A topographical analysis of encephalocele locations: generation of a standardised atlas and cluster analysis.

OBJECTIVE: Encephaloceles are considered to result from defects in the developing skull through which meninges, and potentially brain tissue, herniate. The pathological mechanism underlying this process is incompletely understood. We aimed to describe the location of encephaloceles through the generation of a group atlas to determine whether they occur at random sites or clusters within distinct anatomical regions. METHODS: Patients diagnosed with cranial encephaloceles or meningoceles were identified from a prospectively maintained database between 1984 and 2021. Images were transformed to atlas space using non-linear registration. The bone defect, encephalocele and herniated brain contents were manually segmented allowing for a 3-dimensional heat map of encephalocele locations to be generated. The centroids of the bone defects were clustered utilising a K-mean clustering machine learning algorithm in which the elbow method was used to identify the optimal number of clusters. RESULTS: Of the 124 patients identified, 55 had volumetric imaging in the form of MRI (48/55) or CT (7/55) that could be used for atlas generation. Median encephalocele volume was 14,704 (IQR 3655-86,746) mm3 and the median surface area of the skull defect was 679 (IQR 374-765) mm2. Brain herniation into the encephalocele was found in 45% (25/55) with a median volume of 7433 (IQR 3123-14,237) mm3. Application of the elbow method revealed 3 discrete clusters: (1) anterior skull base (22%; 12/55), (2) parieto-occipital junction (45%; 25/55) and (3) peri-torcular (33%; 18/55). Cluster analysis revealed no correlation between the location of the encephalocele with gender (χ2 (2, n = 91) = 3.86, p = 0.15). Compared to expected population frequencies, encephaloceles were relatively more common in Black, Asian and Other compared to White ethnicities. A falcine sinus was identified in 51% (28/55) of cases. Falcine sinuses were more common (χ2 (2, n = 55) = 6.09, p = 0.05) whilst brain herniation was less common (χ2 (2, n = 55) = .16.24, p < 0.0003) in the parieto-occipital location. CONCLUSION: This analysis revealed three predominant clusters for the location of encephaloceles, with the parieto-occipital junction being the most common. The stereotypic location of encephaloceles into anatomically distinct clusters and the coexistence of distinct venous malformations at certain sites suggests that their location is not random and raises the possibility of distinct pathogenic mechanisms unique to each of these regions.

Multimodal prognostic features of seizure freedom in epilepsy surgery.

OBJECTIVE: Accurate preoperative predictions of seizure freedom following surgery for focal drug resistant epilepsy remain elusive. Our objective was to systematically evaluate all meta-analyses of epilepsy surgery with seizure freedom as the primary outcome, to identify clinical features that are consistently prognostic and should be included in the future models. METHODS: We searched PubMed and Cochrane using free-text and Medical Subject Heading (MeSH) terms according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses. This study was registered on PROSPERO. We classified features as prognostic, non-prognostic and uncertain and into seven subcategories: 'clinical', 'imaging', 'neurophysiology', 'multimodal concordance', 'genetic', 'surgical technique' and 'pathology'. We propose a structural causal model based on these features. RESULTS: We found 46 features from 38 meta-analyses over 22 years. The following were consistently prognostic across meta-analyses: febrile convulsions, hippocampal sclerosis, focal abnormal MRI, Single-Photon Emission Computed Tomography (SPECT) coregistered to MRI, focal ictal/interictal EEG, EEG-MRI concordance, temporal lobe resections, complete excision, histopathological lesions, tumours and focal cortical dysplasia type IIb. Severe learning disability was predictive of poor prognosis. Others, including sex and side of resection, were non-prognostic. There were limited meta-analyses investigating genetic contributions, structural connectivity or multimodal concordance and few adjusted for known confounders or performed corrections for multiple comparisons. SIGNIFICANCE: Seizure-free outcomes have not improved over decades of epilepsy surgery and despite a multitude of models, none prognosticate accurately. Our list of multimodal population-invariant prognostic features and proposed structural causal model may serve as an objective foundation for statistical adjustments of plausible confounders for use in high-dimensional models. PROSPERO REGISTRATION NUMBER: CRD42021185232.

