Neuroimaging and deep brain stimulation

Intraoperative DBS targeting of the globus pallidus internus by using motor evoked potentials

OBJECTIVES

Target localization for deep brain stimulation (DBS) is a crucial step that influences the clinical benefit of the DBS procedure together with the reduction of side effects. In this work, we address the feasibility of DBS target localization in the globus pallidus internus (GPi) aided by intraoperative motor evoked potentials (MEP) with emphasis on the reduction of capsular side effects.

MATERIAL AND METHODS

Micro-macroelectrode recordings were performed intraoperatively on 20 patients that underwent DBS treatment of the GPi (GPi-DBS). MEP were elicited intraoperatively by microelectrode stimulation during stereotactic DBS surgery. We studied the relationship between MEP thresholds and the internal capsule (IC) proximity.

RESULTS

We found a significant correlation between intraoperative MEP thresholds and IC proximity.

CONCLUSIONS

We provide further evidence of the role of MEPs for DBS target localization in the GPi, which extends and confirms the usefulness of MEPs as previously reported by DBS target localization studies dealing with the subthalamic and thalamic nuclei. Our approach is advantageous in that it provides criteria to determine the DBS target without the need to rely on a patient's response while avoiding capsular effects.

Revolutionizing Neurology: The Role of Artificial Intelligence in Advancing Diagnosis and Treatment

Artificial intelligence (AI) has emerged as a powerful tool in the field of neurology, significantly impacting the diagnosis and treatment of neurological disorders. Recent technological breakthroughs have given us access to a plethora of information relevant to many aspects of neurology. Neuroscience and AI share a long history of collaboration. Along with great potential, we encounter obstacles relating to data quality, ethics, and inherent difficulty in applying data science in healthcare. Neurological disorders pose intricate challenges due to their complex manifestations and variability. Automating image interpretation tasks, AI algorithms accurately identify brain structures and detect abnormalities. This accelerates diagnosis and reduces the workload on medical professionals. Treatment optimization benefits from AI simulations that model different scenarios and predict outcomes. These AI systems can currently perform many of the sophisticated perceptual and cognitive capacities of biological systems, such as object identification and decision making. Furthermore, AI is rapidly being used as a tool in neuroscience research, altering our understanding of brain functioning. It has the ability to revolutionize healthcare as we know it into a system in which humans and robots collaborate to deliver better care for our patients. Image analysis activities such as recognizing particular brain regions, calculating changes in brain volume over time, and detecting abnormalities in brain scans can be automated by AI systems. This lessens the strain on radiologists and neurologists while improving diagnostic accuracy and efficiency. It is now obvious that cutting-edge artificial intelligence models combined with high-quality clinical data will lead to enhanced prognostic and diagnostic models in neurological illness, permitting expert-level clinical decision aids across healthcare settings. In conclusion, AI's integration into neurology has revolutionized diagnosis, treatment, and research. As AI technologies advance, they promise to unravel the complexities of neurological disorders further, leading to improved patient care and quality of life. The symbiosis of AI and neurology offers a glimpse into a future where innovation and compassion converge to reshape neurological healthcare. This abstract provides a concise overview of the role of AI in neurology and its transformative potential.

A perspective on translating genomic discoveries into targets for brain-machine interface and deep brain stimulation devices

Mental illnesses have a huge impact on individuals, families, and society, so there is a growing need for more efficient treatments. In this context, brain-computer interface (BCI) technology has the potential to revolutionize the options for neuropsychiatric therapies. However, the development of BCI-based therapies faces enormous challenges, such as power dissipation constraints, lack of credible feedback mechanisms, uncertainty of which brain areas and frequencies to target, and even which patients to treat. Some of these setbacks are due to the large gap in our understanding of brain function. In recent years, large-scale genomic analyses uncovered an unprecedented amount of information regarding the biology of the altered brain function observed across the psychopathology spectrum. We believe findings from genetic studies can be useful to refine BCI technology to develop novel treatment options for mental illnesses. Here, we assess the latest advancements in both fields, the possibilities that can be generated from their intersection, and the challenges that these research areas will need to address to ensure that translational efforts can lead to effective and reliable interventions. Specifically, starting from highlighting the overlap between mechanisms uncovered by large-scale genetic studies and the current targets of deep brain stimulation treatments, we describe the steps that could help to translate genomic discoveries into BCI targets. Because these two research areas have not been previously presented together, the present article can provide a novel perspective for scientists with different research backgrounds. This article is categorized under: Neurological Diseases > Genetics/Genomics/Epigenetics Neurological Diseases > Biomedical Engineering.

Locating the ventral intermediate thalamic nucleus for deep brain stimulation surgery: analysis of a case series comparing CT and MR targeting

BACKGROUND

Deep brain stimulation (DBS) surgery targeting the ventral intermediate thalamic nucleus (Vim) has proven efficacy in the treatment of tremor.

AIMS

The primary aim is to investigate whether there is a statistically significant difference in patient outcomes when CT-guided targeting of the Vim is compared with MRI-guided targeting.

METHODS

This is a retrospective study concerning patients undergoing Vim-targeted DBS at the Department of Neurosurgery, Royal Victoria Infirmary in Newcastle (9th August 2012 to 4th January 2019). Fahn-Tolosa-Marin Tremor Scale (FTM TS) and EQ-5D scores were collected from patient notes. Statistical analysis was performed using IBM® SPSS® Statistics Version 24. Independent samples t-tests were used to compare means.

