Development of a Perfusion-Based Cadaveric Simulation Model Integrated into Neurosurgical Training: Feasibility Based On Reconstitution of Vascular and Cerebrospinal Fluid Systems

Endoscopic Posterior Approach for Cervical Myelopathy and Radiculopathy Using Tubular Retractor: Our Experience, Surgical Technique, and Literature Review

BACKGROUND

Endoscopic posterior approach can effectively decompress cervical root and cord secondary to posterior compression. We present our experience in 229 patients using tubular retractor, and the relevant literature is reviewed.

METHODS

Retrospective analysis of multilevel myelopathy and or radiculopathy was performed. Indications for posterior approach was primary posterior compressions at cord and or root. Combined compression from posterior side and mild to moderate anterior pressure with acceptable lordosis were also decompressed. Bilateral cord decompression and foraminotomy for radiculopathy was performed using tubular retractor.

RESULT

Myelopathy and radiculopathy were present in 220 and 9 patients, respectively. A total of 53 foraminotomy procedures were performed in 36 patients. All patients showed improvement, with the mean preoperative Nurick grade decreasing from 2.72 ± 0.799 to 0.78 ± 0.911 after surgery. There was significant improvement in postoperative Nurick grades compared with preoperative grades (Z-value = 13.306, P < 0.0001). Operative results were better in patients with good preoperative Nurick grades (grades 1 and 2) compared with those with poorer grades (grades 3 and 4). Minor bleeding, small dural tear, and root injury were observed in 42, 4, and 8 patients, respectively.

CONCLUSIONS

Endoscopic approach was effective and safe for root and cord decompression. This study was limited by its single-center, retrospective design, exclusion of some eligible patients, a short postoperative Nurick grade assessment period of 6 months, and absence of a comprehensive long-term postoperative biomechanical assessment. To validate these results, a prospective multicenter study addressing these limitations is needed.

Development and Validation of a Novel Human-Fixed Cadaveric Model Reproducing Cerebrospinal Fluid Circulation for Simulation of Endoscopic Endonasal Skull Base Surgery

BACKGROUND AND OBJECTIVES

Endoscopic endonasal surgery is a well-established surgical approach to the skull base. Surgeons need a reusable long-lasting tool to acquire the skills needed for skull base reconstruction. The aim of this study was to elaborate and validate a human formalin-fixed cadaveric model that reproduces a realistic cerebrospinal fluid (CSF) circulation and that adequately renders a CSF leak.

METHODS

An external ventricular drain that connects with a peristaltic pump is placed in the subarachnoid space, which allows a water circulation that reproduces CSF circulation. Intracranial pressure is measured in real time. Endoscopic endonasal skull base approaches are performed, to create different skull base openings and CSF leaks. Participants were tasked with reconstruction of the defects using a standardized multilayered approach, with the goal of obtaining a watertight closure under normal intracranial pressure ranges. Compiled data included time of reconstruction, years of experience of participants, and success/failure to achieve a watertight reconstruction. A Likert questionnaire was also used.

RESULTS

The cadaveric model reproduced CSF circulation in 4 types of dural defects: sellar, suprasellar, transcribriform, and transclival. Intracranial pressures were similar to physiological conditions and were reproducible. Each model was tested multiple times, over several months. Success rates concurred with training levels (r = .8282 and P = .0017). A strong inverse correlation was also found between years of experience and time of reconstruction (r = .4977 and P < .0001). Participants agreed that the model was realistic (median Likert score of 4), and they strongly agreed that it allowed for the improvement of their surgical skills (median Likert score of 5).

CONCLUSION

This novel human-fixed cadaveric model for CSF circulation is efficient and adequately reproduces surgical conditions for skull base approaches. The model is unique, easy to reproduce, and reusable. It can be used as a tool for teaching and for research purposes.

SimLife®: A New Dynamic Model for Head and Neck Surgical Oncology Simulation

The SimLife® model consists in a human cadaver dynamized by pulsatile vascularization. The objective was to evaluate the face, contents, and constructs validity of the SimLife® model in head and neck surgical oncology simulation. Head and neck surgical oncology simulation sessions on SimLife® models were organized with lateral neck dissection and total laryngectomy. Face and contents validity were addressed by questionnaires. Constructs validity was assessed by objective structured assessment of technical skills (OSATS) score. High realism was demonstrated for consistency of tissues (7.1 ± 1.4), color of arteries and veins (7.3 ± 1.9, 8.5 ± 1.1, respectively), and vein consistency (8.5 ± 1.2). The mean OSATS score was 19.7 ± 5.4 for residents and 32.7 ± 1.9 for senior surgeon (P = .0022). SimLife® is a hyperrealistic model for head and neck surgical oncology simulation and it might become a core component of the surgical resident curriculum.

Latex vascular injection as method for enhanced neurosurgical training and skills

Background

Tridimensional medical knowledge of human anatomy is a key step in the undergraduate and postgraduate medical education, especially in surgical fields. Training simulation before real surgical procedures is necessary to develop clinical competences and to minimize surgical complications.

Methods

Latex injection of vascular system in brain and in head-neck segment is made after washing out of the vascular system and fixation of the specimen before and after latex injection.

Results

Using this latex injection technique, the vascular system of 90% of brains and 80% of head-neck segments are well-perfused. Latex-injected vessels maintain real appearance compared to silicone, and more flexible vessels compared to resins. Besides, latex makes possible a better perfusion of small vessels.

Conclusions

Latex vascular injection technique of the brain and head-neck segment is a simulation model for neurosurgical training based on real experiencing to improve surgical skills and surgical results.

