Clinical outcomes of deep brain stimulation for obsessive-compulsive disorder: Insight as a predictor of symptom changes.

AIM: Deep brain stimulation (DBS) is a safe and effective treatment option for people with refractory obsessive-compulsive disorder (OCD). Yet our understanding of predictors of response and prognostic factors remains rudimentary, and long-term comprehensive follow-ups are lacking. We aim to investigate the efficacy of DBS therapy for OCD patients, and predictors of clinical response. METHODS: Eight OCD participants underwent DBS stimulation of the nucleus accumbens (NAc) in an open-label longitudinal trial, duration of follow-up varied between 9 months and 7 years. Post-operative care involved comprehensive fine tuning of stimulation parameters and adjunct multidisciplinary therapy. RESULTS: Six participants achieved clinical response (35% improvement in obsessions and compulsions on the Yale Brown Obsessive Compulsive Scale (YBOCS)) within 6-9 weeks, response was maintained at last follow up. On average, the YBOCS improved by 45% at last follow up. Mixed linear modeling elucidated directionality of symptom changes: insight into symptoms strongly predicted (P = 0.008) changes in symptom severity during DBS therapy, likely driven by initial changes in depression and anxiety. Precise localization of DBS leads demonstrated that responders most often had their leads (and active contacts) placed dorsal compared to non-responders, relative to the Nac. CONCLUSION: The clinical efficacy of DBS for OCD is demonstrated, and mediators of changes in symptoms are proposed. The symptom improvements within this cohort should be seen within the context of the adjunct psychological and biopsychosocial care that implemented a shared decision-making approach, with flexible iterative DBS programming. Further research should explore the utility of insight as a clinical correlate of response. The trial was prospectively registered with the ANZCTR (ACTRN12612001142820).

Evaluation of CI electrode position from imaging: comparison of an automated technique with the established manual method.

BACKGROUND: A manual evaluation of the CI electrode position from CT and DVT scans may be affected by diagnostic errors due to cognitive biases. The aim of this study was to compare the CI electrode localization using an automated method (image-guided cochlear implant programming, IGCIP) with the clinically established manual method. METHODS: This prospective experimental study was conducted on a dataset comprising N=50 subjects undergoing cochlear implantation with a Nucleus® CI532 or CI632 Slim Modiolar electrode. Scalar localization, electrode-to-modiolar axis distances (EMD) and angular insertion depth (aDOI) were compared between the automated IGCIP tool and the manual method. Two raters made the manual measurements, and the interrater reliability (±1.96·SD) was determined as the reference for the method comparison. The method comparison was performed using a correlation analysis and a Bland-Altman analysis. RESULTS: Concerning the scalar localization, all electrodes were localized both manually and automatically in the scala tympani. The interrater differences ranged between ±0.2 mm (EMD) and ±10° (aDOI). There was a bias between the automatic and manual method in measuring both localization parameters, which on the one hand was smaller than the interrater variations. On the other hand, this bias depended on the magnitude of the EMD respectively aDOI. A post-hoc analysis revealed that the deviations between the methods were likely due to a different selection of mid-modiolar axis. CONCLUSIONS: The IGCIP is a promising tool for automated processing of CT and DVT scans and has useful functionality such as being able to segment the cochlear using post-operative scans. When measuring EMD, the IGCIP tool is superior to the manual method because the smallest possible distance to the axis is determined depending on the cochlear turn, whereas the manual method selects the helicotrema as the reference point rigidly. Functionality to deal with motion artifacts and measurements of aDOI according to the consensus approach are necessary, otherwise the IGCIP is not unrestrictedly ready for clinical use.

Artifacts Can Be Deceiving: The Actual Location of Deep Brain Stimulation Electrodes Differs from the Artifact Seen on Magnetic Resonance Images.

