Automatic segmentation of deep intracerebral electrodes in computed tomography scans

Background: Invasive monitoring of brain activity by means of intracerebral electrodes is widely practiced to improve pre-surgical seizure onset zone localization in patients with medically refractory seizures. Stereo-Electroencephalography (SEEG) is mainly used to localize the epileptogenic zone and a precise knowledge of the location of the electrodes is expected to facilitate the recordings interpretation and the planning of resective surgery. However, the localization of intracerebral electrodes on post-implant acquisitions is usually time-consuming (i.e., manual segmentation), it requires advanced 3D visualization tools, and it needs the supervision of trained medical doctors in order to minimize the errors. In this paper we propose an automated segmentation algorithm specifically designed to segment SEEG contacts from a thresholded post-implant Cone-Beam CT volume (0.4 mm, 0.4 mm, 0.8 mm). The algorithm relies on the planned position of target and entry points for each electrode as a first estimation of electrode axis. We implemented the proposed algorithm into DEETO, an open source C++ prototype based on ITK library. Results: We tested our implementation on a cohort of 28 subjects in total. The experimental analysis, carried out over a subset of 12 subjects (35 multilead electrodes; 200 contacts) manually segmented by experts, show that the algorithm: (i) is faster than manual segmentation (i.e., less than 1s/subject versus a few hours) (ii) is reliable, with an error of 0.5 mm +/- 0.06 mm, and (iii) it accurately maps SEEG implants to their anatomical regions improving the interpretability of electrophysiological traces for both clinical and research studies. Moreover, using the 28-subject cohort we show here that the algorithm is also robust (error <0.005 mm) against deep-brain displacements (<12 mm) of the implanted electrode shaft from those planned before surgery. Conclusions: Our method represents, to the best of our knowledge, the first automatic algorithm for the segmentation of SEEG electrodes. The method can be used to accurately identify the neuroanatomical loci of SEEG electrode contacts by a non-expert in a fast and reliable manner.Peer reviewe

The Effect of Vascular Segmentation Methods on Stereotactic Trajectory Planning for Drug-Resistant Focal Epilepsy: A Retrospective Cohort Study

Background: Stereotactic neurosurgical procedures carry a risk of intracranial hemorrhage, which may result in significant morbidity and mortality. Vascular imaging is crucial for planning stereotactic procedures to prevent conflicts with intracranial vasculature. There is a wide range of vascular imaging methods used for stereoelectroencephalography (SEEG) trajectory planning. Computer-assisted planning (CAP) improves planning time and trajectory metrics. We aimed to quantify the effect of different vascular imaging protocols on CAP trajectories for SEEG. Methods: Ten patients who had undergone SEEG (95 electrodes) following preoperative acquisition of gadolinium-enhanced magnetic resonance imaging (MR + Gad), magnetic resonance angiography and magnetic resonance angiography (MRV + MRA), and digital subtraction catheter angiography (DSA) were identified from a prospectively maintained database. SEEG implantations were planned using CAP using DSA segmentations as the gold standard. Strategies were then recreated using MRV + MRA and MR + Gad to define the “apparent” and “true” risk scores associated with each modality. Vessels of varying diameter were then iteratively removed from the DSA segmentation to identify the size at which all 3 vascular modalities returned the same safety metrics. Results: CAP performed using DSA vessel segmentations resulted in significantly lower “true” risk scores and greater minimum distances from vasculature compared with the “true” risk associated with MR + Gad and MRV + MRA. MRV + MRA and MR + Gad returned similar risk scores to DSA when vessels <2 mm and <4 mm were not considered, respectively. Conclusions: Significant variability in vascular imaging and trajectory planning practices exist for SEEG. CAP performed with MR + Gad or MRV + MRA alone returns “falsely” lower risk scores compared with DSA. It is unclear whether DSA is oversensitive and thus restricting potential trajectories

Retrospective evaluation and SEEG trajectory analysis for interactive multi-trajectory planner assistant