RESULTS

Independent samples t-test did not reveal a statistically significant difference between CT (n = 10; FTM TS mean = 65.40, SD = 11.40; EQ-5D mean = 39.50, SD = 17.87) and MR (n = 7; FTM TS mean = 60.57, SD = 7.50; EQ-5D mean = 32.14, SD = 9.94) groups in pre-surgery FTM TS (t(15) = 0.977, p = 0.344) and EQ-5D (t(15) = 0.982, p = 0.342) scores. No statistically significant difference between the CT (FTM TS mean = 24.12, SD = 20.47; EQ-5D mean = 75.56, SD = 15.63) and MR (FTM TS mean = 22.86, SD = 6.72; EQ-5D mean = 70.43, SD = 15.48) groups was revealed at 1 year assessment of FTM TS (t(14) = 0.155, p = 0.879) and EQ-5D (t(14) = 0.654, p = 0.524). The median difference between pre- and post-surgery FTM TS and EQ-5D scores in the CT group at 1 year was 43.00 and 35.00, respectively. The MR patient group median difference in pre- and post-surgery at 1 year was 35.00 and 35.00 respectively.

CONCLUSION

No statistically significant difference between CT and MR image-guided targeting patient groups was detected.

Deep Brain Stimulation (DBS) in Treatment-Resistant Depression (TRD): Hope and Concern

In this chapter, we explore the historical evolution, current applications, and future directions of Deep Brain Stimulation (DBS) for Treatment-Resistant Depression (TRD). We begin by highlighting the early efforts of neurologists and neurosurgeons who laid the foundations for today's DBS techniques, moving from controversial lobotomies to the precision of stereotactic surgery. We focus on the advent of DBS, emphasizing its emergence as a significant breakthrough for movement disorders and its extension to psychiatric conditions, including TRD. We provide an overview of the neural networks implicated in depression, detailing the rationale for the choice of common DBS targets. We also cover the technical aspects of DBS, from electrode placement to programming and parameter selection. We then critically review the evidence from clinical trials and open-label studies, acknowledging the mixed outcomes and the challenges posed by placebo effects and trial design. Safety and ethical considerations are also discussed. Finally, we explore innovative directions for DBS research, including the potential of closed-loop systems, dual stimulation strategies, and noninvasive alternatives like ultrasound neuromodulation. In the last section, we outline recommendations for future DBS studies, including the use of alternative designs for placebo control, the collection of neural and behavioral recordings, and the application of machine-learning approaches.

Day one postoperative MRI findings following electrode placement for deep brain stimulation: analysis of a large case series

Objective

This study sought to characterize postoperative day one MRI findings in deep brain stimulation (DBS) patients.

Methods

DBS patients were identified by CPT and had their reviewed by a trained neuroradiologist and neurosurgeon blinded to MR sequence and patient information. The radiographic abnormalities of interest were track microhemorrhage, pneumocephalus, hematomas, and edema, and the occurrence of these findings in compare the detection of these complications between T1/T2 gradient-echo (GRE) and T1/T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance (MR) sequences was compared. The presence, size, and association of susceptibility artifact with other radiographic abnormalities was also described. Lastly, the association of multiple microelectrode cannula passes with each radiographic finding was evaluated. Ad-hoc investigation evaluated hemisphere-specific associations. Multiple logistic regression with Bonferroni correction (corrected p = 0.006) was used for all analysis.

Results

Out of 198 DBS patients reviewed, 115 (58%) patients showed entry microhemorrhage; 77 (39%) track microhemorrhage; 44 (22%) edema; 69 (35%) pneumocephalus; and 12 (6%) intracranial hematoma. T2 GRE was better for detecting microhemorrhage (OR = 14.82, p < 0.0001 for entry site and OR = 4.03, p < 0.0001 for track) and pneumocephalus (OR = 11.86, p < 0.0001), while T2 FLAIR was better at detecting edema (OR = 123.6, p < 0.0001). The relatively common findings of microhemorrhage and edema were best visualized by T2 GRE and T2 FLAIR sequences, respectively. More passes intraoperatively was associated with detection of ipsilateral track microhemorrhage (OR = 7.151, p < 0.0001 left; OR = 8.953, p < 0.0001 right). Susceptibility artifact surrounding electrodes possibly interfered with further detection of ipsilateral edema (OR = 4.323, p = 0.0025 left hemisphere only).

Discussion

Day one postoperative magnetic resonance imaging (MRI) for DBS patients can be used to detect numerous radiographic abnormalities not identifiable on a computed tomographic (CT) scan. For this cohort, multiple stimulating cannula passes intraoperatively was associated with increased microhemorrhage along the electrode track. Further studies should be performed to evaluate the clinical relevance of these observations.

Antiparkinsonian Drug Reduction After Directional Versus Omnidirectional Bilateral Subthalamic Deep Brain Stimulation

BACKGROUND

Several pilot trials and the Clinical Evaluation of the Infinity Deep Brain Stimulation System (PROGRESS) study have found that directional stimulation can provide a wider therapeutic window and lower therapeutic current strength than omnidirectional stimulation.

OBJECTIVE

We conducted a single-center, open-label, registry-based, comparative trial to test the hypothesis that directional stimulation can be associated with a greater reduction in the total daily dose of antiparkinsonian medications (ApMeds) than omnidirectional stimulation.

