Comparison of computer-assisted planning and manual planning for depth electrode implantations in epilepsy

Optimising trajectory planning for stereotactic brain tumour biopsy using artificial intelligence: a systematic review of the literature

PURPOSE

Despite advances in technology, stereotactic brain tumour biopsy remains challenging due to the risk of injury to critical structures. Indeed, choosing the correct trajectory remains essential to patient safety. Artificial intelligence can be used to perform automated trajectory planning. We present a systematic review of automated trajectory planning algorithms for stereotactic brain tumour biopsies.

METHODS

A PRISMA adherent systematic review was conducted. Databases were searched using keyword combinations of 'artificial intelligence', 'trajectory planning' and 'brain tumours'. Studies reporting applications of artificial intelligence (AI) to trajectory planning for brain tumour biopsy were included.

RESULTS

All eight studies were in the earliest stage of the IDEAL-D development framework. Trajectory plans were compared through a variety of surrogate markers of safety, of which the minimum distance to blood vessels was the most common. Five studies compared manual to automated planning strategies and favoured automation in all cases. However, this comes with a significant risk of bias.

CONCLUSIONS

This systematic review reveals the need for IDEAL-D Stage 1 research into automated trajectory planning for brain tumour biopsy. Future studies should establish the congruence between expected risk of algorithms and the ground truth through comparisons to real world outcomes.

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.

Planning System for the Optimization of Electric Field Delivery using Implanted Electrodes for Brain Tumor Control

BACKGROUND

The use of non-ionizing electric fields from low intensity voltage sources (<10 V) to control malignant tumor growth is showing increasing potential as a cancer treatment modality. A method of applying these low intensity electric fields using multiple implanted electrodes within or adjacent to tumor volumes has been termed as intratumoral modulation therapy (IMT).

PURPOSE

This study explores advancements in the previously established IMT optimization algorithm, and the development of a custom treatment planning system for patient specific IMT. The practicality of the treatment planning system is demonstrated by implementing the full optimization pipeline on a brain phantom with robotic electrode implantation, post-operative imaging, and treatment stimulation.

METHODS

The integrated planning pipeline in 3D Slicer begins with importing and segmenting patient magnetic resonance images (MRI) or computed tomography (CT) images. The segmentation process is manual, followed by a semi-automatic smoothing step that allows the segmented brain and tumor mesh volumes to be smoothed and simplified by applying selected filters. Electrode trajectories are planned manually on the patient MRI or CT by selecting insertion and tip coordinates for a chosen number of electrodes. The electrode tip positions, and stimulation parameters (phase shift and voltage) can then be optimized with the custom semi-automatic IMT optimization algorithm where users can select the prescription electric field, voltage amplitude limit, tissue electrical properties, nearby organs at risk, optimization parameters (electrode tip location, individual contact phase shift and voltage), desired field coverage percent, and field conformity optimization. Tables of optimization results are displayed, and the resulting electric field is visualized as a field-map superimposed on the MR or CT image, with 3D renderings of the brain, tumor, and electrodes. Optimized electrode coordinates are transferred to robotic electrode implantation software to enable planning and subsequent implantation of the electrodes at the desired trajectories.

RESULTS

An IMT treatment planning system was developed that incorporates patient specific MRI or CT, segmentation, volume smoothing, electrode trajectory planning, electrode tip location and stimulation parameter optimization, and results visualization. All previous manual pipeline steps operating on diverse software platforms were coalesced into a single semi-automated 3D Slicer based user interface. Brain phantom validation of the full system implementation was successful in pre-operative planning, robotic electrode implantation, and post-operative treatment planning to adjust stimulation parameters based on actual implant locations. Voltage measurements were obtained in the brain phantom to determine the electrical parameters of the phantom and validate the simulated electric field distribution.

CONCLUSIONS

A custom treatment planning and implantation system for IMT has been developed in this study, and validated on a phantom brain model, providing an essential step in advancing IMT technology towards future clinical safety and efficacy investigations. This article is protected by copyright. All rights reserved.

Robot-Assisted Insular Depth Electrode Implantation Through Oblique Trajectories: 3-Dimensional Anatomical Nuances, Technique, Accuracy, and Safety

BACKGROUND

The insula is a deep cortical structure that has renewed interest in epilepsy investigation. Invasive EEG recordings of this region have been challenging. Robot-assisted stereotactic electroencephalography has improved feasibility and safety of such procedures.

