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Introduction Anterior Lumbar Interbody Fusion (ALIF) is a commonly performed spine surgery procedure used to treat lumbar conditions such as degenerative disc disease, spondylolisthesis, and spinal deformities. Traditionally, it has been performed using open and mini-open surgical techniques. Recently, however, laparoscopic and robotic-assisted ALIF have gained attention for their potential benefits, including shorter recovery times, fewer complications, and improved patient outcomes. However, the safety, effectiveness, and long-term outcomes of these newer techniques remain to be fully compared to conventional methods. Methods The systematic review was conducted in accordance with the PRISMA 2020 guidelines. MEDLINE and Cochrane databases were searched for studies on laparoscopic and robotic approaches to the anterior spine, with a focus on ALIF. Article selection and data extraction were independently conducted by two reviewers. Studies involving animal models, non-ALIF robotic techniques, or non-English publications were excluded. Results A total of 650 articles were initially identified. After screening, a full-text review was conducted on 80 articles, of which 48 studies met the inclusion criteria: 42 focused on laparoscopic ALIF (L-ALIF) and 6 on robotic-assisted ALIF (R-ALIF). Laparoscopic ALIF achieved similar outcomes to mini-open methods, offering limited consistent benefits while presenting challenges such as a steep learning curve and a higher risk of retrograde ejaculation. Data on robotic-assisted ALIF, though limited, indicated improved precision and a reduced rate of intraoperative complications. However, high costs, logistical challenges, and the lack of substantial long-term outcome data remain significant barriers to the broader adoption of this technique in spine surgery. Conclusion L-ALIF and R-ALIF present promising minimally invasive alternatives to mini-open ALIF approaches. L-ALIF yields outcomes similar to mini-open techniques, though its technical demands warrant careful consideration. R-ALIF shows potential for improved precision and reduced complications, but logistical and financial constraints limit its wider adoption. Future studies should focus on multicenter prospective trials, alongside efforts to reduce costs and enhance training, to refine the role of these techniques in optimizing patient outcomes.

Eosinophilic granuloma (EG) represents a local form of Langerhans cell histiocytosis that occurs mostly in children. It usually presents with a gradually enlarging painless skull mass, and rarely presents a rapid clinical deterioration. This 7-year-old boy who was diagnosed with EG, based on a magnetic resonance imaging scan, after presenting with a painless right parietal swelling of 7-week duration. Three weeks prior his scheduled surgery, he presented to the emergency department with a 2-day history of sudden increased of the subcutaneous swelling associated with a headache, vomiting, and decreased the level of consciousness; there was no history of trauma. Brain computed tomography revealed a right parietal bone defect with large subgaleal and extradural hematoma. He underwent emergent surgical excision of the skull lesion and evacuation of the hematoma. Histopathological examination confirmed the diagnosis of EG. We aim to raise the awareness of physicians of this rare spontaneous hemorrhagic complication of EG and review the literature.