MATERIALS AND METHODS

A total of 52 patients with directional and 57 subjects with omnidirectional bilateral subthalamic deep brain stimulation (STN-DBS) were enrolled. Preoperatively and 12 months postoperatively, the dose of different ApMeds, the number of tablets used daily, the severity of motor and nonmotor symptoms using the Movement Disorder Society-sponsored Unified Parkinson Disease Rating Scale, and the health-related quality of life (HRQoL) using the 39-item Parkinson's Disease Questionnaire (PDQ-39) were assessed.

RESULTS

According to the changes in the levodopa equivalent daily dose, directional STN-DBS led to a 13% greater reduction in the total daily dose of ApMed. The 10.3% greater reduction in the dose of levodopa was the main contributor to this difference. The number of different ApMed types also could be decreased in a greater manner with directional stimulation. The improvement in the severity of motor and nonmotor symptoms was comparable; however, we detected a 15.8% greater improvement in the global HRQoL among patients with directional stimulation according to the changes in the summary index of the PDQ-39. The total electrical energy delivered per second was comparable between the groups at 12-month postoperative visit, whereas the amplitude of stimulation was significantly lower and the impedance was significantly higher with directional leads.

CONCLUSIONS

Directional programming can further increase the reduction in the total daily dose of ApMed after STN-DBS. In addition, directional stimulation can have additional beneficial effects on the global HRQoL. The greater reduction of ApMed doses did not require more energy-consuming stimulation with directional stimulation.

Robotic external ventricular drain placement for acute neurosurgical care in low-resource settings: feasibility considerations and a prototype design

OBJECTIVE

Emergency neurosurgical care in lower-middle-income countries faces pronounced shortages in neurosurgical personnel and infrastructure. In instances of traumatic brain injury (TBI), hydrocephalus, and subarachnoid hemorrhage, the timely placement of external ventricular drains (EVDs) strongly dictates prognosis and can provide necessary stabilization before transfer to a higher-level center of care that has access to neurosurgery. Accordingly, the authors have developed an inexpensive and portable robotic navigation tool to allow surgeons who do not have explicit neurosurgical training to place EVDs. In this article, the authors aimed to highlight income disparities in neurosurgical care, evaluate access to CT imaging around the world, and introduce a novel, inexpensive robotic navigation tool for EVD placement.

METHODS

By combining the worldwide distribution of neurosurgeons, CT scanners, and gross domestic product with the incidence of TBI, meningitis, and hydrocephalus, the authors identified regions and countries where development of an inexpensive, passive robotic navigation system would be most beneficial and feasible. A prototype of the robotic navigation system was constructed using encoders, 3D-printed components, machined parts, and a printed circuit board.

RESULTS

Global analysis showed Montenegro, Antigua and Barbuda, and Seychelles to be primary candidates for implementation and feasibility testing of the novel robotic navigation system. To validate the feasibility of the system for further development, its performance was analyzed through an accuracy study resulting in accuracy and repeatability within 1.53 ± 2.50 mm (mean ± 2 × SD, 95% CI).

CONCLUSIONS

By considering regions of the world that have a shortage of neurosurgeons and a high incidence of EVD placement, the authors were able to provide an analysis of where to prioritize the development of a robotic navigation system. Subsequently, a proof-of-principle prototype has been provided, with sufficient accuracy to target the ventricles for EVD placement.

Frequency-Dependent Energy Demand of Dendritic Responses to Deep Brain Stimulation in Thalamic Neurons: A Model-Based Study

Thalamic deep brain stimulation (DBS) generates excitatory postsynaptic currents and action potentials (APs) by triggering large numbers of synaptic inputs to local cells, which also activates axonal spikes to antidromically invade the soma and dendrites. To maintain signaling, the evoked dendritic responses require metabolic energy to restore ion gradients in each dendrite. The objective of this study is to estimate the energy demand associated with dendritic responses to thalamic DBS. We use a morphologically realistic computational model to simulate dendritic activity in thalamocortical (TC) relay neurons with axonal intracellular stimulation or DBS-like extracellular stimulation. We determine the metabolic cost by calculating the number of adenosine triphosphate (ATP) expended to pump Na⁺ and Ca²⁺ ions out of each dendrite. The ATP demand of dendritic activity exhibits frequency dependence, which is determined by the number of spikes in the dendrites. Each backpropagating AP from the soma activates a spike in the dendrites, and the dendritic firing is dominated by antidromic activation of the soma. High stimulus frequencies decrease dendritic ATP cost by reducing the fidelity of antidromic activation. Synaptic inputs and stimulus-induced polarization govern the ATP cost of dendritic responses by facilitating/suppressing antidromic activation, which also influences the ATP cost by depolarizing/hyperpolarizing each dendrite. These findings are important for understanding the synaptic signaling energy in TC relay neurons and metabolism-dependent functional imaging data of thalamic DBS.

Stimulation Sweet Spot in Subthalamic Deep Brain Stimulation - Myth or Reality? A Critical Review of Literature

INTRODUCTION

While deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been extensively used for more than 20 years in Parkinson's disease (PD), the optimal area of stimulation to relieve motor symptoms remains elusive.

OBJECTIVE

We aimed at localizing the sweet spot within the subthalamic region by performing a systematic review of the literature.

METHOD

PubMed database was searched for published studies exploring optimal stimulation location for STN DBS in PD, published between 2000 and 2019. A standardized assessment procedure based on methodological features was applied to select high-quality publications. Studies conducted more than 3 months after the DBS procedure, employing lateralized scores and/or stimulation condition, and reporting the volume of tissue activated or the position of the stimulating contact within the subthalamic region were considered in the final analysis.