OBJECTIVE

To describe technical nuances of three-dimensional (3D) oblique trajectories for insular robot-assisted depth electrode implantation.

METHODS

Fifty patients who underwent robot-assisted depth electrode implantation between June 2017 and December 2018 were retrospectively analyzed. Insular electrodes were implanted through oblique, orthogonal, or parasagittal trajectories. Type of trajectories, accuracy, number of contacts within insular cortex, imaging, and complication rates were analyzed. Cadaveric and computerized tomography/magnetic resonance imaging 3D reconstructions were used to visualize insular anatomy and the technical implications of oblique trajectories.

RESULTS

Forty-one patients (98 insular electrodes) were included. Thirty (73.2%) patients had unilateral insular coverage. Average insular electrodes per patient was 2.4. The mean number of contacts was 7.1 (SD ± 2.91) for all trajectories and 8.3 (SD ± 1.51) for oblique insular trajectories. The most frequently used was the oblique trajectory (85 electrodes). Mean entry point error was 1.5 mm (0.2-2.8) and target error was 2.4 mm (0.8-4.0), 2.0 mm (1.1-2.9) for anterior oblique and 2.8 mm (0.8-4.9) for posterior oblique trajectories. There were no complications related to insular electrodes.

CONCLUSION

Oblique trajectories are the preferred method for insular investigation at our institution, maximizing the number of contacts within insular cortex without traversing through sulci or major CSF fissures. Robot-assisted procedures are safe and efficient. 3D understanding of the insula's unique anatomical features can help the surgeon to improve targeting of this structure.

SYLVIUS: A multimodal and multidisciplinary platform for epilepsy surgery

BACKGROUND AND OBJECTIVE

We present SYLVIUS, a software platform intended to facilitate and improve the complex workflow required to diagnose and surgically treat drug-resistant epilepsies. In complex epilepsies, additional invasive information from exploration with stereoencephalography (SEEG) with deep electrodes may be needed, for which the input from different diagnostic methods and clinicians from several specialties is required to ensure diagnostic efficacy and surgical safety. We aim to provide a software platform with optimal data flow among the different stages of epilepsy surgery to provide smooth and integrated decision making.

METHODS

The SYLVIUS platform provides a clinical workflow designed to ensure seamless and safe patient data sharing across specialities. It integrates tools for stereo visualization, data registration, transfer of electrode plans referred to distinct datasets, automated postoperative contact segmentation, and novel DWI tractography analysis. Nineteen cases were retrospectively evaluated to track modifications from an initial plan to obtain a final surgical plan, using SYLVIUS.

RESULTS

The software was used to modify trajectories in all 19 consulted cases, which were then imported into the robotic system for the surgical intervention. When available, SYLVIUS provided extra multimodal information, which resulted in a greater number of trajectory modifications.

CONCLUSIONS

The architecture presented in this paper streamlines epilepsy surgery allowing clinicians to have a digital clinical tool that allows recording of the different stages of the procedure, in a common multimodal 2D/3D setting for participation of different clinicians in defining and validating surgical plans for SEEG cases.

[Stereoelectroencephalography (seeg): a brief historical review of modern deep electrode implantation methods used for diagnosis and treatment of epilepsy]

More than 30% of patients with symptomatic epilepsy are resistant to drug therapy and therefore surgical treatment is the method of choice for such patients. Search and localization of the epileptogenic zone and all parts of the neural networks involved in stereotypic seizures are the most important objectives of pre-surgical evaluation and the prerequisite for the successful surgery. In the last decade, stereotactic implantation of multiple intracerebral multi-contact electrodes (SEEG) has been increasingly used for this purpose. The article includes a brief history of SEEG and a description of the major techniques for stereotactic implantation of electrodes. Information on accuracy (errors and deviations from planned target) and on complications are summarized. The data on the clinical value of the method and how these data affected the results of subsequent treatment are highlighted. The method of thermocoagulation and its results are briefly considered.

Surgical planning assistance in keyhole and percutaneous surgery: A systematic review

Surgical planning of percutaneous interventions has a crucial role to guarantee the success of minimally invasive surgeries. In the last decades, many methods have been proposed to reduce clinician work load related to the planning phase and to augment the information used in the definition of the optimal trajectory. In this survey, we include 113 articles related to computer assisted planning (CAP) methods and validations obtained from a systematic search on three databases. First, a general formulation of the problem is presented, independently from the surgical field involved, and the key steps involved in the development of a CAP solution are detailed. Secondly, we categorized the articles based on the main surgical applications, which have been object of study and we categorize them based on the type of assistance provided to the end-user.

