Our next paper will be presented by Peter Ju, Development of an Interoperative Electrophysiological Monitoring Simulator for a Peripheral Nerve Schwannoma Model, and it will be discussed by Dr. Kimberly Harbaugh. Well, I wanted to thank the AANS for this opportunity to present our work today. My name is Peter Ju, I'm a second year medical student at University of Rochester, and for my NREF project, I chose to develop an IEM, or Interoperative Electrophysiological Monitoring Simulator for the Peripheral Nerve Schwannoma Simulator that we created. And so I chose this project because I'm interested in education and learning, and I think Confucius here makes a salient point that doing is the most effective form of learning. And thousands of years later, we in medicine might know this better as the see one, do one, teach one approach. Well, in the modern era, where our patients have a lot of agency in their care, they may not wish for certain residents to practice on their operations. And so the question becomes, how do we train our surgeons without putting our patients at risk? And so to do this, we sought to create a realistic bleeding surgical simulator that replicates all aspects of surgery from pre-incision, inspection, palpation, imaging, all the way to the closure. And we chose the sciatic nerve schwannoma specifically because it's a relatively rare procedure with technical nuances that a lot of residents may not have the opportunities to practice during their training. In order to create this model, we used 3D printing techniques and hydrogels adapted from our previous carotid endarterectomy model, and the goal was to create a cost-effective, realistic-looking model to train on without putting patients at risk. And this just demonstrates the full procedural aspect of this model, where you can use ultrasound to look at the tumor-nerve interface and plan your procedure just as if you would do in a real case. But to make this model fully functional, I sought to create an IEM simulator because the nerve monitoring has been shown in the literature to improve patient outcomes and is an important part of peripheral nerve surgery. And so the purpose of this project was twofold. I sought to first create the nerve stimulator itself and to validate it so that I could accurately detect the nerve when it was present and not detect the nerve when it was not present. Secondly, I wanted to create the stretch sensor so that the strain put on the nerve throughout the procedure could be measured, and this you could think of kind of like a free-running EMG that's used during peripheral nerve surgery. And this would also allow immediate feedback to the practitioner themselves. And so to create the stimulator, I wanted to mimic the functional capabilities of the actual tool used in surgery, which is essentially to detect the nerve. And to do this, I created this simple circuit and incorporated a very thin conductive wire into the hydrogel to act as a nerve fascicle. Now, as you can see here, there's a dark line, and I just colored that to let you know that a nerve fascicle exists. But in the real nerve, you wouldn't be able to see it or feel it, and it's very easy to accidentally transect, which allows for good performance metrics. With the circuit, I incorporated two electrodes on either side, mimicking the actual case where you have a proximal electrode and a distal electrode that measures electrical activity of the nerve, and once stimulated with the probe, the resulting voltage change could be measured across the electrodes. To measure the accuracy of this probe, I took the fascicle and stimulated the tumor in five millimeter increments around the circumference and measured the outcome voltage. And so as you can see, at point zero, which represents where the fascicle lies, there was a dramatic rise in voltage as compared to away from the nerve. And this shows that the probe is able to accurately detect the nerve fascicle to within five millimeters of the fascicle. And so in practice, as you can see, you can stimulate on the nerve, there's a rise in voltage, and away from the nerve, there's a lesser rise in voltage. And in theory, we can create a threshold value where any voltage above the threshold, the machine would make a sound, notifying the provider that there is indeed a nerve. Anything below that, it will remain silent, letting you know that it is safe to cut into the nerve because there is no live fascicle. When stimulated away from the nerve, you notice that there was a lesser increase in voltage, and that was because the hydrogel itself is conductive. But we're able to demonstrate that clearly when you are on the nerve, there's a larger difference in voltage. And so with the stretch sensor, we wanted to mimic the free-running EMG, and to do this, I incorporated a conductive rubber wire into the nerve, and essentially when stretched, the mechanical properties of this wire would change the resistance of the entire circuit and cause the voltage to also change. And