To better understand the emerging role of artificial intelligence (AI) in surgical training, efficacy of AI tutoring systems, such as the Virtual Operative Assistant (VOA), must be tested and compared with conventional approaches. To determine how VOA and remote expert instruction compare in learners' skill acquisition, affective, and cognitive outcomes during surgical simulation training. This instructor-blinded randomized clinical trial included medical students (undergraduate years 0-2) from 4 institutions in Canada during a single simulation training at McGill Neurosurgical Simulation and Artificial Intelligence Learning Centre, Montreal, Canada. Cross-sectional data were collected from January to April 2021. Analysis was conducted based on intention-to-treat. Data were analyzed from April to June 2021. The interventions included 5 feedback sessions, 5 minutes each, during a single 75-minute training, including 5 practice sessions followed by 1 realistic virtual reality brain tumor resection. The 3 intervention arms included 2 treatment groups, AI audiovisual metric-based feedback (VOA group) and synchronous verbal scripted debriefing and instruction from a remote expert (instructor group), and a control group that received no feedback. The coprimary outcomes were change in procedural performance, quantified as Expertise Score by a validated assessment algorithm (Intelligent Continuous Expertise Monitoring System [ICEMS]; range, -1.00 to 1.00) for each practice resection, and learning and retention, measured from performance in realistic resections by ICEMS and blinded Objective Structured Assessment of Technical Skills (OSATS; range 1-7). Secondary outcomes included strength of emotions before, during, and after the intervention and cognitive load after intervention, measured in self-reports. A total of 70 medical students (41 [59%] women and 29 [41%] men; mean [SD] age, 21.8 [2.3] years) from 4 institutions were randomized, including 23 students in the VOA group, 24 students in the instructor group, and 23 students in the control group. All participants were included in the final analysis. ICEMS assessed 350 practice resections, and ICEMS and OSATS evaluated 70 realistic resections. VOA significantly improved practice Expertise Scores by 0.66 (95% CI, 0.55 to 0.77) points compared with the instructor group and by 0.65 (95% CI, 0.54 to 0.77) points compared with the control group (P < .001). Realistic Expertise Scores were significantly higher for the VOA group compared with instructor (mean difference, 0.53 [95% CI, 0.40 to 0.67] points; P < .001) and control (mean difference. 0.49 [95% CI, 0.34 to 0.61] points; P < .001) groups. Mean global OSATS ratings were not statistically significant among the VOA (4.63 [95% CI, 4.06 to 5.20] points), instructor (4.40 [95% CI, 3.88-4.91] points), and control (3.86 [95% CI, 3.44 to 4.27] points) groups. However, on the OSATS subscores, VOA significantly enhanced the mean OSATS overall subscore compared with the control group (mean difference, 1.04 [95% CI, 0.13 to 1.96] points; P = .02), whereas expert instruction significantly improved OSATS subscores for instrument handling vs control (mean difference, 1.18 [95% CI, 0.22 to 2.14]; P = .01). No significant differences in cognitive load, positive activating, and negative emotions were found. In this randomized clinical trial, VOA feedback demonstrated superior performance outcome and skill transfer, with equivalent OSATS ratings and cognitive and emotional responses compared with remote expert instruction, indicating advantages for its use in simulation training. ClinicalTrials.gov Identifier: NCT04700384.

INTRODUCTION Several radiographic methods exist to identify the Rolandic Sulcus (RS). The radiographic relationship between the RS and the central insular sulcus (CIS), specifically on magnetic resonance imaging (MRI), has not been studied. METHODS We reviewed one hundred consecutive normal MRI studies performed at our institution (Sept to Oct 2019). Sagittal and axial FLAIR and T2 sequences were chosen for the best sulcal anatomy. The first step was to identify all the insular sulci of the insular gray matter on the sagittal images. A straight line was then drawn from the CIS to the dorsal cortical surface, and the sulcus in continuity with the CIS was marked. The second step was to confirm the RS by comparing the location of the hand motor area (omega sign or hand knob sign) on the axial and sagittal scans. RESULTS We have reviewed 1233 consecutive MRIs, of which 100 normal MRI studies were included for review (200 hemispheres). The median age of patients was 49.5 years [18-81 years] and 66 patients (66%) were females. The CIS was easily identified in 198 hemispheres (99%). Out of the 198 hemispheres, the CIS was in continuity with the presumed RS in 191 hemispheres (96.5%). This was confirmed in all cases by correlating the presumed RS with the hand motor area (HMA) on axial images. In the remaining seven, the CIS was in continuity with the precentral sulcus (PCS) in 5 hemispheres (2.5%) and with the postcentral sulcus (PoCS) in two hemispheres (1%). The hand motor area (HMA), identified as a hook or a C-shaped structure on sagittal images, was visible in the same section as the CIS in 166 hemispheres (86.9%), but medially in the remaining 25 hemispheres (13.1%). The CIS/RS correlation, however, remained consistent in all instances. CONCLUSION The CIS can be utilized as a highly reliable radiographic landmark for the identification of the RS. Identification of the HMA can also be done reliably with this method.

