Probabilistic Mapping of Deep Brain Stimulation: Insights from 15 Years of Therapy

Stimulation-Induced Dyskinesia in STN DBS Patients

BACKGROUND

Stimulation-induced dyskinesia (SID) is a poorly studied and usually transient manifestation of subthalamic deep brain stimulation (STN DBS) for Parkinson's disease (PD), which can be troubling for patients.

OBJECTIVES

The aim of our study was to describe the features and management of SID in PD patients undergoing STN DBS.

METHODS

We conducted a retrospective study among 86 STN DBS patients. Clinical features and volume of tissue activated (VTA) were correlated to SID occurrence.

RESULTS

SID was identified in 28 (32.6%) patients and persisted for 6 months in six patients (7.0%). VTA overlap with the right motor STN was associated (P < 0.02) with SID. Weaning dopaminergic drugs and reducing the DBS amplitude were the most used strategies to control SID.

CONCLUSIONS

SID is a relatively common complication of STN DBS and can be persistent. It often requires specific postoperative management strategies.

Long-Term Safety and Efficacy of Focused Ultrasound Capsulotomy for Obsessive-Compulsive Disorder and Major Depressive Disorder

BACKGROUND

Magnetic resonance-guided focused ultrasound (MRgFUS) trials targeting the anterior limb of the internal capsule have shown promising results. We evaluated the long-term safety and efficacy of MRgFUS capsulotomy in patients with obsessive-compulsive disorder (OCD) and major depressive disorder (MDD).

METHODS

This phase 1, single-center, open-label study recruited patients with treatment-resistant OCD and MDD. Outcomes were measured 6 months, 12 months, and 18 to 24 months (long term) after MRgFUS capsulotomy. Neuropsychological testing and neuroimaging were conducted at baseline and 12 months postoperatively. The primary outcome was safety. The secondary outcome was clinical response, defined for OCD as a ≥35% improvement in Yale-Brown Obsessive Compulsive Scale scores and for MDD as a ≥50% reduction in Hamilton Depression Rating Scale scores compared with baseline.

RESULTS

No serious adverse effects were registered. In patients with OCD (n= 15), baseline Yale-Brown Obsessive Compulsive Scale scores (31.9 ± 1.2) were significantly reduced by 23% (p = .01) at 6 months and 35% (p < .0001) at 12 months. In patients with MDD (n = 12), a 26% and 25% nonsignificant reduction in Hamilton Depression Rating Scale scores (baseline 24.3 ± 1.2) was observed at 6 months and 12 months, respectively. Neuropsychological testing revealed no negative effects of capsulotomy. In the OCD and MDD cohorts, we found a correlation between clinical outcome and lesion laterality, with more medial left-placed lesions (OCD, p = .08) and more lateral right-placed lesions (MDD, p < .05) being respectively associated with a stronger response. In the MDD cohort, more ventral tracts appeared to be associated with a poorer response.

CONCLUSIONS

MRgFUS capsulotomy is safe in patients with OCD and MDD and particularly effective in the former population.

Clinical and Imaging Correlates of Medication Reduction in Globus Pallidus Stimulation for Parkinson's Disease

BACKGROUND

The magnitude and factors associated with levodopa equivalent daily dose (LEDD) reduction in deep brain stimulation (DBS) of the globus pallidus interna (GPi) for Parkinson's Disease (PD) remain unclear.

OBJECTIVE

To investigate LEDD reduction in GPi DBS and its correlation with anatomical/clinical characteristics.

METHODS

A consecutive cohort of 74 patients who had undergone GPi DBS was analyzed. Regression and probabilistic efficacy mapping were performed to evaluate factors predicting LEDD reduction.

RESULTS

32.4% of GPi individuals experienced significant LEDD reduction (>30%). Anteromedial GPi stimulation was associated with higher LEDD reduction.

CONCLUSION

Anteromedial stimulation of the GPi appears to be associated with medication reduction, challenging the idea that GPi DBS is ineffective at reducing LEDD. Further prospective study will be needed to validate these findings.

Proceedings of the 12th annual deep brain stimulation think tank: cutting edge technology meets novel applications

The Deep Brain Stimulation (DBS) Think Tank XII was held on August 21st to 23rd. This year we showcased groundbreaking advancements in neuromodulation technology, focusing heavily on the novel uses of existing technology as well as next-generation technology. Our keynote speaker shared the vision of using neuro artificial intelligence to predict depression using brain electrophysiology. Innovative applications are currently being explored in stroke, disorders of consciousness, and sleep, while established treatments for movement disorders like Parkinson's disease are being refined with adaptive stimulation. Neuromodulation is solidifying its role in treating psychiatric disorders such as depression and obsessive-compulsive disorder, particularly for patients with treatment-resistant symptoms. We estimate that 300,000 leads have been implanted to date for neurologic and neuropsychiatric indications. Magnetoencephalography has provided insights into the post-DBS physiological changes. The field is also critically examining the ethical implications of implants, considering the long-term impacts on clinicians, patients, and manufacturers.

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.

DBS in the restoration of motor functional recovery following spinal cord injury

The landscape of therapeutic deep brain stimulation (DBS) for locomotor function recovery is rapidly evolving. This review provides an overview of electrical neuromodulation effects on spinal cord injury (SCI), focusing on DBS for motor functional recovery in human and animal models. We highlight research providing insight into underlying cellular and molecular mechanisms. A literature review via Web of Science and PubMed databases from 1990 to May 29, 2024, reveals a growing body of evidence for therapeutic DBS in SCI recovery. Advances in techniques like optogenetics and whole-brain tractogram have helped elucidate DBS mechanisms. Neuronal targets sites for SCI functional recovery include the mesencephalic locomotor region (MLR), cuneiform nucleus (CNF), and nucleus raphe magnus (NRG), with pedunculopontine nucleus (PPN), periaqueductal gray (PAG), and nucleus ventroposterolateral thalami (VPL) for post-injury functional recovery treatment. Radiologically guided DBS optimization and combination therapy with classical rehabilitation have become an effective therapeutic method, though ongoing interventional trials are needed to enhance understanding and validate DBS efficacy in SCI. On the pre-clinical front, standardization of pre-clinical approaches are essential to enhance the quality of evidence on DBS safety and efficacy. Mapping brain targets and optimizing DBS protocols, aided by combined DBS and medical imaging, are critical endeavors. Overall, DBS holds promise for neurological and functional recovery after SCI, akin to other electrical stimulation approaches.

Strong connectivity to the sensorimotor cortex predicts clinical effectiveness of thalamic deep brain stimulation in essential tremor

INTRODUCTION

The outcome of thalamic deep brain stimulation (DBS) for essential tremor (ET) varies, probably due to the difficulty in identifying the optimal target for DBS placement. Recent approaches compared the clinical response with a connectivity-based segmentation of the target area. However, studies are contradictory by indicating the connectivity to the primary motor cortex (M1) or to the premotor/supplementary motor cortex (SMA) to be therapeutically relevant.

OBJECTIVE

To identify the connectivity profile that corresponds to clinical effective targeting of DBS for ET.

METHODS

Patient-specific probabilistic diffusion tensor imaging was performed in 20 ET patients with bilateral thalamic DBS. Following monopolar review, the stimulation response was classified for the most effective contact in each hemisphere as complete vs. incomplete upper limb tremor suppression (40 assessments). Finally, the connectivity profiles of these contacts within the cortical and cerebellar tremor network were estimated and compared between groups.

RESULTS

The active contacts that led to complete (n = 25) vs. incomplete (n = 15) tremor suppression showed significantly higher connectivity to M1 (p < 0.001), somatosensory cortex (p = 0.008), anterior lobe of the cerebellum (p = 0.026) and SMA (p = 0.05); with Cohen's (d) effect sizes of 0.53, 0.42, 0.25 and 0.10, respectively. The clinical benefits were achieved without requiring higher stimulation intensities or causing additional side effects.

CONCLUSION

Clinical effectiveness of DBS for ET corresponded to a distributed connectivity profile, with the connection to the sensorimotor cortex being most relevant. Long-term follow-up in larger cohorts and replication in out-of-sample data are necessary to confirm the robustness of these findings.