Intraoperative overlay of optic radiation tractography during anteromesial temporal resection: a prospective validation study.

OBJECTIVE: Anteromesial temporal lobe resection (ATLR) results in long-term seizure freedom in patients with drug-resistant focal mesial temporal lobe epilepsy (MTLE). There is significant anatomical variation in the anterior projection of the optic radiation (OR), known as Meyer's loop, between individuals and between hemispheres in the same individual. Damage to the OR results in contralateral superior temporal quadrantanopia that may preclude driving in 33%-66% of patients who achieve seizure freedom. Tractography of the OR has been shown to prevent visual field deficit (VFD) when surgery is performed in an interventional MRI (iMRI) suite. Because access to iMRI is limited at most centers, the authors investigated whether use of a neuronavigation system with a microscope overlay in a conventional theater is sufficient to prevent significant VFD during ATLR. METHODS: Twenty patients with drug-resistant MTLE who underwent ATLR (9 underwent right-side ATLR, and 9 were male) were recruited to participate in this single-center prospective cohort study. Tractography of the OR was performed with preoperative 3-T multishell diffusion data that were overlaid onto the surgical field by using a conventional neuronavigation system linked to a surgical microscope. Phantom testing confirmed overlay projection errors of < 1 mm. VFD was quantified preoperatively and 3 to 12 months postoperatively by using Humphrey and Esterman perimetry. RESULTS: Perimetry results were available for all patients postoperatively, but for only 11/20 (55%) patients preoperatively. In 1/20 (5%) patients, a significant VFD occurred that would prevent driving in the UK on the basis of the results on Esterman perimetry. The VFD was identified early in the series, despite the surgical approach not transgressing OR tractography, and was subsequently found to be due to retraction injury. Tractography was also used from this point onward to inform retractor placement, and no further significant VFDs occurred. CONCLUSIONS: Use of OR tractography with overlay outside of an iMRI suite, with application of an appropriate error margin, can be used during approach to the temporal horn of the lateral ventricle and carries a 5% risk of VFD that is significant enough to preclude driving postoperatively. OR tractography can also be used to inform retractor placement. These results warrant a larger prospective comparative study of the use of OR tractography-guided mesial temporal resection.

Brain Lesion Synthesis via Progressive Adversarial Variational Auto-Encoder.

Laser interstitial thermal therapy (LITT) is a novel minimally invasive treatment that is used to ablate intracranial structures to treat mesial temporal lobe epilepsy (MTLE). Region of interest (ROI) segmentation before and after LITT would enable automated lesion quantification to objectively assess treatment efficacy. Deep learning techniques, such as convolutional neural networks (CNNs) are state-of-the-art solutions for ROI segmentation, but require large amounts of annotated data during the training. However, collecting large datasets from emerging treatments such as LITT is impractical. In this paper, we propose a progressive brain lesion synthesis framework (PAVAE) to expand both the quantity and diversity of the training dataset. Concretely, our framework consists of two sequential networks: a mask synthesis network and a mask-guided lesion synthesis network. To better employ extrinsic information to provide additional supervision during network training, we design a condition embedding block (CEB) and a mask embedding block (MEB) to encode inherent conditions of masks to the feature space. Finally, a segmentation network is trained using raw and synthetic lesion images to evaluate the effectiveness of the proposed framework. Experimental results show that our method can achieve realistic synthetic results and boost the performance of down-stream segmentation tasks above traditional data augmentation techniques.

Resective, Ablative and Radiosurgical Interventions for Drug Resistant Mesial Temporal Lobe Epilepsy: A Systematic Review and Meta-Analysis of Outcomes.