Simulated outcomes for durotomy repair in minimally invasive spine surgery

Minimally invasive spine surgery (MISS) is increasingly performed using endoscopic and microscopic visualization, and the captured video can be used for surgical education and development of predictive artificial intelligence (AI) models. Video datasets depicting adverse event management are also valuable, as predictive models not exposed to adverse events may exhibit poor performance when these occur. Given that no dedicated spine surgery video datasets for AI model development are publicly available, we introduce Simulated Outcomes for Durotomy Repair in Minimally Invasive Spine Surgery (SOSpine). A validated MISS cadaveric dural repair simulator was used to educate neurosurgery residents, and surgical microscope video recordings were paired with outcome data. Objects including durotomy, needle, grasper, needle driver, and nerve hook were then annotated. Altogether, SOSpine contains 15,698 frames with 53,238 annotations and associated durotomy repair outcomes. For validation, an AI model was fine-tuned on SOSpine video and detected surgical instruments with a mean average precision of 0.77. In summary, SOSpine depicts spine surgeons managing a common complication, providing opportunities to develop surgical AI models.

Pilot Analysis of Surgeon Instrument Utilization Signatures Based on Shannon Entropy and Deep Learning for Surgeon Performance Assessment in a Cadaveric Carotid Artery Injury Control Simulation

BACKGROUND AND OBJECTIVES

Assessment and feedback are critical to surgical education, but direct observational feedback by experts is rarely provided because of time constraints and is typically only qualitative. Automated, video-based, quantitative feedback on surgical performance could address this gap, improving surgical training. The authors aim to demonstrate the ability of Shannon entropy (ShEn), an information theory metric that quantifies series diversity, to predict surgical performance using instrument detections generated through deep learning.

METHODS

Annotated images from a publicly available video data set of surgeons managing endoscopic endonasal carotid artery lacerations in a perfused cadaveric simulator were collected. A deep learning model was implemented to detect surgical instruments across video frames. ShEn score for the instrument sequence was calculated from each surgical trial. Logistic regression using ShEn was used to predict hemorrhage control success.

RESULTS

ShEn scores and instrument usage patterns differed between successful and unsuccessful trials (ShEn: 0.452 vs 0.370, P < .001). Unsuccessful hemorrhage control trials displayed lower entropy and less varied instrument use patterns. By contrast, successful trials demonstrated higher entropy with more diverse instrument usage and consistent progression in instrument utilization. A logistic regression model using ShEn scores (78% accuracy and 97% average precision) was at least as accurate as surgeons' attending/resident status and years of experience for predicting trial success and had similar accuracy as expert human observers.

CONCLUSION

ShEn score offers a summative signal about surgeon performance and predicted success at controlling carotid hemorrhage in a simulated cadaveric setting. Future efforts to generalize ShEn to additional surgical scenarios can further validate this metric.

Resident Training in Spine Surgery: A Systematic Review of Simulation-Based Educational Models

OBJECTIVE

With the increasing prevalence of spine surgery, ensuring effective resident training is becoming of increasing importance. Training safe, competent surgeons relies heavily on effective teaching of surgical indications and adequate practice to achieve a minimum level of technical proficiency before independent practice. American Council of Graduate Medical Education work-hour restrictions have complicated the latter, forcing programs to identify novel methods of surgical resident training. Simulation-based training is one such method that can be used to complement traditional training. The present review aims to evaluate the educational success of simulation-based models in the spine surgical training of residents.

METHODS

Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, the PubMed, Web of Science, and Google Scholar databases were systematically screened for English full-text studies examining simulation-based spine training curricula. Studies were categorized based on simulation model class, including animal-cadaveric, human-cadaveric, physical/3-dimensional, and computer-based/virtual reality. Outcomes studied included participant feedback regarding the simulator and competency metrics used to evaluate participant performance.

RESULTS

Seventy-two studies were identified. Simulators displayed high face validity and were useful for spine surgery training. Objective measures used to evaluate procedural performance included implant placement evaluation, procedural time, and technical skill assessment, with numerous simulators demonstrating a learning effect.

CONCLUSIONS

While simulation-based educational models are one potential means of training residents to perform spine surgery, traditional in-person operating room training remains pivotal. To establish the efficacy of simulators, future research should focus on improving study quality by leveraging longitudinal study designs and correlating simulation-based training with clinical outcome measures.

Seven bypasses simulation set: description and validity assessment of novel models for microneurosurgical training

OBJECTIVE

Microsurgical training remains indispensable to master cerebrovascular bypass procedures, but simulation models for training that accurately replicate microanastomosis in narrow, deep-operating corridors are lacking. Seven simulation bypass scenarios were developed that included head models in various surgical positions with premade approaches, simulating the restrictions of the surgical corridors and hand positions for microvascular bypass training. This study describes these models and assesses their validity.

METHODS

Simulation models were created using 3D printing of the skull with a designed craniotomy. Brain and external soft tissues were cast using a silicone molding technique from the clay-sculptured prototypes. The 7 simulation scenarios included: 1) temporal craniotomy for a superficial temporal artery (STA)-middle cerebral artery (MCA) bypass using the M4 branch of the MCA; 2) pterional craniotomy and transsylvian approach for STA-M2 bypass; 3) bifrontal craniotomy and interhemispheric approach for side-to-side bypass using the A3 branches of the anterior cerebral artery; 4) far lateral craniotomy and transcerebellomedullary approach for a posterior inferior cerebellar artery (PICA)-PICA bypass or 5) PICA reanastomosis; 6) orbitozygomatic craniotomy and transsylvian-subtemporal approach for a posterior cerebral artery bypass; and 7) extended retrosigmoid craniotomy and transcerebellopontine approach for an occipital artery-anterior inferior cerebellar artery bypass. Experienced neurosurgeons evaluated each model by practicing the aforementioned bypasses on the models. Face and content validities were assessed using the bypass participant survey.