I wanted to correlate this change in voltage with the degree stretched, and so to test this, I stretched the cord in one centimeter increments and measured the electrical change in voltage. And here are the results. As you can see, per centimeter increase, there was a predictable increase in change in voltage, and across four trials, it was really consistent, notified by the error bars. And so this demonstrates that if we have a change in voltage reading, we're able to correlate that to the distance stretched. So to summarize the results, the probe was able to accurately detect the nerve fascicle to within five millimeters, and this would allow the surgeons to plan their approach and also measure the nerve activity both intraoperatively and postoperatively. In terms of the stretch, the change in voltage did correlate with the distance stretched, but for the correlation between distance stretched and the biological significance of this, we haven't, or it's not yet known, but the stretch sensor is able to allow for precise and measurable performance metrics. So the IEM has been shown to improve patient outcomes and is an important part of the peripheral nerve surgery, and one aspect was the stimulator, and integrating this would provide a full procedural, realistic training experience to surgeons without putting patients at risk. Secondly, the stretch sensor in the IEM simulator would allow for real-time feedback and allow for performance metrics to be obtained as well. So for the next step, I'd like to incorporate this IEM simulator into our full model and validate it for face construct and content validity. This would essentially compare expert surgeons with trainees among different performance metrics and allow for a training curriculum to be built so that we can measure how effective this tool is in surgical education. With the training curriculum, we hope to incorporate the IEM simulator into multiple different types of peripheral nerve surgery models so that we can provide a full experience without putting patients at risk. And in closing, I'd like to acknowledge my mentors, Dr. Bates and Dr. Stone, and would like to acknowledge the AANS and the NREF for their support in this project. Thank you. Thank you, Dr. Harbaugh will discuss the paper. I appreciate the opportunity to comment on this paper and the author's impressive efforts in creating a simulator of sciatic nerve schwannoma. Not only did they create the 3D model of the thigh and the sciatic nerve tumor, they were able to implant wires and conductive rubber tubes to simulate intraoperative monitoring. With the surface stimulation, they were able to locate within five millimeters the insulated, the uninsulated 40-gauge wire and register stretch in their single implanted conductive rubber tube to give feedback to the learner. So the question is then, is this simulator, does that really represent a clinical setting where instead of a single wire and a conductive tube, you have multiple fascicles that need to be dissected away from the tumor with this typically non-functioning fascicle. Future models obviously will need to incorporate increased numbers of the wires and the tubes. In addition, in my experience, finding the right peritumoral plane is the key to the procedure. Often there's multiple layers of these false tissue planes over the tumor capsule. You begin your dissection, you think you're in the right spot, suddenly you encounter some major fascicles. Usually if you go back to the area where you first started, you deepen your dissection by just a layer or two, you can find that nice clean plane, almost like peeling an egg. Everybody's had that experience where you peel a hard-boiled egg and you know you're in the right spot. And so that's the kind of thing that you look for. Once you find that right plane, the dissection is usually very straightforward and you can pull out these fairly significant tumors, even in the brachial plexus as we see here. If you do it in the right way, like we see here, as Dr. Klein demonstrated, typically you can take these schwannomas out 90% of the time without creating a new neurological deficit, but finding that plane is really the key to the whole procedure. So again, future models will really need to try and incorporate that because I think that will be really helpful. Other clinical situations that you can simulate include scarring with prior biopsy, functioning fascicles that may course through the tumor, as is the case with neurofibromas. So in conclusion, the office would be congratulated for the creation of a first whole task peripheral nerve simulator with electromonitoring capabilities. Haptic validation is needed, but we look forward to future iterations that have the potential for significant contributions to peripheral nerve education and would add an exciting addition to the hands-on courses. Thank you.

Interoperative Electrophysiological Monitoring Simulator

Peripheral Nerve Schwannoma Model

Surgical Training

Nerve Stimulator

Stretch Sensor