Refining Planning for Stereoelectroencephalography: A Prospective Validation of Spatial Priors for Computer-Assisted Planning With Application of Dynamic Learning

Objective: Stereoelectroencephalography (SEEG) is a procedure in which many electrodes are stereotactically implanted within different regions of the brain to estimate the epileptogenic zone in patients with drug-refractory focal epilepsy. Computer-assisted planning (CAP) improves risk scores, gray matter sampling, orthogonal drilling angles to the skull and intracerebral length in a fraction of the time required for manual planning. Due to differences in planning practices, such algorithms may not be generalizable between institutions. We provide a prospective validation of clinically feasible trajectories using “spatial priors” derived from previous implantations and implement a machine learning classifier to adapt to evolving planning practices.

Methods: Thirty-two patients underwent consecutive SEEG implantations utilizing computer-assisted planning over 2 years. Implanted electrodes from the first 12 patients (108 electrodes) were used as a training set from which entry and target point spatial priors were generated. CAP was then prospectively performed using the spatial priors in a further test set of 20 patients (210 electrodes). A K-nearest neighbor (K-NN) machine learning classifier was implemented as an adaptive learning method to modify the spatial priors dynamically.

Results: All of the 318 prospective computer-assisted planned electrodes were implanted without complication. Spatial priors developed from the training set generated clinically feasible trajectories in 79% of the test set. The remaining 21% required entry or target points outside of the spatial priors. The K-NN classifier was able to dynamically model real-time changes in the spatial priors in order to adapt to the evolving planning requirements.

Conclusions: We provide spatial priors for common SEEG trajectories that prospectively integrate clinically feasible trajectory planning practices from previous SEEG implantations. This allows institutional SEEG experience to be incorporated and used to guide future implantations. The deployment of a K-NN classifier may improve the generalisability of the algorithm by dynamically modifying the spatial priors in real-time as further implantations are performed.

Automated neurosurgical stereotactic planning for intraoperative use: a comprehensive review of the literature and perspectives

The creation of intracranial stereotactic trajectories, from entry point to target point, is still mostly done manually by the neurosurgeon. The development of automated stereotactic planning tools has been described in the literature. This systematic review aims to assess the effectiveness of stereotactic planning procedure automation and develop tools for patients undergoing neurosurgical stereotactic procedures. PubMed/MEDLINE, EMBASE, Google Scholar, CINAHL, PsycINFO, and Cochrane Register of Controlled Trials databases were searched from inception to September 1, 2019, at the exception of Google Scholar (from 1 January 2010 to September 1, 2019) in French and English. Eligible studies included all studies proposing automated stereotactic planning. A total of 1543 studies were screened. Forty-two studies were included in the systematic review, including 18 (42.9%) conference papers. The surgical procedures planned automatically were mainly deep brain stimulation (n = 14, 33.3%), stereoelectroencephalography (n = 12, 28.6%), and not specified (n = 10, 23.8%). The most frequently used surgical constraints to plan the trajectory were blood vessels (n = 32, 76.2%), cerebral sulci (n = 27, 64.3%), and cerebral ventricles (n = 23, 54.8%). The distance from blood vessels ranged from 1.96 to 4.78 mm for manual trajectories and from 2.47 to 7.0 mm for automated trajectories. At least one neurosurgeon was involved in 36 studies (85.7%). The automated stereotactic trajectory was preferred in 75.4% of the studied cases (range 30-92.9). Only 3 (7.1%) studies were multicentric. No study reported prospective use of the planning software. Stereotactic planning automation is a promising tool to provide valuable stereotactic trajectories for clinical applications.

Computer-Assisted Versus Manual Planning for Stereotactic Brain Biopsy: A Retrospective Comparative Pilot Study

BACKGROUND

Stereotactic brain biopsy is among the most common neurosurgical procedures. Planning an optimally safe surgical trajectory requires careful attention to a number of features including the following: (1) traversing the skull perpendicularly; (2) minimizing trajectory length; and (3) avoiding critical neurovascular structures.

OBJECTIVE

To evaluate a platform, SurgiNav, for automated trajectory planning in stereotactic brain biopsy.

