Synthesis and crystallography of high entropy metal carbides: A new class of ultrahigh temperature and irradiation resistant ceramics

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Patient-specific 3D-printed surgical guides for pedicle screw insertion: comparison of different guide design approaches

AIM: Patient-specific 3D-printed guides for pedicle screw insertion in spinal deformity surgery offer an alternative to image-guided, robotic and free-hand methods. Different design features can impact their accuracy and clinical applicability. The aim of this study was to compare the performance of three different guide designs with the nonguided free-hand technique. MATERIAL & METHODS: 3D-printed guides were design and tested using anatomical models of human spines and porcine cadaveric specimens. Three different guided groups (low, medium and full contact) and one nonguided group was formed. RESULTS & CONCLUSIONS: The design approach affected level of accuracy of screw placement. A variability in terms of accuracy of screw insertion between surgeon’s experience using nonguided/guided techniques was also observed, suggesting benefit for junior surgeons in improving surgical accuracy

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

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

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

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

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

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

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

Getting the best outcomes from epilepsy surgery

Neurosurgery is an under-utilised treatment that can potentially cure drug-refractory epilepsy. Careful, multidisciplinary pre-surgical evaluation is vital for selecting patients and ensure optimal outcomes. Advances in neuroimaging have improved diagnosis and guide surgical intervention. Invasive electroencephalography allows the evaluation of complex patients who would otherwise not be candidates for neurosurgery. We review the current state of the assessment and selection of patients and consider established and novel surgical procedures, and associated outcome data. We aim to dispel myths that may inhibit physicians from referring and patients from considering neurosurgical intervention for drug-refractory focal epilepsies