RESULTS

A workflow for model production was developed, and these models were used during microsurgical courses at 2 neurosurgical institutions. Each model is accompanied by a corresponding prototypical case and surgical video, creating a simulation scenario. Seven experienced cerebrovascular neurosurgeons practiced microvascular anastomoses on each of the models and completed surveys. They reported that actual anastomosis within a specific approach was well replicated by the models, and difficulty was comparable to that for real surgery, which confirms the face validity of the models. All experts stated that practice using these models may improve bypass technique, instrument handling, and surgical technique when applied to patients, confirming the content validity of the models.

CONCLUSIONS

The 7 bypasses simulation set includes novel models that effectively simulate surgical scenarios of a bypass within distinct deep anatomical corridors, as well as hand and operator positions. These models use artificial materials, are reusable, and can be implemented for personal training and during microsurgical courses.

Use of surgical video-based automated performance metrics to predict blood loss and success of simulated vascular injury control in neurosurgery: a pilot study

OBJECTIVE

Experts can assess surgeon skill using surgical video, but a limited number of expert surgeons are available. Automated performance metrics (APMs) are a promising alternative but have not been created from operative videos in neurosurgery to date. The authors aimed to evaluate whether video-based APMs can predict task success and blood loss during endonasal endoscopic surgery in a validated cadaveric simulator of vascular injury of the internal carotid artery.

METHODS

Videos of cadaveric simulation trials by 73 neurosurgeons and otorhinolaryngologists were analyzed and manually annotated with bounding boxes to identify the surgical instruments in the frame. APMs in five domains were defined-instrument usage, time-to-phase, instrument disappearance, instrument movement, and instrument interactions-on the basis of expert analysis and task-specific surgical progressions. Bounding-box data of instrument position were then used to generate APMs for each trial. Multivariate linear regression was used to test for the associations between APMs and blood loss and task success (hemorrhage control in less than 5 minutes). The APMs of 93 successful trials were compared with the APMs of 49 unsuccessful trials.

RESULTS

In total, 29,151 frames of surgical video were annotated. Successful simulation trials had superior APMs in each domain, including proportionately more time spent with the key instruments in view (p < 0.001) and less time without hemorrhage control (p = 0.002). APMs in all domains improved in subsequent trials after the participants received personalized expert instruction. Attending surgeons had superior instrument usage, time-to-phase, and instrument disappearance metrics compared with resident surgeons (p < 0.01). APMs predicted surgeon performance better than surgeon training level or prior experience. A regression model that included APMs predicted blood loss with an R2 value of 0.87 (p < 0.001).

CONCLUSIONS

Video-based APMs were superior predictors of simulation trial success and blood loss than surgeon characteristics such as case volume and attending status. Surgeon educators can use APMs to assess competency, quantify performance, and provide actionable, structured feedback in order to improve patient outcomes. Validation of APMs provides a benchmark for further development of fully automated video assessment pipelines that utilize machine learning and computer vision.

Expert surgeons and deep learning models can predict the outcome of surgical hemorrhage from 1 min of video

Major vascular injury resulting in uncontrolled bleeding is a catastrophic and often fatal complication of minimally invasive surgery. At the outset of these events, surgeons do not know how much blood will be lost or whether they will successfully control the hemorrhage (achieve hemostasis). We evaluate the ability of a deep learning neural network (DNN) to predict hemostasis control ability using the first minute of surgical video and compare model performance with human experts viewing the same video. The publicly available SOCAL dataset contains 147 videos of attending and resident surgeons managing hemorrhage in a validated, high-fidelity cadaveric simulator. Videos are labeled with outcome and blood loss (mL). The first minute of 20 videos was shown to four, blinded, fellowship trained skull-base neurosurgery instructors, and to SOCALNet (a DNN trained on SOCAL videos). SOCALNet architecture included a convolutional network (ResNet) identifying spatial features and a recurrent network identifying temporal features (LSTM). Experts independently assessed surgeon skill, predicted outcome and blood loss (mL). Outcome and blood loss predictions were compared with SOCALNet. Expert inter-rater reliability was 0.95. Experts correctly predicted 14/20 trials (Sensitivity: 82%, Specificity: 55%, Positive Predictive Value (PPV): 69%, Negative Predictive Value (NPV): 71%). SOCALNet correctly predicted 17/20 trials (Sensitivity 100%, Specificity 66%, PPV 79%, NPV 100%) and correctly identified all successful attempts. Expert predictions of the highest and lowest skill surgeons and expert predictions reported with maximum confidence were more accurate. Experts systematically underestimated blood loss (mean error - 131 mL, RMSE 350 mL, R2 0.70) and fewer than half of expert predictions identified blood loss > 500 mL (47.5%, 19/40). SOCALNet had superior performance (mean error - 57 mL, RMSE 295 mL, R2 0.74) and detected most episodes of blood loss > 500 mL (80%, 8/10). In validation experiments, SOCALNet evaluation of a critical on-screen surgical maneuver and high/low-skill composite videos were concordant with expert evaluation. Using only the first minute of video, experts and SOCALNet can predict outcome and blood loss during surgical hemorrhage. Experts systematically underestimated blood loss, and SOCALNet had no false negatives. DNNs can provide accurate, meaningful assessments of surgical video. We call for the creation of datasets of surgical adverse events for quality improvement research.

Code-free machine learning for object detection in surgical video: a benchmarking, feasibility, and cost study

OBJECTIVE

While the utilization of machine learning (ML) for data analysis typically requires significant technical expertise, novel platforms can deploy ML methods without requiring the user to have any coding experience (termed AutoML). The potential for these methods to be applied to neurosurgical video and surgical data science is unknown.

METHODS

AutoML, a code-free ML (CFML) system, was used to identify surgical instruments contained within each frame of endoscopic, endonasal intraoperative video obtained from a previously validated internal carotid injury training exercise performed on a high-fidelity cadaver model. Instrument-detection performances using CFML were compared with two state-of-the-art ML models built using the Python coding language on the same intraoperative video data set.