Deep Learning and fMRI-Based Pipeline for Optimization of Deep Brain Stimulation During Parkinson's Disease Treatment: Toward Rapid Semi-Automated Stimulation Optimization

OBJECTIVE

Optimized deep brain stimulation (DBS) is fast becoming a therapy of choice for the treatment of Parkinson's disease (PD). However, the post-operative optimization (aimed at maximizing patient clinical benefits and minimizing adverse effects) of all possible DBS parameter settings using the standard-of-care clinical protocol requires numerous clinical visits, which substantially increases the time to optimization per patient (TPP), patient cost burden and limit the number of patients who can undergo DBS treatment. The TPP is further elongated in electrodes with stimulation directionality or in diseases with latency in clinical feedback. In this work, we proposed a deep learning and fMRI-based pipeline for DBS optimization that can potentially reduce the TPP from ~1 year to a few hours during a single clinical visit.

METHODS AND PROCEDURES

We developed an unsupervised autoencoder (AE)-based model to extract meaningful features from 122 previously acquired blood oxygenated level dependent (BOLD) fMRI datasets from 39 a priori clinically optimized PD patients undergoing DBS therapy. The extracted features are then fed into multilayer perceptron (MLP)-based parameter classification and prediction models for rapid DBS parameter optimization.

RESULTS

The AE-extracted features of optimal and non-optimal DBS were disentangled. The AE-MLP classification model yielded accuracy, precision, recall, F1 score, and combined AUC of 0.96 ± 0.04, 0.95 ± 0.07, 0.92 ± 0.07, 0.93 ± 0.06, and 0.98 respectively. Accuracies of 0.79 ± 0.04, 0.85 ± 0.04, 0.82 ± 0.05, 0.83 ± 0.05, and 0.70 ± 0.07 were obtained in the prediction of voltage, frequency, and x-y-z contact locations, respectively.

CONCLUSION

The proposed AE-MLP models yielded promising results for fMRI-based DBS parameter classification and prediction, potentially facilitating rapid semi-automated DBS parameter optimization. Clinical and Translational Impact Statement-A deep learning-based pipeline for semi-automated DBS parameter optimization is presented, with the potential to significantly decrease the optimization duration per patient and patients' financial burden while increasing patient throughput.

Deep Brain Stimulation for Obsessive-Compulsive Disorder: Optimal Stimulation Sites

BACKGROUND

Deep brain stimulation (DBS) is a promising treatment option for treatment-refractory obsessive-compulsive disorder (OCD). Several stimulation targets have been used, mostly in and around the anterior limb of the internal capsule and ventral striatum. However, the precise target within this region remains a matter of debate.

METHODS

Here, we retrospectively studied a multicenter cohort of 82 patients with OCD who underwent DBS of the ventral capsule/ventral striatum and mapped optimal stimulation sites in this region.

RESULTS

DBS sweet-spot mapping performed on a discovery set of 58 patients revealed 2 optimal stimulation sites associated with improvements on the Yale-Brown Obsessive Compulsive Scale, one in the anterior limb of the internal capsule that overlapped with a previously identified OCD-DBS response tract and one in the region of the inferior thalamic peduncle and bed nucleus of the stria terminalis. Critically, the nucleus accumbens proper and anterior commissure were associated with beneficial but suboptimal clinical improvements. Moreover, overlap with the resulting sweet- and sour-spots significantly estimated variance in outcomes in an independent cohort of 22 patients from 2 additional DBS centers. Finally, beyond obsessive-compulsive symptoms, stimulation of the anterior site was associated with optimal outcomes for both depression and anxiety, while the posterior site was only associated with improvements in depression.

CONCLUSIONS

Our results suggest how to refine targeting of DBS in OCD and may be helpful in guiding DBS programming in existing patients.

High frequency electrical stimulation reduces α-synuclein levels and α-synuclein-mediated autophagy dysfunction

Accumulation of α-synuclein (α-Syn) has been implicated in proteasome and autophagy dysfunction in Parkinson's disease (PD). High frequency electrical stimulation (HFS) mimicking clinical parameters used for deep brain stimulation (DBS) in vitro or DBS in vivo in preclinical models of PD have been found to reduce levels of α-Syn and, in certain cases, provide possible neuroprotection. However, the mechanisms by which this reduction in α-Syn improves cellular dysfunction associated with α-Syn accumulation remains elusive. Using HFS parameters that recapitulate DBS in vitro, we found that HFS led to a reduction of mutant α-Syn and thereby limited proteasome and autophagy impairments due to α-Syn. Additionally, we observed that HFS modulates via the ATP6V0C subunit of V-ATPase and mitigates α-Syn mediated autophagic dysfunction. This study highlights a role for autophagy in reduction of α-Syn due to HFS which may prove to be a viable approach to decrease pathological protein accumulation in neurodegeneration.

GPi/GPe borderland- a potential sweet spot for deep brain stimulation for chorea in Huntington's disease?

BACKGROUND

Pallidal deep brain stimulation (GPi-DBS) has been considered as an effective treatment option for medication-refractory Huntington's disease (HD).

OBJECTIVES

To identify stimulation-dependent effects on motor symptoms and to determine if these alterations are associated with the local impact of DBS on different pallidal parcellations.

METHODS

We prospectively evaluated the effects of bilateral GPi-DBS within one year in 5 HD patients. We evaluated the effects of GPi-DBS on choreatic symptoms and UHDRS. Electrode placement in the pallidum was localized, and the local impact of DBS was estimated.

RESULTS

The chorea subscore (p < 0.001) and UHDRS total motor score was significantly reduced postoperatively (p = 0.019). Pallidal DBS did not improve other motor symptoms. Activation of the lateral GPi/GPe was associated with improvement in choreatic symptoms (p = 0.048; r = 0.90).

CONCLUSIONS

Our findings indicate that stimulation of the lateral GPi has a stable effect on choreatic symptoms. The modulation of the electrical field is relevant for motor outcome.

Probabilistic stimulation mapping from intra-operative thalamic deep brain stimulation data in essential tremor

Deep brain stimulation (DBS) is a therapy for Parkinson's disease (PD) and essential tremor (ET). The mechanism of action of DBS is still incompletely understood. Retrospective group analysis of intra-operative data recorded from ET patients implanted in the ventral intermediate nucleus of the thalamus (Vim) is rare. Intra-operative stimulation tests generate rich data and their use in group analysis has not yet been explored.Objective.To implement, evaluate, and apply a group analysis workflow to generate probabilistic stimulation maps (PSMs) using intra-operative stimulation data from ET patients implanted in Vim.Approach.A group-specific anatomical template was constructed based on the magnetic resonance imaging scans of 6 ET patients and 13 PD patients. Intra-operative test data (total:n= 1821) from the 6 ET patients was analyzed: patient-specific electric field simulations together with tremor assessments obtained by a wrist-based acceleration sensor were transferred to this template. Occurrence and weighted mean maps were generated. Voxels associated with symptomatic response were identified through a linear mixed model approach to form a PSM. Improvements predicted by the PSM were compared to those clinically assessed. Finally, the PSM clusters were compared to those obtained in a multicenter study using data from chronic stimulation effects in ET.Main results.Regions responsible for improvement identified on the PSM were in the posterior sub-thalamic area (PSA) and at the border between the Vim and ventro-oral nucleus of the thalamus (VO). The comparison with literature revealed a center-to-center distance of less than 5 mm and an overlap score (Dice) of 0.4 between the significant clusters. Our workflow and intra-operative test data from 6 ET-Vim patients identified effective stimulation areas in PSA and around Vim and VO, affirming existing medical literature.Significance.This study supports the potential of probabilistic analysis of intra-operative stimulation test data to reveal DBS's action mechanisms and to assist surgical planning.

