scholarly journals DiODe v2: Unambiguous and Fully-Automated Detection of Directional DBS Lead Orientation

2021 ◽  
Vol 11 (11) ◽  
pp. 1450
Author(s):  
Till A. Dembek ◽  
Alexandra Hellerbach ◽  
Hannah Jergas ◽  
Markus Eichner ◽  
Jochen Wirths ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Open Source ◽  
Brain Stimulation ◽  
Center Of Mass ◽  
Automated Detection ◽  
Ct Scans ◽  
True Solution ◽  
X Ray ◽  
The Past ◽  
Deep Brain

Directional deep brain stimulation (DBS) leads are now widely used, but the orientation of directional leads needs to be taken into account when relating DBS to neuroanatomy. Methods that can reliably and unambiguously determine the orientation of directional DBS leads are needed. In this study, we provide an enhanced algorithm that determines the orientation of directional DBS leads from postoperative CT scans. To resolve the ambiguity of symmetric CT artifacts, which in the past, limited the orientation detection to two possible solutions, we retrospectively evaluated four different methods in 150 Cartesia™ directional leads, for which the true solution was known from additional X-ray images. The method based on shifts of the center of mass (COM) of the directional marker compared to its expected geometric center correctly resolved the ambiguity in 100% of cases. In conclusion, the DiODe v2 algorithm provides an open-source, fully automated solution for determining the orientation of directional DBS leads.

scholarly journals Conceptualization and validation of an open-source closed-loop deep brain stimulation system in rat

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Hemmings Wu ◽  
Hartwin Ghekiere ◽  
Dorien Beeckmans ◽  
Tim Tambuyzer ◽  
Kris van Kuyck ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Deep Brain Stimulation ◽  
Open Source ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Symptom Control ◽  
Theta Oscillations ◽  
Open Source Hardware ◽  
Hippocampal Theta ◽  
Deep Brain

Abstract Conventional deep brain stimulation (DBS) applies constant electrical stimulation to specific brain regions to treat neurological disorders. Closed-loop DBS with real-time feedback is gaining attention in recent years, after proved more effective than conventional DBS in terms of pathological symptom control clinically. Here we demonstrate the conceptualization and validation of a closed-loop DBS system using open-source hardware. We used hippocampal theta oscillations as system input and electrical stimulation in the mesencephalic reticular formation (mRt) as controller output. It is well documented that hippocampal theta oscillations are highly related to locomotion, while electrical stimulation in the mRt induces freezing. We used an Arduino open-source microcontroller between input and output sources. This allowed us to use hippocampal local field potentials (LFPs) to steer electrical stimulation in the mRt. Our results showed that closed-loop DBS significantly suppressed locomotion compared to no stimulation and required on average only 56% of the stimulation used in open-loop DBS to reach similar effects. The main advantages of open-source hardware include wide selection and availability, high customizability and affordability. Our open-source closed-loop DBS system is effective and warrants further research using open-source hardware for closed-loop neuromodulation.

scholarly journals Open-loop deep brain stimulation for the treatment of epilepsy: a systematic review of clinical outcomes over the past decade (2008–present)

2018 ◽  
Vol 45 (2) ◽  
pp. E5 ◽  
Author(s):  
James J. Zhou ◽  
Tsinsue Chen ◽  
S. Harrison Farber ◽  
Andrew G. Shetter ◽  
Francisco A. Ponce
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Refractory Epilepsy ◽  
Open Loop ◽  
Electric Stimulation Therapy ◽  
Anterior Nucleus ◽  
The Past ◽  
Centromedian Nucleus ◽  
Deep Brain ◽  
Stimulation Of