METHODS

A prospectively maintained database was searched between February and August 2017 to identify all adult patients who underwent stereotactic brain biopsy and for whom postoperative imaging was available. In each case, the standard preoperative, T1-weighted, gadolinium-enhanced magnetic resonance imaging was used to generate a model of the cortex. A surgical trajectory was then generated using computer-assisted planning (CAP) , and metrics of the trajectory were compared to the trajectory of the previously implemented manual plan (MP).

RESULTS

Fifteen consecutive patients were identified. Feasible trajectories were generated using CAP in all patients, and the mean angle determined using CAP was more perpendicular to the skull than using MP (10.0° vs 14.6° from orthogonal; P = .07), the mean trajectory length was shorter (38.5 vs 43.5 mm; P = .01), and the risk score was lower (0.27 vs 0.52; P = .03).

CONCLUSION

CAP for stereotactic brain biopsy appears feasible and may be safer in selected cases.

Computer-Assisted Planning for Stereoelectroencephalography (SEEG)

Stereoelectroencephalography (SEEG) is a diagnostic procedure in which multiple electrodes are stereotactically implanted within predefined areas of the brain to identify the seizure onset zone, which needs to be removed to achieve remission of focal epilepsy. Computer-assisted planning (CAP) has been shown to improve trajectory safety metrics and generate clinically feasible trajectories in a fraction of the time needed for manual planning. We report a prospective validation study of the use of EpiNav (UCL, London, UK) as a clinical decision support software for SEEG. Thirteen consecutive patients (125 electrodes) undergoing SEEG were prospectively recruited. EpiNav was used to generate 3D models of critical structures (including vasculature) and other important regions of interest. Manual planning utilizing the same 3D models was performed in advance of CAP. CAP was subsequently employed to automatically generate a plan for each patient. The treating neurosurgeon was able to modify CAP generated plans based on their preference. The plan with the lowest risk score metric was stereotactically implanted. In all cases (13/13), the final CAP generated plan returned a lower mean risk score and was stereotactically implanted. No complication or adverse event occurred. CAP trajectories were generated in 30% of the time with significantly lower risk scores compared to manually generated. EpiNav has successfully been integrated as a clinical decision support software (CDSS) into the clinical pathway for SEEG implantations at our institution. To our knowledge, this is the first prospective study of a complex CDSS in stereotactic neurosurgery and provides the highest level of evidence to date.

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.

Stereoelectroencephalography in Pediatric Epilepsy Surgery

Stereoelectroencephalography (SEEG) is an invasive technique used during the surgical management of medically refractory epilepsy. The utility of SEEG rests in its ability to survey the three-dimensional organization of the epileptogenic zone as well as nearby eloquent cortices. Once concentrated to specialized centers in Europe and Canada, the SEEG methodology has gained worldwide popularity due to its favorable morbidity profile, superior coverage of deep structures, and ability to perform multilobar explorations without the need for craniotomy. This rapid shift in practice represents both a challenge and an opportunity for pediatric neurosurgeons familiar with the subdural grid approach. The purpose of this review is to discuss the indications, technique, and safety of long-term SEEG monitoring in children. In addition to reviewing the conceptual and technical points of the diagnostic evaluation, attention will also be given to SEEG-based interventions (e.g., radiofrequency thermo-coagulation).

Optimizing Trajectories for Cranial Laser Interstitial Thermal Therapy Using Computer-Assisted Planning: A Machine Learning Approach

Laser interstitial thermal therapy (LITT) is an alternative to open surgery for drug-resistant focal mesial temporal lobe epilepsy (MTLE). Studies suggest maximal ablation of the mesial hippocampal head and amygdalohippocampal complex (AHC) improves seizure freedom rates while better neuropsychological outcomes are associated with sparing of the parahippocampal gyrus (PHG). Optimal trajectories avoid sulci and CSF cavities and maximize distance from vasculature. Computer-assisted planning (CAP) improves these metrics, but the combination of entry and target zones has yet to be determined to maximize ablation of the AHC while sparing the PHG. We apply a machine learning approach to predict entry and target parameters and utilize these for CAP. Ten patients with hippocampal sclerosis were identified from a prospectively managed database. CAP LITT trajectories were generated using entry regions that include the inferior occipital, middle occipital, inferior temporal, and middle temporal gyri. Target points were varied by sequential AHC erosions and transformations of the centroid of the amygdala. A total of 7600 trajectories were generated, and ablation volumes of the AHC and PHG were calculated. Two machine learning approaches (random forest and linear regression) were investigated to predict composite ablation scores and determine entry and target point combinations that maximize ablation of the AHC while sparing the PHG. Random forest and linear regression predictions had a high correlation with the calculated values in the test set (ρ = 0.7) for both methods. Maximal composite ablation scores were associated with entry points around the junction of the inferior occipital, middle occipital, and middle temporal gyri. The optimal target point was the anteromesial amygdala. These parameters were then used with CAP to generate clinically feasible trajectories that optimize safety metrics. Machine learning techniques accurately predict composite ablation score. Prospective studies are required to determine if this improves seizure-free outcome while reducing neuropsychological morbidity following LITT for MTLE.