RESULTS

The CFML system successfully ingested surgical video without the use of any code. A total of 31,443 images were used to develop this model; 27,223 images were uploaded for training, 2292 images for validation, and 1928 images for testing. The mean average precision on the test set across all instruments was 0.708. The CFML model outperformed two standard object detection networks, RetinaNet and YOLOv3, which had mean average precisions of 0.669 and 0.527, respectively, in analyzing the same data set. Significant advantages to the CFML system included ease of use, relatively low cost, displays of true/false positives and negatives in a user-friendly interface, and the ability to deploy models for further analysis with ease. Significant drawbacks of the CFML model included an inability to view the structure of the trained model, an inability to update the ML model once trained with new examples, and the inability for robust downstream analysis of model performance and error modes.

CONCLUSIONS

This first report describes the baseline performance of CFML in an object detection task using a publicly available surgical video data set as a test bed. Compared with standard, code-based object detection networks, CFML exceeded performance standards. This finding is encouraging for surgeon-scientists seeking to perform object detection tasks to answer clinical questions, perform quality improvement, and develop novel research ideas. The limited interpretability and customization of CFML models remain ongoing challenges. With the further development of code-free platforms, CFML will become increasingly important across biomedical research. Using CFML, surgeons without significant coding experience can perform exploratory ML analyses rapidly and efficiently.

Utility of the Simulated Outcomes Following Carotid Artery Laceration Video Data Set for Machine Learning Applications

IMPORTANCE

Surgical data scientists lack video data sets that depict adverse events, which may affect model generalizability and introduce bias. Hemorrhage may be particularly challenging for computer vision-based models because blood obscures the scene.

OBJECTIVE

To assess the utility of the Simulated Outcomes Following Carotid Artery Laceration (SOCAL)-a publicly available surgical video data set of hemorrhage complication management with instrument annotations and task outcomes-to provide benchmarks for surgical data science techniques, including computer vision instrument detection, instrument use metrics and outcome associations, and validation of a SOCAL-trained neural network using real operative video.

DESIGN, SETTING, AND PARTICIPANTS

For this quailty improvement study, a total of 75 surgeons with 1 to 30 years' experience (mean, 7 years) were filmed from January 1, 2017, to December 31, 2020, managing catastrophic surgical hemorrhage in a high-fidelity cadaveric training exercise at nationwide training courses. Videos were annotated from January 1 to June 30, 2021.

INTERVENTIONS

Surgeons received expert coaching between 2 trials.

MAIN OUTCOMES AND MEASURES

Hemostasis within 5 minutes (task success, dichotomous), time to hemostasis (in seconds), and blood loss (in milliliters) were recorded. Deep neural networks (DNNs) were trained to detect surgical instruments in view. Model performance was measured using mean average precision (mAP), sensitivity, and positive predictive value.

RESULTS

SOCAL contains 31 443 frames with 65 071 surgical instrument annotations from 147 trials with associated surgeon demographic characteristics, time to hemostasis, and recorded blood loss for each trial. Computer vision-based instrument detection methods using DNNs trained on SOCAL achieved a mAP of 0.67 overall and 0.91 for the most common surgical instrument (suction). Hemorrhage control challenges standard object detectors: detection of some surgical instruments remained poor (mAP, 0.25). On real intraoperative video, the model achieved a sensitivity of 0.77 and a positive predictive value of 0.96. Instrument use metrics derived from the SOCAL video were significantly associated with performance (blood loss).

CONCLUSIONS AND RELEVANCE

Hemorrhage control is a high-stakes adverse event that poses unique challenges for video analysis, but no data sets of hemorrhage control exist. The use of SOCAL, the first data set to depict hemorrhage control, allows the benchmarking of data science applications, including object detection, performance metric development, and identification of metrics associated with outcomes. In the future, SOCAL may be used to build and validate surgical data science models.

Improved surgeon performance following cadaveric simulation of internal carotid artery injury during endoscopic endonasal surgery: training outcomes of a nationwide prospective educational intervention

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.

Endoscopic Third Ventriculostomy - A Review

BACKGROUND

Endoscopic third ventriculostomy (ETV) has become a proven modality for treating obstructive and selected cases of communicating hydrocephalus.

OBJECTIVE

This review aims to summarize the indications, preoperative workup, surgical technique, results, postoperative care, complications, advantages, and limitations of an ETV.

MATERIALS AND METHODS

A thorough review of PubMed and Google Scholar was performed. This review is based on the relevant articles and authors' experience.

RESULTS

ETV is indicated in obstructive hydrocephalus and selected cases of communicating hydrocephalus. Studying preoperative imaging is critical, and a detailed assessment of interthalamic adhesions, the thickness of floor, arteries or membranes below the third ventricle floor, and prepontine cistern width is essential. Blunt perforation in a thin floor, while bipolar cautery at low settings and water jet dissection are preferred in a thick floor. The appearance of stoma pulsations and intraoperative ventriculostomography reassure stoma and basal cistern patency. The intraoperative decision for shunt, external ventricular drainage, or Ommaya reservoir can be taken. Magnetic resonance ventriculography and cine phase-contrast magnetic resonance imaging can determine stoma patency. Good postoperative care with repeated cerebrospinal fluid drainage enhances outcomes in selected cases. Though the complications mostly occur in an early postoperative phase, delayed lethal ones may happen. Watching live surgeries, assisting expert surgeons, and practicing on cadavers and models can shorten the learning curve.

CONCLUSION

ETV is an excellent technique for managing obstructive and selected cases of communicating hydrocephalus. Good case selection, methodical technique, and proper training under experts are vital.

3D-printed cranial models simulating operative field depth for microvascular training in neurosurgery

BACKGROUND

The skills required for neurosurgical operations using microsurgical techniques in a deep operating field are difficult to master in the operating room without risk to patients. Although there are many microsurgical training models, most do not use a skull model to simulate a deep field. To solve this problem, 3D models were created to provide increased training in the laboratory before the operating room, improving patient safety.