INTRODUCTION: Deep brain stimulation (DBS) is a common treatment for a variety of neurological and psychiatric disorders. Recent studies have highlighted the role of neuroimaging in localizing the position of electrode contacts relative to target brain areas in order to optimize DBS programming. Among different imaging methods, postoperative magnetic resonance imaging (MRI) has been widely used for DBS electrode localization; however, the geometrical distortion induced by the lead limits its accuracy. In this work, we investigated to what degree the difference between the actual location of the lead's tip and the location of the tip estimated from the MRI artifact varies depending on the MRI sequence parameters such as acquisition plane and phase encoding direction, as well as the lead's extracranial configuration. Accordingly, an imaging technique to increase the accuracy of lead localization was devised and discussed. METHODS: We designed and constructed an anthropomorphic phantom with an implanted DBS system following 18 clinically relevant configurations. The phantom was scanned at a Siemens 1.5 Tesla Aera scanner using a T1MPRAGE sequence optimized for clinical use and a T1TSE sequence optimized for research purposes. We varied slice acquisition plane and phase encoding direction and calculated the distance between the caudal tip of the DBS lead MRI artifact and the actual tip of the lead, as estimated from MRI reference markers. RESULTS: Imaging parameters and lead configuration substantially altered the difference in the depth of the lead within its MRI artifact on the scale of several millimeters - with a difference as large as 4.99 mm. The actual tip of the DBS lead was found to be consistently more rostral than the tip estimated from the MR image artifact. The smallest difference between the tip of the DBS lead and the tip of the MRI artifact using the clinically relevant sequence (i.e., T1MPRAGE) was found with the sagittal acquisition plane and anterior-posterior phase encoding direction. DISCUSSION/CONCLUSION: The actual tip of an implanted DBS lead is located up to several millimeters rostral to the tip of the lead's artifact on postoperative MR images. This distance depends on the MRI sequence parameters and the DBS system's extracranial trajectory. MRI parameters may be altered to improve this localization.

ECG Electrode Localization: 3D DS Camera System for Use in Diverse Clinical Environments.

Models of the human body representing digital twins of patients have attracted increasing interest in clinical research for the delivery of personalized diagnoses and treatments to patients. For example, noninvasive cardiac imaging models are used to localize the origin of cardiac arrhythmias and myocardial infarctions. The precise knowledge of a few hundred electrocardiogram (ECG) electrode positions is essential for their diagnostic value. Smaller positional errors are obtained when extracting the sensor positions, along with the anatomical information, for example, from X-ray Computed Tomography (CT) slices. Alternatively, the amount of ionizing radiation the patient is exposed to can be reduced by manually pointing a magnetic digitizer probe one by one to each sensor. An experienced user requires at least 15 min. to perform a precise measurement. Therefore, a 3D depth-sensing camera system was developed that can be operated under adverse lighting conditions and limited space, as encountered in clinical settings. The camera was used to record the positions of 67 electrodes attached to a patient's chest. These deviate, on average, by 2.0 mm ±1.5 mm from manually placed markers on the individual 3D views. This demonstrates that the system provides reasonable positional precision even when operated within clinical environments.

Validation of 3D fluoroscopy for image-guidance registration in depth electrode implantation for medically refractory epilepsy.

BACKGROUND: Frame registration is a critical step to ensure accurate electrode placement in stereotactic procedures such as stereoelectroencephalography (SEEG) and is routinely done by merging a computed tomography (CT) scan with the preoperative magnetic resonance (MR) examination. Three-dimensional fluoroscopy (XT) has emerged as a method for intraoperative electrode verification following electrode implantation and more recently has been proposed as a registration method with several advantages. METHODS: We compared the accuracy of SEEG electrode placement by frame registration with CT and XT imaging by analyzing the Euclidean distance between planned and post-implantation trajectories of the SEEG electrodes to calculate the error in both the entry (EP) and target (TP) points. Other variables included radiation dose, efficiency, and complications. RESULTS: Twenty-seven patients (13 CT and 14 XT) underwent placement of SEEG electrodes (319 in total). The mean EP and TP errors for the CT group were 2.3 mm and 3.3 mm, respectively, and 1.9 mm and 2.9 mm for the XT group, with no statistical difference (p = 0.75 and p = 0.246). The time to first electrode placement was similar (XT, 82 ± 10 min; CT, 84 ± 22 min; p = 0.858) and the average radiation exposure with XT (234 ± 55 mGy*cm) was significantly lower than CT (1245 ± 123 mGy*cm) (p < 0.0001). Four complications were documented with equal incidence in both groups. CONCLUSIONS: The use of XT as a method for registration resulted in similar implantation accuracy compared with CT. Advantages of XT are the substantial reduction in radiation dose and the elimination of the need to transfer the patient out of the room which may have an impact on patient safety and OR efficiency.