OBJECTIVEThe field of deep brain stimulation (DBS) for epilepsy has grown tremendously since its inception in the 1970s and 1980s. The goal of this review is to identify and evaluate all studies published on the topic of open-loop DBS for epilepsy over the past decade (2008 to present).METHODSA PubMed search was conducted to identify all articles reporting clinical outcomes of open-loop DBS for the treatment of epilepsy published since January 1, 2008. The following composite search terms were used: (“epilepsy” [MeSH] OR “seizures” [MeSH] OR “kindling, neurologic” [MeSH] OR epilep* OR seizure* OR convuls*) AND (“deep brain stimulation” [MeSH] OR “deep brain stimulation” OR “DBS”) OR (“electric stimulation therapy” [MeSH] OR “electric stimulation therapy” OR “implantable neurostimulators” [MeSH]).RESULTSThe authors identified 41 studies that met the criteria for inclusion. The anterior nucleus of the thalamus, centromedian nucleus of the thalamus, and hippocampus were the most frequently evaluated targets. Among the 41 articles, 19 reported on stimulation of the anterior nucleus of the thalamus, 6 evaluated stimulation of the centromedian nucleus of the thalamus, and 9 evaluated stimulation of the hippocampus. The remaining 7 articles reported on the evaluation of alternative DBS targets, including the posterior hypothalamus, subthalamic nucleus, ventral intermediate nucleus of the thalamus, nucleus accumbens, caudal zone incerta, mammillothalamic tract, and fornix. The authors evaluated each study for overall epilepsy response rates as well as adverse events and other significant, nonepilepsy outcomes.CONCLUSIONSLevel I evidence supports the safety and efficacy of stimulating the anterior nucleus of the thalamus and the hippocampus for the treatment of medically refractory epilepsy. Level III and IV evidence supports stimulation of other targets for epilepsy. Ongoing research into the efficacy, adverse effects, and mechanisms of open-loop DBS continues to expand the knowledge supporting the use of these treatment modalities in patients with refractory epilepsy.

Frameless ROSA® Robot-Assisted Lead Implantation for Deep Brain Stimulation: Technique and Accuracy

2019 ◽  
Vol 19 (1) ◽  
pp. 57-64 ◽  
Author(s):  
Lannie Liu ◽  
Sarah Giulia Mariani ◽  
Emmanuel De Schlichting ◽  
Sylvie Grand ◽  
Michel Lefranc ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Ct Scans ◽  
X Rays ◽  
Robot Assisted ◽  
Lead Position ◽  
The Mean ◽  
Group 2 ◽  
Deep Brain ◽  
Group 1

Abstract BACKGROUND Frameless robotic-assisted surgery is an innovative technique for deep brain stimulation (DBS) that has not been assessed in a large cohort of patients. OBJECTIVE To evaluate accuracy of DBS lead placement using the ROSA® robot (Zimmer Biomet) and a frameless registration. METHODS All patients undergoing DBS surgery in our institution between 2012 and 2016 were prospectively included in an open label single-center study. Accuracy was evaluated by measuring the radial error (RE) of the first stylet implanted on each side and the RE of the final lead position at the target level. RE was measured on intraoperative telemetric X-rays (group 1), on intraoperative O-Arm® (Medtronic) computed tomography (CT) scans (group 2), and on postoperative CT scans or magnetic resonance imaging (MRI) in both groups. RESULTS Of 144 consecutive patients, 119 were eligible for final analysis (123 DBS; 186 stylets; 192 leads). In group 1 (76 patients), the mean RE of the stylet was 0.57 ± 0.02 mm, 0.72 ± 0.03 mm for DBS lead measured intraoperatively, and 0.88 ± 0.04 mm for DBS lead measured postoperatively on CT scans. In group 2 (43 patients), the mean RE of the stylet was 0.68 ± 0.05 mm, 0.75 ± 0.04 mm for DBS lead measured intraoperatively; 0.86 ± 0.05 mm and 1.10 ± 0.08 mm for lead measured postoperatively on CT scans and on MRI, respectively No statistical difference regarding the RE of the final lead position was found between the different intraoperative imaging modalities and postoperative CT scans in both groups. CONCLUSION Frameless ROSA® robot-assisted technique for DBS reached submillimeter accuracy. Intraoperative CT scans appeared to be reliable and sufficient to evaluate the final lead position.