METHODS

A patient's head was scanned using computed tomography. The data were reconstructed and converted into a standard 3D printing file. The skull was printed with several openings to simulate common surgical approaches. These models were then used to create a deep operating field while practicing on a chicken thigh (femoral artery anastomosis) and on a rat (abdominal aortic anastomosis).

RESULTS

The advantages of practicing with the 3D printed models were clearly demonstrated by our trainees, including appropriate hand position on the skull, becoming comfortable with the depth of the anastomosis, and simulating proper skull angle and rigid fixation. One limitation is the absence of intracranial structures, which is being explored in future work.

CONCLUSION

This neurosurgical model can improve microsurgery training by recapitulating the depth of a real operating field. Improved training can lead to increased accuracy and efficiency of surgical procedures, thereby minimizing the risk to patients.

Simulation of Cerebrospinal Fluid Leak Repair Using a 3-Dimensional Printed Model

BACKGROUND

Acquiring proficiency for the repair of a cerebrospinal fluid (CSF) leak is challenging in great part due to its relative rarity, which offers a finite number of training opportunities.

OBJECTIVE

The purpose of this study was to evaluates the use of a 3-dimensional (3D) printed, anatomically accurate model to simulate CSF leak closure.

METHODS

Volunteer participants completed two simulation sessions. Questionnaires to assess their professional qualifications and a standardized 5-point Likert scale to estimate the level of confidence, were completed before and after each session. Participants were also queried on the overall educational utility of the simulation.

RESULTS

Thirteen otolaryngologists and 11 neurosurgeons, met the inclusion criteria. A successful repair of the CSF leak was achieved by 20/24 (83.33%), and 24/24 (100%) during the first and second simulation sessions respectively (average time 04:04 ± 1.39 and 02:10 ± 01:11). Time-to-close-the-CSF-leak during the second session was significantly shorter than the first (p < 0.001). Confidence scores increased across the training sessions (3.3 ± 1.0, before the simulation, 3.7 ± 0.6 after the first simulation, and 4.2 ± 0.4 after the second simulation; p < 0.001). All participants reported an increase in confidence and believed that the model represented a valuable training tool.

CONCLUSIONS

Despite significant differences with varying clinical scenarios, 3D printed models for cerebrospinal leak repair offer a feasible simulation for the training of residents and novice surgeons outside the constrictions of a clinical environment.

Tracking Scan to Incision Time in Patients with Emergent Operative Traumatic Brain Injuries as a Measure for Systems-Based Practice in Neurosurgical Trainees

BACKGROUND

Evaluation of trainee performance remains a challenge in resident education, particularly for systems-based practice (SysBP) metrics including care coordination and interdisciplinary teamwork. Time to intervention is an important modifiable outcome variable in severe traumatic brain injury (TBI) and may serve as a trackable metric for SysBP evaluation.

METHODS

We retrospectively studied time from computed tomography head scan to surgical incision (CTH-INC, minutes) among neurosurgical trainees treating patients with emergently operative TBI as a proxy SysBP measure. Our institutional operative database was utilized to identify all emergent TBI cases between July 2015 and June 2020. Patients evaluated by program year (PGY)-2 residents proceeding directly to the operating room from the emergency department were included. Statistical analysis was performed using linear regression.

RESULTS

One hundred sixty-six cases triaged by 14 PGY-2 neurosurgical trainees were analyzed. Median CTH-INC was 104 minutes (interquartile range, 82-136 minutes). CTH-INC improved 20.1% over the academic year (95% confidence interval, 4.3%-33.2%, P = 0.015). Between the first and second 6-month periods, the rate of CTH-INC within 90 minutes (29% vs. 46%, P = 0.04) improved. On a per-individual PGY-2 basis, median CTH-INC ranged from 83-127 minutes, 25th percentile CTH-INC ranged from 62-108 minutes, and fastest CTH-INC ranged from 45-92 minutes.

CONCLUSIONS

CTH-INC is an objective and trackable proxy measure for evaluating SysBP during neurosurgical training. Use of CTH-INC or other time metrics in resident evaluations should not supersede the safe and effective delivery of patient care.

The Use of a Novel Perfusion-Based Human Cadaveric Model for Simulation of Dural Venous Sinus Injury and Repair

BACKGROUND

Dural sinus injuries are potentially serious complications associated with acute blood loss. It is imperative that neurosurgery trainees are able to recognize and manage this challenging scenario.

OBJECTIVE

To assess the feasibility of a novel perfusion-based cadaveric simulation model to provide the fundamentals of dural sinus repair to neurosurgical trainees.

METHODS

A total of 10 perfusion-based human cadaveric models underwent superior sagittal sinus (SSS) laceration. Neurosurgery residents were instructed to achieve hemostasis by any method in the first trial and then repeated the trial after watching the instructional dural flap technique video. Trials were timed until hemostasis and control of the region of injury was achieved. Pre- and post-trial questionnaires were administered to assess trainee confidence levels.

RESULTS

The high-flow extravasation of the perfusion-based cadaveric model mimicked similar conditions and challenges encountered during acute SSS injury. Mean ± standard deviation time to hemostasis was 341.3 ± 65 s in the first trial and 196.9 ± 41.8 s in the second trial (P < .0001). Mean trainee improvement time was 144.4 s (42.3%). Of the least-experienced trainees with longest repair times in the initial trial, a mean improvement time of 188.3 s (44.8%) was recorded. All participants reported increased confidence on post-trial questionnaires following the simulation (median pretrial confidence of 2 vs post-trial confidence of 4, P = .002).

CONCLUSION

A perfusion-based human cadaveric model accurately simulates acute dural venous sinus injury, affording neurosurgical trainees the opportunity to hone management skills in a simulated and realistic environment.