RESULTS

Out of 439 references, 24 were finally retained, including 21 studies based on contact location and 3 studies based on volume of tissue activated (VTA). Most studies (all VTA-based studies and 13 of the 21 contact-based studies) suggest the superior-lateral STN and the adjacent white matter as the optimal sites for stimulation. Remaining contact-based studies were either inconclusive (5/21), favoured the caudal zona incerta (1/21), or suggested a better outcome of STN stimulation than adjacent white matter stimulation (2/21).

CONCLUSION

Using a standardized methodological approach, our review supports the presence of a sweet spot located within the supero-lateral STN and extending to the adjacent white matter.

In vivo localization of chronically implanted electrodes and optic fibers in mice

Electrophysiology provides a direct readout of neuronal activity at a temporal precision only limited by the sampling rate. However, interrogating deep brain structures, implanting multiple targets or aiming at unusual angles still poses significant challenges for operators, and errors are only discovered by post-hoc histological reconstruction. Here, we propose a method combining the high-resolution information about bone landmarks provided by micro-CT scanning with the soft tissue contrast of the MRI, which allowed us to precisely localize electrodes and optic fibers in mice in vivo. This enables arbitrating the success of implantation directly after surgery with a precision comparable to gold standard histology. Adjustment of the recording depth with micro-drives or early termination of unsuccessful experiments saves many working hours, and fast 3-dimensional feedback helps surgeons avoid systematic errors. Increased aiming precision enables more precise targeting of small or deep brain nuclei and multiple targeting of specific cortical or hippocampal layers.

Multi-Atlas Segmentation of Anatomical Brain Structures Using Hierarchical Hypergraph Learning

Accurate segmentation of anatomical brain structures is crucial for many neuroimaging applications, e.g., early brain development studies and the study of imaging biomarkers of neurodegenerative diseases. Although multi-atlas segmentation (MAS) has achieved many successes in the medical imaging area, this approach encounters limitations in segmenting anatomical structures associated with poor image contrast. To address this issue, we propose a new MAS method that uses a hypergraph learning framework to model the complex subject-within and subject-to-atlas image voxel relationships and propagate the label on the atlas image to the target subject image. To alleviate the low-image contrast issue, we propose two strategies equipped with our hypergraph learning framework. First, we use a hierarchical strategy that exploits high-level context features for hypergraph construction. Because the context features are computed on the tentatively estimated probability maps, we can ultimately turn the hypergraph learning into a hierarchical model. Second, instead of only propagating the labels from the atlas images to the target subject image, we use a dynamic label propagation strategy that can gradually use increasing reliably identified labels from the subject image to aid in predicting the labels on the difficult-to-label subject image voxels. Compared with the state-of-the-art label fusion methods, our results show that the hierarchical hypergraph learning framework can substantially improve the robustness and accuracy in the segmentation of anatomical brain structures with low image contrast from magnetic resonance (MR) images.

Improving Safety of MRI in Patients with Deep Brain Stimulation Devices

MRI is a valuable clinical and research tool for patients undergoing deep brain stimulation (DBS). However, risks associated with imaging DBS devices have led to stringent regulations, limiting the clinical and research utility of MRI in these patients. The main risks in patients with DBS devices undergoing MRI are heating at the electrode tips, induced currents, implantable pulse generator dysfunction, and mechanical forces. Phantom model studies indicate that electrode tip heating remains the most serious risk for modern DBS devices. The absence of adverse events in patients imaged under DBS vendor guidelines for MRI demonstrates the general safety of MRI for patients with DBS devices. Moreover, recent work indicates that-given adequate safety data-patients may be imaged outside these guidelines. At present, investigators are primarily focused on improving DBS device and MRI safety through the development of tools, including safety simulation models. Existing guidelines provide a standardized framework for performing safe MRI in patients with DBS devices. It also highlights the possibility of expanding MRI as a tool for research and clinical care in these patients going forward.

High-resolution QSM for functional and structural depiction of subthalamic nuclei in DBS presurgical mapping

OBJECTIVE

Faithful depiction of the subthalamic nucleus (STN) is critical for planning deep brain stimulation (DBS) surgery in patients with Parkinson's disease (PD). Quantitative susceptibility mapping (QSM) has been shown to be superior to traditional T2-weighted spin echo imaging (T2w). The aim of the study was to describe submillimeter QSM for preoperative imaging of the STN in planning of DBS.

METHODS

Seven healthy volunteers were included in this study. T2w and QSM were obtained for all healthy volunteers, and images of different resolutions were reconstructed. Image quality and visibility of STN anatomical features were analyzed by a radiologist using a 5-point scale, and contrast properties of the STN and surrounding tissue were calculated. Additionally, data from 10 retrospectively and randomly selected PD patients who underwent 3-T MRI for DBS were analyzed for STN size and susceptibility gradient measurements.

RESULTS

Higher contrast-to-noise ratio (CNR) values were observed in both high-resolution and low-resolution QSM images. Inter-resolution comparison demonstrated improvement in CNR for QSM, but not for T2w images. QSM provided higher inter-quadrant contrast ratios (CR) within the STN, and depicted a gradient in the distribution of susceptibility sources not visible in T2w images.