Objectives: One-third of individuals with focal epilepsy do not achieve seizure freedom despite best medical therapy. Mesial temporal lobe epilepsy (MTLE) is the most common form of drug resistant focal epilepsy. Surgery may lead to long-term seizure remission if the epileptogenic zone can be defined and safely removed or disconnected. We compare published outcomes following open surgical techniques, radiosurgery (SRS), laser interstitial thermal therapy (LITT) and radiofrequency ablation (RF-TC). Methods: PRISMA systematic review was performed through structured searches of PubMed, Embase and Cochrane databases. Inclusion criteria encompassed studies of MTLE reporting seizure-free outcomes in ≥10 patients with ≥12 months follow-up. Due to variability in open surgical approaches, only comparative studies were included to minimize the risk of bias. Random effects meta-analysis was performed to calculate effects sizes and a pooled estimate of the probability of seizure freedom per person-year. A mixed effects linear regression model was performed to compare effect sizes between interventions. Results: From 1,801 screened articles, 41 articles were included in the quantitative analysis. Open surgery included anterior temporal lobe resection as well as transcortical and trans-sylvian selective amygdalohippocampectomy. The pooled seizure-free rate per person-year was 0.72 (95% CI 0.66-0.79) with trans-sylvian selective amygdalohippocampectomy, 0.59 (95% CI 0.53-0.65) with LITT, 0.70 (95% CI 0.64-0.77) with anterior temporal lobe resection, 0.60 (95% CI 0.49-0.73) with transcortical selective amygdalohippocampectomy, 0.38 (95% CI 0.14-1.00) with RF-TC and 0.50 (95% CI 0.34-0.73) with SRS. Follow up duration and study sizes were limited with LITT and RF-TC. A mixed-effects linear regression model suggests significant differences between interventions, with LITT, ATLR and SAH demonstrating the largest effects estimates and RF-TC the lowest. Conclusions: Overall, novel "minimally invasive" approaches are still comparatively less efficacious than open surgery. LITT shows promising seizure effectiveness, however follow-up durations are shorter for minimally invasive approaches so the durability of the outcomes cannot yet be assessed. Secondary outcome measures such as Neurological complications, neuropsychological outcome and interventional morbidity are poorly reported but are important considerations when deciding on first-line treatments.

Clinical applications of magnetic resonance imaging based functional and structural connectivity.

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Comparison of robotic and manual implantation of intracerebral electrodes: a single-centre, single-blinded, randomised controlled trial.

There has been a significant rise in robotic trajectory guidance devices that have been utilised for stereotactic neurosurgical procedures. These devices have significant costs and associated learning curves. Previous studies reporting devices usage have not undertaken prospective parallel-group comparisons before their introduction, so the comparative differences are unknown. We study the difference in stereoelectroencephalography electrode implantation time between a robotic trajectory guidance device (iSYS1) and manual frameless implantation (PAD) in patients with drug-refractory focal epilepsy through a single-blinded randomised control parallel-group investigation of SEEG electrode implantation, concordant with CONSORT statement. Thirty-two patients (18 male) completed the trial. The iSYS1 returned significantly shorter median operative time for intracranial bolt insertion, 6.36 min (95% CI 5.72-7.07) versus 9.06 min (95% CI 8.16-10.06), p = 0.0001. The PAD group had a better median target point accuracy 1.58 mm (95% CI 1.38-1.82) versus 1.16 mm (95% CI 1.01-1.33), p = 0.004. The mean electrode implantation angle error was 2.13° for the iSYS1 group and 1.71° for the PAD groups (p = 0.023). There was no statistically significant difference for any other outcome. Health policy and hospital commissioners should consider these differences in the context of the opportunity cost of introducing robotic devices.Trial registration: ISRCTN17209025 ( https://doi.org/10.1186/ISRCTN17209025 ).

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

Resection of the piriform cortex for temporal lobe epilepsy: a Novel approach on imaging segmentation and surgical application.