A large normative connectome for exploring the tractographic correlates of focal brain interventions

Diffusion-weighted MRI (dMRI) is a widely used neuroimaging modality that permits the in vivo exploration of white matter connections in the human brain. Normative structural connectomics - the application of large-scale, group-derived dMRI datasets to out-of-sample cohorts - have increasingly been leveraged to study the network correlates of focal brain interventions, insults, and other regions-of-interest (ROIs). Here, we provide a normative, whole-brain connectome in MNI space that enables researchers to interrogate fiber streamlines that are likely perturbed by given ROIs, even in the absence of subject-specific dMRI data. Assembled from multi-shell dMRI data of 985 healthy Human Connectome Project subjects using generalized Q-sampling imaging and multispectral normalization techniques, this connectome comprises ~12 million unique streamlines, the largest to date. It has already been utilized in at least 18 peer-reviewed publications, most frequently in the context of neuromodulatory interventions like deep brain stimulation and focused ultrasound. Now publicly available, this connectome will constitute a useful tool for understanding the wider impact of focal brain perturbations on white matter architecture going forward.

The role of the motor thalamus in deep brain stimulation for essential tremor

The advent of next-generation technology has significantly advanced the implementation and delivery of Deep Brain Stimulation (DBS) for Essential Tremor (ET), yet controversies persist regarding optimal targets and networks responsible for tremor genesis and suppression. This review consolidates key insights from anatomy, neurology, electrophysiology, and radiology to summarize the current state-of-the-art in DBS for ET. We explore the role of the thalamus in motor function and describe how differences in parcellations and nomenclature have shaped our understanding of the neuroanatomical substrates associated with optimal outcomes. Subsequently, we discuss how seminal studies have propagated the ventral intermediate nucleus (Vim)-centric view of DBS effects and shaped the ongoing debate over thalamic DBS versus stimulation in the posterior subthalamic area (PSA) in ET. We then describe probabilistic- and network-mapping studies instrumental in identifying the local and network substrates subserving tremor control, which suggest that the PSA is the optimal DBS target for tremor suppression in ET. Taken together, DBS offers promising outcomes for ET, with the PSA emerging as a better target for suppression of tremor symptoms. While advanced imaging techniques have substantially improved the identification of anatomical targets within this region, uncertainties persist regarding the distinct anatomical substrates involved in optimal tremor control. Inconsistent subdivisions and nomenclature of motor areas and other subdivisions in the thalamus further obfuscate the interpretation of stimulation results. While loss of benefit and habituation to DBS remain challenging in some patients, refined DBS techniques and closed-loop paradigms may eventually overcome these limitations.

Somatotopic organization of the ventral nuclear group of the dorsal thalamus: deep brain stimulation for neuropathic pain reveals new insights into the facial homunculus

Deep Brain Stimulation (DBS) is an experimental treatment for medication-refractory neuropathic pain. The ventral posteromedial (VPM) and ventral posterolateral (VPL) nuclei of the thalamus are popular targets for the treatment of facial and limb pain, respectively. While intraoperative testing is used to adjust targeting of patient-specific pain locations, a better understanding of thalamic somatotopy may improve targeting of specific body regions including the individual trigeminal territories, face, arm, and leg. To elucidate the somatotopic organization of the ventral nuclear group of the dorsal thalamus using in vivo macrostimulation data from patients undergoing DBS for refractory neuropathic pain. In vivo macrostimulation data was retrospectively collected for 14 patients who underwent DBS implantation for neuropathic pain syndromes at our institution. 56 contacts from 14 electrodes reconstructed with LeadDBS were assigned to macrostimulation-related body regions: tongue, face, arm, or leg. 33 contacts from 9 electrodes were similarly assigned to one of three trigeminal territories: V1, V2, or V3. MNI coordinates in the x, y, and z axes were compared by using MANOVA. Across the horizontal plane of the ventral nuclear group of the dorsal thalamus, the tongue was represented significantly medially, followed by the face, arm, and leg most laterally (p < 0.001). The trigeminal territories displayed significant mediolateral distribution, proceeding from V1 and V2 most medial to V3 most lateral (p < 0.001). Along the y-axis, V2 was also significantly anterior to V3 (p = 0.014). While our results showed that the ventral nuclear group of the dorsal thalamus displayed mediolateral somatotopy of the tongue, face, arm, and leg mirroring the cortical homunculus, the mediolateral distribution of trigeminal territories did not mirror the established cortical homunculus. This finding suggests that the facial homunculus may be inverted in the ventral nuclear group of the dorsal thalamus.

Elevating the field for applying neuroimaging to individual patients in psychiatry

Although neuroimaging has been widely applied in psychiatry, much of the exuberance in decades past has been tempered by failed replications and a lack of definitive evidence to support the utility of imaging to inform clinical decisions. There are multiple promising ways forward to demonstrate the relevance of neuroimaging for psychiatry at the individual patient level. Ultra-high field magnetic resonance imaging is developing as a sensitive measure of neurometabolic processes of particular relevance that holds promise as a new way to characterize patient abnormalities as well as variability in response to treatment. Neuroimaging may also be particularly suited to the science of brain stimulation interventions in psychiatry given that imaging can both inform brain targeting as well as measure changes in brain circuit communication as a function of how effectively interventions improve symptoms. We argue that a greater focus on individual patient imaging data will pave the way to stronger relevance to clinical care in psychiatry. We also stress the importance of using imaging in symptom-relevant experimental manipulations and how relevance will be best demonstrated by pairing imaging with differential treatment prediction and outcome measurement. The priorities for using brain imaging to inform psychiatry may be shifting, which compels the field to solidify clinical relevance for individual patients over exploratory associations and biomarkers that ultimately fail to replicate.

Uncovering neuroanatomical correlates of impaired coordinated movement after pallidal deep brain stimulation

BACKGROUND

The loss of the ability to swim following deep brain stimulation (DBS), although rare, poses a worrisome risk of drowning. It is unclear what anatomic substrate and neural circuitry underlie this phenomenon. We report a case of cervical dystonia with lost ability to swim and dance during active stimulation of globus pallidus internus. We investigated the anatomical underpinning of this phenomenon using unique functional and structural imaging analysis.

METHODS

Tesla (3T) functional MRI (fMRI) of the patient was used during active DBS and compared with a cohort of four matched patients without this side effect. Structural connectivity mapping was used to identify brain network engagement by stimulation.

RESULTS

fMRI during stimulation revealed significant (Pbonferroni<0.0001) stimulation-evoked responses (DBS ON

CONCLUSIONS

These stimulation-induced impairments are likely a manifestation of a broader deficit in interlimb coordination mediated by stimulation effects on the SMA. This neuroanatomical underpinning can help inform future patient-specific stimulation and targeting.

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Key Words

• DYSTONIA
• ELECTRICAL STIMULATION
• FUNCTIONAL IMAGING
• MRI
• NEUROSURGERY

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MESH Headings

• Humans
• Globus Pallidus/diagnostic imaging
• Globus Pallidus/physiology
• Deep Brain Stimulation/adverse effects
• Deep Brain Stimulation/methods
• Treatment Outcome
• Magnetic Resonance Imaging

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Affiliation(s)

Brendan Santyr Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada
Aaron Loh Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada
Artur Vetkas Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada
Dave Gwun Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada
Wilson Kw Fung Edmond J. Safra Program in Parkinson's Disease and Morton and Gloria Shulman Movement Disorders Centre, Toronto Western Hospital, Toronto, Ontario, Canada
Shakeel Qazi Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada
Jurgen Germann Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada
Alexandre Boutet Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada Joint Department of Medical Imaging, Toronto Western Hospital, Toronto, Ontario, Canada
Can Sarica Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada
Andrew Yang Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada
Gavin Elias Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada
Suneil K Kalia Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada Center for Advancing Neurotechnological Innovation to Application (CRANIA), University Health Network, Toronto, Ontario, Canada
Alfonso Fasano Edmond J. Safra Program in Parkinson's Disease and Morton and Gloria Shulman Movement Disorders Centre, Toronto Western Hospital, Toronto, Ontario, Canada Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada Center for Advancing Neurotechnological Innovation to Application (CRANIA), University Health Network, Toronto, Ontario, Canada Division of Neurology, University of Toronto, Toronto, Ontario, Canada
Andres M Lozano Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada

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Comparative neural correlates of DBS and MRgFUS lesioning for tremor control in essential tremor

BACKGROUND

Given high rates of early complications and non-reversibility, refined targeting is necessitated for magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy for essential tremor (ET). Selection of lesion location can be informed by considering optimal stimulation area from deep brain stimulation (DBS).