CONCLUSIONS

For 3-T MRI, submillimeter QSM provides accurate delineation of the functional and anatomical STN features for DBS targeting.

Energy Cost of Action Potential Generation and Propagation in Thalamocortical Relay Neurons During Deep Brain Stimulation

Thalamocortical (TC) relay neurons generate antidromic and orthodromic action potentials (APs) during thalamic deep brain stimulation (DBS). To maintain signaling, each AP requires Na⁺/K⁺ pump to expend adenosine triphosphate (ATP) to restore Na⁺ and K⁺ gradients. Our aim was to estimate the energy demand associated with AP generation and propagation within TC relay cells during DBS. We used a morphology-based computational model to simulate the APs at different locations. We determined AP energy cost by calculating the amount of ATP required to reverse Na⁺ influx during the spike and measured metabolic efficiency by using Na⁺/K⁺ charge overlap. The ATP cost for AP generation exhibited location dependence, which was determined by spike shape, spatial morphology, and heterogeneously distributed currents. The APs in the axonal initial segment (AIS) were energetically efficient, but backpropagation to the soma and forward propagation to the axon were inefficient. Due to large surface area, the soma and AIS dominated the overall ATP usage. The AP cost also depended on membrane potential, which controlled T-type Ca²⁺ conductance and degree of availability of Na⁺ and K⁺ channels. The excitatory/inhibitory synaptic inputs affected spike cost by increasing/reducing the excitability of local cells. There was a tradeoff between AP cost and firing rate at high firing frequencies. We explained a fundamental link between biophysics of ionic currents, spatial morphology of neural segments, and ATP cost per AP. The predictions should be considered when understanding the functional magnetic resonance imaging data of thalamic DBS.

Reducing RF-induced Heating near Implanted Leads through High-Dielectric Capacitive Bleeding of Current (CBLOC)

Patients with implanted medical devices such as deep brain stimulation or spinal cord stimulation are often unable to receive magnetic resonance imaging (MRI). This is because once the device is within the radiofrequency (RF) field of the MRI scanner, electrically conductive leads act as antenna, amplifying the RF energy deposition in the tissue and causing possible excessive tissue heating. Here we propose a novel concept in lead design in which 40cm lead wires are coated with a ~1.2mm layer of high dielectric constant material (155 < ε r < 250) embedded in a weakly conductive insulation (σ = 20S/m). The technique called High-Dielectric Capacitive Bleeding of Current, or CBLOC, works by forming a distributed capacitance along the lengths of the lead, efficiently dissipating RF energy before it reaches the exposed tip. Measurements during RF exposure at 64 MHz and 123 MHz demonstrated that CBLOC leads generated 20-fold less heating at 1.5 T, and 40-fold less heating at 3 T compared to control leads. Numerical simulations of RF exposure at 297 MHz (7T) predicted a 15-fold reduction in specific absorption rate (SAR) of RF energy around the tip of CBLOC leads compared to control leads.

Automatic localization of the subthalamic nucleus on patient-specific clinical MRI by incorporating 7 T MRI and machine learning: Application in deep brain stimulation

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has shown clinical potential for relieving the motor symptoms of advanced Parkinson's disease. While accurate localization of the STN is critical for consistent across-patients effective DBS, clear visualization of the STN under standard clinical MR protocols is still challenging. Therefore, intraoperative microelectrode recordings (MER) are incorporated to accurately localize the STN. However, MER require significant neurosurgical expertise and lengthen the surgery time. Recent advances in 7 T MR technology facilitate the ability to clearly visualize the STN. The vast majority of centers, however, still do not have 7 T MRI systems, and fewer have the ability to collect and analyze the data. This work introduces an automatic STN localization framework based on standard clinical MRIs without additional cost in the current DBS planning protocol. Our approach benefits from a large database of 7 T MRI and its clinical MRI pairs. We first model in the 7 T database, using efficient machine learning algorithms, the spatial and geometric dependency between the STN and its adjacent structures (predictors). Given a standard clinical MRI, our method automatically computes the predictors and uses the learned information to predict the patient-specific STN. We validate our proposed method on clinical T2 W MRI of 80 subjects, comparing with experts-segmented STNs from the corresponding 7 T MRI pairs. The experimental results show that our framework provides more accurate and robust patient-specific STN localization than using state-of-the-art atlases. We also demonstrate the clinical feasibility of the proposed technique assessing the post-operative electrode active contact locations.

Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging

Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural/functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient's preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the preprocessing method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.

Intraoperative Localization of the Subthalamic Nucleus Using Long-Latency Somatosensory Evoked Potentials

BACKGROUND

Target localization for deep brain stimulation (DBS) is a challenging step that determines not only the correct placement of stimulation electrodes, but also influences the success of the DBS procedure as reflected in the desired clinical outcome of a patient.

OBJECTIVE

We report on the feasibility of DBS target localization in the subthalamic nucleus (STN) by long-latency somatosensory evoked potentials (LL-SSEPs) (>40 msec) in Parkinson's disease (PD) patients.

METHODS

Micro-macroelectrode recordings were performed intraoperatively on seven PD patients (eight STN hemispheres) who underwent DBS treatment. LL-SSEPs were elicited by ipsi- and contralateral median nerve stimulation to the wrist.

RESULTS

Four distinctive LL-SSEP components were elicited ("LL-complex" consisting of P80, N100, P140, and N200). The P80 appeared as the most visible and reliable intraoperative component. Localization of the "LL-complex" within the target was approved with typical microelectrode firing activity patterns, atlas visualization of recording electrodes, and postoperative CT-based visualization of final DBS electrodes.