BACKGROUND: The piriform cortex (PC) occupies both banks of the endorhinal sulcus and has an important role in the pathophysiology of temporal lobe epilepsy (TLE). A recent study showed that resection of more than 50% of PC increased the odds of becoming seizure free by a factor of 16. OBJECTIVE: We report the feasibility of manual segmentation of PC and application of the Geodesic Information Flows (GIF) algorithm to automated segmentation, to guide resection. METHODS: Manual segmentation of PC was performed by two blinded independent examiners in 60 patients with TLE (55% Left TLE, 52% female) with a median age of 35 years (IQR, 29-47 years) and 20 controls (60% Women) with a median age of 39.5 years (IQR, 31-49). The GIF algorithm was used to create an automated pipeline for parcellating PC which was used to guide excision as part of temporal lobe resection for TLE. RESULTS: Right PC was larger in patients and controls. Parcellation of PC was used to guide anterior temporal lobe resection, with subsequent seizure freedom and no visual field or language deficit. CONCLUSION: Reliable segmentation of PC is feasible and can be applied prospectively to guide neurosurgical resection that increases the chances of a good outcome from temporal lobe resection for TLE.

Enhancing the estimation of fiber orientation distributions using convolutional neural networks.

Local fiber orientation distributions (FODs) can be computed from diffusion magnetic resonance imaging (dMRI). The accuracy and ability of FODs to resolve complex fiber configurations benefits from acquisition protocols that sample a high number of gradient directions, a high maximum b-value, and multiple b-values. However, acquisition time and scanners that follow these standards are limited in clinical settings, often resulting in dMRI acquired at a single shell (single b-value). In this work, we learn improved FODs from clinically acquired dMRI. We evaluate patch-based 3D convolutional neural networks (CNNs) on their ability to regress multi-shell FODs from single-shell FODs, using constrained spherical deconvolution (CSD). We evaluate U-Net and High-Resolution Network (HighResNet) 3D CNN architectures on data from the Human Connectome Project and an in-house dataset. We evaluate how well each CNN can resolve FODs 1) when training and testing on datasets with the same dMRI acquisition protocol; 2) when testing on a dataset with a different dMRI acquisition protocol than used to train the CNN; and 3) when testing on a dataset with a fewer number of gradient directions than used to train the CNN. This work is a step towards more accurate FOD estimation in time- and resource-limited clinical environments.

Occipitocervical instrumented fixation utilising patient-specific C2 3D-printed spinal screw trajectory guides in complex paediatric skeletal dysplasia.

PURPOSE: Instability of the craniocervical junction in paediatric patients with skeletal dysplasia poses a unique set of challenges including anatomical abnormalities, poor bone quality, skeletal immaturity and associated general anaesthetic risks. Instrumented fixation provides optimal stabilisation and fusion rates. The small vertebrae make the placement of C2 pedicle screws technically demanding with low margins of error between the spinal canal and the vertebral artery. METHODS: We describe a novel clinical strategy utilising 3D-printed spinal screw trajectory guides (3D-SSTG) for individually planned C2 pedicle and laminar screws. The technique is based on a pre-operative CT scan and does not require intraoperative CT imaging. This reduces the radiation burden to the patient and forgoes the associated time and cost. The time for model generation and sterilisation was < 24 h. RESULTS: We describe two patients (3 and 6 years old) requiring occipitocervical instrumented fixation for cervical myelopathy secondary to Morquio syndrome with 3D-SSTGs. In the second case, bilateral laminar screw trajectories were also incorporated into the same guide due to the presence of high-riding vertebral arteries. Registration of the postoperative CT to the pre-operative imaging revealed that screws were optimally placed and accurately followed the predefined trajectory. CONCLUSION: To our knowledge, we present the first clinical report of 3D-printed spinal screw trajectory guides at the craniocervical junction in paediatric patients with skeletal dysplasia. The novel combination of multiple trajectories within the same guide provides the intraoperative flexibility of potential bailout options. Future studies will better define the potential of this technology to optimise personalised non-standard screw trajectories.

Patient-specific prediction of SEEG electrode bending for stereotactic neurosurgical planning.