Cerebrospinal Fluid Leak Repair Simulation Model: Face, Content, and Construct Validation

Background

Cerebrospinal fluid leak (CSFL) repair simulation models are scarce; however, these models are valuable tools for skull base reconstruction surgery training.

Objectives

This study aims to assess the face, content, and construct validity of a CSFL repair simulation model.

Method

Eight novices (residents- PGY3) and eight experts have performed skull base reconstruction in multiple sites in twelve human cadaveric heads in simulated surgical environment. The experts completed a post-study 21-item questionnaire to assess the face and content validity. The performances of the participants were recorded and scored by two independent investigators who were blinded to the participant's level. Global Rating Scale of Operative Performance (GRSOP) and a Specific Skull Base Reconstruction Checklist (SBRC) were used to score the performances.

Results

The responses from the expert group for the 21-item questionnaire were high for all items (4.13–4.88 out of 5). The internal consistency reliability of the questionnaire and the intraclass correlation, which was derived by Cronbach’s Alpha, were 0.913 and 0.941 respectively. Differences in construct validity between the two groups were statistically significant for both the GRSOP and SBRS (P-value < 0.001).

Conclusion

We demonstrated the face, content, and construct validity of the CSFL repair simulation model, which facilitates the acquisition of technical skills necessary for skull base reconstruction surgery. The model includes realistic features that make it useful in educational courses.

Cadaveric Simulation Training in Cardiothoracic Surgery: A Systematic Review

Simulation training has become increasingly relevant in the educational curriculum of surgical trainees. The types of simulation models used, goals of simulation training, and an objective assessment of its utility and effectiveness are highly variable. The role and effectiveness of cadaveric simulation in cardiothoracic surgical training has not been well established. The objective of this study was to evaluate the current medical literature available on the utility and the effectiveness of cadaveric simulation in cardiothoracic surgical residency training. A literature search was performed using PubMed, Cochrane Library, Embase, Scopus, and CINAHL from inception to February 2019. Of the 362 citations obtained, 23 articles were identified and retrieved for full review, yielding ten eligible articles that were included for analysis. One additional study was identified and included in the analysis. Extraction of data from the selected articles was performed using predetermined data fields, including study design, study participants, simulation task, performance metrics, and costs. Most of these studies were only descriptive of a cadaveric or perfused cadaveric simulation model that could be used to augment clinical operative training in cardiothoracic surgery. There is a paucity of evidence in the literature that specifically evaluates the utility and the efficacy of cadavers in cardiothoracic surgery training. Of the few studies that have been published in the literature, cadaveric simulation does seem to have a role in cardiothoracic surgery training beyond simply learning basic skills. Additional research in this area is needed.

Development and validation of a preclinical model for training and assessment of cerebrospinal fluid leak repair in endoscopic skull base surgery

BACKGROUND

Achieving an effective endoscopic skull base reconstruction in case of large dural defects requires specific training and can be extremely challenging. The aim of this study was to describe the development and validation of a preclinical model for cerebrospinal fluid (CSF) leak repair, which can be used for training and to test the mechanical efficacy of endoscopic skull base reconstruction.

METHODS

Eleven fresh-frozen cadaver heads were dissected. A catheter was inserted in the subdural space via a cervical access, which was sealed with mastic; a vertical graduated tube connected to the catheter measured intracranial pressure (ICP), while stained water was injected intracranially. After endoscopic skull base reconstruction was performed, an expert surgeon assessed its efficacy. ICP was then gradually increased until a leak was evident and CSF leak pressure value was recorded. The correlation between subjective and quantitative evaluations was investigated through Pearson and Spearman correlation tests.

RESULTS

The model was successfully tested in 11 specimens. A single, large dural defect was created in each model (transplanum-transtuberculum = 4; transplanum-transtuberculum-transsellar = 3; transclival = 3; transcribriform-transplanum = 1). Skull base reconstruction always comprised a rigid buttress with temporal fascia and/or fat. The CSF leak pressure ranged from 4 to 110 cmH₂ O. The correlation between expert subjective and quantitative assessment of skull base reconstruction mechanical efficacy was high (r = 0.7; r_s = 0.7; p = 0.010 and p = 0.006, respectively).

CONCLUSION

This preclinical model is simple, easily reproducible, and effective in simulating an intraoperative leak and objectively measures the CSF leak pressure point of a skull base reconstruction.

Beyond the Learning Curve: Comparison of Microscopic and Endoscopic Incidences of Internal Carotid Injury in a Series of Highly Experienced Operators

BACKGROUND

As the endoscopic endonasal approach (EEA) has gained popularity as an alternative to microsurgery (MS) for transsphenoidal resection (TSR), numerous studies have attempted to assess the differential risk of internal carotid artery (ICA) injury between the techniques, yet results have been equivocal and contradictory. The aim of this study was to evaluate ICA injury in MS versus EEA among highly experienced neurosurgeons.

METHODS

We performed a systematic literature review of publications from 2002-2017 reporting ICA injury outcomes in ≥250 cases using MS or EEA.

RESULTS

Seventeen series reporting 11,149 patients were included: 3 MS series, 13 EEA series, and 1 series with adequate samples for each. ICA injury incidences were 0.0%-1.6% in cohorts of 275-3000. MS series documented 5 ICA injuries in 2672 operations, for an overall incidence of 0.2% (range, 0.0%-0.4%), and EEA series reported 30 ICA injuries in 8477 operations, for a 0.4% injury rate (range, 0.0%-1.6%); the difference was nonsignificant (P = 0.25). Increased operative experience was associated with decreased incidence of ICA injury, a finding preserved in the overall study cohort and within discretely examined MS and EEA subgroups (overall r² = 0.08, MS r² = 0.23, EEA r² = 0.07).

