scholarly journals Efficient automated localization of ECoG electrodes in CT images via shape analysis

2021 ◽  
Vol 16 (4) ◽  
pp. 543-554
Author(s):  
Jessica Centracchio ◽  
Antonio Sarno ◽  
Daniele Esposito ◽  
Emilio Andreozzi ◽  
Luigi Pavone ◽  
...  
Keyword(s):  
Shape Analysis ◽  
Focal Epilepsy ◽  
Support Vector ◽  
Epileptogenic Zone ◽  
Platinum Electrodes ◽  
Public Repository ◽  
Automated Method ◽  
Depth Electrodes ◽  
Ethical Approval ◽  
Cortical Regions

Abstract Purpose People with drug-refractory epilepsy are potential candidates for surgery. In many cases, epileptogenic zone localization requires intracranial investigations, e.g., via ElectroCorticoGraphy (ECoG), which uses subdural electrodes to map eloquent areas of large cortical regions. Precise electrodes localization on cortical surface is mandatory to delineate the seizure onset zone. Simple thresholding operations performed on patients’ computed tomography (CT) volumes recognize electrodes but also other metal objects (e.g., wires, stitches), which need to be manually removed. A new automated method based on shape analysis is proposed, which provides substantially improved performances in ECoG electrodes recognition. Methods The proposed method was retrospectively tested on 24 CT volumes of subjects with drug-refractory focal epilepsy, presenting a large number (> 1700) of round platinum electrodes. After CT volume thresholding, six geometric features of voxel clusters (volume, symmetry axes lengths, circularity and cylinder similarity) were used to recognize the actual electrodes among all metal objects via a Gaussian support vector machine (G-SVM). The proposed method was further tested on seven CT volumes from a public repository. Simultaneous recognition of depth and ECoG electrodes was also investigated on three additional CT volumes, containing penetrating depth electrodes. Results The G-SVM provided a 99.74% mean classification accuracy across all 24 single-patient datasets, as well as on the combined dataset. High accuracies were obtained also on the CT volumes from public repository (98.27% across all patients, 99.68% on combined dataset). An overall accuracy of 99.34% was achieved for the recognition of depth and ECoG electrodes. Conclusions The proposed method accomplishes automated ECoG electrodes localization with unprecedented accuracy and can be easily implemented into existing software for preoperative analysis process. The preliminary yet surprisingly good results achieved for the simultaneous depth and ECoG electrodes recognition are encouraging. Ethical approval n°NCT04479410 by “IRCCS Neuromed” (Pozzilli, Italy), 30th July 2020.

Technique, Results, and Complications Related to Robot-Assisted Stereoelectroencephalography

Neurosurgery ◽  
2015 ◽  
Vol 78 (2) ◽  
pp. 169-180 ◽  
Author(s):  
Jorge González-Martínez ◽  
Juan Bulacio ◽  
Susan Thompson ◽  
John Gale ◽  
Saksith Smithason ◽  
...  
Keyword(s):  
Focal Epilepsy ◽  
Interquartile Range ◽  
Implantation Technique ◽  
Target Point ◽  
Seizure Outcome ◽  
Seizure Freedom ◽  
Epileptogenic Zone ◽  
Robot Assisted ◽  
Depth Electrodes

ABSTRACT BACKGROUND: Robot-assisted stereoelectroencephalography (SEEG) may represent a simplified, precise, and safe alternative to the more traditional SEEG techniques. OBJECTIVE: To report our clinical experience with robotic SEEG implantation and to define its utility in the management of patients with medically refractory epilepsy. METHODS: The prospective observational analyses included all patients with medically refractory focal epilepsy who underwent robot-assisted stereotactic placement of depth electrodes for extraoperative brain monitoring between November 2009 and May 2013. Technical nuances of the robotic implantation technique are presented, as well as an analysis of demographics, time of planning and procedure, seizure outcome, in vivo accuracy, and procedure-related complications. RESULTS: One hundred patients underwent 101 robot-assisted SEEG procedures. Their mean age was 33.2 years. In total, 1245 depth electrodes were implanted. On average, 12.5 electrodes were implanted per patient. The time of implantation planning was 30 minutes on average (range, 15-60 minutes). The average operative time was 130 minutes (range, 45-160 minutes). In vivo accuracy (calculated in 500 trajectories) demonstrated a median entry point error of 1.2 mm (interquartile range, 0.78-1.83 mm) and a median target point error of 1.7 mm (interquartile range, 1.20-2.30 mm). Of the group of patients who underwent resective surgery (68 patients), 45 (66.2%) gained seizure freedom status. Mean follow-up was 18 months. The total complication rate was 4%. CONCLUSION: The robotic SEEG technique and method were demonstrated to be safe, accurate, and efficient in anatomically defining the epileptogenic zone and subsequently promoting sustained seizure freedom status in patients with difficult-to-localize seizures.