METHODS

118 patients with ET who received DBS (39) or MRgFUS (79) of the ventral intermediate nucleus (VIM) underwent stimulation/lesion mapping, probabilistic mapping of clinical efficacy and normative structural connectivity analysis. The efficacy maps were compared, which depict the relationship between stimulation/lesion location and clinical outcome.

RESULTS

Efficacy maps overlap around the VIM ventral border and encompass the dentato-rubro-thalamic tract. While the MRgFUS map extends inferiorly into the posterior subthalamic area, the DBS map spreads inside the VIM antero-superiorly.

CONCLUSION

Comparing the efficacy maps of DBS and MRgFUS suggests a potential alternative location for lesioning, more antero-superiorly. This may reduce complications, without sacrificing efficacy, and individualise targeting.

TRIAL REGISTRATION NUMBER

NCT02252380.

Computational Neurosurgery in Deep Brain Stimulation

Computational methods and technologies are critical for neurosurgery in general and in deep brain stimulation (DBS) in particular. They increasingly inform every aspect of clinical DBS therapy, from presurgical planning and hardware implantation to postoperative adjustment of stimulation parameters. Computational methods also occupy a prominent position within the DBS research sphere, where they facilitate efforts to better understand DBS' underlying mechanisms and optimize and individualize its delivery. This chapter provides a high-level overview of the various computational tools and methods that have been applied to DBS. First, we discuss the invaluable contribution of computational neuroimaging (primarily magnetic resonance imaging) to DBS, targeting and the role of postoperative methods of image analysis-specifically, electrode localization, volume of activated tissue modeling, and sweet-spot mapping-in precisely localizing DBS' targets in the brain and discerning optimal treatment loci. We then address the growing field of connectomics, which leverages specific magnetic resonance imaging (MRI) sequences and post-acquisition processing algorithms to explore how DBS operates at the level of brain-wide networks. Next, the search for electrophysiological and imaging-based biomarkers of optimal DBS therapy is explored. We lastly touch on the incipient field of spatial characterization analysis and discuss the ongoing development of adaptive, closed-loop DBS systems.

Graph Theory and Modeling of Network Topology in Clinical Neurosurgery

The last several decades have seen a shift in understanding many neurological disorders as abnormalities in brain networks rather than specific brain regions. This conceptual revolution, coupled with advancements in computing capabilities and resources, has enabled a wealth of research on delineating and treating aberrant brain networks. One approach to network neuroscience, graph theory, involves modeling network topologies as mathematical graphs and computing various metrics that describe its characteristics. Using graph theory, researchers have derived new insights into the pathophysiology of many neuropsychiatric disorders and even developed treatments targeted at restoring network disturbances. In this chapter, we provide an overview of the principles of graph theory and how to implement it, specific applications of graph theory within clinical neurosurgery, and a discussion on the advantages and limitations of these approaches.

Structural connections of the centromedian nucleus of thalamus and their relevance for neuromodulation in generalized drug-resistant epilepsy: insight from a tractography study

Background

Epilepsy is a widespread neurologic disorder and almost one-third of patients suffer from drug-resistant epilepsy (DRE). Neuromodulation targeting the centromediannucleus of the thalamus (CM) has been showing promising results for patients with generalized DRE who are not surgical candidates. Recently, the effect of CM- deep brain stimulation (DBS) in DRE patients was investigated in the Electrical Stimulation of Thalamus for Epilepsy of Lennox-Gastaut phenotype (ESTEL) trial, a monocentric randomized-controlled study. The same authors described a 'cold-spot' and a 'sweet-spot', which are defined as the volume of stimulation in the thalamus yielding the least and the best clinical response, respectively. However, it remains unclear which structural connections may contribute to the anti-seizure effect of the stimulation.

Objective

We investigated the differences in structural connectivity among CM, the sweet-spot and the cold-spot. Furthermore, we tried to validate our results in a cohort of DRE patients who underwent CM-DBS or CM-RNS (responsive neurostimulation). We hypothesized that the sweet-spot would share similar structural connectivity with responder patients.

Methods

By using the software FMRIB Software Library (FSL), probabilistic tractography was performed on 100 subjects from the Human Connectome Project to calculate the probability of connectivity of the whole CM, the sweet-spot and the cold-spot to 45 cortical and subcortical areas. Results among the three seeds were compared with multivariate analysis of variance (MANOVA). Similarly, the structural connectivity of volumes of tissue activated (VTAs) from eight DRE patients was investigated. Patients were divided into responders and non-responders based on the degree of reduction in seizure frequency, and the mean probabilities of connectivity were similarly compared between the two groups.

Results

The sweet-spot demonstrated a significantly higher probability of connectivity (p < 0.001) with the precentral gyrus, superior frontal gyrus, and the cerebellum than the whole CM and the cold-spot. Responder patients displayed a higher probability of connectivity with both ipsilateral (p = 0.011) and contralateral cerebellum (p = 0.04) than the non-responders.

Conclusion

Cerebellar connections seem to contribute to the beneficial effects of CM-neuromodulation in patients with drug-resistant generalized epilepsy.

Deep Brain Stimulation for Refractory Status Dystonicus in Children: Multicenter Case Series and Systematic Review

OBJECTIVE

We sought to better understand the workflow, outcomes, and complications of deep brain stimulation (DBS) for pediatric status dystonicus (SD). We present a systematic review, alongside a multicenter case series of pediatric patients with SD treated with DBS.

METHODS

We collected individual data regarding treatment, stimulation parameters, and dystonia severity for a multicenter case series (n = 8) and all previously published cases (n = 77). Data for case series were used to create probabilistic voxelwise maps of stimulated tissue associated with dystonia improvement.

RESULTS

In our institutional series, DBS was implanted a mean of 25 days after SD onset. Programming began a mean of 1.6 days after surgery. All 8 patients in our case series and 73 of 74 reported patients in the systematic review had resolution of their SD with DBS, most within 2 to 4 weeks of surgery. Mean follow-up for patients in the case series was 16 months. DBS target for all patients in the case series and 68 of 77 in our systematic review was the globus pallidus pars interna (GPi). In our case series, stimulation of the posterior-ventrolateral GPi was associated with improved dystonia. Mean dystonia improvement was 32% and 51% in our institutional series and systematic review, respectively. Mortality was 4% in the review, which is lower than reported for treatment with pharmacotherapy alone (10-12.5%).

INTERPRETATION

DBS is a feasible intervention with potential to reverse refractory pediatric SD and improve survival. More work is needed to increase awareness of DBS in this setting, so that it can be implemented in a timely manner. ANN NEUROL 2023.

Pathological pallidal beta activity in Parkinson's disease is sustained during sleep and associated with sleep disturbance

Parkinson's disease (PD) is associated with excessive beta activity in the basal ganglia. Brain sensing implants aim to leverage this biomarker for demand-dependent adaptive stimulation. Sleep disturbance is among the most common non-motor symptoms in PD, but its relationship with beta activity is unknown. To investigate the clinical potential of beta activity as a biomarker for sleep quality in PD, we recorded pallidal local field potentials during polysomnography in PD patients off dopaminergic medication and compared the results to dystonia patients. PD patients exhibited sustained and elevated beta activity across wakefulness, rapid eye movement (REM), and non-REM sleep, which was correlated with sleep disturbance. Simulation of adaptive stimulation revealed that sleep-related beta activity changes remain unaccounted for by current algorithms, with potential negative outcomes in sleep quality and overall quality of life for patients.