Standardized fluoroscopy-guided implantation technique enables optimal electrode placement in sacral neuromodulation: a cadaver study.

BACKGROUND: Sacral neuromodulation (SNM) is an established treatment option for patients with faecal incontinence. The location of the stimulating electrode is considered to be essential for treatment success. The purpose of this study was to evaluate the position of SNM electrodes after using a standardized fluoroscopy-guided implantation technique. METHODS: For this cadaver study, SNM electrodes were implanted bilaterally in 5 lower body specimens. The lower edge of the sacroiliac joint and the medial edge of the sacral foramina were marked using fluoroscopy to draw an 'H' with the crossing points identifying S3. After electrode placement the pelvis was dissected to describe the exact position of the SNM electrodes. RESULTS: The electrodes were inserted at an angle with a median degree measure of 60° (range 50-65°) to the skin, with a median distance of 9 mm (range 0-13 mm) from the S3 marking. All electrodes entered the third sacral foramen. The median distance of the electrodes to the sacral nerve was 0 mm (range 0-3 mm) for the most proximal, 0.5 mm (range 0-5 mm) for the second, 2.25 mm (range 0-11 mm) for the third and 1.75 mm (range 0-16 mm) for the most distant electrode. There was neither a significant difference in the proximity of the electrodes to the nerve between the right and left side (proximal to distal electrode: p = 0.18, p = 0.16, p = 0.07, p = 0.07) nor between male and female cadavers (p = 0.25, p = 0.21, p = 0.66, p = 0.66). CONCLUSIONS: A standardized fluoroscopy-guided implantation technique enables a close contact between electrode and nerve. This can potentially result in an improved clinical outcome.

Investigation of Magnetoelectric Sensor Requirements for Deep Brain Stimulation Electrode Localization and Rotational Orientation Detection.

Correct position and orientation of a directional deep brain stimulation (DBS) electrode in the patient's brain must be known to fully exploit its benefit in guiding stimulation programming. Magnetoelectric (ME) sensors can play a critical role here. The aim of this study was to determine the minimum required limit of detection (LOD) of a ME sensor that can be used for this application by measuring the magnetic field induced by DBS. For this experiment, a commercial DBS system was integrated into a head phantom and placed inside of a state-of-the-art Superconducting Quantum Interference Device (SQUID)-based magnetoencephalography system. Measurements were performed and analyzed with digital signal processing. Investigations have shown that the minimum required detection limit depends on various factors such as: measurement distance to electrode, bandwidth of magnetic sensor, stimulation amplitude, stimulation pulse width, and measurement duration. For a sensor that detects only a single DBS frequency (stimulation frequency or its harmonics), a LOD of at least 0.04 pT/Hz0.5 is required for 3 mA stimulation amplitude and 60 µµs pulse width. This LOD value increases by an order of magnitude to 0.4 pT/Hz0.5 for a 1 kHz, and by approximately two orders to 3 pT/Hz0.5 for a 10 kHz sensor bandwidth. By averaging, the LOD can be reduced by at least another 2 orders of magnitude with a measurement duration of a few minutes.

The accuracy of 3D fluoroscopy (XT) vs computed tomography (CT) registration in deep brain stimulation (DBS) surgery.