Stereoelectroencephalography Using Magnetic Resonance Angiography for Avascular Trajectory Planning: Technical Report

BACKGROUND

Stereoelectroencephalography (SEEG) requires high-quality angiographic studies because avascular trajectory planning is a prerequisite for the safety of this procedure. Some epilepsy surgery groups have begun to use computed tomography angiography and magnetic resonance T1-weighted sequence with contrast enhancement for this purpose.

OBJECTIVE

To present the first series of patients with avascular trajectory planning of SEEG based on magnetic resonance angiography (MRA).

METHODS

Thirty-six SEEG explorations for drug-resistant focal epilepsy were performed from January 2013 to December 2015. A retrospective analysis of this consecutive surgical series was then performed. Magnetic resonance imaging included MRA with a modified contrast-enhanced magnetic resonance venography (MRV) protocol with a short acquisition delay, which allowed simultaneous arterial and venous visualization. Our criteria for satisfactory MRA were the visualization of at least first-order branches of the angular artery, paracentral and calcarine artery, and third-order tributaries of the superficial Sylvian vein, vein of Labbe, and vein of Trolard.

RESULTS

Thirty-four patients underwent 36 SEEG explorations with 369 electrodes carrying 4321 contacts. Contrast-enhanced MRA using the MRV protocol was judged satisfactory for SEEG planning in all explorations. Postoperative complications were not observed in our series of 36 SEEG explorations, which included 50 transopercular insular trajectories.

CONCLUSION

MRA using an MRV protocol may be applied for avascular trajectory planning during SEEG procedures. This technique provides a simultaneous visualization of cortical arteries and veins without the need for additional radiation exposure or intra-arterial catheter placement.

Computer-assisted planning for the insertion of stereoelectroencephalography electrodes for the investigation of drug-resistant focal epilepsy: an external validation study

OBJECTIVE

One-third of cases of focal epilepsy are drug refractory, and surgery might provide a cure. Seizure-free outcome after surgery depends on the correct identification and resection of the epileptogenic zone. In patients with no visible abnormality on MRI, or in cases in which presurgical evaluation yields discordant data, invasive stereoelectroencephalography (SEEG) recordings might be necessary. SEEG is a procedure in which multiple electrodes are placed stereotactically in key targets within the brain to record interictal and ictal electrophysiological activity. Correlating this activity with seizure semiology enables identification of the seizure-onset zone and key structures within the ictal network. The main risk related to electrode placement is hemorrhage, which occurs in 1% of patients who undergo the procedure. Planning safe electrode placement for SEEG requires meticulous adherence to the following: 1) maximize the distance from cerebral vasculature, 2) avoid crossing sulcal pial boundaries (sulci), 3) maximize gray matter sampling, 4) minimize electrode length, 5) drill at an angle orthogonal to the skull, and 6) avoid critical neurological structures. The authors provide a validation of surgical strategizing and planning with EpiNav, a multimodal platform that enables automated computer-assisted planning (CAP) for electrode placement with user-defined regions of interest.

METHODS

Thirteen consecutive patients who underwent implantation of a total 116 electrodes over a 15-month period were studied retrospectively. Models of the cortex, gray matter, and sulci were generated from patient-specific whole-brain parcellation, and vascular segmentation was performed on the basis of preoperative MR venography. Then, the multidisciplinary implantation strategy and precise trajectory planning were reconstructed using CAP and compared with the implemented manually determined plans. Paired results for safety metric comparisons were available for 104 electrodes. External validity of the suitability and safety of electrode entry points, trajectories, and target-point feasibility was sought from 5 independent, blinded experts from outside institutions.