Optimal subthalamic stimulation sites and related networks for freezing of gait in Parkinson's disease

Freezing of gait is a common and debilitating symptom in Parkinson's disease. Although high-frequency subthalamic deep brain stimulation is an effective treatment for Parkinson's disease, post-operative freezing of gait severity has been reported to alleviate, deteriorate or remain constant. We conducted this study to explore the optimal stimulation sites and related connectivity networks for high-frequency subthalamic deep brain stimulation treating freezing of gait in Parkinson's disease. A total of 76 Parkinson's disease patients with freezing of gait who underwent bilateral high-frequency subthalamic stimulation were retrospectively included. The volumes of tissue activated were estimated based on individual electrode reconstruction. The optimal and sour stimulation sites were calculated at coordinate/voxel/mapping level and mapped to anatomical space based on patient-specific images and stimulation settings. The structural and functional predictive connectivity networks for the change of the post-operative Freezing of Gait-Questionnaire were also identified based on normative connectomes derived from the Parkinson's Progression Marker Initiative database. Leave-one-out cross-validation model validated the above results, and the model remained significant after including covariates. The dorsolateral two-thirds of the subthalamic nucleus was identified as the optimal stimulation site, while the ventrocentral portion of the right subthalamic nucleus and internal capsule surrounding the left central subthalamic nucleus were considered as the sour stimulation sites. Modulation of the fibre tracts connecting to the supplementary motor area, pre-supplementary motor area and pedunculopontine nucleus accounted for the alleviation of freezing of gait, whereas tracts connecting to medial and ventrolateral prefrontal cortices contributed to the deterioration of freezing of gait. The optimal/sour stimulation sites and structural/functional predictive connectivity networks for high-frequency subthalamic deep brain stimulation treating freezing of gait are identified and validated through sizable Parkinson's disease patients in this study. With the growing understanding of stimulation sites and related networks, individualized deep brain stimulation treatment with directional leads will become an optimal choice for Parkinson's disease patients with freezing of gait in the future.

Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation

BACKGROUND

Deep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome.

OBJECTIVE/HYPOTHESIS

We aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort.

METHODS

Volumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome ('discriminative' streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures.

RESULTS

PSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047).

CONCLUSION(S)

These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.

Validation of Lead-DBS β-Oscillation Localization with Directional Electrodes

In deep brain stimulation (DBS) studies in patients with Parkinson's disease, the Lead-DBS toolbox allows the reconstruction of the location of β-oscillations in the subthalamic nucleus (STN) using Vercise Cartesia directional electrodes (Boston Scientific). The objective was to compare these probabilistic locations with those of intraoperative monopolar β-oscillations computed from local field potentials (0.5-3 kHz) recorded by using shielded single wires and an extracranial shielded reference electrode. For each electrode contact, power spectral densities of the β-band (13-31 Hz) were compared with those of all eight electrode contacts on the directional electrodes. The DBS Intrinsic Template AtLas (DISTAL), electrophysiological, and DBS target atlases of the Lead-DBS toolbox were applied to the reconstructed electrodes from preoperative MRI and postoperative CT. Thirty-six electrodes (20 patients: 7 females, 13 males; both STN electrodes for 16 of 20 patients; one single STN electrode for 4 of 20 patients) were analyzed. Stimulation sites both dorsal and/or lateral to the sensorimotor STN were the most efficient. In 33 out of 36 electrodes, at least one contact was measured with stronger β-oscillations, including 23 electrodes running through or touching the ventral subpart of the β-oscillations' probabilistic volume, while 10 did not touch it but were adjacent to this volume; in 3 out of 36 electrodes, no contact was found with β-oscillations and all 3 were distant from this volume. Monopolar local field potentials confirmed the ventral subpart of the probabilistic β-oscillations.

How Sample Size Impacts Probabilistic Stimulation Maps in Deep Brain Stimulation

Probabilistic stimulation maps of deep brain stimulation (DBS) effect based on voxel-wise statistics (p-maps) have increased in literature over the last decade. These p-maps require correction for Type-1 errors due to multiple testing based on the same data. Some analyses do not reach overall significance, and this study aims to evaluate the impact of sample size on p-map computation. A dataset of 61 essential tremor patients treated with DBS was used for the investigation. Each patient contributed with four stimulation settings, one for each contact. From the dataset, 5 to 61 patients were randomly sampled with replacement for computation of p-maps and extraction of high- and low-improvement volumes. For each sample size, the process was iterated 20 times with new samples generating in total 1140 maps. The overall p-value corrected for multiple comparisons, significance volumes, and dice coefficients (DC) of the volumes within each sample size were evaluated. With less than 30 patients (120 simulations) in the sample, the variation in overall significance was larger and the median significance volumes increased with sample size. Above 120 simulations, the trends stabilize but present some variations in cluster location, with a highest median DC of 0.73 for n = 57. The variation in location was mainly related to the region between the high- and low-improvement clusters. In conclusion, p-maps created with small sample sizes should be evaluated with caution, and above 120 simulations in single-center studies are probably required for stable results.

Internal Capsule/Nucleus Accumbens Deep Brain Stimulation Increases Impulsive Decision Making in Obsessive-Compulsive Disorder

BACKGROUND

Deep brain stimulation of the anterior limb of the internal capsule (ALIC)/nucleus accumbens is an effective treatment in patients with obsessive-compulsive disorder but may increase impulsive behavior. We aimed to investigate how active stimulation alters subdomains of impulsive decision making and whether respective effects depend on the location of stimulation sites.

METHODS

We assessed 15 participants with obsessive-compulsive disorder performing the Cambridge Gambling Task during active and inactive ALIC/nucleus accumbens deep brain stimulation. Specifically, we determined stimulation-induced changes in risk adjustment and delay aversion. To characterize underlying neural pathways, we computed probabilistic stimulation maps and applied fiber filtering based on normative structural connectivity data to identify "hot" and "cold" spots/fibers related to changes in impulsive decision making.

RESULTS

Active stimulation significantly reduced risk adjustment while increasing delay aversion, both implying increased impulsive decision making. Changes in risk adjustment were robustly associated with stimulation sites located in the central ALIC and fibers connecting the thalamus and subthalamic nucleus with the medial and lateral prefrontal cortex. Both hot spots and fibers for changes in risk adjustment were robust to leave-one-out cross-validation. Changes in delay aversion were similarly associated with central ALIC stimulation, but validation hereof was nonsignificant.

CONCLUSIONS

Our findings provide experimental evidence that ALIC/nucleus accumbens stimulation increases impulsive decision making in obsessive-compulsive disorder. We show that changes in risk adjustment depend on the location of stimulation volumes and affected fiber bundles. The relationship between impulsive decision making and long-term clinical outcomes requires further investigation.

Probabilistic mapping of deep brain stimulation in childhood dystonia

OBJECTIVES

In adults with dystonia Probabilistic Stimulation Mapping (PSM) has identified putative "sweet spots" for stimulation. We aimed to apply PSM to a cohort of Children and Young People (CYP) following DBS surgery.

METHODS

Pre-operative MRI and post-operative CT images were co-registered for 52 CYP undergoing bilateral pallidal DBS (n = 31 genetic/idiopathic dystonia, and n = 21 Cerebral Palsy (CP)). DBS electrodes (n = 104) were automatically detected, and Volumes of Tissue Activation (VTA) derived from individual patient stimulation settings. VTAs were normalised to the MNI105 space, weighted by percentage improvement in Burke-Fahn-Marsden Dystonia Rating scale (BFMDRS) at one-year post surgery and mean improvement was calculated for each voxel.

RESULTS

For the genetic/idiopathic dystonia group, BFMDRS improvement was associated with stimulation across a broad volume of the GPi. A spatial clustering of the upper 25th percentile of voxels corresponded with a more delineated volume within the posterior ventrolateral GPi. The MNI coordinates of the centroid of this volume (X = -23.0, Y = -10.5 and Z = -3.5) were posterior and superior to the typical target for electrode placement. Volume of VTA overlap with a previously published "sweet spots" correlated with improvement following surgery. In contrast, there was minimal BFMDRS improvement for the CP group, no spatial clustering of efficacious clusters and a correlation between established "sweet spots" could not be established.