CONCLUSIONS

LL-SSEPs represent a promising approach for DBS target localization in the STN, provided deeper understanding on their anesthesia effect is obtained. This approach is advantageous in that it does not require the patient's participation in an intraoperative setting.

Neurostimulation Devices for the Treatment of Neurologic Disorders

Rapid advancements in neurostimulation technologies are providing relief to an unprecedented number of patients affected by debilitating neurologic and psychiatric disorders. Neurostimulation therapies include invasive and noninvasive approaches that involve the application of electrical stimulation to drive neural function within a circuit. This review focuses on established invasive electrical stimulation systems used clinically to induce therapeutic neuromodulation of dysfunctional neural circuitry. These implantable neurostimulation systems target specific deep subcortical, cortical, spinal, cranial, and peripheral nerve structures to modulate neuronal activity, providing therapeutic effects for a myriad of neuropsychiatric disorders. Recent advances in neurotechnologies and neuroimaging, along with an increased understanding of neurocircuitry, are factors contributing to the rapid rise in the use of neurostimulation therapies to treat an increasingly wide range of neurologic and psychiatric disorders. Electrical stimulation technologies are evolving after remaining fairly stagnant for the past 30 years, moving toward potential closed-loop therapeutic control systems with the ability to deliver stimulation with higher spatial resolution to provide continuous customized neuromodulation for optimal clinical outcomes. Even so, there is still much to be learned about disease pathogenesis of these neurodegenerative and psychiatric disorders and the latent mechanisms of neurostimulation that provide therapeutic relief. This review provides an overview of the increasingly common stimulation systems, their clinical indications, and enabling technologies.

Comparison of T2*-weighted and QSM contrasts in Parkinson's disease to visualize the STN with MRI

The subthalamic nucleus (STN) plays a crucial role in the surgical treatment of Parkinson’s disease (PD). Studies investigating optimal protocols for STN visualization using state of the art magnetic resonance imaging (MRI) techniques have shown that susceptibility weighted images, which display the magnetic susceptibility distribution, yield better results than T₁-weighted, T₂-weighted, and T₂*-weighted contrasts. However, these findings are based on young healthy individuals, and require validation in elderly individuals and persons suffering from PD. Using 7T MRI, the present study set out to investigate which MRI contrasts yielded the best results for STN visualization in 12 PD patients and age-matched healthy controls (HC). We found that STNs were more difficult to delineate in PD as reflected by a lower inter-rater agreement when compared to HCs. No STN size differences were observed between the groups. Analyses of quantitative susceptibility mapping (QSM) images showed a higher inter-rater agreement reflected by increased Dice-coefficients. The location of the center of mass of the STN was not affected by contrast. Overall, contrast-to-noise ratios (CNR) were higher in QSM than in T₂*-weighted images. This can at least partially, explain the higher inter-rater agreement in QSM. The current results indicate that the calculation of QSM contrasts contributes to an improved visualization of the entire STN. We conclude that QSM contrast is the preferred choice for the visualization of the STN in persons with PD as well as in aging HC.

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

The basal ganglia is part of a complex system of neuronal circuits that play a key role in the integration and execution of motor, cognitive and emotional function in the human brain. Parkinson’s disease is a progressive neurological disorder of the motor circuit characterized by tremor, rigidity, and slowness of movement. Deep brain stimulation (DBS) of the subthalamic nucleus and the globus pallidus pars interna provides an efficient treatment to reduce symptoms and levodopa-induced side effects in Parkinson’s disease patients. While the underlying mechanism of action of DBS is still unknown, the potential modulation of white matter tracts connecting the surgical targets has become an active area of research. With the introduction of advanced diffusion MRI acquisition sequences and sophisticated post-processing techniques, the architecture of the human brain white matter can be explored in vivo. The goal of this study is to investigate the white matter connectivity between the subthalamic nucleus and the globus pallidus. Two multi-fiber tractography methods were used to reconstruct pallido-subthalamic, subthalamo-pallidal and pyramidal fibers in five healthy subjects datasets of the Human Connectome Project. The anatomical accuracy of the tracts was assessed by four judges with expertise in neuroanatomy, functional neurosurgery, and diffusion MRI. The variability among subjects was evaluated based on the fractional anisotropy and mean diffusivity of the tracts. Both multi-fiber approaches enabled the detection of complex fiber architecture in the basal ganglia. The qualitative evaluation by experts showed that the identified tracts were in agreement with the expected anatomy. Tract-derived measurements demonstrated relatively low variability among subjects. False-negative tracts demonstrated the current limitations of both methods for clinical decision-making. Multi-fiber tractography methods combined with state-of-the-art diffusion MRI data have the potential to help identify white matter tracts connecting DBS targets in functional neurosurgery intervention.

Cognitive and Psychiatric Effects of STN versus GPi Deep Brain Stimulation in Parkinson's Disease: A Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Deep brain stimulation (DBS) of either the subthalamic nucleus (STN) or the globus pallidus interna (GPi) can reduce motor symptoms in patients with Parkinson's disease (PD) and improve their quality of life. However, the effects of STN DBS and GPi DBS on cognitive functions and their psychiatric effects remain controversial. The present meta-analysis was therefore performed to clarify these issues.

