Neurosurgical team acceptability of brain-computer interfaces: a two-stage international cross-sectional survey

OBJECTIVE: Invasive brain-computer interfaces (BCIs) require neurosurgical implantation, which confers a range of risks. Despite this, no studies have assessed the acceptability of invasive BCIs amongst the neurosurgical team. This study aims to establish baseline knowledge of BCIs within the neurosurgical team and identify attitudes towards different applications of invasive BCI. METHOD: A two-stage cross-sectional international survey of the neurosurgical team (neurosurgeons, anaesthetists, and operating room nurses) was conducted. Results from the first, qualitative, survey were used to guide the second stage quantitative survey, which assessed acceptability of invasive BCI applications. 5-part Likert Scales were used to collect quantitative data. Surveys were distributed internationally via social media and collaborators. RESULTS: 108 qualitative responses were collected. Themes included the promise of BCIs positively impacting disease targets, concerns regarding stability, and an overall positive emotional reaction to BCI technology. The quantitative survey generated 538 responses from 32 countries. Baseline knowledge of BCI technology was poor, with 9% claiming to have a ‘good’ or ‘expert’ knowledge of BCIs. Acceptability of invasive BCI for rehabilitative purposes was >80%. Invasive BCI for augmentation in healthy populations divided opinion. CONCLUSION: The neurosurgical team’s view of the acceptability of BCI was divided across a range of indications. Some applications (for example stroke rehabilitation) were viewed as more appropriate than other applications (such as augmentation for military use). This range in views highlights the need for stakeholder consultation on acceptable use cases along with regulation and guidance to govern initial BCI implantations if patients are to realise the potential benefits

Process analysis of the patient pathway for automated data collection: an exemplar using pituitary surgery

Introduction: Automation of routine clinical data shows promise in relieving health systems of the burden associated with manual data collection. Identifying consistent points of documentation in the electronic health record (EHR) provides salient targets to improve data entry quality. Using our pituitary surgery service as an exemplar, we aimed to demonstrate how process mapping can be used to identify reliable areas of documentation in the patient pathway to target structured data entry interventions. Materials and methods: This mixed methods study was conducted in the largest pituitary centre in the UK. Purposive snowball sampling identified frontline stakeholders for process mapping to produce a patient pathway. The final patient pathway was subsequently validated against a real-world dataset of 50 patients who underwent surgery for pituitary adenoma. Events were categorized by frequency and mapped to the patient pathway to determine critical data points. Results: Eighteen stakeholders encompassing all members of the multidisciplinary team (MDT) were consulted for process mapping. The commonest events recorded were neurosurgical ward round entries (N = 212, 14.7%), pituitary clinical nurse specialist (CNS) ward round entries (N = 88, 6.12%) and pituitary MDT treatment decisions (N = 88, 6.12%) representing critical data points. Operation notes and neurosurgical ward round entries were present for every patient. 43/44 (97.7%) had a pre-operative pituitary MDT entry, pre-operative clinic letter, a post-operative clinic letter, an admission clerking entry, a discharge summary, and a post-operative histopathology pituitary multidisciplinary (MDT) team entries. Conclusion: This is the first study to produce a validated patient pathway of patients undergoing pituitary surgery, serving as a comparison to optimise this patient pathway. We have identified salient targets for structured data entry interventions, including mandatory datapoints seen in every admission and have also identified areas to improve documentation adherence, both of which support movement towards automation

Benchtop simulation of the retrosigmoid approach: Validation of a surgical simulator and development of a task-specific outcome measure score

