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

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

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

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 μ = 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

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

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

Neuroimaging in epilepsy

PURPOSE OF REVIEW: Epilepsy neuroimaging is important for detecting the seizure onset zone, predicting and preventing deficits from surgery and illuminating mechanisms of epileptogenesis. An aspiration is to integrate imaging and genetic biomarkers to enable personalized epilepsy treatments. RECENT FINDINGS: The ability to detect lesions, particularly focal cortical dysplasia and hippocampal sclerosis, is increased using ultra high-field imaging and postprocessing techniques such as automated volumetry, T2 relaxometry, voxel-based morphometry and surface-based techniques. Statistical analysis of PET and single photon emission computer tomography (STATISCOM) are superior to qualitative analysis alone in identifying focal abnormalities in MRI-negative patients. These methods have also been used to study mechanisms of epileptogenesis and pharmacoresistance. Recent language fMRI studies aim to localize, and also lateralize language functions. Memory fMRI has been recommended to lateralize mnemonic function and predict outcome after surgery in temporal lobe epilepsy. SUMMARY: Combinations of structural, functional and post-processing methods have been used in multimodal and machine learning models to improve the identification of the seizure onset zone and increase understanding of mechanisms underlying structural and functional aberrations in epilepsy

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 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