METHODS

We searched the PUBMED, EMBASE, and the Cochrane Central Register of Controlled Trials databases. Other sources, including internet-based clinical trial registries and grey literature sources, were also searched. After searching the literature, two investigators independently performed literature screens to assess the quality of the included trials and to extract the data. The outcomes included the effects of STN DBS and GPi DBS on multiple cognitive domains, depression, anxiety, and quality of life.

RESULTS

Seven articles related to four randomized controlled trials that included 521 participants were incorporated into the present meta-analysis. Compared with GPi DBS, STN DBS was associated with declines in selected cognitive domains after surgery, including attention, working memory and processing speed, phonemic fluency, learning and memory, and global cognition. However, there were no significant differences in terms of quality of life or psychiatric effects, such as depression and anxiety, between the two groups.

CONCLUSIONS

A selective decline in frontal-subcortical cognitive functions is observed after STN DBS in comparison with GPi DBS, which should not be ignored in the target selection for DBS treatment in PD patients. In addition, compared to GPi DBS, STN DBS does not affect depression, anxiety, and quality of life.

The treatment of Parkinson's disease with deep brain stimulation: current issues

Deep brain stimulation has become a well-established symptomatic treatment for Parkinson's disease during the last 25 years. Besides improving motor symptoms and long-term motor complications, positive effects on patients' mobility, activities of daily living, emotional well-being and health-related quality of life have been recognized. Apart from that, numerous clinical trials analyzed effects on non-motor symptoms and side effects of deep brain stimulation. Several technical issues and stimulation paradigms have been and are still being developed to optimize the therapeutic effects, minimize the side effects and facilitate handling. This review summarizes current therapeutic issues, i.e., patient and target selection, surgical procedure and programming paradigms. In addition it focuses on neuropsychological effects and side effects of deep brain stimulation.

Magnetic Resonance Techniques Applied to the Diagnosis and Treatment of Parkinson's Disease

Parkinson's disease (PD) affects at least 10 million people worldwide. It is a neurodegenerative disease, which is currently diagnosed by neurological examination. No neuroimaging investigation or blood biomarker is available to aid diagnosis and prognosis. Most effort toward diagnosis using magnetic resonance (MR) has been focused on the use of structural/anatomical neuroimaging and diffusion tensor imaging (DTI). However, deep brain stimulation, a current strategy for treating PD, is guided by MR imaging (MRI). For clinical prognosis, diagnosis, and follow-up investigations, blood oxygen level-dependent MRI, DTI, spectroscopy, and transcranial magnetic stimulation have been used. These techniques represent the state of the art in the last 5 years. Here, we focus on MR techniques for the diagnosis and treatment of Parkinson's disease.

A novel brain stimulation technology provides compatibility with MRI

Clinical electrical stimulation systems--such as pacemakers and deep brain stimulators (DBS)--are an increasingly common therapeutic option to treat a large range of medical conditions. Despite their remarkable success, one of the significant limitations of these medical devices is the limited compatibility with magnetic resonance imaging (MRI), a standard diagnostic tool in medicine. During an MRI exam, the leads used with these devices, implanted in the body of the patient, act as an electric antenna potentially causing a large amount of energy to be absorbed in the tissue, which can lead to serious heat-related injury. This study presents a novel lead design that reduces the antenna effect and allows for decreased tissue heating during MRI. The optimal parameters of the wire design were determined by a combination of computational modeling and experimental measurements. The results of these simulations were used to build a prototype, which was tested in a gel phantom during an MRI scan. Measurement results showed a three-fold decrease in heating when compared to a commercially available DBS lead. Accordingly, the proposed design may allow a significantly increased number of patients with medical implants to have safe access to the diagnostic benefits of MRI.

Semiautomatic segmentation of brain subcortical structures from high-field MRI

Volumetric segmentation of subcortical structures, such as the basal ganglia and thalamus, is necessary for noninvasive diagnosis and neurosurgery planning. This is a challenging problem due in part to limited boundary information between structures, similar intensity profiles across the different structures, and low contrast data. This paper presents a semiautomatic segmentation system exploiting the superior image quality of ultrahigh field (7 T) MRI. The proposed approach utilizes the complementary edge information in the multiple structural MRI modalities. It combines optimally selected two modalities from susceptibility-weighted, T2-weighted, and diffusion MRI, and introduces a tailored new edge indicator function. In addition to this, we employ prior shape and configuration knowledge of the subcortical structures in order to guide the evolution of geometric active surfaces. Neighboring structures are segmented iteratively, constraining oversegmentation at their borders with a nonoverlapping penalty. Several experiments with data acquired on a 7 T MRI scanner demonstrate the feasibility and power of the approach for the segmentation of basal ganglia components critical for neurosurgery applications such as deep brain stimulation surgery.

Neural stimulators: a guide to imaging and postoperative appearances

Implantable neural stimulators have been developed to aid patients with debilitating neurological conditions that are not amenable to other therapies. The aim of this article is to improve understanding of correct anatomical placement as well as the relevant imaging methods used to assess these devices. Potential complications following their insertion and an overview of the current indications and potential mechanism of action of these devices is provided.

High-Resolution 3-Dimensional T2*-Weighted Angiography (HR 3-D SWAN)

BACKGROUND:

Subthalamic nucleus deep brain stimulation (STN-DBS) is an established treatment for Parkinson's disease.

OBJECTIVE:

To characterize an optimized magnetic resonance imaging (MRI) sequence (high-resolution 3-dimensional T2*-weighted angiography [HR 3-D SWAN]) for direct STN targeting.