BACKGROUND: Stereotactic registration is the most critical step ensuring accuracy in deep brain stimulation (DBS) surgery. 3D fluoroscopy (XT) is emerging as an alternative to CT. XT has been shown to be safe and effective for intraoperative confirmation of lead position following implantation. However, there is a lack of studies evaluating the suitability of XT to be used for the more crucial step of registration and its capability of being merged to a preoperative MRI. This is the first study comparing accuracy, efficiency, and radiation exposure of XT- vs CT-based stereotactic registration and XT/MRI merging in deep brain stimulation. METHODS: Mean absolute differences and Euclidean distance between planned (adjusted for intraoperative testing) and actual lead trajectories were calculated for accuracy of implantation. The radiation dose from each scan was recorded as the dose length product (DLP). Efficiency was measured as the time between the patient entering the operating room and the initial skin incision. A one-way ANOVA compared these parameters between patients that had either CT- or XT-based registration. RESULTS: Forty-one patients underwent DBS surgery-25 in the CT group and 16 in the XT group. The mean absolute difference between CT and XT was not statistically significant in the x (p = 0.331), y (p = 0.951), or z (p = 0.807) directions. The Euclidean distance between patient groups did not differ significantly (p = 0.874). The average radiation exposure with XT (220.0 ± 0.1 mGy*cm) was significantly lower than CT (1269.3 ± 112.9 mGy*cm) (p < 0.001). There was no significant difference in registration time between CT (107.8 ± 23.1 min) and XT (106.0 ± 18.2 min) (p = 0.518). CONCLUSION: XT-based frame registration was shown to result in similar implantation accuracy and significantly less radiation exposure compared with CT. Our results surprisingly showed no significant difference in registration time, but this may be due to a learning curve effect.

GridLoc: An automatic and unsupervised localization method for high-density ECoG grids.

Precise localization of electrodes is essential in the field of high-density (HD) electrocorticography (ECoG) brain signal analysis in order to accurately interpret the recorded activity in relation to functional anatomy. Current localization methods for subchronically implanted HD electrode grids involve post-operative imaging. However, for situations where post-operative imaging is not available, such as during acute measurements in awake surgery, electrode localization is complicated. Intra-operative photographs may be informative, but not for electrode grids positioned partially or fully under the skull. Here we present an automatic and unsupervised method to localize HD electrode grids that does not require post-operative imaging. The localization method, named GridLoc, is based on the hypothesis that the anatomical and vascular brain structures under the ECoG electrodes have an effect on the amplitude of the recorded ECoG signal. More specifically, we hypothesize that the spatial match between resting-state high-frequency band power (45-120 Hz) patterns over the grid and the anatomical features of the brain under the electrodes, such as the presence of sulci and larger blood vessels, can be used for adequate HD grid localization. We validate this hypothesis and compare the GridLoc results with electrode locations determined with post-operative imaging and/or photographs in 8 patients implanted with HD-ECoG grids. Locations agreed with an average difference of 1.94 ±â€¯0.11 mm, which is comparable to differences reported earlier between post-operative imaging and photograph methods. The results suggest that resting-state high-frequency band activity can be used for accurate localization of HD grid electrodes on a pre-operative MRI scan and that GridLoc provides a convenient alternative to methods that rely on post-operative imaging or intra-operative photographs.

Three-dimensional localization of cortical electrodes in deep brain stimulation surgery from intraoperative fluoroscopy.

Electrophysiological recordings from subdural electrocorticography (ECoG) electrodes implanted temporarily during deep brain stimulation (DBS) surgeries offer a unique opportunity to record cortical activity for research purposes. The optimal utilization of this important research method relies on accurate and robust localization of ECoG electrodes, and intraoperative fluoroscopy is often the only imaging modality available to visualize electrode locations. However, the localization of a three-dimensional electrode position using a two-dimensional fluoroscopic image is problematic due to the lost dimension orthogonal to the fluoroscopic image, a parallax distortion implicit to fluoroscopy, and variability of visible skull contour among fluoroscopic images. Here, we present a method to project electrodes visible on the fluoroscopic image onto a reconstructed cortical surface by leveraging numerous common landmarks to translate, rotate, and scale coregistered computed tomography (CT) and magnetic resonance imaging (MRI) reconstructed surfaces in order to recreate the coordinate framework in which the fluoroscopic image was acquired, while accounting for parallax distortion. Validation of this approach demonstrated high precision with an average total Euclidian distance between three independent reviewers of 1.65±0.68mm across 8 patients and 82 electrodes. Spatial accuracy was confirmed by correspondence between recorded neural activity over sensorimotor cortex during hand movement. This semi-automated interface reliably estimates the location of temporarily implanted subdural ECoG electrodes visible on intraoperative fluoroscopy to a cortical surface.