CONCLUSIONS

ICA injury is the most serious complication of TSR of pituitary neoplasms. Operator inexperience may be a more important risk factor than choice of surgical technique, given the comparably low rates of injury obtained by highly experienced surgeons independent of technique. This emphasizes the need for consolidated care in pituitary centers of excellence, improvement of high-fidelity simulators, and skull base mentorship between senior and junior staff.

Simulation of Dural Repair in Minimally Invasive Spine Surgery With the Use of a Perfusion-Based Cadaveric Model

BACKGROUND AND IMPORTANCE

In an era of curtailed work hours and concerns over achieving technical proficiency in the repertoire of procedures necessary for independent practice, many residencies have turned to model simulation as an educational adjunct. Cerebrospinal fluid (CSF) leak repair after inadvertent durotomy in spine surgery is a fundamental skillset for any spine surgeon. While primary closure with suture is not always necessary for small durotomies, larger defects, on the other hand, must be repaired. However, the dire consequences of inadequate repair dictate that it is generally performed by the most experienced surgeon. Few intraoperative opportunities, therefore, exist for CSF leak repair by trainees.

OBJECTIVE

To simulate dural repair in spine surgery using minimal-access techniques.

METHODS

A cohort of 8 neurosurgery residents was evaluated on their durotomy repair efforts in a perfusion-based cadaveric model.

RESULTS

Study participants demonstrated consistent improvement across trials, with a significant reduction in closure times between their initial (12 min, 7 sec ± 4 min, 43 sec) and final attempts (7 min, 4 sec ± 2 min, 6 sec; P = .02). Moreover, all trainees—irrespective of postgraduate year—were able to accomplish robust dural closures resistant to simulated Valsalva maneuvers. Participants reported high degrees of model realism and exhibited significant increases in postprocedure confidence scores.

CONCLUSION

Our results support use of perfusion-based simulation models as a complement to neurosurgery training, as it affords unrestricted opportunities for honing psychomotor skillsets when resident learning is increasingly being challenged by work-hour limitations and stricter oversight in the context of value-based healthcare.

Costs and training results of an objectively validated cadaveric perfusion-based internal carotid artery injury simulation during endoscopic skull base surgery

BACKGROUND

Internal carotid artery injury (ICAI) is a rare, life-threatening complication of endoscopic endonasal approaches (EEAs). High-fidelity simulation methods exist, but optimization of the training cohort, training paradigm, and costs of simulation training remain unknown.

METHODS

Using our previously validated, high-fidelity, perfused-cadaver model, participants attempted to manage a simulated ICAI. After a brief instructional video and coaching, the simulation was repeated. Training success was defined as successful ICAI control on the second attempt after failure on the initial attempt. Marginal costs were measured.

RESULTS

Seventy-two surgeons participated in the standardized simulation, which lasted ≤15 minutes. The marginal cost of simulation was $275.00 per surgeon. A total of 44.4% (n = 32) succeeded on the first attempt before training (previously proficient); 44.4% (n = 32) failed the first attempt, but succeeded after training (training successes); and 11.1% (n = 8) failed both attempts. The cost per training success was $618.75. Forty-two surgeons had never treated an ICAI, with 24 becoming training successes (57.1% overall, 82.8% when excluding previously proficient surgeons). Twenty-nine had experienced a real or simulated ICAI, with 8 (27.6% overall, 72.7% excluding previously proficient surgeons) becoming training successes. The cost per training success was lowest in the ICAI-naive group ($481.25) and highest among surgeons with simulated and real ICAI experience ($1650).

CONCLUSIONS

Surgeons can be trained to manage ICAI in a single, brief, low-cost session. Although all groups improved, training an ICAI-naive or resident cohort may maximize training results. A perfused-cadaver model is a reproducible, realistic, and low-cost method for training surgeons to manage life-threatening ICAI during an EEA.

Step-up Establishment of Neurosurgical Laboratory Starting with Limited Resources-Tips and Tricks

BACKGROUND

Neurosurgical diseases have a devastating impact on society. It is estimated that approximately 14 million essential neurosurgical cases develop worldwide annually, of which more than 80% arise in low- and middle-income countries. Neurosurgical cadaveric dissection remains largely unexploited as a learning tool for the training of surgeons in developing countries, often because of the assumed high costs.

METHODS

The minimum requirements to establish a neurosurgical cadaver laboratory are the availability of minimally equipped environment to perform dissection, respecting safety requirements, fitting surgical instruments, anatomic samples, and materials to be used for preservation and preparation of anatomical specimens. Moving from these basic foundations, we established our Neurosurgical Dissection Laboratory at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome, Italy. The laboratory is located at the Institute of Public Health Section of Legal Medicine of University.

RESULTS

After reviewing relevant literature and discussing our experience, we provide advice for setting up a neurosurgical dissection cadaver laboratory with specific focus on suitable location identification, surgical equipment procurement, fresh cadaver and frozen specimen acquisition, and preparation and description of a step-up strategy to progressively enrich the laboratory.

CONCLUSIONS

Our study demonstrates the feasibility of establishing a neurosurgical cadaver dissection laboratory for training and research purposes even in presence of limited resources. The introduction of cost-effective guidelines and targeted funding could represent an added value to target the unmet neurosurgical disease need by promoting development of local neurosurgical expertise with the aim of providing health coverage for the treatment of common neurosurgical pathologies in developing countries.

Novel rodent model for simulation of sylvian fissure dissection and cerebrovascular bypass under subarachnoid hemorrhage conditions: technical note and timing study

OBJECTIVE

Sylvian fissure dissection following subarachnoid hemorrhage (SAH) is a challenging but fundamental skill in microneurosurgery, and one that has become increasingly difficult to develop during residency, given the overarching management trends. The authors describe a novel rodent model for simulation of sylvian fissure dissection and cerebrovascular bypass under SAH conditions.