PURPOSE : Electrode bending observed after stereotactic interventions is typically not accounted for in either computer-assisted planning algorithms, where straight trajectories are assumed, or in quality assessment, where only metrics related to entry and target points are reported. Our aim is to provide a fully automated and validated pipeline for the prediction of stereo-electroencephalography (SEEG) electrode bending. METHODS : We transform electrodes of 86 cases into a common space and compare features-based and image-based neural networks on their ability to regress local displacement ([Formula: see text]) or electrode bending ([Formula: see text]). Electrodes were stratified into six groups based on brain structures at the entry and target point. Models, both with and without Monte Carlo (MC) dropout, were trained and validated using tenfold cross-validation. RESULTS : mage-based models outperformed features-based models for all groups, and models that predicted [Formula: see text] performed better than for [Formula: see text]. Image-based model prediction with MC dropout resulted in lower mean squared error (MSE) with improvements up to 12.9% ([Formula: see text]) and 39.9% ([Formula: see text]), compared to no dropout. Using an image of brain tissue types (cortex, white and deep grey matter) resulted in similar, and sometimes better performance, compared to using a T1-weighted MRI when predicting [Formula: see text]. When inferring trajectories of image-based models (brain tissue types), 86.9% of trajectories had an MSE[Formula: see text] mm. CONCLUSION : An image-based approach regressing local displacement with an image of brain tissue types resulted in more accurate electrode bending predictions compared to other approaches, inputs, and outputs. Future work will investigate the integration of electrode bending into planning and quality assessment algorithms.

Visual field defects in temporal lobe epilepsy surgery.

PURPOSE OF REVIEW: Surgery can provide a robust long-standing seizure remission in drug-refractory mesial temporal lobe epilepsy (MTLE). Despite this, a significant proportion of postoperative patients are ineligible to gain a driving licence due to the size of the subsequent visual field defect (VFD). The amygdala and hippocampus are intimately related to several important white fibre association tracts and damage to the optic radiation results in a contralateral superior quadrantanopia. For this reason, several different modifications to established surgical approaches and novel techniques have recently been applied to mitigate or prevent damage to the optic radiation. There is still no consensus on which operative technique results in optimal outcomes regarding seizure remission, neuropsychological sequelae and VFD rates. We explore contemporary surgical approaches to the mesial temporal lobe and describe the intraoperative use of tractography and iMRI in preventing VFDs. RECENT FINDINGS: Established approaches for the surgical treatment of MTLE include standardized approaches in the form of anterior temporal lobectomies, selective approaches and various modifications thereof. Recent advancements in microsurgical techniques have seen numerous modifications to these approaches to spare the optic radiation as well as the introduction of minimally invasive alternatives such as laser interstitial thermal therapy (LITT) and stereotactic radiosurgery (SRS). The intraoperative use of optic radiation tractography through overlays in the operative microscope and interventional MRI suites to correct for brain shift have been shown to reduce VFDs. SUMMARY: VFDs following the surgical treatment of drug-refractory MTLE can have a significant impact on the quality of life. Each of the surgical techniques carries a risk to the visual pathways but the use of minimally invasive techniques as well as surgical adjuncts may reduce or prevent acquired VFDs.

A generative model of hyperelastic strain energy density functions for multiple tissue brain deformation.

