Neuroimaging Technological Advancements for Targeting in Functional Neurosurgery

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.

A Soft, High-Density Neuroelectronic Array

Techniques to study brain activities have evolved dramatically, yet tremendous challenges remain in acquiring high-throughput electrophysiological recordings minimally invasively. Here, we develop an integrated neuroelectronic array that is filamentary, high-density and flexible. Specifically, with a design of single-transistor multiplexing and current sensing, the total 256 neuroelectrodes achieve only a 2.3 × 0.3 mm2 area, unprecedentedly on a flexible substrate. A novel single-transistor multiplexing acquisition circuit further reduces noise from the electrodes, decreased the footprint of each pixel, and potentially increased the device lifetime. The filamentary neuroelectronic array also integrates with a rollable contact pad design, allowing the device to be injected through a syringe, enabling potential minimally invasive array delivery. Successful acute auditory experiments in rats validate the ability of the array to record neural signals with high tone decoding accuracy. Together, these results establish soft, high-density neuroelectronic arrays as promising devices for neuroscience research and clinical applications.

Deep brain stimulation in Parkinson's disease: state of the art and future perspectives

For more than 30 years, Deep Brain Stimulation (DBS) has been a therapeutic option for Parkinson's disease (PD) treatment. However, this therapy is still underutilized mainly due to misinformation regarding risks and clinical outcomes. DBS can ameliorate several motor and non-motor symptoms, improving patients' quality of life. Furthermore, most of the improvement after DBS is long-lasting and present even in advanced PD. Adequate patient selection, precise electric leads placement, and correct DBS programming are paramount for good surgical outcomes. Nonetheless, DBS still has many limitations: axial symptoms and signs, such as speech, balance and gait, do not improve to the same extent as appendicular symptoms and can even be worsened as a direct or indirect consequence of surgery and stimulation. In addition, there are still unanswered questions regarding patient's selection, surgical planning and programming techniques, such as the role of surgicogenomics, more precise imaging-based lead placement, new brain targets, advanced programming strategies and hardware features. The net effect of these innovations should not only be to refine the beneficial effect we currently observe on selected symptoms and signs but also to improve treatment resistant facets of PD, such as axial and non-motor features. In this review, we discuss the current state of the art regarding DBS selection, implant, and programming, and explore new advances in the DBS field.

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.

Neuromodulatory treatments for psychiatric disease: A comprehensive survey of the clinical trial landscape

BACKGROUND

Numerous neuromodulatory therapies are currently under investigation or in clinical use for the treatment of psychiatric conditions.

OBJECTIVE/HYPOTHESIS

We sought to catalogue past and present human research studies on psychiatric neuromodulation and identify relevant trends in this field.

METHODS

ClinicalTrials.gov (https://www.clinicaltrials.gov/) and the International Clinical Trials Registry Platform (https://www.who.int/ictrp/en/) were queried in March 2020 for trials assessing the outcome of neuromodulation for psychiatric disorders. Relevant trials were categorized by variables such as neuromodulation modality, country, brain target, publication status, design, and funding source.

RESULTS

From 72,086 initial search results, 1252 unique trials were identified. The number of trials registered annually has consistently increased. Half of all trials were active and a quarter have translated to publications. The largest proportion of trials involved depression (45%), schizophrenia (18%), and substance use disorders (14%). Trials spanned 37 countries; China, the second largest contributor (13%) after the United States (28%), has increased its output substantially in recent years. Over 75% of trials involved non-convulsive non-invasive modalities (e.g., transcranial magnetic stimulation), while convulsive (e.g., electroconvulsive therapy) and invasive modalities (e.g., deep brain stimulation) were less represented. 72% of trials featured approved or cleared interventions. Characteristic inter-modality differences were observed with respect to enrollment size, trial design/phase, and funding. Dorsolateral prefrontal cortex accounted for over half of focal neuromodulation trial targets. The proportion of trials examining biological correlates of neuromodulation has increased.

CONCLUSION(S)

These results provide a comprehensive overview of the state of psychiatric neuromodulation research, revealing the growing scope and internationalism of this field.