scholarly journals The comparative study of invasive electroencephalography modalities in temporal lobe epilepsy

2021 ◽  
Vol 23 (3) ◽  
pp. 14-22
Author(s):  
V. M. Dzhafarov ◽  
A. B. Dmitriev ◽  
N. P. Denisova ◽  
D. A. Rzaev
Keyword(s):  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Focal Epilepsy ◽  
Epileptogenic Zone ◽  
Foramen Ovale ◽  
Seizure Onset ◽  
Depth Electrodes ◽  
Seizure Onset Zone ◽  
Temporal Lobe Seizures ◽  
Mesial Temporal Lobe

Introduction. Invasive video-EEG monitoring (invasive EEG) is indicated in patients with refractory focal epilepsy while localization of the epileptogenic zone is unclear. Methods of invasive EEG in different groups of patients demonstrate variable results.Objective: to analyse the results of invasive EEG via subdural and depth electrodes in patients with refractory temporal lobe epilepsy with mesial temporal lobe seizures.Materials and methods. The series of 37 patients who underwent invasive EEG from 2013 to 2020 was retrospectively analysed. The study includes primary adult patients with structural refractory focal epilepsy with mesial temporal lobe seizures without tumor and vascular pathology. Patients were divided onto 3 groups: 1) with foramen ovale electrodes 2) subdural strip electrodes and 3) combination of subdural strips and depths electrodes. The results of anteromedial temporal lobectomy after 6 months were classified according to Engel scale.Results. A group with foramen ovale electrodes included 7 patients, subdural strips – 23, combination – 7. The seizure onset zone was detected in 36 (97 %) cases. Serious complications were observed in 2 (29 %) cases in the group with foramen ovale electrodes. The mean follow-up in 23 (76 %) patients after resective surgery was 28.3 months. Favourable results (Engel I, II) were observed in 4 (80 %) patients with foramen ovale electrodes, in 8 (67 %) patients with subdural electrodes, in 6 (100 %) with combination. Unfavourable results (Engel III, IV) were noted in 1 (20 %) patient with foramen ovale electrode, in 4 (33 %) patients with subdural strips.Conclusion. All the presented modalities of invasive EEG are effective for localizing of seizure onset zone in this category of patients. Foramen ovale electrode using may be limited due to increased risk of complications.

A multimodal concept for invasive diagnostics and surgery based on neuronavigated voxel-based morphometric MRI postprocessing data in previously nonlesional epilepsy

2018 ◽  
Vol 128 (4) ◽  
pp. 1178-1186 ◽  
Author(s):  
Daniel Delev ◽  
Carlos M. Quesada ◽  
Alexander Grote ◽  
Jan P. Boström ◽  
Christian Elger ◽  
...  
Keyword(s):  
Focal Epilepsy ◽  
Diagnostic Yield ◽  
Focal Cortical Dysplasia ◽  
Seizure Outcome ◽  
Epileptogenic Zone ◽  
Mri Findings ◽  
Additional Information ◽  
Resective Surgery ◽  
Depth Electrodes ◽  
Class 1