CONCLUSIONS

PSM in CYP with genetic/idiopathic dystonia suggests the presence of a "sweet spot" for electrode placement within the GPi, consistent with previous studies. Further work is required to identify and validate putative "sweet spots" across different cohorts of patients.

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.

Ipsilateral and axial tremor response to focused ultrasound thalamotomy for essential tremor: clinical outcomes and probabilistic mapping

BACKGROUND

MR-guided focused ultrasound (MRgFUS) thalamotomy has been shown to be a safe and effective treatment for essential tremor (ET).

OBJECTIVE

To investigate the effects of MRgFUS in patients with ET with an emphasis on ipsilateral-hand and axial tremor subscores.

METHODS

Tremor scores and adverse effects of 100 patients treated between 2012 and 2018 were assessed at 1 week, 3, 12, and 24 months. A subgroup analysis of ipsilateral-hand tremor responders (defined as patients with ≥30% improvement at any time point) and non-responders was performed. Correlations and predictive factors for improvement were analysed. Weighted probabilistic maps of improvement were generated.

RESULTS

Significant improvement in axial, contralateral-hand and total tremor scores was observed at all study visits from baseline (p<0.0001). There was no significant improvement in ipsilateral subscores. A subset of patients (n=20) exhibited group-level ipsilateral-hand improvement that remained significant through all follow-ups (p<0.001). Multivariate regression analysis revealed that higher baseline scores predict better improvement in ipsilateral-hand and axial tremor. Probabilistic maps demonstrated that the lesion hotspot for axial improvement was situated more medially than that for contralateral improvement.

CONCLUSION

MRgFUS significantly improved axial, contralateral-hand and total tremor scores. In a subset of patients, a consistent group-level treatment effect was observed for ipsilateral-hand tremor. While ipsilateral improvement seemed to be less directly related to lesion location, a spatial relationship between lesion location and axial and contralateral improvement was observed that proved consistent with the somatotopic organisation of the ventral intermediate nucleus.

TRIAL REGISTRATION NUMBERS

NCT01932463, NCT01827904, and NCT02252380.

Probabilistic maps for deep brain stimulation - Impact of methodological differences

BACKGROUND

Group analysis of patients with deep brain stimulation (DBS) has the potential to help understand and optimize the treatment of patients with movement disorders. Probabilistic stimulation maps (PSM) are commonly used to analyze the correlation between tissue stimulation and symptomatic effect but are applied with different methodological variations.

OBJECTIVE

To compute a group-specific MRI template and PSMs for investigating the impact of PSM model parameters.

METHODS

Improvement and occurrence of dizziness in 68 essential tremor patients implanted in caudal zona incerta were analyzed. The input data includes the best parameters for each electrode contact (screening), and the clinically used settings. Patient-specific electric field simulations (n = 488) were computed for all DBS settings. The electric fields were transformed to a group-specific MRI template for analysis and visualization. The different comparisons were based on PSMs representing occurrence (N-map), mean improvement (M-map), weighted mean improvement (wM-map), and voxel-wise t-statistics (p-map). These maps were used to investigate the impact from input data (clinical/screening settings), clustering methods, sampling resolution, and weighting function.

RESULTS

Screening or clinical settings showed the largest impacts on the PSMs. The average differences of wM-maps were 12.4 and 18.2% points for the left and right sides respectively. Extracting clusters based on wM-map or p-map showed notable variation in volumes, while positioning was similar. The impact on the PSMs was small from weighting functions, except for a clear shift in the positioning of the wM-map clusters.

CONCLUSION

The distribution of the input data and the clustering method are most important to consider when creating PSMs for studying the relationship between anatomy and DBS outcome.

Brain Connectomics

A central tenet of modern neuroscience is the conceptualization of the brain as a collection of complex networks or circuits with a shift away from traditional "localizationist" theories. Connectomics seeks to unravel these brain networks and their role in the pathophysiology of neurologic diseases. This article discusses the science of connectomics with the examples of its potential role in clinical medicine and neuromodulation in multiple disorders, such as essential tremor, Parkinson's disease, obsessive-compulsive disorder, and epilepsy.

Neural correlates of optimal deep brain stimulation for cervical dystonia

Fifteen subjects with cervical dystonia and good outcome following pallidal deep brain stimulation underwent resting-state functional magnetic resonance imaging under three conditions: stimulation using a priori clinically determined optimal settings (ON-Op), non-optimal settings (ON-NOp), and stimulation off (OFF). ON-Op>OFF and ON-Op>ON-NOp were both associated with significant deactivation within sensorimotor cortex (changes not seen with ON-NOp>OFF). Brain responses to stimulation were related to individual long-term clinical improvement (R=0.73 , R² =0.53, p=0.001). The relationship was consistent when this model included four additional patients with generalized or truncal dystonia. These findings highlight the potential for immediate imaging-based biomarkers of clinical efficacy. This article is protected by copyright. All rights reserved.

Lead-OR: A multimodal platform for deep brain stimulation surgery

Background

Deep brain stimulation (DBS) electrode implant trajectories are stereotactically defined using preoperative neuroimaging. To validate the correct trajectory, microelectrode recordings (MERs) or local field potential recordings can be used to extend neuroanatomical information (defined by MRI) with neurophysiological activity patterns recorded from micro- and macroelectrodes probing the surgical target site. Currently, these two sources of information (imaging vs. electrophysiology) are analyzed separately, while means to fuse both data streams have not been introduced.

Methods

Here, we present a tool that integrates resources from stereotactic planning, neuroimaging, MER, and high-resolution atlas data to create a real-time visualization of the implant trajectory. We validate the tool based on a retrospective cohort of DBS patients (N = 52) offline and present single-use cases of the real-time platform.

Results

We establish an open-source software tool for multimodal data visualization and analysis during DBS surgery. We show a general correspondence between features derived from neuroimaging and electrophysiological recordings and present examples that demonstrate the functionality of the tool.

Conclusions

This novel software platform for multimodal data visualization and analysis bears translational potential to improve accuracy of DBS surgery. The toolbox is made openly available and is extendable to integrate with additional software packages.

Funding

Deutsche Forschungsgesellschaft (410169619, 424778381), Deutsches Zentrum für Luft- und Raumfahrt (DynaSti), National Institutes of Health (2R01 MH113929), and Foundation for OCD Research (FFOR).

Personalizing Deep Brain Stimulation Using Advanced Imaging Sequences

OBJECTIVE

With a growing appreciation for interindividual anatomical variability and patient-specific brain connectivity, advanced imaging sequences offer the opportunity to directly visualize anatomical targets for deep brain stimulation (DBS). The lack of quantitative evidence demonstrating their clinical utility, however, has hindered their broad implementation in clinical practice.

METHODS

Using fast gray matter acquisition T1 inversion recovery (FGATIR) sequences, the present study identified a thalamic hypointensity that holds promise as a visual marker in DBS. To validate the clinical utility of the identified hypointensity, we retrospectively analyzed 65 patients (26 female, mean age = 69.1 ± 12.7 years) who underwent DBS in the treatment of essential tremor. We characterized its neuroanatomical substrates and evaluated the hypointensity's ability to predict clinical outcome using stimulation volume modeling and voxelwise mapping. Finally, we determined whether the hypointensity marker could predict symptom improvement on a patient-specific level.

RESULTS

Anatomical characterization suggested that the identified hypointensity constituted the terminal part of the dentatorubrothalamic tract. Overlap between DBS stimulation volumes and the hypointensity in standard space significantly correlated with tremor improvement (R²  = 0.16, p = 0.017) and distance to hotspots previously reported in the literature (R²  = 0.49, p = 7.9e-4). In contrast, the amount of variance explained by other anatomical atlas structures was reduced. When accounting for interindividual neuroanatomical variability, the predictive power of the hypointensity increased further (R²  = 0.37, p = 0.002).

INTERPRETATION

Our findings introduce and validate a novel imaging-based marker attainable from FGATIR sequences that has the potential to personalize and inform targeting and programming in DBS for essential tremor. ANN NEUROL 2022;91:613-628.