An open-source automated platform for three-dimensional visualization of subdural electrodes using CT-MRI coregistration.

OBJECTIVE: Visualizing implanted subdural electrodes in three-dimensional (3D) space can greatly aid in planning, executing, and validating resection in epilepsy surgery. Coregistration software is available, but cost, complexity, insufficient accuracy, or validation limit adoption. We present a fully automated open-source application, based on a novel method using postimplant computerized tomography (CT) and postimplant magnetic resonance (MR) images, for accurately visualizing intracranial electrodes in 3D space. METHODS: CT-MR rigid brain coregistration, MR nonrigid registration, and prior-based segmentation were carried out on seven patients. Postimplant CT, postimplant MR, and an external labeled atlas were then aligned in the same space. The coregistration algorithm was validated by manually marking identical anatomic landmarks on the postimplant CT and postimplant MR images. Following coregistration, distances between the center of the landmark masks on the postimplant MR and the coregistered CT images were calculated for all subjects. Algorithms were implemented in open-source software and translated into a "drag and drop" desktop application for Apple Mac OS X. RESULTS: Despite postoperative brain deformation, the method was able to automatically align intrasubject multimodal images and segment cortical subregions, so that all electrodes could be visualized on the parcellated brain. Manual marking of anatomic landmarks validated the coregistration algorithm with a mean misalignment distance of 2.87 mm (standard deviation 0.58 mm)between the landmarks. Software was easily used by operators without prior image processing experience. SIGNIFICANCE: We demonstrate an easy to use, novel platform for accurately visualizing subdural electrodes in 3D space on a parcellated brain. We rigorously validated this method using quantitative measures. The method is unique because it involves no preprocessing, is fully automated, and freely available worldwide. A desktop application, as well as the source code, are both available for download on the International Epilepsy Electrophysiology Portal (https://www.ieeg.org) for use and interactive refinement.

Application of phase coherence in assessment of spatial alignment of electrodes during simultaneous endocardial-epicardial direct contact mapping of atrial fibrillation.

AIMS: Mapping and interpretation of wave conduction patterns recorded during simultaneous mapping of the electrical activity on both endocardial and epicardial surfaces are challenging because of the difficulty of reconstruction of reciprocal alignment of electrodes in space. Here, we suggest a method to overcome this difficulty using a concept of maximized endo-epicardial phase coherence. METHODS AND RESULTS: Endo-epicardial mapping was performed in six humans during induced atrial fibrillation (AF) in right atria using two sets of 8 × 8 electrode plaques. For each electrode, mean phase coherence (MPC) with all electrodes on the opposite side of the atrial wall was calculated. Localization error was defined as a distance between the directly opposing electrode and the electrode with the maximal MPC. Overall, there was a linear correlation between MPC and distance between electrodes with R(2) = 0.34. Localization error obtained for electrodes of the plaque in six patients resulted in a mean 2.3 ± 1.9 mm for 25 s electrogram segment length. Eighty-four per cent of the measurements resulted in error smaller than 3.4 mm. The duration of the recording used to compute MPC was negatively correlated with localization error; however, the effect reached plateau for segment durations longer than 15 s. CONCLUSION: Application of the concept of maximized endo-epicardial phase coherence to electrograms during AF allows reconstruction of reciprocal alignment of the electrodes on the opposite side of the atrial wall. This approach may be especially useful in settings where the spatial position of endo- and epicardial electrodes for intracardiac mapping cannot otherwise be determined.

EEG electrodes and where to find them: automated localization from 3D scans.