PURPOSE: Estimation of brain deformation is crucial during neurosurgery. Whilst mechanical characterisation captures stress-strain relationships of tissue, biomechanical models are limited by experimental conditions. This results in variability reported in the literature. The aim of this work was to demonstrate a generative model of strain energy density functions can estimate the elastic properties of tissue using observed brain deformation. METHODS: For the generative model a Gaussian Process regression learns elastic potentials from 73 manuscripts. We evaluate the use of neo-Hookean, Mooney-Rivlin and 1-term Ogden meta-models to guarantee stability. Single and multiple tissue experiments validate the ability of our generative model to estimate tissue properties on a synthetic brain model and in eight temporal lobe resection cases where deformation is observed between pre- and post-operative images. RESULTS: Estimated parameters on a synthetic model are close to the known reference with a root-mean-square error (RMSE) of 0.1 mm and 0.2 mm between surface nodes for single and multiple tissue experiments. In clinical cases, we were able to recover brain deformation from pre- to post-operative images reducing RMSE of differences from 1.37 to 1.08 mm on the ventricle surface and from 5.89 to 4.84 mm on the resection cavity surface. CONCLUSION: Our generative model can capture uncertainties related to mechanical characterisation of tissue. When fitting samples from elastography and linear studies, all meta-models performed similarly. The Ogden meta-model performed the best on hyperelastic studies. We were able to predict elastic parameters in a reference model on a synthetic phantom. However, deformation observed in clinical cases is only partly explained using our generative model.

Printing in a Pandemic: 3D printing solutions for healthcare during COVID-19. A Protocol for a PRISMA systematic review.

Introduction: The COVID-19 pandemic had an unprecedented global socioeconomic impact. Responses to pandemics include strategies to accumulate vast stockpiles of vital medical equipment. In such times of desperation, 3D-printing could be a life-saving alternative. Methods: We undertook a PRISMA systematic review of 3D printing solutions in response to COVID-19 utilising the PICO methodology. The objectives were to identify the uses of 3D printing during the COVID-19 pandemic, determine the extent of preclinical testing, comparison to commercial alternatives, presence of regulatory approvals and replicability regarding the description of the printing parameters and the availability of the print file. Results: Literature searches of MEDLINE (OVID interface)/ PubMed identified 601 studies. Of these, 10 studies fulfilled the inclusion and exclusion criteria. Reported uses of 3D printing included personal protective equipment (PPE), nasopharyngeal swabs and adjunctive anaesthetic equipment. Few studies undertook formal safety and efficacy testing before clinical use with only one study comparing to the commercial equivalent. Six articles made their model print files available for wider use. Conclusion: We describe a protocol for a systematic review of 3D-printed healthcare solutions in response to COVID-19. This remains a viable method of producing vital healthcare equipment when supply chains are exhausted. We hope that this will serve as a summary of innovative 3D-printed solutions during the peak of the pandemic and also highlight concerns and omissions regarding safety and efficacy testing that should be addressed urgently in preparation for a subsequent resurgences and future pandemics.

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.

An Exit Strategy for Resuming Nonemergency Neurosurgery after Severe Acute Respiratory Syndrome Coronavirus 2: A United Kingdom Perspective.

INTRODUCTION: Substantial healthcare resources have been diverted to manage the effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, and nonemergency neurosurgery has been effectively closed. As we begin to emerge from the crisis, we will need to manage the backlog of nonemergency neurosurgical patients whose treatment has been delayed and remain responsive to further possible surges of SARS-CoV-2 infections. METHODS: In the present study, we aimed to identify the core themes and challenges that will limit resumption of a normal neurosurgical service after the SARS-CoV-2 pandemic and to provide pragmatic advice and solutions that could be of utility to clinicians seeking to resume nonemergency neurosurgical care. We reviewed the relevant international policies, a wide range of journalistic and media sources, and expert opinion documents to address the stated aims. RESULTS: We have presented and discussed a range of factors that could become potential barriers to resuming full elective neurosurgical provision and important steps that must be completed to achieve pre-SARS-CoV-2 surgical capacity. We also explored how these challenges can be overcome and outlined the key requirements for a successful neurosurgical exit strategy from the pandemic. CONCLUSION: The performance of nonemergency neurosurgery can start once minimum criteria have been fulfilled: 1) a structured prioritization of surgical cases; 2) virus infection incidence decreased sufficiently to release previously diverted healthcare resources; 3) adequate safety criteria met for patients and staff, including sufficient personal protective equipment and robust testing availability; and 4) maintenance of systems for rapid communication at organizational and individual levels.

Automation Advances in Stereoelectroencephalography Planning.