Ventral intermediate nucleus structural connectivity-derived segmentation: anatomical reliability and variability

The Ventral intermediate nucleus (Vim) of thalamus is the most targeted structure for the treatment of drug-refractory tremors. Since methodological differences across existing studies are remarkable and no gold-standard pipeline is available, in this study, we tested different parcellation pipelines for tractography-derived putative Vim identification. Thalamic parcellation was performed on a high quality, multi-shell dataset and a downsampled, clinical-like dataset using two different diffusion signal modeling techniques and two different voxel classification criteria, thus implementing a total of four parcellation pipelines. The most reliable pipeline in terms of inter-subject variability has been picked and parcels putatively corresponding to motor thalamic nuclei have been selected by calculating similarity with a histology-based mask of Vim. Then, spatial relations with optimal stimulation points for the treatment of essential tremor have been quantified. Finally, effect of data quality and parcellation pipelines on a volumetric index of connectivity clusters has been assessed. We found that the pipeline characterized by higher-order signal modeling and threshold-based voxel classification criteria was the most reliable in terms of inter-subject variability regardless data quality. The maps putatively corresponding to Vim were those derived by precentral and dentate nucleus-thalamic connectivity. However, tractography-derived functional targets showed remarkable differences in shape and sizes when compared to a ground truth model based on histochemical staining on seriate sections of human brain. Thalamic voxels connected to contralateral dentate nucleus resulted to be the closest to literature-derived stimulation points for essential tremor but at the same time showing the most remarkable inter-subject variability. Finally, the volume of connectivity parcels resulted to be significantly influenced by data quality and parcellation pipelines. Hence, caution is warranted when performing thalamic connectivity-based segmentation for stereotactic targeting.

Directional Deep Brain Stimulation of the Posteromedial Hypothalamus for Refractory Intermittent Explosive Disorder: A Case Series Using a Novel Neurostimulation Device and Intraoperative Microdialysis

BACKGROUND

Intermittent explosive disorder (IED) is a psychiatric disorder characterized by recurrent outbursts of aggressive behavior. Deep brain stimulation (DBS) in the posteromedial nucleus of the hypothalamus (pHyp) is an alternative therapy for extreme cases and shows promising results. Intraoperative microdialysis can help elucidate the neurobiological mechanism of pHyp-DBS. We sought to evaluate efficacy and safety of pHyp-DBS using 8-contact directional leads in patients with refractory IED (rIED) and the accompanying changes in neurotransmitters.

METHODS

This was a prospective study in which patients with a diagnosis of rIED were treated with pHyp-DBS for symptom alleviation. Bilateral pHyp-DBS was performed with 8-contact directional electrodes. Follow-up was performed at 3, 6, and 12 months after surgery.

RESULTS

Four patients (3 men, mean age 27 ± 2.8 years) were included. All patients were diagnosed with rIED and severe intellectual disability. Two patients had congenital rubella, one had a co-diagnosis of infantile autism, and the fourth presented with drug-resistant epilepsy. There was a marked increase in the levels of gamma-aminobutyric acid and glycine during intraoperative stimulation. The average improvement in aggressive behavior in the last follow-up was 6 points (Δ: 50%, P = 0.003) while also documenting an important improvement of the Short Form Health Survey in all domains except bodily pain. No adverse events associated with pHyp-DBS were observed.

CONCLUSIONS

This is the first study to show the safety and beneficial effect of directional lead pHyp-DBS in patients with rIED and to demonstrate the corresponding mechanism of action through increases in gamma-aminobutyric acid and glycine concentration in the pHyp.

Brain MRI-guided focused ultrasound conceptualised as a tool for brain network intervention

Magnetic resonance imaging guided high intensity focused ultrasound (HIFU) has emerged as a tool offering incisionless intervention on brain tissue. The low risk and rapid recovery from this procedure, in addition to the ability to assess for clinical benefit and adverse events intraprocedurally, makes it an ideal tool for intervention upon brain networks both for clinical and research applications. This review article proposes that conceptualising brain focused ultrasound as a tool for brain network intervention and adoption of methodology to complement this approach may result in better clinical outcomes, fewer adverse events and may unveil or allow treatment opportunities not otherwise possible. A brief introduction to network neuroscience is discussed before a description of pathological brain networks is provided for a number of conditions for which MRI-guided brain HIFU intervention has been implemented. Essential Tremor is discussed as the most advanced example of MRI-guided brain HIFU intervention adoption along with the issues that present with this treatment modality compared to alternatives. The brain network intervention paradigm is proposed to overcome these issues and a number of examples of implementation of this are discussed. The ability of low intensity MRI guided focussed ultrasound to neuromoduate brain tissue without lesioning is introduced. This tool is discussed with regards to its potential clinical application as well as its potential to further our understanding of network neuroscience via its ability to interrogate brain networks without damaging tissue. Finally, a number of current clinical trials utilising brain focused ultrasound are discussed, along with the additional applications available from the utilisation of low intensity focused ultrasound.