Deep brain stimulation for obsessive-compulsive disorder: past, present, and future

2010 ◽  
Vol 29 (2) ◽  
pp. E10 ◽  
Author(s):  
Matthew K. Mian ◽  
Michael Campos ◽  
Sameer A. Sheth ◽  
Emad N. Eskandar
Keyword(s):  
Deep Brain Stimulation ◽  
Obsessive Compulsive Disorder ◽  
Brain Stimulation ◽  
Clinical Effectiveness ◽  
Research Approach ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
The Past ◽  
Neurosurgical Techniques ◽  
Deep Brain

Obsessive-compulsive disorder (OCD) is a psychiatric illness that can lead to chronic functional impairment. Some patients with severe, chronic OCD have been treated with ablative neurosurgical techniques over the past 4 decades. More recently, deep brain stimulation (DBS) has been investigated as a therapy for refractory OCD, and the procedure was granted a limited humanitarian device exemption by the FDA in 2009. In this article, the authors review the development of DBS for OCD, describe the current understanding of the pathophysiological mechanisms of the disorder and how the underlying neural circuits might be modulated by DBS, and discuss the clinical studies that provide evidence for the use of this evolving therapy. The authors conclude with suggestions for how a combined basic science and translational research approach could drive the understanding of the neural mechanisms underlying OCD as well as the clinical effectiveness of DBS in the setting of recalcitrant disease.

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

2018 ◽  
Author(s):  
Andreas Horn ◽  
Ningfei Li ◽  
Till A Dembek ◽  
Ari Kappel ◽  
Chadwick Boulay ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Functional Connectivity ◽  
Open Source ◽  
Brain Stimulation ◽  
Rapid Development ◽  
Clinical Results ◽  
Electrode Placement ◽  
Imaging Data ◽  
High Field Imaging ◽  
Deep Brain

AbstractDeep 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 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.

scholarly journals Erratum: Conceptualization and validation of an open-source closed-loop deep brain stimulation system in rat

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Hemmings Wu ◽  
Hartwin Ghekiere ◽  
Dorien Beeckmans ◽  
Tim Tambuyzer ◽  
Kris van Kuyck ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Open Source ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Stimulation System ◽  
Deep Brain

3D X-ray based visualization of directional deep brain stimulation lead orientation

2021 ◽  
Author(s):  
Karl Egger ◽  
Alexander Rau ◽  
Horst Urbach ◽  
Marco Reisert ◽  
Peter C. Reinacher
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
X Ray ◽  
Deep Brain

Removing deep brain stimulation artifacts from the electroencephalogram: Issues, recommendations and an open-source toolbox

2018 ◽  
Vol 129 (10) ◽  
pp. 2170-2185 ◽  
Author(s):  
Guillaume Lio ◽  
Stéphane Thobois ◽  
Bénédicte Ballanger ◽  
Brian Lau ◽  
Philippe Boulinguez
Keyword(s):  
Deep Brain Stimulation ◽  
Open Source ◽  
Brain Stimulation ◽  
Deep Brain

scholarly journals ApproXON: Heuristic Approximation to the E-Field-Threshold for Deep Brain Stimulation Volume-of-Tissue-Activated Estimation

2019 ◽  
Author(s):  
Daniele Proverbio ◽  
Andreas Husch
Keyword(s):  
Deep Brain Stimulation ◽  
Open Source ◽  
Brain Stimulation ◽  
Pulse Width ◽  
Axon Diameter ◽  
Stimulation Pulse ◽  
Implementation In Matlab ◽  
Deep Brain

AbstractThis paper introduces a heuristic approximation of the e-field threshold used for volume-of-tissue-activated computation in deep brain stimulation. Pulse width and axon diameter are used as predictors. An open source implementation in MATLAB is provided together with an integration in the open LeadDBS deep brain stimulation research toolbox.

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