Video-Based Performance Analysis in Pituitary Surgery - Part 2: Artificial Intelligence Assisted Surgical Coaching.

BACKGROUND: Superior surgical skill improves surgical outcomes in endoscopic pituitary adenoma surgery. Video-based coaching programs, pioneered in professional sports, have shown promise in surgical training. In this study, we developed and assessed a video-based coaching program, using artificial intelligence (AI). METHODS: AI-assisted video-based surgical coaching was implemented over 6 months with the pituitary surgery team. The program consisted of 1) monthly random video analysis and review; and 2) quarterly 2-hour educational meetings discussing these videos and learning points. Each video was annotated for surgical phases and steps using AI, which improved video interactivity and allowed calculation of quantitative metrics. Primary outcomes were program feasibility, acceptability and appropriateness. Surgical performance (via modified Objective Structured Assessment of Technical Skills; mOSATS) and early surgical outcomes were recorded for every case during the 6-month coaching period, and a preceding 6-month control period. Beta and logistic regression were used to assess the change in mOSATS and surgical outcomes after the coaching program implementation. RESULTS: All participants highly rated the program's feasibility, acceptability and appropriateness. During the coaching program, 63 endoscopic pituitary adenoma cases were included, with 41 in the control group. Surgical performance across all operative phases improved during the coaching period (p<0.001), with a reduction in new post-operative anterior pituitary hormone deficit (p=0.01). CONCLUSION: We have developed a novel AI-assisted video surgical coaching program for endoscopic pituitary adenoma surgery - demonstrating its viability and impact on surgical performance. Early results also suggest improvement in patient outcomes. Future studies should be multicenter and longer term.

Mapping the clinical pathway for patients undergoing vestibular schwannoma resection.

BACKGROUND: The introduction of electronic health records (EHR) has improved the collection and storage of patient information, enhancing clinical communication and academia. However, EHRs remain limited by data quality and the time-consuming task of manual data extraction. This study aims to utilise process mapping to help identify critical data entry points within the clinical pathway for VS patients, ideal for structured data entry and automated data collection, in an effort to improve patient care and research. METHODS: A two-stage methodology was conducted at a neurosurgical unit. Process maps were developed using semi-structured interviews with stakeholders in the management of VS resection. Process maps were then retrospectively validated against EHR for patients admitted between August 2019 and December 2021, establishing critical data entry points. RESULTS: Twenty stakeholders were interviewed in the process map development. Process maps were validated against the EHR of 36 patients admitted for VS resection. Operation notes, surgical inpatient reviews (including ward rounds) and discharge summaries were present for all patients, representing critical data entry points. Areas for documentation improvement were present in the preoperative clinics (30/36, 83.3%), preoperative skull base multidisciplinary team (32/36, 88.9%), postoperative follow-up clinics (32/36, 88.9%), and the postoperative skull base multidisciplinary team meeting (29/36, 80.6%). CONCLUSION: This is a first use of a two-stage methodology for process mapping the clinical pathway for patients undergoing VS resection. Our study identified critical data entry points which can be targeted for structured data entry and for automated data collection tools, positively impacting patient care and research.

Mapping patient education encounters in elective surgery: a cohort study and cross-sectional survey.

OBJECTIVE: Develop a process map of when patients learn about their proposed surgery and what resources patients use to educate themselves. DESIGN: A mixed methods design, combining semistructured stakeholder interviews, quantitative validation using electronic healthcare records (EHR) in a retrospective cohort and a cross-sectional patient survey. SETTING: A single surgical centre in the UK. PARTICIPANTS: Fourteen members of the spinal multidisciplinary team were interviewed to develop the process map.This process map was validated using the EHR of 50 patients undergoing elective spine surgery between January and June 2022. Postprocedure, feedback was gathered from 25 patient surveys to identify which resources they used to learn about their spinal procedure. Patients below the age of 18 or who received emergency surgery were excluded. INTERVENTIONS: Elective spine surgery and patient questionnaires given postoperatively either on the ward or in follow-up clinic. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was the percentage of the study cohort that was present at encounters on the process map. Key timepoints were defined if >80% of patients were present. The secondary outcome was the percentage of the study cohort that used educational resources listed in the patient questionnaire. RESULTS: There were 342 encounters which occurred across the cohort, with 16 discrete event categories identified. The initial surgical clinic (88%), anaesthetic preoperative assessment (96%) and admission for surgery (100%) were identified as key timepoints. Surveys identified that patients most used verbal information from their surgeon (100%) followed by written information from their surgeon (52%) and the internet (40%) to learn about their surgery. CONCLUSIONS: Process mapping is an effective method of illustrating the patient pathway. The initial surgical clinic, anaesthetic preoperative assessment and surgical admission are key timepoints where patients receive information. This has future implications for guiding patient education interventions to focus at key timepoints.

Early evaluation of a natural language processing tool to improve access to educational resources for surgical patients.