Background: Neurosurgical training is changing globally. Reduced working hours and training opportunities, increased patient safety expectations, and the impact of COVID-19 have reduced operative exposure. Benchtop simulators enable trainees to develop surgical skills in a controlled environment. We aim to validate a highfidelity simulator model (RetrosigmoidBox, UpSurgeOn) for the retrosigmoid approach to the cerebellopontine angle (CPA). Methods: Novice and expert Neurosurgeons and Ear, Nose, and Throat surgeons performed a surgical task using the model – identification of the trigeminal nerve. Experts completed a post-task questionnaire examining face and content validity. Construct validity was assessed through scoring of operative videos employing Objective Structured Assessment of Technical Skills (OSATS) and a novel Task-Specific Outcome Measure score. Results: Fifteen novice and five expert participants were recruited. Forty percent of experts agreed or strongly agreed that the brain tissue looked real. Experts unanimously agreed that the RetrosigmoidBox was appropriate for teaching. Statistically significant differences were noted in task performance between novices and experts, demonstrating construct validity. Median total OSATS score was 14/25 (IQR 10–19) for novices and 22/25 (IQR 20–22) for experts (p < 0.05). Median Task-Specific Outcome Measure score was 10/20 (IQR 7–17) for novices compared to 19/20 (IQR 18.5–19.5) for experts (p < 0.05). Conclusion: The RetrosigmoidBox benchtop simulator has a high degree of content and construct validity and moderate face validity. The changing landscape of neurosurgical training mean that simulators are likely to become increasingly important in the delivery of high-quality education. We demonstrate the validity of a TaskSpecific Outcome Measure score for performance assessment of a simulated approach to the CPA

The effect of specific bioactive collagen peptides on function and muscle remodeling during human resistance training

Aim: Bioactive collagen peptides (CP) have been suggested to augment the functional, structural (size and architecture), and contractile adaptations of skeletal muscle to resistance training (RT), but with limited evidence. This study aimed to determine if CP vs. placebo (PLA) supplementation enhanced the functional and underpinning structural, and contractile adaptations after 15 weeks of lower body RT. Methods: Young healthy males were randomized to consume either 15 g of CP (n = 19) or PLA (n = 20) once every day during a standardized program of progressive knee extensor, knee flexor, and hip extensor RT 3 times/wk. Measurements pre‐ and post‐RT included: knee extensor and flexor isometric strength; quadriceps, hamstrings, and gluteus maximus volume with MRI; evoked twitch contractions, 1RM lifting strength, and architecture (with ultrasound) of the quadriceps. Results: Percentage changes in maximum strength (isometric or 1RM) did not differ between‐groups (0.684 ≤ p ≤ 0.929). Increases in muscle volume were greater (quadriceps 15.2% vs. 10.3%; vastus medialis (VM) 15.6% vs. 9.7%; total muscle volume 15.7% vs. 11.4%; [all] p ≤ 0.032) or tended to be greater (hamstring 16.5% vs. 12.8%; gluteus maximus 16.6% vs. 12.9%; 0.089 ≤ p ≤ 0.091) for CP vs. PLA. There were also greater increases in twitch peak torque (22.3% vs. 12.3%; p = 0.038) and angle of pennation of the VM (16.8% vs. 5.8%, p = 0.046), but not other muscles, for CP vs. PLA. Conclusions: CP supplementation produced a cluster of consistent effects indicating greater skeletal muscle remodeling with RT compared to PLA. Notably, CP supplementation amplified the quadriceps and total muscle volume increases induced by RT

A synthetic model simulator for intracranial aneurysm clipping: validation of the UpSurgeOn AneurysmBox

Background and objectives: In recent decades, the rise of endovascular management of aneurysms has led to a significant decline in operative training for surgical aneurysm clipping. Simulation has the potential to bridge this gap and benchtop synthetic simulators aim to combine the best of both anatomical realism and haptic feedback. The aim of this study was to validate a synthetic benchtop simulator for aneurysm clipping (AneurysmBox, UpSurgeOn). Methods: Expert and novice surgeons from multiple neurosurgical centres were asked to clip a terminal internal carotid artery aneurysm using the AneurysmBox. Face and content validity were evaluated using Likert scales by asking experts to complete a post-task questionnaire. Construct validity was evaluated by comparing expert and novice performance using the modified Objective Structured Assessment of Technical Skills (mOSATS), developing a curriculum-derived assessment of Specific Technical Skills (STS), and measuring the forces exerted using a force-sensitive glove. Results: Ten experts and eighteen novices completed the task. Most experts agreed that the brain looked realistic (8/10), but far fewer agreed that the brain felt realistic (2/10). Half the expert participants (5/10) agreed that the aneurysm clip application task was realistic. When compared to novices, experts had a significantly higher median mOSATS (27 vs. 14.5; p < 0.01) and STS score (18 vs. 9; p < 0.01); the STS score was strongly correlated with the previously validated mOSATS score (p < 0.01). Overall, there was a trend towards experts exerting a lower median force than novices, however, these differences were not statistically significant (3.8 N vs. 4.0 N; p = 0.77). Suggested improvements for the model included reduced stiffness and the addition of cerebrospinal fluid (CSF) and arachnoid mater. Conclusion: At present, the AneurysmBox has equivocal face and content validity, and future versions may benefit from materials that allow for improved haptic feedback. Nonetheless, it has good construct validity, suggesting it is a promising adjunct to training