Importance To better elucidate the role of artificial intelligence (AI) in surgical skills training requires investigations in the potential existence of a hidden curriculum. Objective To assess the pedagogical value of AI-selected technical competencies and their extended effects in surgical simulation training. Design, Setting, and Participants This cohort study was a follow-up of a randomized clinical trial conducted at the Neurosurgical Simulation and Artificial Intelligence Learning Centre at the Montreal Neurological Institute, McGill University, Montreal, Canada. Surgical performance metrics of medical students exposed to an AI-enhanced training curriculum were compared with a control group of participants who received no feedback and with expert benchmarks. Cross-sectional data were collected from January to April 2021 from medical students and from March 2015 to May 2016 from experts. This follow-up secondary analysis was conducted from June to September 2022. Participants included medical students (undergraduate year 0-2) in the intervention cohorts and neurosurgeons to establish expertise benchmarks. Exposure Performance assessment and personalized feedback by an intelligent tutor on 4 AI-selected learning objectives during simulation training. Main Outcomes and Measures Outcomes of interest were unintended performance outcomes, measured by significant within-participant difference from baseline in 270 performance metrics in the intervention cohort that was not observed in the control cohort. Results A total of 46 medical students (median [range] age, 22 [18-27] years; 27 [59%] women) and 14 surgeons (median [range] age, 45 [35-59] years; 14 [100%] men) were included in this study, and no participant was lost to follow-up. Feedback on 4 AI-selected technical competencies was associated with additional performance change in 32 metrics over the entire procedure and 20 metrics during tumor removal that was not observed in the control group. Participants exposed to the AI-enhanced curriculum demonstrated significant improvement in safety metrics, such as reducing the rate of healthy tissue removal (mean difference, −7.05 × 10−5[95% CI, −1.09 × 10−4to −3.14 × 10−5] mm3per 20 ms;P < .001) and maintaining a focused bimanual control of the operative field (mean difference in maximum instrument divergence, −4.99 [95% CI, −8.48 to −1.49] mm,P = .006) compared with the control group. However, negative unintended effects were also observed. These included a significantly lower velocity and acceleration in the dominant hand (velocity: mean difference, −0.13 [95% CI, −0.17 to −0.09] mm per 20 ms;P < .001; acceleration: mean difference, −2.25 × 10−2[95% CI, −3.20 × 10−2to −1.31 × 10−2] mm per 20 ms2;P < .001) and a significant reduction in the rate of tumor removal (mean difference, −4.85 × 10−5[95% CI, −7.22 × 10−5to −2.48 × 10−5] mm3per 20 ms;P < .001) compared with control. These unintended outcomes diverged students’ movement and efficiency performance metrics away from the expertise benchmarks. Conclusions and Relevance In this cohort study of medical students, an AI-enhanced curriculum for bimanual surgical skills resulted in unintended changes that improved performance in safety but negatively affected some efficiency metrics. Incorporating AI in course design requires ongoing assessment to maintain transparency and foster evidence-based learning objectives.

Introduction: Multiple studies have demonstrated the effectiveness of virtual reality (VR) simulators in surgical skills training and assessment. Anterior cervical discectomy and fusion (ACDF) is among the most common spine procedures and requires trainees to master a broad spectrum of surgical techniques. The Sim-ortho VR simulator provides a validated anterior cervical discectomy and fusion (ACDF) simulated task. This validated tool can be used in the evaluation and assessment of surgical skill.Objective This thesis aims to analyze the three-dimensional data recorded by the Sim-Ortho VR simulator platform during the discectomy component of the ACDF task. We aim to use the generated data to develop novel metrics to assess the performance of participants with different levels of expertise.HypothesisWe hypothesize that the results of this analysis would establish a methodology to develop novel metrics that can identify performance variability between different groups of expertise and provide new insights into surgical expertise.MethodsWe recruited participants with different levels of expertise to perform a standardized ACDF simulation task. The three-dimensional structural data were generated from the simulator and recorded after each step. We collected and analyzed different data including volumes of each structure at different stages of the procedure and rate of removal of the disc. Statistical significance was set as p < 0.05.ResultsTwenty-seven participants were included and divided into three groups based on their surgical expertise: medical student, resident, and post-resident groups. Medical students took longer to perform the discectomy compared to the other groups and left almost three times of disc residual as the resident and post-resident groups (p = 0.068). During the annulotomy component, the post-resident group removed 47.4% more disc than the resident and 102% more than the medical student group (p = 0.03). No statistically significant differences between groups were found during the second stage of the discectomy regarding disc residual and rate of removal. The post-resident group spent 19.1% of their surgical time actively working on areas adjacent to the dura, compared to 13.7% and 5.1% in the resident and medical student groups, respectively (p = 0.017).ConclusionExpert performance is associated with higher efficiency compared to resident and medical student groups. The amount removed and rate of removal represent other features of expertise during the annulotomy stage of the discectomy. These differences expose some of the features of experts’ performance that can be further studied and taught to junior trainees