The past decade has seen a significant shift in the number of centers performing intracranial electroencephalography from subdural grids and strips to stereoelectroencephalography (SEEG). Unlike grid and strip insertion or other stereotactic procedures in which the cortical surface is visualized, SEEG involves insertion of an electrode through a bolt anchored into the skull. Due to the multidisciplinary nature of SEEG trajectory planning, it often is time-consuming and iterative. Computer-assisted planning improves time taken and efficacy of SEEG trajectory planning. This article provides an overview of the considerations, controversies, and practicalities of implementing an automated computer-assisted planning solution for SEEG planning.

Automated computation and analysis of accuracy metrics in stereoencephalography.

BACKGROUND: Implantation accuracy of electrodes during neurosurgical interventions is necessary to ensure safety and efficacy. Typically, metrics are computed by visual inspection which is tedious, prone to inter-/intra-observer variation, and difficult to replicate across sites. NEW METHOD: We propose an automated approach for computing implantation metrics and investigate potential sources of error. We focus on accuracy metrics commonly reported in the literature to validate our approach against metrics computed manually including entry point (EP) and target point (TP) localisation errors and angle differences between planned and implanted trajectories in 15 patients with a total of 158 stereoelectroencephalography (SEEG) electrodes. We evaluate the effect of line-of-best-fit approaches, EP definition and lateral versus Euclidean distance on metrics to provide recommendations for reporting implantation accuracy metrics. RESULTS: We found no bias between manual and automated approaches for calculating accuracy metrics with limits of agreement of ±1 mm and ±1°. Automated metrics are robust to sources of errors including registration and electrode bending. We observe the highest error in EP deviations of µâ€¯= 0.25 mm when the post-implantation CT is used to define the point of entry. COMPARISON WITH EXISTING METHOD(S): We found no reports of automated approaches for quality assessment of SEEG electrode implantation. Neither the choice of metrics nor the possible errors that could occur have been investigated previously. CONCLUSIONS: Our automated approach is useful to avoid human errors, unintentional bias and variation that may be introduced when manually computing metrics. Our work is relevant and timely to facilitate comparisons of studies reporting implantation accuracy.

Computer-assisted planning for minimally invasive anterior two-thirds laser corpus callosotomy: A feasibility study with probabilistic tractography validation.

BACKGROUND: Anterior two-thirds corpus callosotomy is an effective palliative neurosurgical procedure for drug-refractory epilepsy that is most commonly used to treat drop-attacks. Laser interstitial thermal therapy is a novel stereotactic ablative technique that has been utilised as a minimally invasive alternative to resective and disconnective open neurosurgery. Case series have reported success in performing laser anterior two-thirds corpus callosotomy. Computer-assisted planning algorithms may help to automate and optimise multi-trajectory planning for this procedure. OBJECTIVE: To undertake a simulation-based feasibility study of computer-assisted corpus callostomy planning in comparison with expert manual plans in the same patients. METHODS: Ten patients were selected from a prospectively maintained database. Patients had previously undergone diffusion-weighted imaging and digital subtraction angiography as part of routine SEEG care. Computer-assisted planning was performed using the EpiNav™ platform and compared to manually planned trajectories from two independent blinded experts. Estimated ablation cavities were used in conjunction with probabilistic tractography to simulate the expected extent of interhemispheric disconnection. RESULTS: Computer-assisted planning resulted in significantly improved trajectory safety metrics (risk score and minimum distance to vasculature) compared to blinded external expert manual plans. Probabilistic tractography revealed residual interhemispheric connectivity in 1/10 cases following computer-assisted planning compared to 4/10 and 2/10 cases with manual planning. CONCLUSION: Computer-assisted planning successfully generates multi-trajectory plans capable of LITT anterior two-thirds corpus callosotomy. Computer-assisted planning may provide a means of standardising trajectory planning and serves as a potential new tool for optimising trajectories. A prospective validation study is now required to determine if this translates into improved patient outcomes.