ESM-CT: a precise method for localization of DBS electrodes in CT images

Refining Stereotaxic Deep Brain Stimulation Surgery Procedures for Parkinson Disease in Pursuit of Zero Pneumocephalus: 2-Dimensional Operative Video

BACKGROUND AND OBJECTIVES

Deep brain stimulation (DBS) is a well-established intervention for alleviating both motor and nonmotor symptoms of Parkinson disease. However, a common complication of stereotaxic DBS surgery is pneumocephalus, which can compromise electrode accuracy, complicate postoperative assessments, and negatively affect the long-term outcomes of DBS surgery. This report proposes a comprehensive and robust set of recommendations aimed at optimizing DBS surgical protocols to achieve zero pneumocephalus outcomes.

METHODS

A retrospective analysis was undertaken on 138 patients with Parkinson disease who underwent simultaneous bilateral stereotaxic DBS targeting either the subthalamic nucleus or the globus pallidus internus at a single institution. The study compared the pneumocephalus volume and postsurgical electrode tip displacement between the original surgical technique and a refined procedure that incorporated modified supine position, dural puncture, and liquid sealing.

RESULTS

With the implementation of the refined procedure, the volume of pneumocephalus significantly decreased from 14.40 ± 17.00 to 0.32 ± 1.02 mL, with 92.9% of patients showing no visible pneumocephalus or intracranial air less than 1 mL. In addition, the refined procedure was associated with less electrode tip displacement in the postoperative stage.

CONCLUSION

The refined procedure effectively minimized the average pneumocephalus volume to approximately 0, and bilateral DBS electrodes exhibited enhanced stability during the postoperative stage.

Causal network localization of brain stimulation targets for trait anxiety

Transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS) can treat some neuropsychiatric disorders, but there is no consensus approach for identifying new targets. We localized causal circuit-based targets for anxiety that converged across multiple natural experiments. Lesions (n=451) and TMS sites (n=111) that modify anxiety mapped to a common normative brain circuit (r=0.68, p=0.01). In an independent dataset (n=300), individualized TMS site connectivity to this circuit predicted anxiety change (p=0.02). Subthalamic DBS sites overlapping the circuit caused more anxiety (n=74, p=0.006), thus demonstrating a network-level effect, as the circuit was derived without any subthalamic sites. The circuit was specific to trait versus state anxiety in datasets that measured both (p=0.003). Broadly, this illustrates a pathway for discovering novel circuit-based targets across neuropsychiatric disorders.

In Vivo Transcranial Acoustoelectric Brain Imaging of Different Deep Brain Stimulation Currents

Deep brain stimulation (DBS) is an effective treatment for neurologic disease and its clinical effect is highly dependent on the DBS leads localization and current stimulating state. However, standard human brain imaging modalities could not provide direct feedback on DBS currents spatial distribution and dynamic changes. Acoustoelectric brain imaging (AEBI) is an emerging neuroimaging method that can directly map current density distribution. Here, we investigate in vivo AEBI of different DBS currents to explore the potential of DBS visualization using AEBI. According to the typical DBS stimulus parameters, four types of DBS currents, including time pattern, waveform, frequency, and amplitude are designed to implement AEBI experiments in living rat brains. Based on acoustoelectric (AE) signals, the AEBI images of each type DBS current are explored and the resolution is quantitatively analyzed for performance evaluation. Furtherly, the AE signals are decoded to characterize DBS currents from multiple perspectives, including time-frequency domain, spatial distribution, and amplitude comparation. The results show that in vivo transcranial AEBI can accurately locate the DBS contact position with a millimeter spatial resolution (< 2 mm) and millisecond temporal resolution (< 10 ms). Besides, the decoded AE signal at DBS contact position is capable of describing the corresponding DBS current characteristics and identifying current pattern changes. This study first validates that AEBI can localize in vivo DBS contact and characterize different DBS currents. AEBI is expected to develop into a noninvasive DBS real-time monitoring technology with high spatiotemporal resolution.

Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks

Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.

Interrater reliability of deep brain stimulation electrode localizations

Lead-DBS is an open-source, semi-automatized and widely applied software tool facilitating precise localization of deep brain stimulation electrodes both in native as well as in standardized stereotactic space. While automatized preprocessing steps within the toolbox have been tested and validated in previous studies, the interrater reliability in manual refinements of electrode localizations using the tool has not been objectified so far. Here, we investigate the variance introduced in this processing step by different raters when localizing electrodes based on postoperative CT or MRI. Furthermore, we compare the performance of novel trainees that received a structured training and more experienced raters with an expert user. We show that all users yield similar results with an average difference in localizations ranging between 0.52-0.75 mm with 0.07-0.12 mm increases in variability when using postoperative MRI and following normalization to standard space. Our findings may pave the way toward formal training for using Lead-DBS and demonstrate its reliability and ease-of-use for imaging research in the field of deep brain stimulation.

Resting-State Functional Connectivity Predicts STN DBS Clinical Response

BACKGROUND

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

METHODS

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

RESULTS

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

DISCUSSION

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

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.