METHODS:

Sequence distortions were measured using the Leksell stereotactic phantom. Eight consecutive candidates for STN-DBS underwent HR 3-D SWAN MRI for direct identification of the 16 STN. Two senior neurosurgeons independently determined the boundaries of STN on a semiquantitative scale (ranging from 1 [identification very easy] to 4 [identification very difficult]) and the anatomic target within the nucleus. The anatomic data were compared with electrophysiological recordings (48 microrecordings). We examined the anatomic location of the active contacts on MRI.

RESULTS:

The mean distortion error over the phantom was 0.16 mm. For the 16 STNs, identification of the upper, internal, anterior, and external edges was considered to be easy (scores of 1 or 2). The distinction between the substantia nigra and the STN was rated 1 or 2 for all but 6 nuclei. In the mediolateral axis, electrophysiological recordings covered perfectly anatomic data. In the craniocaudal axis, the mean differences between the electrophysiological data and the anatomic data were 0.8 mm and 0.19 mm for the “entry” and “exit” of the STN, respectively. All active contacts were located within the STN on MRI.

CONCLUSION:

HR 3-D SWAN allows easy visualization of the STN. Adapted to stereotactic requirement, the sequence simplifies direct targeting in STN-DBS surgery.

Fiducial registration with spoiled gradient-echo magnetic resonance imaging enhances the accuracy of subthalamic nucleus targeting

BACKGROUND

A variety of imaging strategies may be used to derive reliable stereotactic coordinates when performing deep brain stimulation lead implants. No single technique has yet proved optimal.

OBJECTIVE

To compare the relative accuracy of stereotactic coordinates for the subthalamic nucleus (STN) derived either from fast spin echo/inversion recovery (FSE/IR) magnetic resonance imaging MRI alone (group 1) or FSE/IR in conjunction with T1-weighted spoiled gradient-echo MRI (group 2).

METHODS

A retrospective analysis of 145 consecutive STN deep brain stimulation lead placements (group 1, n = 72; group 2, n = 73) was performed in 81 Parkinson disease patients by 1 surgical team. From the operative reports, we recorded the number of microelectrode recording trajectories required to localize the desired STN target and the span of STN traversed along the implantation trajectory. In addition, we calculated the 3-dimensional vector difference between the initial MRI-derived coordinates and the final physiologically refined coordinates.

RESULTS

The proportion of implants completed with just 1 microelectrode recording trajectory was greater (81% vs 58%; P < .001) and the 3-dimensional vector difference between the anatomically selected target and the microelectrode recording-refined target was smaller (0.6 ± 1.2 vs 0.9 ± 1.3; P = .04) in group 2 than in group 1. At the same time, the mean expanse of STN recorded along the implantation trajectory was 8% greater in group 2 (4.8 ± 0.6 vs 5.2 ± 0.6 mm; P < .001).

CONCLUSION

A combination of stereotactic FSE/IR and spoiled gradient-echo MRI yields more accurate coordinates for the STN than FSE/IR MRI alone.

Magnetic resonance imaging techniques for visualization of the subthalamic nucleus

The authors reviewed 70 publications on MR imaging-based targeting techniques for identifying the subthalamic nucleus (STN) for deep brain stimulation in patients with Parkinson disease. Of these 70 publications, 33 presented quantitatively validated results. There is still no consensus on which targeting technique to use for surgery planning; methods vary greatly between centers. Some groups apply indirect methods involving anatomical landmarks, or atlases incorporating anatomical or functional data. Others perform direct visualization on MR imaging, using T2-weighted spin echo or inversion recovery protocols. The combined studies do not offer a straightforward conclusion on the best targeting protocol. Indirect methods are not patient specific, leading to varying results between cases. On the other hand, direct targeting on MR imaging suffers from lack of contrast within the subthalamic region, resulting in a poor delineation of the STN. These deficiencies result in a need for intraoperative adaptation of the original target based on test stimulation with or without microelectrode recording. It is expected that future advances in MR imaging technology will lead to improvements in direct targeting. The use of new MR imaging modalities such as diffusion MR imaging might even lead to the specific identification of the different functional parts of the STN, such as the dorsolateral sensorimotor part, the target for deep brain stimulation.

A review of low-intensity focused ultrasound pulsation

With the recent approval by the Food and Drug Administration (FDA) of Deep Brain Stimulation (DBS) for Parkinson's Disease, dystonia and obsessive compulsive disorder (OCD), vagus nerve stimulation (VNS) for epilepsy and depression, and repetitive transcranial magnetic stimulation (rTMS) for the treatment of depression, neuromodulation has become increasingly relevant to clinical research. However, these techniques have significant drawbacks (eg, lack of special specificity and depth for the rTMS, and invasiveness and cumbersome maintenance for DBS). This article reviews the background, rationale, and pilot studies to date, using a new brain stimulation method-low-intensity focused ultrasound pulsation (LIFUP). The ability of ultrasound to be focused noninvasively through the skull anywhere within the brain, together with concurrent imaging (ie, functional magnetic resonance imaging [fMRI]) techniques, may create a role for research and clinical use of LIFUP. This technique is still in preclinical testing and needs to be assessed thoroughly before being advanced to clinical trials. In this study, we review over 50 years of research data on the use of focused ultrasound (FUS) in neuronal tissue and live brain, and propose novel applications of this noninvasive neuromodulation method.