RESULTS

CAP-generated electrode trajectories resulted in a statistically significant improvement in electrode length, drilling angle, gray matter-sampling ratio, minimum distance from segmented vasculature, and risk (p < 0.05). The blinded external raters had various opinions of trajectory feasibility that were not statistically significant, and they considered a mean of 69.4% of manually determined trajectories and 62.2% of CAP-generated trajectories feasible; 19.4% of the CAP-generated electrode-placement plans were deemed feasible when the manually determined plans were not, whereas 26.5% of the manually determined electrode-placement plans were rated feasible when CAP-determined plans were not (no significant difference).

CONCLUSIONS

CAP generates clinically feasible electrode-placement plans and results in statistically improved safety metrics. CAP is a useful tool for automating the placement of electrodes for SEEG; however, it requires the operating surgeon to review the results before implantation, because only 62% of electrode-placement plans were rated feasible, compared with 69% of the manually determined placement plans, mainly because of proximity of the electrodes to unsegmented vasculature. Improved vascular segmentation and sulcal modeling could lead to further improvements in the feasibility of CAP-generated trajectories.

Automated trajectory planning for laser interstitial thermal therapy in mesial temporal lobe epilepsy

OBJECTIVE

Surgical resection of the mesial temporal structures brings seizure remission in 65% of individuals with drug-resistant mesial temporal lobe epilepsy (MTLE). Laser interstitial thermal therapy (LiTT) is a novel therapy that may provide a minimally invasive means of ablating the mesial temporal structures with similar outcomes, while minimizing damage to the neocortex. Systematic trajectory planning helps ensure safety and optimal seizure freedom through adequate ablation of the amygdalohippocampal complex (AHC). Previous studies have highlighted the relationship between the residual unablated mesial hippocampal head and failure to achieve seizure freedom. We aim to implement computer-assisted planning (CAP) to improve the ablation volume and safety of LiTT trajectories.

METHODS

Twenty-five patients who had previously undergone LiTT for MTLE were studied retrospectively. The EpiNav platform was used to automatically generate an optimal ablation trajectory, which was compared with the previous manually planned and implemented trajectory. Expected ablation volumes and safety profiles of each trajectory were modeled. The implemented laser trajectory and achieved ablation of mesial temporal lobe structures were quantified and correlated with seizure outcome.

RESULTS

CAP automatically generated feasible trajectories with reduced overall risk metrics (P < .001) and intracerebral length (P = .007). There was a significant correlation between the actual and retrospective CAP-anticipated ablation volumes, supporting a 15 mm diameter ablation zone model (P < .001). CAP trajectories would have provided significantly greater ablation of the amygdala (P = .0004) and AHC (P = .008), resulting in less residual unablated mesial hippocampal head (P = .001), and reduced ablation of the parahippocampal gyrus (P = .02).

SIGNIFICANCE

Compared to manually planned trajectories CAP provides a better safety profile, with potentially improved seizure-free outcome and reduced neuropsychological deficits, following LiTT for MTLE.

Improving patient safety during introduction of novel medical devices through cumulative summation analysis

OBJECTIVE The aim of this study was to implement cumulative summation (CUSUM) analysis as an early-warning detection and quality assurance system for preclinical testing of the iSYS1 novel robotic trajectory guidance system. METHODS Anatomically accurate 3D-printed skull phantoms were created for 3 patients who underwent implantation of 21 stereoelectroencephalography electrodes by surgeons using the current standard of care (frameless technique). Implantation schema were recreated using the iSYS1 system, and paired accuracy measures were compared with the previous frameless implantations. Entry point, target point, and implantation angle accuracy were measured on postimplantation CT scans. CUSUM analysis was undertaken prospectively. RESULTS The iSYS1 trajectory guidance system significantly improved electrode entry point accuracies from 1.90 ± 0.96 mm (mean ± SD) to 0.76 ± 0.57 mm (mean ± SD) without increasing implantation risk. CUSUM analysis was successful as a continuous measure of surgical performance and acted as an early-warning detection system. The surgical learning curve, although minimal, showed improvement after insertion of the eighth electrode. CONCLUSIONS The iSYS1 trajectory guidance system did not show any increased risk during phantom preclinical testing when used by neurosurgeons who had no experience with its use. CUSUM analysis is a simple technique that can be applied to all stages of the IDEAL (idea, development, exploration, assessment) framework as an extra patient safety mechanism. Further clinical trials are required to prove the efficacy of the device.