Purpose: Focal epilepsy is a neurological disease that can be surgically treated by removing area of the brain generating the seizures. The stereotactic electroencephalography (SEEG) procedure allows patient brain activity to be recorded in order to localize the onset of seizures through the placement of intracranial electrodes. The planning phase can be cumbersome and very time consuming, and no quantitative information is provided to neurosurgeons regarding the safety and efficacy of their trajectories. In this work, we present a novel architecture specifically designed to ease the SEEG trajectory planning using the 3D Slicer platform as a basis. Methods: Trajectories are automatically optimized following criteria like vessel distance and insertion angle. Multi-trajectory optimization and conflict resolution are optimized through a selective brute force approach based on a conflict graph construction. Additionally, electrode-specific optimization constraints can be defined, and an advanced verification module allows neurosurgeons to evaluate the feasibility of the trajectory. Results: A retrospective evaluation was performed using manually planned trajectories on 20 patients: the planning algorithm optimized and improved trajectories in 98% of cases. We were able to resolve and optimize the remaining 2% by applying electrode-specific constraints based on manual planning values. In addition, we found that the global parameters used discards 68% of the manual planned trajectories, even when they represent a safe clinical choice. Conclusions: Our approach improved manual planned trajectories in 98% of cases in terms of quantitative indexes, even when applying more conservative criteria with respect to actual clinical practice. The improved multi-trajectory strategy overcomes the previous work limitations and allows electrode optimization within a tolerable time span

Previous, current, and future stereotactic EEG techniques for localising epileptic foci

INTRODUCTION: Drug-resistant focal epilepsy presents a significant morbidity burden globally, and epilepsy surgery has been shown to be an effective treatment modality. Therefore, accurate identification of the epileptogenic zone for surgery is crucial, and in those with unclear noninvasive data, stereoencephalography is required. AREAS COVERED: This review covers the history and current practices in the field of intracranial EEG, particularly analyzing how stereotactic image-guidance, robot-assisted navigation, and improved imaging techniques have increased the accuracy, scope, and use of SEEG globally. EXPERT OPINION: We provide a perspective on the future directions in the field, reviewing improvements in predicting electrode bending, image acquisition, machine learning and artificial intelligence, advances in surgical planning and visualization software and hardware. We also see the development of EEG analysis tools based on machine learning algorithms that are likely to work synergistically with neurophysiology experts and improve the efficiency of EEG and SEEG analysis and 3D visualization. Improving computer-assisted planning to minimize manual input from the surgeon, and seamless integration into an ergonomic and adaptive operating theater, incorporating hybrid microscopes, virtual and augmented reality is likely to be a significant area of improvement in the near future

IntrAnat Electrodes: A Free Database and Visualization Software for Intracranial Electroencephalographic Data Processed for Case and Group Studies

In some cases of pharmaco-resistant and focal epilepsies, intracranial recordings performed epidurally (electrocorticography, ECoG) and/or in depth (stereoelectroencephalography, SEEG) can be required to locate the seizure onset zone and the eloquent cortex before surgical resection. In SEEG, each electrode contact records brain’s electrical activity in a spherical volume of 3 mm diameter approximately. The spatial coverage is around 1% of the brain and differs between patients because the implantation of electrodes is tailored for each case. Group studies thus need a large number of patients to reach a large spatial sampling, which can be achieved more easily using a multicentric approach such as implemented in our F-TRACT project (f-tract.eu). To facilitate group studies, we developed a software—IntrAnat Electrodes—that allows to perform virtual electrode implantation in patients’ neuroanatomy and to overlay results of epileptic and functional mapping, as well as resection masks from the surgery. IntrAnat Electrodes is based on a patient database providing multiple search criteria to highlight various group features. For each patient, the anatomical processing is based on a series of software publicly available. Imaging modalities (Positron Emission Tomography (PET), anatomical MRI pre-implantation, post-implantation and post-resection, functional MRI, diffusion MRI, Computed Tomography (CT) with electrodes) are coregistered. The 3D T1 pre-implantation MRI gray/white matter is segmented and spatially normalized to obtain a series of cortical parcels using different neuroanatomical atlases. On post-implantation images, the user can position 3D models of electrodes defined by their geometry. Each electrode contact is then labeled according to its position in the anatomical atlases, to the class of tissue (gray or white matter, cerebro-spinal fluid) and to its presence inside or outside the resection mask. Users can add more functionally informed labels on contact, such as clinical responses after electrical stimulation, cortico-cortical evoked potentials, gamma band activity during cognitive tasks or epileptogenicity. IntrAnat Electrodes software thus provides a means to visualize multimodal data. The contact labels allow to search for patients in the database according to multiple criteria representing almost all available data, which is to our knowledge unique in current SEEG software. IntrAnat Electrodes will be available in the forthcoming release of BrainVisa software and tutorials can be found on the F-TRACT webpage