The optimal target and connectivity for DBS in Lennox‐Gastaut syndrome

Objective

Deep brain stimulation (DBS) can reduce seizures in Lennox–Gastaut syndrome (LGS). However, little is known about the optimal target and whether efficacy depends on connectivity of the stimulation site. Using outcome data from the ESTEL trial, we aimed to determine the optimal target and connectivity for DBS in LGS.

Methods

A total of 20 patients underwent bilateral DBS of the thalamic centromedian nucleus (CM). Outcome was percentage seizure reduction from baseline after 3 months of DBS, defined using three measures (monthly seizure diaries, 24‐hour scalp electroencephalography [EEG], and a novel diary‐EEG composite). Probabilistic stimulation mapping identified thalamic locations associated with higher/lower efficacy. Two substitute diffusion MRI datasets (a normative dataset from healthy subjects and a “disease‐matched” dataset from a separate group of LGS patients) were used to calculate structural connectivity between DBS sites and a map of areas known to express epileptic activity in LGS, derived from our previous EEG‐fMRI research.

Results

Results were similar across the three outcome measures. Stimulation was most efficacious in the anterior and inferolateral “parvocellular” CM border, extending into the ventral lateral nucleus (posterior subdivision). There was a positive association between diary‐EEG composite seizure reduction and connectivity to areas of a priori EEG‐fMRI activation, including premotor and prefrontal cortex, putamen, and pontine brainstem. In contrast, outcomes were not associated with baseline clinical variables.

Interpretation

Efficacious CM‐DBS for LGS is linked to stimulation of the parvocellular CM and the adjacent ventral lateral nucleus, and is associated with connectivity to, and thus likely modulation of, the “secondary epileptic network” underlying the shared electroclinical manifestations of LGS. ANN NEUROL 2022;92:61–74

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.

Identifying the neural network for neuromodulation in epilepsy through connectomics and graphs

Deep brain stimulation is a treatment option for patients with drug-resistant epilepsy. The precise mechanism of neuromodulation in epilepsy is unknown, and biomarkers are needed for optimizing treatment. The aim of this study was to describe the neural network associated with deep brain stimulation targets for epilepsy and to explore its potential application as a novel biomarker for neuromodulation. Using seed-to-voxel functional connectivity maps, weighted by seizure outcomes, brain areas associated with stimulation were identified in normative resting state functional scans of 1000 individuals. To pinpoint specific regions in the normative epilepsy deep brain stimulation network, we examined overlapping areas of functional connectivity between the anterior thalamic nucleus, centromedian thalamic nucleus, hippocampus and less studied epilepsy deep brain stimulation targets. Graph network analysis was used to describe the relationship between regions in the identified network. Furthermore, we examined the associations of the epilepsy deep brain stimulation network with disease pathophysiology, canonical resting state networks and findings from a systematic review of resting state functional MRI studies in epilepsy deep brain stimulation patients. Cortical nodes identified in the normative epilepsy deep brain stimulation network were in the anterior and posterior cingulate, medial frontal and sensorimotor cortices, frontal operculum and bilateral insulae. Subcortical nodes of the network were in the basal ganglia, mesencephalon, basal forebrain and cerebellum. Anterior thalamic nucleus was identified as a central hub in the network with the highest betweenness and closeness values, while centromedian thalamic nucleus and hippocampus showed average centrality values. The caudate nucleus and mammillothalamic tract also displayed high centrality values. The anterior cingulate cortex was identified as an important cortical hub associated with the effect of deep brain stimulation in epilepsy. The neural network of deep brain stimulation targets shared hubs with known epileptic networks and brain regions involved in seizure propagation and generalization. Two cortical clusters identified in the epilepsy deep brain stimulation network included regions corresponding to resting state networks, mainly the default mode and salience networks. Our results were concordant with findings from a systematic review of resting state functional MRI studies in patients with deep brain stimulation for epilepsy. Our findings suggest that the various epilepsy deep brain stimulation targets share a common cortico-subcortical network, which might in part underpin the antiseizure effects of stimulation. Interindividual differences in this network functional connectivity could potentially be used as biomarkers in selection of patients, stimulation parameters and neuromodulation targets.

Clinically-derived oscillatory biomarker predicts optimal subthalamic stimulation for Parkinson's disease

OBJECTIVE

Choosing the optimal electrode trajectory, stimulation location, and stimulation amplitude in subthalamic nucleus deep brain stimulation (STN DBS) for Parkinson's disease (PD) remains a time-consuming empirical effort. In this retrospective study, we derive a data-driven electrophysiological biomarker that predicts clinical DBS location and parameters, and we consolidate this information into a quantitative score that may facilitate an objective approach to STN DBS surgery and programming.

APPROACH

Random-forest feature selection was applied to a dataset of 1046 microelectrode recordings sites across 20 DBS implant trajectories to identify features of oscillatory activity that predict clinically programmed volumes of tissue activation (VTA). A cross-validated classifier was used to retrospectively predict VTA regions from these features. Spatial convolution of probabilistic classifier outputs along MER trajectories produced a biomarker score that reflects the probability of localization within a clinically optimized VTA.

MAIN RESULTS

Biomarker scores peaked within the VTA region and were significantly correlated with percent improvement in postoperative motor symptoms (MDS-UPRDS Part III, R = 0.61, p = 0.004). Notably, the length of STN, a common criterion for trajectory selection, did not show similar correlation (R = -0.31, p = 0.18). These findings suggest that biomarker-based trajectory selection and programming may improve motor outcomes by 9 ± 3 percentage points (p = 0.047) in this dataset.

SIGNIFICANCE

A clinically defined electrophysiological biomarker not only predicts VTA size and location but also correlates well with motor outcomes. Use of this biomarker for trajectory selection and initial stimulation may potentially simplify STN DBS surgery and programming.

Structural Connectivity of Subthalamic Nucleus Stimulation for Improving Freezing of Gait

BACKGROUND

Freezing of gait (FOG) is among the most common and disabling symptoms of Parkinson's disease (PD). Studies show that deep brain stimulation (DBS) of the subthalamic nucleus (STN) can reduce FOG severity. However, there is uncertainty about pathways that need to be modulated to improve FOG.

OBJECTIVE

To investigate whether STN-DBS effectively reduces FOG postoperatively and whether structural connectivity of the stimulated tissue explains variance of outcomes.

METHODS

We investigated 47 patients with PD and preoperative FOG. Freezing prevalence and severity was primarily assessed using the Freezing of Gait Questionnaire (FOG-Q). In a subset of 18 patients, provoked FOG during a standardized walking course was assessed. Using a publicly available model of basal-ganglia pathways we determined stimulation-dependent connectivity associated with postoperative changes in FOG. A region-of-interest analysis to a priori defined mesencephalic regions was performed using a disease-specific normative connectome.

RESULTS

Freezing of gait significantly improved six months postoperatively, marked by reduced frequency and duration of freezing episodes. Optimal stimulation volumes for improving FOG structurally connected to motor areas, the prefrontal cortex and to the globus pallidus. Stimulation of the lenticular fasciculus was associated with worsening of FOG. This connectivity profile was robust in a leave-one-out cross-validation. Subcortically, stimulation of fibers crossing the pedunculopontine nucleus and the substantia nigra correlated with postoperative improvement.

CONCLUSION

STN-DBS can alleviate FOG severity by modulating specific pathways structurally connected to prefrontal and motor cortices. More differentiated FOG assessments may allow to differentiate pathways for specific FOG subtypes in the future.