OBJECTIVEDiagnosis and surgical treatment of refractory and apparent nonlesional focal epilepsy is challenging. Morphometric MRI voxel-based and other postprocessing methods can help to localize the epileptogenic zone and thereby support the planning of further invasive electroencephalography (EEG) diagnostics, and maybe resective epilepsy surgery.METHODSThe authors developed an algorithm to implement regions of interest (ROI), based on postprocessed MRI data, into a neuronavigation tool. This was followed by stereotactic ROI-guided implantation of depth electrodes and ROI-navigated resective surgery. Data on diagnostic yield, histology, and seizure outcome were collected and evaluated.RESULTSFourteen consecutive patients with apparently nonlesional epilepsy were included in this study. Reevaluation of the MR images with the help of MRI postprocessing analysis led to the identification of probable subtle lesions in 11 patients. Additional information obtained by SPECT imaging and MRI reevaluation suggested possible lesions in the remaining 3 patients. The ROI-guided invasive implantation of EEG yielded interictal and ictal activity in 13 patients who were consequently referred to resective surgery. Despite the apparently negative MRI findings, focal cortical dysplasia was found in 64% of the patients (n = 9). At the last available outcome, 8 patients (57%) were completely seizure free (International League Against Epilepsy Class 1).CONCLUSIONSThe results demonstrate the feasibility and usefulness of a robust and straightforward algorithm for implementation of MRI postprocessing-based targets into the neuronavigation system. This approach allowed the stereotactic implantation of a low number of depth electrodes only, which confirmed the seizure-onset hypothesis in 90% of the cases without causing any complications. Furthermore, the neuronavigated ROI-guided lesionectomy helped to perform resective surgery in this rather challenging subgroup of patients with apparent nonlesional epilepsy.

Simultaneous Frame-assisted Stereotactic Placement of Subdural Grid Electrodes and Intracerebral Depth Electrodes

2019 ◽  
Vol 80 (05) ◽  
pp. 353-358 ◽  
Author(s):  
Peter C. Reinacher ◽  
Dirk-Matthias Altenmüller ◽  
Marie T. Krüger ◽  
Andreas Schulze-Bonhage ◽  
Horst Urbach ◽  
...  
Keyword(s):  
Focal Epilepsy ◽  
Epileptogenic Zone ◽  
Drug Resistant ◽  
Surgical Time ◽  
Depth Electrodes ◽  
Group A ◽  
The Mean ◽  
Group B ◽  
Intracranial Electrodes ◽  
Complex Cases

Background and Study Aims In complex cases of drug-resistant focal epilepsy, the precise localization of the epileptogenic zone requires simultaneous implantation of depth and subdural grid electrodes. This study describes a new simple frame-assisted method that facilitates the simultaneous placement of both types of intracranial electrodes. Material and Methods Ten consecutive patients were evaluated and divided into two groups. Group A included patients with simultaneous frame-assisted placement of depth and subdural grid electrodes. In group B, depth electrodes were implanted stereotactically; grid electrodes were implanted in a separate surgery. Results The placement of the subdural grid was accurate as individually designed by the epileptologists in all five patients from group A. In group B, one patient showed a slight and another one a significant deviation of the subdural grid position postoperatively. The mean surgical time in group A was shorter (280±62 minutes) compared with the mean duration of the surgical procedures in group B (336±51 minutes). Conclusion The frame-assisted placement of subdural grid electrodes facilitates the surgical procedure for invasive video-electroencephalography monitoring in complex cases of drug-resistant focal epilepsy in which a combination of depth electrodes and subdural grid electrodes is needed, by reducing the surgical time and guaranteeing highly accurate electrode localizations.

scholarly journals Future of Neurology & Technology: Stereo-electroencephalography in Presurgical Epilepsy Evaluation

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000013088
Author(s):  
Guillermo Delgado-Garcia ◽  
Birgit Frauscher
Keyword(s):  
North America ◽  
Temporal Dynamics ◽  
Focal Epilepsy ◽  
Three Dimensional ◽  
Epileptic Seizures ◽  
Epileptic Activity ◽  
Seizure Freedom ◽  
Epileptogenic Zone ◽  
Drug Resistant ◽  
Depth Electrodes

Stereo-electroencephalography (SEEG) is not only a sophisticated and highly technological investigation but a new and better way to conceptualize the spatial and temporal dynamics of epileptic activity. The first intracranial investigations with SEEG were carried out in France in the mid-twentieth century; however, its use in North America is much more recent. Given its significantly lower risk of complications and its ability to sample both superficial and deep structures as well as both hemispheres simultaneously, SEEG has become the preferred method to conduct intracranial EEG monitoring in most comprehensive epilepsy centers in North America. SEEG is an invasive neurophysiological methodology used for advanced pre-surgical work-up in the 20% of drug-resistant patients with more complex focal epilepsy in whom non-invasive investigations do not allow to decide on surgical candidacy. SEEG uses stereotactically-implanted depth electrodes to map the origin and propagation of epileptic seizures by creating a three-dimensional representation of the abnormal electrical activity in the brain. SEEG analysis takes into account the background, interictal, and ictal activity, as well as the results of cortical electrical stimulation procedures, to reliably delineate the epileptogenic network. By means of a clinical vignette, this article will walk general neurologists, but especially neurology trainees through the immense potential of this methodology. In summary, SEEG enables to accurately identify the epileptogenic zone in patients with drug-resistant focal epilepsy who otherwise would be not amenable to surgical treatment, the best way to improve seizure control and achieve seizure-freedom in this patient population.

