OBJECTIVE Internal carotid artery injury (ICAI) is a rare, life-threatening complication of endoscopic endonasal approaches that will be encountered by most skull base neurosurgeons and otolaryngologists. Rates of surgical proficiency for managing ICAI are not known, and the role of simulation to improve performance has not been studied on a nationwide scale. METHODS Attending and resident neurosurgery and otorhinolaryngology surgeons (n = 177) were recruited from multicenter regional and national training courses to assess training outcomes and validity at scale of a prospective educational intervention to improve surgeon technical skills using a previously validated, perfused human cadaveric simulator. Participants attempted an initial trial (T1) of simulated ICAI control using their preferred technique. An educational intervention including personalized instruction was performed. Participants attempted a second trial (T2). Task success (dichotomous), time to hemostasis (TTH), estimated blood loss (EBL), and surgeon heart rate were measured. RESULTS Participant rating scales confirmed that the simulation retained face and construct validity across eight instructional settings. Trial success (ICAI control) improved from 56% in T1 to 90% in T2 (p < 0.0001). EBL and TTH decreased by 37% and 38%, respectively (p < 0.0001). Postintervention resident surgeon performance (TTH, EBL, and success rate) was superior to preintervention attending surgeon performance. The most improved quartile of participants achieved 62% improvement in TTH and 73% improvement in EBL, with trial success improvement from 25.6% in T1 to 100% in T2 (p < 0.0001). Baseline surgeon confidence was uncorrelated with T1 success, while posttraining confidence correlated with T2 success. Tachycardia was measured in 57% of surgeon participants, but was attenuated during T2, consistent with development of resiliency. CONCLUSIONS Prior to training, many attending and most resident surgeons could not manage the rare, life-threatening intraoperative complication of ICAI. A simulated educational intervention significantly improved surgeon performance and remained valid when deployed at scale. Simulation also promoted the development of favorable cognitive skills (accurate perception of skill and resiliency). Rare, life-threatening intraoperative complications may be optimal targets for educational interventions using surgical simulation.

Key Points Question What is the utility of a data set that contains videos of surgeons managing hemorrhage? Findings This quality improvement study of the Simulated Outcomes Following Carotid Artery Laceration (SOCAL), a public data set of surgeons managing catastrophic surgical hemorrhage in a cadaveric training exercise included 65 071 instrument annotations with recorded outcomes. Computer vision–based instrument detection achieved a mean average precision of 0.67 on SOCAL and a sensitivity of 0.77 and a positive predictive value of 0.96 at detecting surgical instruments from real intraoperative video. Meaning A corpus of videos of surgeons managing catastrophic hemorrhage is a novel, valuable resource for surgical data science.

Purpose Functional pituitary adenomas (FPAs) cause severe neuro-endocrinopathies including Cushing's disease (CD) and acromegaly. While many are effectively cured following FPA resection, some encounter disease recurrence/progression or hormonal non-remission requiring adjuvant treatment. Identification of risk factors for suboptimal postoperative outcomes may guide initiation of adjuvant multimodal therapies. Methods Patients undergoing endonasal transsphenoidal resection for CD, acromegaly, and mammosomatotroph adenomas between 1992 and 2019 were identified. Good outcomes were defined as hormonal remission without imaging/biochemical evidence of disease recurrence/progression, while suboptimal outcomes were defined as hormonal non-remission or MRI evidence of recurrence/progression despite adjuvant treatment. Multivariate regression modeling and multilayered neural networks (NN) were implemented. The training sets randomly sampled 60% of all FPA patients, and validation/testing sets were 20% samples each. Results 348 patients with mean age of 41.7 years were identified. Eighty-one patients (23.3%) reported suboptimal outcomes. Variables predictive of suboptimal outcomes included: Requirement for additional surgery in patients who previously had surgery and continue to have functionally active tumor (p = 0.0069; OR = 1.51, 95%CI 1.12-2.04), Preoperative visual deficit not improved after surgery (p = 0.0033; OR = 1.12, 95%CI 1.04-1.20), Transient diabetes insipidus (p = 0.013; OR = 1.27, 95%CI 1.05-1.52), Higher MIB-1/Ki-67 labeling index (p = 0.038; OR = 1.08, 95%CI 1.01-1.15), and preoperative low cortisol axis (p = 0.040; OR = 2.72, 95%CI 1.06-7.01). The NN had overall accuracy of 87.1%, sensitivity of 89.5%, specificity of 76.9%, positive predictive value of 94.4%, and negative predictive value of 62.5%. NNs for all FPAs were more robust than for CD or acromegaly/mammosomatotroph alone. Conclusion We demonstrate capability of predicting suboptimal postoperative outcomes with high accuracy. NNs may aid in stratifying patients for risk of suboptimal outcomes, thereby guiding implementation of adjuvant treatment in high-risk patients.

OBJECTIVE Virtual reality (VR) and augmented reality (AR) systems are increasingly available to neurosurgeons. These systems may provide opportunities for technical rehearsal and assessments of surgeon performance. The assessment of neurosurgeon skill in VR and AR environments and the validity of VR and AR feedback has not been systematically reviewed. METHODS A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted through MEDLINE and PubMed. Studies published in English between January 1990 and February 2021 describing the use of VR or AR to quantify surgical technical performance of neurosurgeons without the use of human raters were included. The types and categories of automated performance metrics (APMs) from each of these studies were recorded. RESULTS Thirty-three VR studies were included in the review; no AR studies met inclusion criteria. VR APMs were categorized as either distance to target, force, kinematics, time, blood loss, or volume of resection. Distance and time were the most well-studied APM domains, although all domains were effective at differentiating surgeon experience levels. Distance was successfully used to track improvements with practice. Examining volume of resection demonstrated that attending surgeons removed less simulated tumor but preserved more normal tissue than trainees. More recently, APMs have been used in machine learning algorithms to predict level of training with a high degree of accuracy. Key limitations to enhanced-reality systems include limited AR usage for automated surgical assessment and lack of external and longitudinal validation of VR systems. CONCLUSIONS VR has been used to assess surgeon performance across a wide spectrum of domains. The VR environment can be used to quantify surgeon performance, assess surgeon proficiency, and track training progression. AR systems have not yet been used to provide metrics for surgeon performance assessment despite potential for intraoperative integration. VR-based APMs may be especially useful for metrics that are difficult to assess intraoperatively, including blood loss and extent of resection.