Characterization of patients with idiopathic normal pressure hydrocephalus using natural language processing within an electronic healthcare record system

OBJECTIVE: Idiopathic normal pressure hydrocephalus (iNPH) is an underdiagnosed, progressive, and disabling condition. Early treatment is associated with better outcomes and improved quality of life. In this paper, the authors aimed to identify features associated with patients with iNPH using natural language processing (NLP) to characterize this cohort, with the intention to later target the development of artificial intelligence–driven tools for early detection. / METHODS: The electronic health records of patients with shunt-responsive iNPH were retrospectively reviewed using an NLP algorithm. Participants were selected from a prospectively maintained single-center database of patients undergoing CSF diversion for probable iNPH (March 2008–July 2020). Analysis was conducted on preoperative health records including clinic letters, referrals, and radiology reports accessed through CogStack. Clinical features were extracted from these records as SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) concepts using a named entity recognition machine learning model. In the first phase, a base model was generated using unsupervised training on 1 million electronic health records and supervised training with 500 double-annotated documents. The model was fine-tuned to improve accuracy using 300 records from patients with iNPH double annotated by two blinded assessors. Thematic analysis of the concepts identified by the machine learning algorithm was performed, and the frequency and timing of terms were analyzed to describe this patient group. / RESULTS: In total, 293 eligible patients responsive to CSF diversion were identified. The median age at CSF diversion was 75 years, with a male predominance (69% male). The algorithm performed with a high degree of precision and recall (F1 score 0.92). Thematic analysis revealed the most frequently documented symptoms related to mobility, cognitive impairment, and falls or balance. The most frequent comorbidities were related to cardiovascular and hematological problems. / CONCLUSIONS: This model demonstrates accurate, automated recognition of iNPH features from medical records. Opportunities for translation include detecting patients with undiagnosed iNPH from primary care records, with the aim to ultimately improve outcomes for these patients through artificial intelligence–driven early detection of iNPH and prompt treatment

Testing for the Dual-Route Cascade Reading Model in the Brain: An fMRI Effective Connectivity Account of an Efficient Reading Style

Neuropsychological data about the forms of acquired reading impairment provide a strong basis for the theoretical framework of the dual-route cascade (DRC) model which is predictive of reading performance. However, lesions are often extensive and heterogeneous, thus making it difficult to establish precise functional anatomical correlates. Here, we provide a connective neural account in the aim of accommodating the main principles of the DRC framework and to make predictions on reading skill. We located prominent reading areas using fMRI and applied structural equation modeling to pinpoint distinct neural pathways. Functionality of regions together with neural network dissociations between words and pseudowords corroborate the existing neuroanatomical view on the DRC and provide a novel outlook on the sub-regions involved. In a similar vein, congruent (or incongruent) reliance of pathways, that is reliance on the word (or pseudoword) pathway during word reading and on the pseudoword (or word) pathway during pseudoword reading predicted good (or poor) reading performance as assessed by out-of-magnet reading tests. Finally, inter-individual analysis unraveled an efficient reading style mirroring pathway reliance as a function of the fingerprint of the stimulus to be read, suggesting an optimal pattern of cerebral information trafficking which leads to high reading performance