Habenular Involvement in Response to Subcallosal Cingulate Deep Brain Stimulation for Depression

The habenula (Hb) is a small, evolutionarily conserved epithalamic structure implicated in functions such as reward and mood regulation. Prior imaging work suggests that Hb's structural and functional properties may relate to treatment response in depression and other mood disorders. We used multimodal MRI techniques to investigate the potential involvement of Hb in response to subcallosal cingulate area deep brain stimulation (SCC-DBS) for treatment-resistant mood disorders. Using an automated segmentation technique, we compared Hb volume at baseline and at a subsequent post-operative timepoint (4.4 ± 3.0 years after surgery) in a cohort of 32 patients who received SCC-DBS. Clinical response to treatment (≥50% decrease in HAMD-17 from baseline to 12 months post-operation) was significantly associated with longitudinal Hb volume change: responders tended to have increased Hb volume over time, while non-responders showed decreased Hb volume (t = 2.4, p = 0.021). We additionally used functional MRI (fMRI) in a subcohort of SCC-DBS patients (n = 12) to investigate immediate within-patient changes in Hb functional connectivity associated with SCC-DBS stimulation. Active DBS was significantly associated with increased Hb connectivity to several prefrontal and corticolimbic regions (TFCE-adjusted p _Bonferroni < 0.0001), many of which have been previously implicated in the neurocircuitry of depression. Taken together, our results suggest that Hb may play an important role in the antidepressant effect of SCC-DBS.

3 T MRI of rapid brain activity changes driven by subcallosal cingulate deep brain stimulation

Deep brain stimulation targeting the subcallosal cingulate area (SCC-DBS), a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While SCC-DBS drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0 Tesla functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of twelve patients with fully implanted SCC-DBS devices. Four additional SCC-DBS patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n=78 acquisitions overall) during i) inactive DBS; ii) clinically optimal active DBS; iii) suboptimal active DBS. All scans were acquired within a single MRI session, each separated by a 5-minute washout period. Analysis of the amplitude of low frequency fluctuations (ALFF) in each sequence indicated that clinically optimal SCC-DBS reduced spontaneous brain activity in several areas, including bilateral dorsal anterior cingulate cortex (dACC), posterior cingulate cortex (PCC), precuneus, and left inferior parietal lobule (pBonferroni<0.0001). Stimulation-induced dACC signal reduction correlated with immediate within-session mood fluctuations, was greater at optimal versus suboptimal settings, and related to local cingulum bundle engagement. Moreover, linear modelling showed that immediate changes in dACC, PCC, and precuneus activity could predict individual long-term antidepressant improvement. A model derived from the primary cohort that incorporated ALFF changes in these three areas (along with pre-operative symptom severity) explained 55% of the variance in clinical improvement in that cohort. The same model also explained 93% of the variance in the out-of-sample validation cohort. Additionally all three brain areas exhibited significant changes in functional connectivity between active and inactive DBS states (pBonferroni<0.01). These results provide insight into the network-level mechanisms of SCC-DBS and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.

Predicting Outcome in a Cohort of Isolated and Combined Dystonia within Probabilistic Brain Mapping

Background

Probabilistic brain mapping is a promising tool to estimate the expected benefit of pallidal deep brain stimulation (GPi‐DBS) in patients with isolated dystonia (IsoD).

Objectives

To investigate the role of probabilistic mapping in combined dystonia (ComD).

Methods

We rendered the pallidal atlas and the volume of tissue activated (VTA) for a cohort of patients with IsoD (n = 20) and ComD (n = 10) that underwent GPi‐DBS. The VTA was correlated with clinical improvement. Afterwards, each VTA was applied on the previously published probabilistic model (Reich et al., 2019). The correlation between predicted and observed clinical benefit was studied in a linear regression model.

Results

A good correlation between observed and predicted outcome was found for both patients with IsoD (n = 14) and ComD (n = 7) (r² = 0.32; P < 0.05). In ComD, 42% of the variance in DBS response is explained by VTA‐based outcome map.

Conclusion

A probabilistic model would be helpful in clinical practice to circumvent unpredictable and less impressive motor results often found in ComD.

Connectivity correlates to predict essential tremor deep brain stimulation outcome: Evidence for a common treatment pathway

BACKGROUND AND PURPOSE

Deep brain stimulation (DBS) is the most common surgical treatment for essential tremor (ET), yet there is variation in outcome and stimulation targets. This study seeks to consolidate proposed stimulation "sweet spots," as well as assess the value of structural connectivity in predicting treatment outcomes.

MATERIALS AND METHODS

Ninety-seven ET individuals with unilateral thalamic DBS were retrospectively included. Using normative brain connectomes, structural connectivity measures were correlated with the percentage improvement in contralateral tremor, based on the Fahn-Tolosa-Marin tremor rating scale (TRS), after parameter optimization (range 3.1-12.9 months) using a leave-one-out cross-validation in 83 individuals. The predictive feature map was used for cross-validation in a separate cohort of 14 ET individuals treated at another center. Lastly, estimated volumes of tissue activated (VTA) were used to assess a treatment "sweet spot," which was compared to seven previously reported stimulation sweet spots and their relationship to the tract identified by the predictive feature map.

RESULTS

In the training cohort, structural connectivity between the VTA and dentato-rubro-thalamic tract (DRTT) correlated with contralateral tremor improvement (R = 0.41; p < 0.0001). The same connectivity profile predicted outcomes in a separate validation cohort (R = 0.59; p = 0.028). The predictive feature map represented the anatomical course of the DRTT, and all seven analyzed sweet spots overlapped the predictive tract (DRTT).

CONCLUSIONS

Our results strongly support the possibility that structural connectivity is a predictor of contralateral tremor improvement in ET DBS. The results suggest the future potential for a patient-specific functionally based surgical target. Finally, the results showed convergence in "sweet spots" suggesting the importance of the DRTT to the outcome.

Implantable Pulse Generators for Deep Brain Stimulation: Challenges, Complications, and Strategies for Practicality and Longevity

Deep brain stimulation (DBS) represents an important treatment modality for movement disorders and other circuitopathies. Despite their miniaturization and increasing sophistication, DBS systems share a common set of components of which the implantable pulse generator (IPG) is the core power supply and programmable element. Here we provide an overview of key hardware and software specifications of commercially available IPG systems such as rechargeability, MRI compatibility, electrode configuration, pulse delivery, IPG case architecture, and local field potential sensing. We present evidence-based approaches to mitigate hardware complications, of which infection represents the most important factor. Strategies correlating positively with decreased complications include antibiotic impregnation and co-administration and other surgical considerations during IPG implantation such as the use of tack-up sutures and smaller profile devices.Strategies aimed at maximizing battery longevity include patient-related elements such as reliability of IPG recharging or consistency of nightly device shutoff, and device-specific such as parameter delivery, choice of lead configuration, implantation location, and careful selection of electrode materials to minimize impedance mismatch. Finally, experimental DBS systems such as ultrasound, magnetoelectric nanoparticles, and near-infrared that use extracorporeal powered neuromodulation strategies are described as potential future directions for minimally invasive treatment.

Blood oxygen level-dependent (BOLD) response patterns with thalamic deep brain stimulation in patients with medically refractory epilepsy

OBJECTIVE

Anterior nucleus of thalamus (ANT) deep brain stimulation (DBS) has shown promise as a treatment for medically refractory epilepsy. To better understand the mechanism of this intervention, we used functional magnetic resonance imaging (fMRI) to map the acute blood oxygen level-dependent (BOLD) response pattern to thalamic DBS in fully implanted patients with epilepsy.

METHODS

Two patients with epilepsy implanted with bilateral ANT-DBS devices underwent four fMRI acquisitions each, during which active left-sided monopolar stimulation was delivered in a 30-s DBS-ON/OFF cycling paradigm. Each fMRI acquisition featured left-sided stimulation of a different electrode contact to vary the locus of stimulation within the thalamus and to map the brain regions modulated as a function of different contact selection. To determine the extent of peri-electrode stimulation and the engagement of local structures during each fMRI acquisition, volume of tissue activated (VTA) modeling was also performed.

RESULTS

Marked changes in the pattern of BOLD response were produced with thalamic stimulation, which varied with the locus of the active contact in each patient. BOLD response patterns to stimulation that directly engaged at least 5% of the anterior nuclear group by volume were characterized by changes in the bilateral putamen, thalamus, and posterior cingulate cortex, ipsilateral middle cingulate cortex and precuneus, and contralateral medial prefrontal and anterior cingulate.

SIGNIFICANCE

The differential BOLD response patterns associated with varying thalamic DBS parameters provide mechanistic insights and highlight the possibilities of fMRI biomarkers of optimizing stimulation in patients with epilepsy.