Stereoelectroencephalography: Indication and Efficacy

Stereoelectroencephalography (SEEG) is a method for invasive study of patients with refractory epilepsy. Localization of the epileptogenic zone in SEEG relied on the hypothesis of anatomo-electro-clinical analysis limited by X-ray, analog electroencephalography (EEG), and seizure semiology in the 1950s. Modern neuroimaging studies and digital video-EEG have developed the hypothesis aiming at more precise localization of the epileptic network. Certain clinical scenarios favor SEEG over subdural EEG (SDEEG). SEEG can cover extensive areas of bilateral hemispheres with highly accurate sampling from sulcal areas and deep brain structures. A hybrid technique of SEEG and subdural strip electrode placement has been reported to overcome the SEEG limitations of poor functional mapping. Technological advances including acquisition of three-dimensional angiography and magnetic resonance image (MRI) in frameless conditions, advanced multimodal planning, and robot-assisted implantation have contributed to the accuracy and safety of electrode implantation in a simplified fashion. A recent meta-analysis of the safety of SEEG concluded the low value of the pooled prevalence for all complications. The complications of SEEG were significantly less than those of SDEEG. The removal of electrodes for SEEG was much simpler than for SDEEG and allowed sufficient time for data analysis, discussion, and consensus for both patients and physicians before the proceeding treatment. Furthermore, SEEG is applicable as a therapeutic alternative for deep-seated lesions, e.g., nodular heterotopia, in nonoperative epilepsies using SEEG-guided radiofrequency thermocoagulation. We review the SEEG method with technological advances for planning and implantation of electrodes. We highlight the indication and efficacy, advantages and disadvantages of SEEG compared with SDEEG.

Accuracy of intracranial electrode placement for stereoencephalography: A systematic review and meta-analysis

OBJECTIVE

Stereoencephalography (SEEG) is a procedure in which electrodes are inserted into the brain to help define the epileptogenic zone. This is performed prior to definitive epilepsy surgery in patients with drug-resistant focal epilepsy when noninvasive data are inconclusive. The main risk of the procedure is hemorrhage, which occurs in 1-2% of patients. This may result from inaccurate electrode placement or a planned electrode damaging a blood vessel that was not detected on the preoperative vascular imaging. Proposed techniques include the use of a stereotactic frame, frameless image guidance systems, robotic guidance systems, and customized patient-specific fixtures.

METHODS

Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, a structured search of the PubMed, Embase, and Cochrane databases identified studies that involve the following: (1) SEEG placement as part of the presurgical workup in patients with (2) drug-resistant focal epilepsy for which (3) accuracy data have been provided.

RESULTS

Three hundred twenty-six publications were retrieved, of which 293 were screened following removal of duplicate and non-English-language studies. Following application of the inclusion and exclusion criteria, 15 studies were included in the qualitative and quantitative synthesis of the meta-analysis. Accuracies for SEEG electrode implantations have been combined using a random-effects analysis and stratified by technique.

SIGNIFICANCE

The published literature regarding accuracy of SEEG implantation techniques is limited. There are no prospective controlled clinical trials comparing different SEEG implantation techniques. Significant systematic heterogeneity exists between the identified studies, preventing any meaningful comparison between techniques. The recent introduction of robotic trajectory guidance systems has been suggested to provide a more accurate method of implantation, but supporting evidence is limited to class 3 only. It is important that new techniques are compared to the previous "gold-standard" through well-designed and methodologically sound studies before they are introduced into widespread clinical practice.

Invasive epilepsy surgery evaluation

Intracranial EEG (iEEG) recordings are widely used for the work up of pharmacoresistant epilepsy. Different iEEG recording techniques namely subdural grids, strips, depth electrodes and stereoencephalography (SEEG) are available with distinct limitations and advantages. Epilepsy centres mastering multiple techniques apply them in an individualised patient approach. These tools are used to map the seizure onset zone which is pivotal in approximating the epileptogenic zone, i.e. the zone which is indispensable for the generation of seizures and when resected will render the patient seizure free. Besides, the implanted electrodes can be used to define eloquent cortex through direct cortical stimulation. Different clinical scenarios exist which favour one iEEG recording technique over the other. Proximity of the presumed epileptogenic zone to eloquent cortex, for example, is a clinical scenario which may favour grid electrodes over SEEG. We here review the indication for iEEG for the work-up of patients suffering from pharmacoresistant epilepsy. In addition, we provide a description of the recording techniques focussing on the main techniques used: grid electrodes, depth electrodes and stereoencephalography. We then outline different clinical scenarios and the preferred technical approach for intracranial recordings in these scenarios. Finally, we highlight which advances have been made in the field of iEEG and which advances are in the pipeline waiting to be established for clinical use. This review provides the clinician with an update on the diagnostic use of intracranial EEG for epilepsy surgery and thus aids in understanding patient selection for this technique which may ultimately improve referral patterns.