Background and objective Sacroiliac joint (SIJ) dysfunction, a frequently underdiagnosed cause of low back pain, remains relatively understudied. Minimally invasive methods, including navigation and robotic technology, are gaining popularity due to their lower surgical risks. This study aimed to compare outcomes of navigation-assisted (NA) SIJ fusion and robotic-assisted (RA) SIJ fusion performed at our institution. Methods We retrospectively reviewed adult patients who underwent SIJ fusion between November 2022 and September 2024. Details of demographic data, operative details (OR time, screw placement accuracy), postoperative complications, and pain scores (preoperative, postoperative) were collected. Changes in pain scores and surgical metrics were compared between the NA and RA groups. Results Our study included 31 patients who underwent SIJ fusion during the study period: 19 with NA and 12 with RA. Both cohorts were comparable at baseline in age (p=0.416), BMI (p=0.478), and prior surgeries (p=0.879). The group comprised 21 females and 10 males, with an average age of 65.5 years. Operative time was significantly longer in the RA group (p<0.001). Regarding screw placement accuracy, no intraoperative screw misplacements occurred in either group. The NA cohort had 10.3% improvement in their pain scores within 30 days postoperatively, while the RA group had 31.0% improvement (p=0.52). No postoperative complication necessitating a revision surgery occurred in the patient cohort. Two hardware failures (screw fractures) were observed in the NA group without worsening of symptoms. Long-term pain outcomes were also comparable, showing an improvement of around 5% in the RA group and 62% in the NA group (p=0.083). Conclusions While there was no statistically significant difference between the groups, a trend toward lower postoperative pain scores was observed in the RA group. The extended operative time in the RA group is attributable to the new technique at our hospital.

Background: Lack of surgical apprenticeship caused by the COVID-19 pandedmic has limited learners preparation for residency and may impair their psychomotor competence. Using virtual reality simulation and videotelephony technology, we designed a telementoring opportunity for medical students interested in surgery to receive expert coaching for technical skill acquisition. The following report outlines this innovative approach and investigates its effectiveness. Methods: In a 3-week workshop, senior neurosurgery residents were trained to teach brain tumour resection techniques using the Objective Structured Assessment of Technical Skills (OSATS) rating scale and the Promoting Excellence And Reflective Learning in Simulation (PEARLS) debriefing guide for assessment and feedback, respectively. Medical students were recruited to participate in neurosurgical simulation training. Participants performed 5 tumour resections for practice and 1 complex tumour resection for skill evaluation. The intervention's effectiveness was measured and compared with a no-feedback control grroup using the final resection's blinded OSATS rating in a randomized controlled trial. Results: Good interrater reliability (intraclass correlation coefficient = 0.84) was achieved, and the OSATS scale demonstrated good internal consistency (a = 0.82). Forty-seven medical students from 4 institutions were randomly assigned to instructor (n = 23) and control (n = 23) groups. In the instructor group, live on-screen performance of participants was assessed remotely with verbal debriefing provided upon completion of each practice resection. No performance assessment or feedback was provided to the control group. Blinded OSATS assessment showed that instructor feedback significantly enhanced respect for tissue (p = 0.027), economy of movement (p = 0.024), and instrument handling (p = 0.012). Conclusion: Residents were engaged in providing effective assessment and feedback in remote-based simulation training for undergraduate medical students.

Background: Bimanual psychomotor skills are essential to surgical education, therefore medical trainees require multiple opportunities to master their skills. However, developing these technical skills can be a highly stressful and emotional experience. Therefore, we sought to investigate the impact of emotions on performance outcomes in surgical simulation training through the following research questions. Do emotions measured at baseline group students in a meaningful way? Do students' membership in emotion groups predict students' change in performance? Methods: Participants completed 5 practice simulated brain tumour resections followed by 1 realistic virtual reality simulated brain tumour resection; after each simulation, an expertise score was generated. Students also completed a survey on emotions prior to simulations. We used a multivariate clustering approach to group students by their emotions and then conducted regression analysis to examine the predictive relationship between emotion groups and performance change. Results: Seventy-two medical students participated in the study. Cluster analysis identified 3 distinct emotion groups: high positive- and negative-activating emotions (group 1, n = 31), high positive-activating and -deactivating emotions (group 2, n = 22), and low emotions (group 3, n = 19). Regression analysis revealed membership in group 1 significantly predicted positive performance change from fifth practice expertise score to sixth realistic simulated tumour resection expertise score (R2 = 0.05, T1,70 = 4.023, p = 0.049). Conclusion: Our study showed that students who experienced more activating emotions tended to show positive performance change as they shifted from practice to realistic simulations. Students' emotions should be considered during surgical simulation to promote better learning and transfer of skills.