METHODS

A standardized microvascular anastomosis model comprising rat femoral arteries and veins was used for the experimental framework. In the experimental protocol, following exposure and skeletonization of the vessels, extensive, superficial (1- to 2-mm) soft-tissue debridement was conducted and followed by wound closure and delayed reexploration at intervals of 7, 14, and 28 days. Two residents dissected 1 rat each per time point (n = 6 rats), completing vessel skeletonization followed by end-to-end artery/vein anastomoses. Videos were reviewed postprocedure to assess scar score and relative difficulty of dissection by blinded raters using 4-point Likert scales.

RESULTS

At all time points, vessels were markedly invested in friable scar, and exposure was subjectively assessed as a reasonable surrogate for sylvian fissure dissection under SAH conditions. Scar score and relative difficulty of dissection both indicated 14 days as the most challenging time point.

CONCLUSIONS

The authors’ experimental model of femoral vessel skeletonization, circumferential superficial soft-tissue injury, and delayed reexploration provides a novel approximation of sylvian fissure dissection and cerebrovascular bypass under SAH conditions. The optimal reexploration interval appears to be 7–14 days. To the authors’ knowledge, this is the first model of SAH simulation for microsurgical training, particularly in a live animal system.

Surgical simulation of a catastrophic internal carotid artery injury: a laser-sintered model

BACKGROUND

The catastrophic and rare nature of an internal carotid artery (ICA) injury during endonasal surgery limits training opportunities. Cadaveric and animal simulation models have been proposed, but expense and complicated logistics have limited their adoption. Three-dimensional (3D) printed models are portable, modular, reusable, less costly, and proven to improve psychomotor skills required for managing different lesions. In this study we evaluate the role of a simplified laser-sintered model combined with standardized training in improving the effectiveness of managing an ICA injury endoscopically.

METHODS

A 3-mm defect was created in the parasellar carotid canal of a laser-sintered model representing a sphenoid sinus. Artificial blood was directed to simulate the copious bleeding arising from an ICA injury. Twenty otolaryngologists and 26 neurosurgeons, with varying training and experience levels, were individually asked to stop the "bleeding" as they would in a clinical scenario, and provided no other instructions. This was followed by individualized formative training and a second simulation. Volume of blood loss, time to hemostasis, and self-assessed confidence scores were compared.

RESULTS

At the end of the study, time to hemostasis was reduced from 105.49 seconds to 40.41 seconds (p < 0.001). The volume of blood loss was reduced from 690 to 272 mL (p < 0.001), and the confidence scores increased in 95.7% of participants, from an average of 3 up to 8.

CONCLUSION

This ICA injury model, along with a formal training algorithm, appears to be valuable, realistic, portable, and cost-effective. Significant improvement in all parameters suggests the acquisition of psychomotor skills required to control an ICA injury.

The use of a novel perfusion-based cadaveric simulation model with cerebrospinal fluid reconstitution comparing dural repair techniques: a pilot study

BACKGROUND CONTEXT

Watertight dural repair is crucial for both incidental durotomy and closure after intradural surgery.

PURPOSE

The study aimed to describe a perfusion-based cadaveric simulation model with cerebrospinal fluid (CSF) reconstitution and to compare spine dural repair techniques.

STUDY DESIGN/SETTING

The study is set in a fresh tissue dissection laboratory.

SAMPLE SIZE

The sample includes eight fresh human cadavers.

OUTCOME MEASURES

A watertight closure was achieved when pressurized saline up to 40 mm Hg did not cause further CSF leakage beyond the suture lines.

METHODS

Fresh human cadaveric specimens underwent cannulation of the intradural cervical spine for intrathecal reconstitution of the CSF system. The cervicothoracic dura was then exposed from C7-T12 via laminectomy. The entire dura was then opened in six cadavers (ALLSPINE) and closed with 6-0 Prolene (n=3) or 4-0 Nurolon (n=3), and pressurized with saline via a perfusion system to 60 mm Hg to check for leakage. In two cadavers (INCISION), six separate 2-cm incisions were made and closed with either 6-0 Prolene or 4-0 Nurolon, and then pressurized. A hydrogel sealant was then added and the closure was pressurized again to check for further leakage.

RESULTS

Spinal laminectomy with repair of intentional durotomy was successfully performed in eight cadavers. The operative microscope was used in all cases, and the model provided a realistic experience of spinal durotomy repair. For ALLSPINE cadavers (mean: 240 mm dura/cadaver repaired), the mean pressure threshold for CSF leakage was observed at 66.7 (±2.9) mm Hg in the 6-0 Prolene group and at 43.3 (±14.4) mm Hg in the 4-0 Nurolon group (p>.05). For INCISION cadavers, the mean pressure threshold for CSF leakage without hydrogel sealant was significantly higher in 6-0 Prolene group than in the 4-0 Nurolon group (6-0 Prolene: 80.0±4.5 mm Hg vs. 4-0 Nurolon: 32.5±2.7 mm Hg; p<.01). The mean pressure threshold for CSF leakage with the hydrogel sealants was not significantly different (6-0 Prolene: 100.0±0.0 mm Hg vs. 4-0 Nurolon: 70.0±33.1 mm Hg). The use of a hydrogel sealant significantly increased the pressure thresholds for possible CSF leakage in both the 6-0 Prolene group (p=.01) and the 4-0 Nurolon group (p<.01) when compared with mean pressures without the hydrogel sealant.

CONCLUSIONS

We described the feasibility of using a novel cadaveric model for both the study and training of watertight dural closure techniques. 6-0 Prolene was observed to be superior to 4-0 Nurolon for watertight dural closure without a hydrogel sealant. The use of a hydrogel sealant significantly improved watertight dural closures for both 6-0 Prolene and 4-0 Nurolon groups in the cadaveric model.