Objective.The accurate localization of electroencephalography (EEG) electrode positions is crucial for accurate source localization. Recent advancements have proposed alternatives to labor-intensive, manual methods for spatial localization of the electrodes, employing technologies such as 3D scanning and laser scanning. These novel approaches often integrate magnetic resonance imaging (MRI) as part of the pipeline in localizing the electrodes. The limited global availability of MRI data restricts its use as a standard modality in several clinical scenarios. This limitation restricts the use of these advanced methods.Approach.In this paper, we present a novel, versatile approach that utilizes 3D scans to localize EEG electrode positions with high accuracy. Importantly, while our method can be integrated with MRI data if available, it is specifically designed to be highly effective even in the absence of MRI, thus expanding the potential for advanced EEG analysis in various resource-limited settings. Our solution implements a two-tiered approach involving landmark/fiducials localization and electrode localization, creating an end-to-end framework.Main results.The efficacy and robustness of our approach have been validated on an extensive dataset containing over 400 3D scans from 278 subjects. The framework identifies pre-auricular points and achieves correct electrode positioning accuracy in the range of 85.7% to 91.0%. Additionally, our framework includes a validation tool that permits manual adjustments and visual validation if required.Significance.This study represents, to the best of the authors' knowledge, the first validation of such a method on a substantial dataset, thus ensuring the robustness and generalizability of our innovative approach. Our findings focus on developing a solution that facilitates source localization, without the need for MRI, contributing to the critical discussion on balancing cost effectiveness with methodological accuracy to promote wider adoption in both research and clinical settings.

Voxeloc: A time-saving graphical user interface for localizing and visualizing stereo-EEG electrodes.

BACKGROUND: Thanks to its unrivalled spatial and temporal resolutions and signal-to-noise ratio, intracranial EEG (iEEG) is becoming a valuable tool in neuroscience research. To attribute functional properties to cortical tissue, it is paramount to be able to determine precisely the localization of each electrode with respect to a patient's brain anatomy. Several software packages or pipelines offer the possibility to localize manually or semi-automatically iEEG electrodes. However, their reliability and ease of use may leave to be desired. NEW METHOD: Voxeloc (voxel electrode locator) is a Matlab-based graphical user interface to localize and visualize stereo-EEG electrodes. Voxeloc adopts a semi-automated approach to determine the coordinates of each electrode contact, the user only needing to indicate the deep-most contact of each electrode shaft and another point more proximally. RESULTS: With a deliberately streamlined functionality and intuitive graphical user interface, the main advantages of Voxeloc are ease of use and inter-user reliability. Additionally, oblique slices along the shaft of each electrode can be generated to facilitate the precise localization of each contact. Voxeloc is open-source software and is compatible with the open iEEG-BIDS (Brain Imaging Data Structure) format. COMPARISON WITH EXISTING METHODS: Localizing full patients' iEEG implants was faster using Voxeloc than two comparable software packages, and the inter-user agreement was better. CONCLUSIONS: Voxeloc offers an easy-to-use and reliable tool to localize and visualize stereo-EEG electrodes. This will contribute to democratizing neuroscience research using iEEG.

A Unified Deep-Learning-Based Framework for Cochlear Implant Electrode Array Localization.

Cochlear implants (CIs) are neuroprosthetics that can provide a sense of sound to people with severe-to-profound hearing loss. A CI contains an electrode array (EA) that is threaded into the cochlea during surgery. Recent studies have shown that hearing outcomes are correlated with EA placement. An image-guided cochlear implant programming technique is based on this correlation and utilizes the EA location with respect to the intracochlear anatomy to help audiologists adjust the CI settings to improve hearing. Automated methods to localize EA in postoperative CT images are of great interest for large-scale studies and for translation into the clinical workflow. In this work, we propose a unified deep-learning-based framework for automated EA localization. It consists of a multi-task network and a series of postprocessing algorithms to localize various types of EAs. The evaluation on a dataset with 27 cadaveric samples shows that its localization error is slightly smaller than the state-of-the-art method. Another evaluation on a large-scale clinical dataset containing 561 cases across two institutions demonstrates a significant improvement in robustness compared to the state-of-the-art method. This suggests that this technique could be integrated into the clinical workflow and provide audiologists with information that facilitates the programming of the implant leading to improved patient care.

Efficient volume-based localization and automatic labeling of intracranial depth electrodes.