Artificial Intelligence in Brain Tumour Surgery—An Emerging Paradigm

Artificial intelligence (AI) platforms have the potential to cause a paradigm shift in brain tumour surgery. Brain tumour surgery augmented with AI can result in safer and more effective treatment. In this review article, we explore the current and future role of AI in patients undergoing brain tumour surgery, including aiding diagnosis, optimising the surgical plan, providing support during the operation, and better predicting the prognosis. Finally, we discuss barriers to the successful clinical implementation, the ethical concerns, and we provide our perspective on how the field could be advanced

The Effect of Specific Bioactive Collagen Peptides on Tendon Remodelling during 15 Weeks of Lower Body Resistance Training

Purpose Collagen peptide supplementation has been reported to enhance synthesis rates or growth in a range of musculoskeletal tissues and could enhance tendinous tissue adaptations to resistance training (RT). This double-blind placebo-controlled study aimed to determine if tendinous tissue adaptations, size (patellar tendon cross-sectional area [CSA] and vastus lateralis [VL] aponeurosis area) and mechanical properties (patellar tendon), following 15 weeks of RT could be augmented with collagen peptide (CP) vs. placebo (PLA) supplementation Methods Young healthy recreationally active men were randomized to consume either 15 g of CP (n=19) or PLA (n=20) once every day during a standardized program of lower-body RT (3 times/wk). Measurements pre- and post-RT included: patellar tendon CSA and VL aponeurosis area (via MRI); patellar tendon mechanical properties during isometric knee extension ramp contractions. Results No between-group differences were detected for any of the tendinous tissue adaptations to RT (ANOVA group x time, 0.365 ≤ P ≤ 0.877). There were within-group increases in VL aponeurosis area (CP: +10.0%, PLA: +9.4%), patellar tendon stiffness (CP: +17.3% PLA: +20.9%) and Young’s Modulus (CP: +17.8%; PLA: +20.6%) in both groups (paired t-tests [all] P ≤ 0.007). There were also within-group decreases in patellar tendon elongation (CP: -10.8%, PLA: -9.6%) and strain (CP: -10.6%, PLA: -8.9%) in both groups (paired t-tests [all] P ≤ 0.006). Whilst no within-group changes in patellar tendon CSA (mean or regional) occurred for CP or PLA, a modest overall time effect (n=39) was observed for mean (+1.4%) and proximal region (+2.4%) patellar tendon CSA (ANOVA, 0.017 ≤ P ≤ 0.048). Conclusions In conclusion, CP supplementation did not enhance RT-induced tendinous tissue remodelling (either size or mechanical properties) compared to PLA within a population of healthy young males

Benchtop simulation of the retrosigmoid approach: Validation of a surgical simulator and development of a task-specific outcome measure score

Background: Neurosurgical training is changing globally. Reduced working hours and training opportunities, increased patient safety expectations, and the impact of COVID-19 have reduced operative exposure. Benchtop simulators enable trainees to develop surgical skills in a controlled environment. We aim to validate a high-fidelity simulator model (RetrosigmoidBox, UpSurgeOn) for the retrosigmoid approach to the cerebellopontine angle (CPA). Methods: Novice and expert Neurosurgeons and Ear, Nose, and Throat surgeons performed a surgical task using the model – identification of the trigeminal nerve. Experts completed a post-task questionnaire examining face and content validity. Construct validity was assessed through scoring of operative videos employing Objective Structured Assessment of Technical Skills (OSATS) and a novel Task-Specific Outcome Measure score. Results: Fifteen novice and five expert participants were recruited. Forty percent of experts agreed or strongly agreed that the brain tissue looked real. Experts unanimously agreed that the RetrosigmoidBox was appropriate for teaching. Statistically significant differences were noted in task performance between novices and experts, demonstrating construct validity. Median total OSATS score was 14/25 (IQR 10–19) for novices and 22/25 (IQR 20–22) for experts (p < 0.05). Median Task-Specific Outcome Measure score was 10/20 (IQR 7–17) for novices compared to 19/20 (IQR 18.5–19.5) for experts (p < 0.05). Conclusion: The RetrosigmoidBox benchtop simulator has a high degree of content and construct validity and moderate face validity. The changing landscape of neurosurgical training mean that simulators are likely to become increasingly important in the delivery of high-quality education. We demonstrate the validity of a Task-Specific Outcome Measure score for performance assessment of a simulated approach to the CPA