Three-Tesla Magnetic Resonance Imaging of Patients With Deep Brain Stimulators: Results From a Phantom Study and a Pilot Study in Patients

BACKGROUND

Deep brain stimulation (DBS) is a standard of care treatment for multiple neurologic disorders. Although 3-tesla (3T) magnetic resonance imaging (MRI) has become the gold-standard modality for structural and functional imaging, most centers refrain from 3T imaging in patients with DBS devices in place because of safety concerns. 3T MRI could be used not only for structural imaging, but also for functional MRI to study the effects of DBS on neurocircuitry and optimize programming.

OBJECTIVE

To use an anthropomorphic phantom design to perform temperature and voltage safety testing on an activated DBS device during 3T imaging.

METHODS

An anthropomorphic 3D-printed human phantom was constructed and used to perform temperature and voltage testing on a DBS device during 3T MRI. Based on the phantom assessment, a cohort study was conducted in which 6 human patients underwent MRI with their DBS device in an activated (ON) state.

RESULTS

During the phantom study, temperature rises were under 2°C during all sequences, with the DBS in both the deactivated and activated states. Radiofrequency pulses from the MRI appeared to modulate the electrical discharge from the DBS, resulting in slight fluctuations of voltage amplitude. Six human subjects underwent MRI with their DBS in an activated state without any serious adverse events. One patient experienced stimulation-related side effects during T1-MPRAGE scanning with the DBS in an ON state because of radiofrequency-induced modulation of voltage amplitude.

CONCLUSION

Following careful phantom-based safety testing, 3T structural and functional MRI can be safely performed in subjects with activated deep brain stimulators.

Self-adjustment of deep brain stimulation delays optimization in Parkinson's disease

BACKGROUND

Parkinson's Disease patients undergo time-consuming programming to refine stimulation parameters after deep brain stimulation surgery.

OBJECTIVE

To assess whether the use of the advanced functions of a patient's programmer would facilitate programming of deep brain stimulation.

METHODS

Thirty patients were randomly allocated to the use of advanced versus simple mode of the patient programmer in this single-centre, prospective, randomized, controlled study. Primary outcome was the number of days required to optimize the stimulation settings.

RESULTS

The number of days required to optimize stimulation was significantly lower in the simple mode (88.5 ± 33.1 vs. 142.1 ± 67.4, p = 0.01). In addition, the advanced mode group had a higher number of side effects (5.4 ± 3.1 vs. 2.6 ± 1.9, p = 0.0055).

CONCLUSIONS

The use of the advanced functions of patient programmer delays programming optimization and it is associated with a higher number of side effects. These findings highlight the need for other methods for faster and safer stimulation programming.

Towards Tracking of Deep Brain Stimulation Electrodes Using an Integrated Magnetometer

This paper presents a tracking system using magnetometers, possibly integrable in a deep brain stimulation (DBS) electrode. DBS is a treatment for movement disorders where the position of the implant is of prime importance. Positioning challenges during the surgery could be addressed thanks to a magnetic tracking. The system proposed in this paper, complementary to existing procedures, has been designed to bridge preoperative clinical imaging with DBS surgery, allowing the surgeon to increase his/her control on the implantation trajectory. Here the magnetic source required for tracking consists of three coils, and is experimentally mapped. This mapping has been performed with an in-house three-dimensional magnetic camera. The system demonstrates how magnetometers integrated directly at the tip of a DBS electrode, might improve treatment by monitoring the position during and after the surgery. The three-dimensional operation without line of sight has been demonstrated using a reference obtained with magnetic resonance imaging (MRI) of a simplified brain model. We observed experimentally a mean absolute error of 1.35 mm and an Euclidean error of 3.07 mm. Several areas of improvement to target errors below 1 mm are also discussed.

A literature review of magnetic resonance imaging sequence advancements in visualizing functional neurosurgery targets

OBJECTIVE

Historically, preoperative planning for functional neurosurgery has depended on the indirect localization of target brain structures using visible anatomical landmarks. However, recent technological advances in neuroimaging have permitted marked improvements in MRI-based direct target visualization, allowing for refinement of "first-pass" targeting. The authors reviewed studies relating to direct MRI visualization of the most common functional neurosurgery targets (subthalamic nucleus, globus pallidus, and thalamus) and summarize sequence specifications for the various approaches described in this literature.