Automated multiple trajectory planning algorithm for the placement of stereo-electroencephalography (SEEG) electrodes in epilepsy treatment

Purpose

About one-third of individuals with focal epilepsy continue to have seizures despite optimal medical management. These patients are potentially curable with neurosurgery if the epileptogenic zone (EZ) can be identified and resected. Stereo-electroencephalography (SEEG) to record epileptic activity with intracranial depth electrodes may be required to identify the EZ. Each SEEG electrode trajectory, the path between the entry on the skull and the cerebral target, must be planned carefully to avoid trauma to blood vessels and conflicts between electrodes. In current clinical practice trajectories are determined manually, typically taking 2–3 h per patient (15 min per electrode). Manual planning (MP) aims to achieve an implantation plan with good coverage of the putative EZ, an optimal spatial resolution, and 3D distribution of electrodes. Computer-assisted planning tools can reduce planning time by quantifying trajectory suitability.

Methods

We present an automated multiple trajectory planning (MTP) algorithm to compute implantation plans. MTP uses dynamic programming to determine a set of plans. From this set a depth-first search algorithm finds a suitable plan. We compared our MTP algorithm to (a) MP and (b) an automated single trajectory planning (STP) algorithm on 18 patient plans containing 165 electrodes.

Results

MTP changed all 165 trajectories compared to MP. Changes resulted in lower risk (122), increased grey matter sampling (99), shorter length (92), and surgically preferred entry angles (113). MTP changed 42 % (69/165) trajectories compared to STP. Every plan had between 1 to 8 (median 3.5) trajectories changed to resolve electrode conflicts, resulting in surgically preferred plans.

Conclusion

MTP is computationally efficient, determining implantation plans containing 7–12 electrodes within 1 min, compared to 2–3 h for MP.

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Epilepsy surgery is challenging and the use of 3D multimodality image integration (3DMMI) to aid presurgical planning is well-established. Multimodality image integration can be technically demanding, and is underutilised in clinical practice. We have developed a single software platform for image integration, 3D visualization and surgical planning. Here, our pipeline is described in step-by-step fashion, starting with image acquisition, proceeding through image co-registration, manual segmentation, brain and vessel extraction, 3D visualization and manual planning of stereoEEG (SEEG) implantations. With dissemination of the software this pipeline can be reproduced in other centres, allowing other groups to benefit from 3DMMI. We also describe the use of an automated, multi-trajectory planner to generate stereoEEG implantation plans. Preliminary studies suggest this is a rapid, safe and efficacious adjunct for planning SEEG implantations. Finally, a simple solution for the export of plans and models to commercial neuronavigation systems for implementation of plans in the operating theater is described. This software is a valuable tool that can support clinical decision making throughout the epilepsy surgery pathway.

Brain imaging in the assessment for epilepsy surgery

Brain imaging has a crucial role in the presurgical assessment of patients with epilepsy. Structural imaging reveals most cerebral lesions underlying focal epilepsy. Advances in MRI acquisitions including diffusion-weighted imaging, post-acquisition image processing techniques, and quantification of imaging data are increasing the accuracy of lesion detection. Functional MRI can be used to identify areas of the cortex that are essential for language, motor function, and memory, and tractography can reveal white matter tracts that are vital for these functions, thus reducing the risk of epilepsy surgery causing new morbidities. PET, SPECT, simultaneous EEG and functional MRI, and electrical and magnetic source imaging can be used to infer the localisation of epileptic foci and assist in the design of intracranial EEG recording strategies. Progress in semi-automated methods to register imaging data into a common space is enabling the creation of multimodal three-dimensional patient-specific datasets. These techniques show promise for the demonstration of the complex relations between normal and abnormal structural and functional data and could be used to direct precise intracranial navigation and surgery for individual patients.