Background: The accurate localization and anatomical labeling of intracranial depth electrodes are crucial for stereoelectroencephalography (SEEG) recordings and the interpretation of results in patients with epilepsy. The laborious electrode localization procedure requires an efficient and easy-to-use pipeline. Thus, we developed a useful tool, which we called the depth electrode localizer (DELLO), to automatically identify and label depth electrode contacts with ease. Methods: The DELLO is an open-source package developed in MATLAB (MathWorks). It was specifically fine-tuned to expedite the localization of depth electrodes. The basic procedures include preoperative magnetic resonance imaging (MRI) and postoperative computed tomography coregistration, intensity threshold electrode spatial sampling, the hierarchical clustering of electrode samples, and gray-matter and automatic anatomical labeling (AAL). The DELLO also has a graphical user interface (GUI) that can be used to review the results. The only manual intervention procedures are the identification of the target (tip) and entry point of each electrode and the naming of the clustered electrode contact groups, which generally take ~5 min per case. The coordinates of each contact were recorded in individual spaces and were also transformed in standard space by applying a volume-based deformation field. To validate the performance of the current method, 7 patients with epilepsy were retrospectively included in the analysis. Results: A total of 80 depth electrodes, including 1,030 contacts from the 7 patients with epilepsy, were localized. All the procedures functioned well, and the entire process was robust and intuitive. Among the 1,030 contacts, 746 (72.43%) were labeled as inside the gray matter. The gray-matter and AAL accuracy rates were 95.83% and 90.78%, respectively, over all contacts. Conclusions: The DELLO is an integrated tool that was designed to semi-automatically localize and label intracranial depth electrodes. It is open source and freely available. Given its high accuracy and efficiency, the DELLO could facilitate SEEG interpretation and be used in SEEG-based cognitive neuroscience studies.

Computer vision-based algorithm to sUppoRt coRrect electrode placemeNT (CURRENT) for home-based electric non-invasive brain stimulation.

OBJECTIVE: Home-based non-invasive brain stimulation (NIBS) has been suggested as an adjunct treatment strategy for neuro-psychiatric disorders. There are currently no available solutions to direct and monitor correct placement of the stimulation electrodes. To address this issue, we propose an easy-to-use digital tool to support patients for self-application. METHODS: We recruited 36 healthy participants and compared their cap placement performance with the one of a NIBS-expert investigator. We tested participants' placement accuracy with instructions before (Pre) and after the investigator's placement (Post), as well as participants using the support tool (CURRENT). User experience (UX) and confidence were further evaluated. RESULTS: Permutation tests demonstrated a smaller deviation within the CURRENT compared with Pre cap placement (p = 0.02). Subjective evaluation of ease of use and usefulness of the tool were vastly positive (8.04 out of 10). CURRENT decreased the variability of performance, ensured placement within the suggested maximum of deviation (10 mm) and supported confidence of correct placement. CONCLUSIONS: This study supports the usability of this novel technology for correct electrode placement during self-application in home-based settings. SIGNIFICANCE: CURRENT provides an exciting opportunity to promote home-based, self-applied NIBS as a safe, high-frequency treatment strategy that can be well integrated in patients' daily lives.

EEG electrode localization with 3D iPhone scanning using point-cloud electrode selection (PC-ES).

Objective.Electroencephalography source imaging (ESI) is a valuable tool in clinical evaluation for epilepsy patients but is underutilized in part due to sensitivity to anatomical modeling errors. Accurate localization of scalp electrodes is instrumental to ESI, but existing localization devices are expensive and not portable. As a result, electrode localization challenges further impede access to ESI, particularly in inpatient and intensive care settings.Approach.To address this challenge, we present a portable and affordable electrode digitization method using the 3D scanning feature in modern iPhone models. This technique combines iPhone scanning with semi-automated image processing using point-cloud electrode selection (PC-ES), a custom MATLAB desktop application. We compare iPhone electrode localization to state-of-the-art photogrammetry technology in a human study with over 6000 electrodes labeled using each method. We also characterize the performance of PC-ES with respect to head location and examine the relative impact of different algorithm parameters.Main Results.The median electrode position variation across reviewers was 1.50 mm for PC-ES scanning and 0.53 mm for photogrammetry, and the average median distance between PC-ES and photogrammetry electrodes was 3.4 mm. These metrics demonstrate comparable performance of iPhone/PC-ES scanning to currently available technology and sufficient accuracy for ESI.Significance.Low cost, portable electrode localization using iPhone scanning removes barriers to ESI in inpatient, outpatient, and remote care settings. While PC-ES has current limitations in user bias and processing time, we anticipate these will improve with software automation techniques as well as future developments in iPhone 3D scanning technology.