scholarly journals Synaptic Reshaping and Neuronal Outcomes in the Temporal Lobe Epilepsy

2021 ◽  
Vol 22 (8) ◽  
pp. 3860
Author(s):  
Elisa Ren ◽  
Giulia Curia
Keyword(s):  
Animal Models ◽  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Current Knowledge ◽  
Focal Epilepsy ◽  
Ex Vivo ◽  
Hippocampal Sclerosis ◽  
Control Group ◽  
Epileptogenic Zone ◽  
Epileptiform Discharges

Temporal lobe epilepsy (TLE) is one of the most common types of focal epilepsy, characterized by recurrent spontaneous seizures originating in the temporal lobe(s), with mesial TLE (mTLE) as the worst form of TLE, often associated with hippocampal sclerosis. Abnormal epileptiform discharges are the result, among others, of altered cell-to-cell communication in both chemical and electrical transmissions. Current knowledge about the neurobiology of TLE in human patients emerges from pathological studies of biopsy specimens isolated from the epileptogenic zone or, in a few more recent investigations, from living subjects using positron emission tomography (PET). To overcome limitations related to the use of human tissue, animal models are of great help as they allow the selection of homogeneous samples still presenting a more various scenario of the epileptic syndrome, the presence of a comparable control group, and the availability of a greater amount of tissue for in vitro/ex vivo investigations. This review provides an overview of the structural and functional alterations of synaptic connections in the brain of TLE/mTLE patients and animal models.

scholarly journals NLOS Multipath Classification of GNSS Signal Correlation Output Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2503
Author(s):  
Taro Suzuki ◽  
Yoshiharu Amano
Keyword(s):  
Machine Learning ◽  
Satellite System ◽  
Training Data ◽  
Support Vector ◽  
Positioning Errors ◽  
Automated Method ◽  
Global Navigation Satellite ◽  
Better Than ◽  
Signal Correlation

This paper proposes a method for detecting non-line-of-sight (NLOS) multipath, which causes large positioning errors in a global navigation satellite system (GNSS). We use GNSS signal correlation output, which is the most primitive GNSS signal processing output, to detect NLOS multipath based on machine learning. The shape of the multi-correlator outputs is distorted due to the NLOS multipath. The features of the shape of the multi-correlator are used to discriminate the NLOS multipath. We implement two supervised learning methods, a support vector machine (SVM) and a neural network (NN), and compare their performance. In addition, we also propose an automated method of collecting training data for LOS and NLOS signals of machine learning. The evaluation of the proposed NLOS detection method in an urban environment confirmed that NN was better than SVM, and 97.7% of NLOS signals were correctly discriminated.

Continuous Intraoperative Neurophysiological Monitoring of the Motor Pathways Using Depth Electrodes During Surgical Resection of an Epileptogenic Lesion: A Novel Technique

2021 ◽  
Author(s):  
Denise F Chen ◽  
Jon T Willie ◽  
David Cabrera ◽  
Katie L Bullinger ◽  
Ioannis Karakis
Keyword(s):  
Motor Cortex ◽  
Surgical Resection ◽  
Radiation Necrosis ◽  
World Health ◽  
Intraoperative Neurophysiological Monitoring ◽  
Neurophysiological Monitoring ◽  
Epileptogenic Zone ◽  
Motor Pathways ◽  
Depth Electrodes ◽  
Epileptogenic Lesion

