of RAND SF-36 had very different outcome between patients and follow-ups and were not associated with tremor-related outcomes.

CONCLUSIONS

The benefits of DBS in HT might not be always long lasting. Although QoL slightly improved, this change seemed to be independent of the motor outcome following DBS. The estimation of DBS target and VTA proximity could be a useful tool for DBS clinicians in order to facilitate the DBS programming process and optimize DBS treatment.

Neurocircuitry of Deep Brain Stimulation for Obsessive-Compulsive Disorder as Revealed by Tractography: A Systematic Review

Objective: Deep brain stimulation (DBS) was proposed in 1999 to treat refractory obsessive-compulsive disorder (OCD). Despite the accumulated experience over more than two decades, 30-40% of patients fail to respond to this procedure. One potential reason to explain why some patients do not improve in the postoperative period is that DBS might not have engaged structural therapeutic networks that are crucial to a favorable outcome in non-responders. This article reviews magnetic resonance imaging diffusion studies (DTI-MRI), analyzing neural networks likely modulated by DBS in OCD patients and their corresponding clinical outcome. Methods: We used a systematic review process to search for studies published from 2005 to 2020 in six electronic databases. Search terms included obsessive-compulsive disorder, deep brain stimulation, diffusion-weighted imaging, diffusion tensor imaging, diffusion tractography, tractography, connectome, diffusion analyses, and white matter. No restriction was made concerning the surgical target, DTI-MRI technique and the method of data processing. Results: Eight studies published in the last 15 years were fully assessed. Most of them used 3 Tesla DTI-MRI, and different methods of data acquisition and processing. There was no consensus on potential structures and networks underlying DBS effects. Most studies stimulated the ventral anterior limb of the internal capsule (ALIC)/nucleus accumbens. However, the contribution of different white matter pathways that run through the ALIC for the effects of DBS remains elusive. Moreover, the improvement of cognitive and affective symptoms in OCD patients probably relies on electric modulation of distinct networks. Conclusion: Though, tractography is a valuable tool to understand neural circuits, the effects of modulating different fiber tracts in OCD are still unclear. Future advances on image acquisition and data processing and a larger number of studies are still required for the understanding of the role of tractography-based targeting and to clarify the importance of different tracts for the mechanisms of DBS.

Opportunities of connectomic neuromodulation

The process of altering neural activity - neuromodulation - has long been used to treat patients with brain disorders and answer scientific questions. Deep brain stimulation in particular has provided clinical benefit to over 150,000 patients. However, our understanding of how neuromodulation impacts the brain is evolving. Instead of focusing on the local impact at the stimulation site itself, we are considering the remote impact on brain regions connected to the stimulation site. Brain connectivity information derived from advanced magnetic resonance imaging data can be used to identify these connections and better understand clinical and behavioral effects of neuromodulation. In this article, we review studies combining neuromodulation and brain connectomics, highlighting opportunities where this approach may prove particularly valuable. We focus on deep brain stimulation, but show that the same principles can be applied to other forms of neuromodulation, such as transcranial magnetic stimulation and MRI-guided focused ultrasound. We outline future perspectives and provide testable hypotheses for future work.

Image Guidance in Deep Brain Stimulation Surgery to Treat Parkinson's Disease: A Comprehensive Review

Deep brain stimulation (DBS) is an effective therapy as an alternative to pharmaceutical treatments for Parkinson's disease (PD). Aside from factors such as instrumentation, treatment plans, and surgical protocols, the success of the procedure depends heavily on the accurate placement of the electrode within the optimal therapeutic targets while avoiding vital structures that can cause surgical complications and adverse neurologic effects. Although specific surgical techniques for DBS can vary, interventional guidance with medical imaging has greatly contributed to the development, outcomes, and safety of the procedure. With rapid development in novel imaging techniques, computational methods, and surgical navigation software, as well as growing insights into the disease and mechanism of action of DBS, modern image guidance is expected to further enhance the capacity and efficacy of the procedure in treating PD. This article surveys the state-of-the-art techniques in image-guided DBS surgery to treat PD, and discusses their benefits and drawbacks, as well as future directions on the topic.

A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder

Multiple surgical targets for treating obsessive-compulsive disorder with deep brain stimulation (DBS) have been proposed. However, different targets may modulate the same neural network responsible for clinical improvement. We analyzed data from four cohorts of patients (N = 50) that underwent DBS to the anterior limb of the internal capsule (ALIC), the nucleus accumbens or the subthalamic nucleus (STN). The same fiber bundle was associated with optimal clinical response in cohorts targeting either structure. This bundle connected frontal regions to the STN. When informing the tract target based on the first cohort, clinical improvements in the second could be significantly predicted, and vice versa. To further confirm results, clinical improvements in eight patients from a third center and six patients from a fourth center were significantly predicted based on their stimulation overlap with this tract. Our results show that connectivity-derived models may inform clinical improvements across DBS targets, surgeons and centers. The identified tract target is openly available in atlas form.

Li et al. analyzed structural connectivity of deep brain stimulation electrodes in 50 patients suffering from obsessive-compulsive disorder operated at four centers. Connectivity to a specific tract within the anterior limb of the internal capsule was associated with optimal treatment response across cohorts, surgeons and centers.

Deep brain stimulation: Imaging on a group level

Deep Brain Stimulation (DBS) is an established treatment option for movement disorders and is under investigation for treatment in a growing number of other brain diseases. It has been shown that exact electrode placement crucially affects the efficacy of DBS and this should be considered when investigating novel indications or DBS targets. To measure clinical improvement as a function of electrode placement, neuroscientific methodology and specialized software tools are needed. Such tools should have the goal to make electrode placement comparable across patients and DBS centers, and include statistical analysis options to validate and define optimal targets. Moreover, to allow for comparability across different centers, these need to be performed within an algorithmically and anatomically standardized and openly available group space. With the publication of Lead-DBS software in 2014, an open-source tool was introduced that allowed for precise electrode reconstructions based on pre- and postoperative neuroimaging data. Here, we introduce Lead Group, implemented within the Lead-DBS environment and specifically designed to meet aforementioned demands. In the present article, we showcase the various processing streams of Lead Group in a retrospective cohort of 51 patients suffering from Parkinson's disease, who were implanted with DBS electrodes to the subthalamic nucleus (STN). Specifically, we demonstrate various ways to visualize placement of all electrodes in the group and map clinical improvement values to subcortical space. We do so by using active coordinates and volumes of tissue activated, showing converging evidence of an optimal DBS target in the dorsolateral STN. Second, we relate DBS outcome to the impact of each electrode on local structures by measuring overlap of stimulation volumes with the STN. Finally, we explore the software functions for connectomic mapping, which may be used to relate DBS outcomes to connectivity estimates with remote brain areas. The manuscript is accompanied by a walkthrough tutorial which allows users to reproduce all main results presented here. All data and code needed to reproduce results are openly available.

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.