PURPOSE: Accessible patient information sources are vital in educating patients about the benefits and risks of spinal surgery, which is crucial for obtaining informed consent. We aim to assess the effectiveness of a natural language processing (NLP) pipeline in recognizing surgical procedures from clinic letters and linking this with educational resources. METHODS: Retrospective examination of letters from patients seeking surgery for degenerative spinal disease at a single neurosurgical center. We utilized MedCAT, a named entity recognition and linking NLP, integrated into the electronic health record (EHR), which extracts concepts and links them to systematized nomenclature of medicine-clinical terms (SNOMED-CT). Investigators reviewed clinic letters, identifying words or phrases that described or identified operations and recording the SNOMED-CT terms as ground truth. This was compared to SNOMED-CT terms identified by the model, untrained on our dataset. A pipeline linking clinic letters to patient-specific educational resources was established, and precision, recall, and F1 scores were calculated. RESULTS: Across 199 letters the model identified 582 surgical procedures, and the overall pipeline after adding rules a total of 784 procedures (precision = 0.94, recall = 0.86, F1 = 0.91). Across 187 letters with identified SNOMED-CT terms the integrated pipeline linking education resources directly to the EHR was successful in 157 (78%) patients (precision = 0.99, recall = 0.87, F1 = 0.92). CONCLUSIONS: NLP accurately identifies surgical procedures in pre-operative clinic letters within an untrained subspecialty. Performance varies among letter authors and depends on the language used by clinicians. The identified procedures can be linked to patient education resources, potentially improving patients' understanding of surgical procedures.

High fidelity simulation of the endoscopic transsphenoidal approach: Validation of the UpSurgeOn TNS Box.

Objective: Endoscopic endonasal transsphenoidal surgery is an established technique for the resection of sellar and suprasellar lesions. The approach is technically challenging and has a steep learning curve. Simulation is a growing training tool, allowing the acquisition of technical skills pre-clinically and potentially resulting in a shorter clinical learning curve. We sought validation of the UpSurgeOn Transsphenoidal (TNS) Box for the endoscopic endonasal transsphenoidal approach to the pituitary fossa. Methods: Novice, intermediate and expert neurosurgeons were recruited from multiple centres. Participants were asked to perform a sphenoidotomy using the TNS model. Face and content validity were evaluated using a post-task questionnaire. Construct validity was assessed through post-hoc blinded scoring of operative videos using a Modified Objective Structured Assessment of Technical Skills (mOSAT) and a Task-Specific Technical Skill scoring system. Results: Fifteen participants were recruited of which n = 10 (66.6%) were novices and n = 5 (33.3%) were intermediate and expert neurosurgeons. Three intermediate and experts (60%) agreed that the model was realistic. All intermediate and experts (n = 5) strongly agreed or agreed that the TNS model was useful for teaching the endonasal transsphenoidal approach to the pituitary fossa. The consensus-derived mOSAT score was 16/30 (IQR 14-16.75) for novices and 29/30 (IQR 27-29) for intermediate and experts (p < 0.001, Mann-Whitney U). The median Task-Specific Technical Skill score was 10/20 (IQR 8.25-13) for novices and 18/20 (IQR 17.75-19) for intermediate and experts (p < 0.001, Mann-Whitney U). Interrater reliability was 0.949 (CI 0.983-0.853) for OSATS and 0.945 (CI 0.981-0.842) for Task-Specific Technical Skills. Suggested improvements for the model included the addition of neuro-vascular anatomy and arachnoid mater to simulate bleeding vessels and CSF leak, respectively, as well as improvement in materials to reproduce the consistency closer to that of human tissue and bone. Conclusion: The TNS Box simulation model has demonstrated face, content, and construct validity as a simulator for the endoscopic endonasal transsphenoidal approach. With the steep learning curve associated with endoscopic approaches, this simulation model has the potential as a valuable training tool in neurosurgery with further improvements including advancing simulation materials, dynamic models (e.g., with blood flow) and synergy with complementary technologies (e.g., artificial intelligence and augmented reality).

Improving Neurosurgery Education Using Social Media Case-Based Discussions: A Pilot Study.

BACKGROUND: The increasing shift toward a more generalized medical undergraduate curriculum has led to limited exposure to subspecialties, including neurosurgery. The lack of standardized teaching may result in insufficient coverage of core learning outcomes. Social media (SoMe) in medical education are becoming an increasingly accepted and popular way for students to meet learning objectives outside formal medical school teaching. We delivered a series of case-based discussions (CbDs) over SoMe to attempt to meet core learning needs in neurosurgery and determine whether SoMe-based CbDs were an acceptable method of education. METHODS: Twitter was used as a medium to host 9 CbDs pertaining to common neurosurgical conditions in practice. A sequence of informative and interactive tweets were formulated before live CbDs and tweeted in progressive order. Demographic data and participant feedback were collected. RESULTS: A total of 277 participants were recorded across 9 CbDs, with 654,584 impressions generated. Feedback responses were received from 135 participants (48.7%). Participants indicated an increase of 77% in their level of knowledge after participating. Of participants, 57% (n = 77) had previous CbD experience as part of traditional medical education, with 62% (n = 84) receiving a form of medical education previously through SoMe. All participants believed that the CbDs objectives were met and would attend future sessions. Of participants, 99% (n = 134) indicated that their expectations were met. CONCLUSIONS: SoMe has been shown to be a favorable and feasible medium to host live, text-based interactive CbDs. SoMe is a useful tool for teaching undergraduate neurosurgery and is easily translatable to all domains of medicine and surgery.

Neurosurgery in Aberdeen Royal Infirmary c. 1920-c.1940: knowledge, skills and styles.

A neurosurgical unit was established in Aberdeen Royal Infirmary (ARI) in 1948 with the appointment of Martin Nichols as its first full-time neurosurgeon. Despite there being no formal neurosurgical ward or specialist dedicated to neurosurgery in ARI prior to this, a number of neurosurgical procedures were undertaken between 1920 and 1940. From 1923 to 1932, the procedures were predominantly cranial and were performed by general surgeons. The operations evolved in 1933 to include the spine and peripheral nerves after the arrival of Sir James Learmonth. This paper chronicles the development of surgical neurology at the ARI in the 30 years preceding a formal unit. It considers the factors and background that enabled neurosurgical practices to be undertaken and led to evolution of neurosurgery from general surgery.