METHODS

The peer-reviewed literature on MRI visualization of the subthalamic nucleus, globus pallidus, and thalamus was obtained by searching MEDLINE. Publications examining direct MRI visualization of these deep brain stimulation targets were included for review.

RESULTS

A variety of specialized sequences and postprocessing methods for enhanced MRI visualization are in current use. These include susceptibility-based techniques such as quantitative susceptibility mapping, which exploit the amount of tissue iron in target structures, and white matter attenuated inversion recovery, which suppresses the signal from white matter to improve the distinction between gray matter nuclei. However, evidence confirming the superiority of these sequences over indirect targeting with respect to clinical outcome is sparse. Future targeting may utilize information about functional and structural networks, necessitating the use of resting-state functional MRI and diffusion-weighted imaging.

CONCLUSIONS

Specialized MRI sequences have enabled considerable improvement in the visualization of common deep brain stimulation targets. With further validation of their ability to improve clinical outcomes and advances in imaging techniques, direct visualization of targets may play an increasingly important role in preoperative planning.

Sign-specific stimulation 'hot' and 'cold' spots in Parkinson's disease validated with machine learning

Deep brain stimulation of the subthalamic nucleus has become a standard therapy for Parkinson’s disease. Despite extensive experience, however, the precise target of optimal stimulation and the relationship between site of stimulation and alleviation of individual signs remains unclear. We examined whether machine learning could predict the benefits in specific Parkinsonian signs when informed by precise locations of stimulation. We studied 275 Parkinson’s disease patients who underwent subthalamic nucleus deep brain stimulation between 2003 and 2018. We selected pre-deep brain stimulation and best available post-deep brain stimulation scores from motor items of the Unified Parkinson's Disease Rating Scale (UPDRS-III) to discern sign-specific changes attributable to deep brain stimulation. Volumes of tissue activated were computed and weighted by (i) tremor, (ii) rigidity, (iii) bradykinesia and (iv) axial signs changes. Then, sign-specific sites of optimal (‘hot spots’) and suboptimal efficacy (‘cold spots’) were defined. These areas were subsequently validated using machine learning prediction of sign-specific outcomes with in-sample and out-of-sample data (n = 51 subthalamic nucleus deep brain stimulation patients from another institution). Tremor and rigidity hot spots were largely located outside and dorsolateral to the subthalamic nucleus whereas hot spots for bradykinesia and axial signs had larger overlap with the subthalamic nucleus. Using volume of tissue activated overlap with sign-specific hot and cold spots, support vector machine classified patients into quartiles of efficacy with ≥92% accuracy. The accuracy remained high (68–98%) when only considering volume of tissue activated overlap with hot spots but was markedly lower (41–72%) when only using cold spots. The model also performed poorly (44–48%) when using only stimulation voltage, irrespective of stimulation location. Out-of-sample validation accuracy was ≥96% when using volume of tissue activated overlap with the sign-specific hot and cold spots. In two independent datasets, distinct brain areas could predict sign-specific clinical changes in Parkinson’s disease patients with subthalamic nucleus deep brain stimulation. With future prospective validation, these findings could individualize stimulation delivery to optimize quality of life improvement.

Mapping efficacious deep brain stimulation for pediatric dystonia

OBJECTIVE

The objective of this study was to report the authors' experience with deep brain stimulation (DBS) of the internal globus pallidus (GPi) as a treatment for pediatric dystonia, and to elucidate substrates underlying clinical outcome using state-of-the-art neuroimaging techniques.

METHODS

A retrospective analysis was conducted in 11 pediatric patients (6 girls and 5 boys, mean age 12 ± 4 years) with medically refractory dystonia who underwent GPi-DBS implantation between June 2009 and September 2017. Using pre- and postoperative MRI, volumes of tissue activated were modeled and weighted by clinical outcome to identify brain regions associated with clinical outcome. Functional and structural networks associated with clinical benefits were also determined using large-scale normative data sets.

RESULTS

A total of 21 implanted leads were analyzed in 11 patients. The average follow-up duration was 19 ± 20 months (median 5 months). Using a 7-point clinical rating scale, 10 patients showed response to treatment, as defined by scores < 3. The mean improvement in the Burke-Fahn-Marsden Dystonia Rating Scale motor score was 40% ± 23%. The probabilistic map of efficacy showed that the voxel cluster most associated with clinical improvement was located at the posterior aspect of the GPi, comparatively posterior and superior to the coordinates of the classic GPi target. Strong functional and structural connectivity was evident between the probabilistic map and areas such as the precentral and postcentral gyri, parietooccipital cortex, and brainstem.