Electroencephalographic source imaging: a prospective study of 152 operated epileptic patients

Electroencephalography is mandatory to determine the epilepsy syndrome. However, for the precise localization of the irritative zone in patients with focal epilepsy, costly and sometimes cumbersome imaging techniques are used. Recent small studies using electric source imaging suggest that electroencephalography itself could be used to localize the focus. However, a large prospective validation study is missing. This study presents a cohort of 152 operated patients where electric source imaging was applied as part of the pre-surgical work-up allowing a comparison with the results from other methods. Patients (n = 152) with >1 year postoperative follow-up were studied prospectively. The sensitivity and specificity of each imaging method was defined by comparing the localization of the source maximum with the resected zone and surgical outcome. Electric source imaging had a sensitivity of 84% and a specificity of 88% if the electroencephalogram was recorded with a large number of electrodes (128-256 channels) and the individual magnetic resonance image was used as head model. These values compared favourably with those of structural magnetic resonance imaging (76% sensitivity, 53% specificity), positron emission tomography (69% sensitivity, 44% specificity) and ictal/interictal single-photon emission-computed tomography (58% sensitivity, 47% specificity). The sensitivity and specificity of electric source imaging decreased to 57% and 59%, respectively, with low number of electrodes (<32 channels) and a template head model. This study demonstrated the validity and clinical utility of electric source imaging in a large prospective study. Given the low cost and high flexibility of electroencephalographic systems even with high channel counts, we conclude that electric source imaging is a highly valuable tool in pre-surgical epilepsy evaluatio

Electroencephalographic source imaging: a prospective study of 152 operated epileptic patients

Electroencephalography is mandatory to determine the epilepsy syndrome. However, for the precise localization of the irritative zone in patients with focal epilepsy, costly and sometimes cumbersome imaging techniques are used. Recent small studies using electric source imaging suggest that electroencephalography itself could be used to localize the focus. However, a large prospective validation study is missing. This study presents a cohort of 152 operated patients where electric source imaging was applied as part of the pre-surgical work-up allowing a comparison with the results from other methods. Patients (n = 152) with >1 year postoperative follow-up were studied prospectively. The sensitivity and specificity of each imaging method was defined by comparing the localization of the source maximum with the resected zone and surgical outcome. Electric source imaging had a sensitivity of 84% and a specificity of 88% if the electroencephalogram was recorded with a large number of electrodes (128–256 channels) and the individual magnetic resonance image was used as head model. These values compared favourably with those of structural magnetic resonance imaging (76% sensitivity, 53% specificity), positron emission tomography (69% sensitivity, 44% specificity) and ictal/interictal single-photon emission-computed tomography (58% sensitivity, 47% specificity). The sensitivity and specificity of electric source imaging decreased to 57% and 59%, respectively, with low number of electrodes (<32 channels) and a template head model. This study demonstrated the validity and clinical utility of electric source imaging in a large prospective study. Given the low cost and high flexibility of electroencephalographic systems even with high channel counts, we conclude that electric source imaging is a highly valuable tool in pre-surgical epilepsy evaluation