Abstract BACKGROUND AND IMPORTANCE Intraoperative neurophysiological monitoring of the motor pathways during epilepsy surgery is essential to safely achieve maximal resection of the epileptogenic zone. Motor evoked potential (MEP) recording is usually performed intermittently during resection using a handheld stimulator or continuously through an electrode array placed on the motor cortex. We present a novel variation of continuous MEP acquisition through previously implanted depth electrodes in the perirolandic cortex. CLINICAL PRESENTATION A 60-yr-old woman with a history of a left frontal meningioma (World Health Organization [WHO] grade II) treated with surgical resection and radiation presented with residual right hemiparesis and refractory epilepsy. Imaging demonstrated a perirolandic lesion with surrounding edema and mass effect in the prior surgical site, suspicious for radiation necrosis versus tumor recurrence. Presurgical electrocorticography (ECoG) with orthogonal, stereotactically implanted depth electrodes (stereoelectroencephalography [SEEG]) of the perirolandic cortex captured seizure onsets from the supplementary motor area (SMA) and primary motor cortex (PMC). The patient underwent a left frontal craniotomy for repeat resection and tissue diagnosis. Intraoperative ECoG and MEPs were obtained continuously with direct cortical stimulation through the indwelling SEEG electrodes in the PMC. Maximal resection was achieved with preservation of direct cortical MEPs and without deterioration of her baseline hemiparesis. Biopsy revealed radiation necrosis. At 30-mo follow-up, the patient had only rare seizures (Engel class IIB). CONCLUSION Intraoperative cortical MEP acquisition through implanted SEEG electrode arrays is a potentially safe and effective alternative approach to continuously monitor the motor pathways during the resection of a perirolandic epileptogenic lesion, without the need for surgical interruptions.

EEG Source Imaging (ESI) utility in clinical practice

2020 ◽  
Vol 65 (6) ◽  
pp. 673-682
Author(s):  
Pegah Khosropanah ◽  
Eric Tatt-Wei Ho ◽  
Kheng-Seang Lim ◽  
Si-Lei Fong ◽  
Minh-An Thuy Le ◽  
...  
Keyword(s):  
Focal Epilepsy ◽  
Cost Effective ◽  
Head Model ◽  
Computational Technique ◽  
Epileptogenic Zone ◽  
Clinical Tool ◽  
Source Imaging ◽  
Localization Accuracy ◽  
Eeg Source Imaging ◽  
Surgical Evaluation

AbstractEpilepsy surgery is an important treatment modality for medically refractory focal epilepsy. The outcome of surgery usually depends on the localization accuracy of the epileptogenic zone (EZ) during pre-surgical evaluation. Good localization can be achieved with various electrophysiological and neuroimaging approaches. However, each approach has its own merits and limitations. Electroencephalography (EEG) Source Imaging (ESI) is an emerging model-based computational technique to localize cortical sources of electrical activity within the brain volume, three-dimensionally. ESI based pre-surgical evaluation gives an overall clinical yield of 73–91%, depending on choice of head model, inverse solution and EEG electrode density. It is a cost effective, non-invasive method which provides valuable additional information in presurgical evaluation due to its high localizing value specifically in MRI-negative cases, extra or basal temporal lobe epilepsy, multifocal lesions such as tuberous sclerosis or cases with multiple hypotheses. Unfortunately, less than 1% of surgical centers in developing countries use this method as a part of pre-surgical evaluation. This review promotes ESI as a useful clinical tool especially for patients with lesion-negative MRI to determine EZ cost-effectively with high accuracy under the optimized conditions.

scholarly journals Analysis of gabor filter based features with PCA and GA for the detection of drusen in fundus images

2018 ◽  
Vol 7 (1) ◽  
pp. 115
Author(s):  
Sheela N. ◽  
Basavaraj L.
Keyword(s):  
Genetic Algorithm ◽  
Nearest Neighbor ◽  
Gabor Filter ◽  
Age Related Macular Degeneration ◽  
Misclassification Rate ◽  
Support Vector ◽  
K Nearest Neighbor ◽  
Automated Method ◽  
Age Related ◽  
Predictive Rate

Human eye can be affected by different types of diseases. Age-Related Macular Degeneration (AMD) is one of the such diseases, and it mainly occurs after 50 years of age. This disease is characterized by the occurrence of yellow spots called as Drusen. In this work, an automated method for the detection of drusen in Fundus image has been developed, and it has been tested on 70 images consisting of 30 normal images and 40 images with drusen. Performance of the Support Vector Machine (SVM) and K Nearest Neighbor (KNN) classifier has been evaluated using Data's reduction using Principle Component Analysis (PCA) and Data's selection using Genetic Algorithm (GA).Performance evaluation has been done in terms of accuracy, sensitivity, specificity, misclassification rate, positive predictive rate, negative predictive rate and Youden’s Index. The proposed method has achieved highest accuracy of 98.7% when data selection using Genetic Algorithm has been applied.

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