Deep Brain Stimulation Electrode Reconstruction: Comparison between Lead-DBS and Surgical Planning System.

BACKGROUND: Electrode reconstruction for postoperative deep brain simulation (DBS) can be achieved manually using a surgical planning system such as Surgiplan, or in a semi-automated manner using software such as the Lead-DBS toolbox. However, the accuracy of Lead-DBS has not been thoroughly addressed. METHODS: In our study, we compared the DBS reconstruction results of Lead-DBS and Surgiplan. We included 26 patients (21 with Parkinson's disease and 5 with dystonia) who underwent subthalamic nucleus (STN)-DBS, and reconstructed the DBS electrodes using the Lead-DBS toolbox and Surgiplan. The electrode contact coordinates were compared between Lead-DBS and Surgiplan with postoperative CT and MRI. The relative positions of the electrode and STN were also compared between the methods. Finally, the optimal contact during follow-up was mapped onto the Lead-DBS reconstruction results to check for overlap between the contacts and the STN. RESULTS: We found significant differences in all axes between Lead-DBS and Surgiplan with postoperative CT, with the mean variance for the X, Y, and Z coordinates being -0.13, -1.16, and 0.59 mm, respectively. Y and Z coordinates showed significant differences between Lead-DBS and Surgiplan with either postoperative CT or MRI. However, no significant difference in the relative distance of the electrode and the STN was found between the methods. All optimal contacts were located in the STN, with 70% of them located within the dorsolateral region of the STN in the Lead-DBS results. CONCLUSIONS: Although significant differences in electrode coordinates existed between Lead-DBS and Surgiplan, our results suggest that the coordinate difference was around 1 mm, and Lead-DBS can capture the relative distance between the electrode and the DBS target, suggesting it is reasonably accurate for postoperative DBS reconstruction.

Anatomical targeting for electrode localization in subthalamic nucleus deep brain stimulation: A comparative study.

BACKGROUND AND PURPOSE: In deep brain stimulation (DBS), accurate electrode placement is essential for optimizing patient outcomes. Localizing electrodes enables insight into therapeutic outcomes and development of metrics for use in clinical trials. Methods of defining anatomical targets have been described with varying accuracy and objectivity. To assess variability in anatomical targeting, we compare four methods of defining an appropriate target for DBS of the subthalamic nucleus for Parkinson's disease. METHODS: The methods compared are direct visualization, red nucleus-based indirect targeting, mid-commissural point-based indirect targeting, and automated template-based targeting. This study assessed 226 hemispheres in 113 DBS recipients (39 females, 73 males, 62.2 ± 7.7 years). We utilized the electrode placement error (the Euclidean distance between the defined target and closest DBS electrode) as a metric for comparative analysis. Pairwise differences in electrode placement error across the four methods were compared using the Kruskal-Wallis H-test and Wilcoxon signed-rank tests. RESULTS: Interquartile ranges of the differences in electrode placement error spanned 1.18-1.56 mm. A Kruskal-Wallis H-test reported a statistically significant difference in the median of at least two groups (H(5) = 41.052, p < .001). Wilcoxon signed-rank tests reported statistically significant difference in two comparisons: direct visualization versus red nucleus-based indirect, and direct visualization versus automated template-based methods (T < 9215, p < .001). CONCLUSIONS: All methods were similarly discordant in their relative accuracy, despite having significant technical differences in their application. The differing protocols and technical aspects of each method, however, have the implication that one may be more practical depending on the clinical or research application at hand.