CONCLUSIONS

This study reported on a series of pediatric patients with dystonia in whom GPi-DBS resulted in variable clinical benefit and described a clinically favorable stimulation site for this cohort, as well as its structural and functional connectivity. This information could be valuable for improving surgical planning, simplifying programming, and further informing disease pathophysiology.

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

Deep brain stimulation (DBS) depends on precise delivery of electrical current to target tissues. However, the specific brain structures responsible for best outcome are still debated. We applied probabilistic stimulation mapping to a retrospective, multidisorder DBS dataset assembled over 15 years at our institution (n_total = 482 patients; n_{Parkinson disease} = 303; n_dystonia = 64; n_tremor = 39; n_{treatment-resistant depression/anorexia nervosa} = 76) to identify the neuroanatomical substrates of optimal clinical response. Using high-resolution structural magnetic resonance imaging and activation volume modeling, probabilistic stimulation maps (PSMs) that delineated areas of above-mean and below-mean response for each patient cohort were generated and defined in terms of their relationships with surrounding anatomical structures. Our results show that overlap between PSMs and individual patients' activation volumes can serve as a guide to predict clinical outcomes, but that this is not the sole determinant of response. In the future, individualized models that incorporate advancements in mapping techniques with patient-specific clinical variables will likely contribute to the optimization of DBS target selection and improved outcomes for patients. ANN NEUROL 2021;89:426-443.

Technology of deep brain stimulation: current status and future directions

Deep brain stimulation (DBS) is a neurosurgical procedure that allows targeted circuit-based neuromodulation. DBS is a standard of care in Parkinson disease, essential tremor and dystonia, and is also under active investigation for other conditions linked to pathological circuitry, including major depressive disorder and Alzheimer disease. Modern DBS systems, borrowed from the cardiac field, consist of an intracranial electrode, an extension wire and a pulse generator, and have evolved slowly over the past two decades. Advances in engineering and imaging along with an improved understanding of brain disorders are poised to reshape how DBS is viewed and delivered to patients. Breakthroughs in electrode and battery designs, stimulation paradigms, closed-loop and on-demand stimulation, and sensing technologies are expected to enhance the efficacy and tolerability of DBS. In this Review, we provide a comprehensive overview of the technical development of DBS, from its origins to its future. Understanding the evolution of DBS technology helps put the currently available systems in perspective and allows us to predict the next major technological advances and hurdles in the field.

The Use of Tractography-Based Targeting in Deep Brain Stimulation for Psychiatric Indications

Deep Brain Stimulation (DBS) has been investigated as a treatment option for patients with refractory psychiatric illness. Over the past two decades, neuroimaging developments have helped to advance the field, particularly the use of diffusion tensor imaging (DTI) and tractographic reconstruction of white-matter pathways. In this article, we review translational considerations and how DTI and tractography have been used to improve targeting during DBS surgery for depression, obsessive compulsive disorder (OCD) and post-traumatic stress disorder (PTSD).

Evaluation of Automatic Segmentation of Thalamic Nuclei through Clinical Effects Using Directional Deep Brain Stimulation Leads: A Technical Note

Automatic anatomical segmentation of patients’ anatomical structures and modeling of the volume of tissue activated (VTA) can potentially facilitate trajectory planning and post-operative programming in deep brain stimulation (DBS). We demonstrate an approach to evaluate the accuracy of such software for the ventral intermediate nucleus (VIM) using directional leads. In an essential tremor patient with asymmetrical brain anatomy, lead placement was adjusted according to the suggested segmentation made by the software (Brainlab). Postoperatively, we used directionality to assess lead placement using side effect testing (internal capsule and sensory thalamus). Clinical effects were then compared to the patient-specific visualization and VTA simulation in the GUIDE™ XT software (Boston Scientific). The patient’s asymmetrical anatomy was correctly recognized by the software and matched the clinical results. VTA models matched best for dysarthria (6 out of 6 cases) and sensory hand side effects (5/6), but least for facial side effects (1/6). Best concordance was observed for the modeled current anterior and back spread of the VTA, worst for the current side spread. Automatic anatomical segmentation and VTA models can be valuable tools for DBS planning and programming. Directional DBS leads allow detailed postoperative assessment of the concordance of such image-based simulation and visualization with clinical effects.