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DTSTART;TZID=America/Toronto:20250905T161000
DTEND;TZID=America/Toronto:20250905T162500
DTSTAMP:20250905T200733Z
CREATED:20250905T180504Z
LAST-MODIFIED:20250905T200733Z
UID:10000599-1757088600-1757089500@bme.utoronto.ca
SUMMARY:Graduate Student Seminar Series - Yuyang (Tony) Jiao
DESCRIPTION:Graduate Student Seminar Series\nPlease ensure you invite your Principal Investigator by adding their email via the ‘Add Guest’ button and they will also be notified of your presentation.\nLocation: MS2158 – 1 King’s College Circle\nPresentation Title: Patient Specific Virtual Reality for Spine Surgery Education\nAbstract:\nBackground & Prior Work: Effective surgical education benefits from multimodal approaches\, yet hands-on training is constrained by patient safety and limited operating room access. Virtual Reality (VR) simulations improve cognitive and procedural performance\, providing risk-free practice environments (1). Existing VR simulations for spine surgery focus on standardized\, generic scenarios\, they fail to align with the specific cases trainees encounter (2) impacting their adoption by trainees. Our novel approach generates patient-specific 3D models to enhance relevance and integration into competency-based curricula. Spinal stenosis treatment requires decompression procedures that rely on thoroughly understanding spinal anatomy (bone\, ligament\, disc\, and neural elements)\, as neural compression occurs at multiple sites (i.e.\, central\, lateral recess)\, and from many degenerative anatomical changes. Previous work has demonstrated VR’s effectiveness in spinal decompression training\, with participants highlighting its utility for learning spinal stenosis pathoanatomy (88%)\, laminectomy concepts (75%)\, and preoperative planning (96%). Our group has also shown the effectiveness and broad acceptance of VR for spinal decompression surgery simulation. The training was shown to be successful\, with junior (PGY-I and PGY-II) residents exhibiting the strongest improvement in test scores following utilization of the VR simulation module (3).\nObjective & Hypothesis: This study aims to evaluate a VR training platform using patient-specific 3D anatomical models to improve orthopaedic spine surgery education through realistic and clinically relevant simulations. We predict that this approach will significantly enhance trainees’ knowledge\, decision-making\, and long-term competency while increasing confidence and preparedness for live surgeries\, especially among junior residents.\nProposed Methods: The unique nature of our platform is the use of patient specific models. Current workflows for building these models require significant time and multiple software packages\, which is impractical for routine surgical training. We have developed tools for automating this workflow\, using Magnetic Resonance (MR) and Computed Tomography (CT) images to detect and segment relevant anatomical landmarks (4-7). Generated models will include detailed anatomical structures necessary for simulating spinal decompression procedures. The training will involve two modes: multi-player sessions\, where staff surgeons guide trainees through procedures in a collaborative virtual operating room\, and individual practice sessions\, allowing trainees to refine their skills independently. To assess the effectiveness of the training\, pre- and post-session tests will measure knowledge of anatomy\, surgical strategy\, and decision-making\, with statistical analysis using Fisher’s exact test to evaluate short-term improvements (8). Long-term effects will be measured through annual assessments\, correlating cumulative VR exposure tracked by session frequency and duration\, with competency improvements. Learners will be drawn from the University of Toronto’s orthopaedic residency and spine fellowship programs. A sample size of 30 learners will be recruited to detect significant correlations\, assuming a correlation coefficient of 0.5 (9). Usage metrics such as access duration and models loaded will be monitored through the VR platform\, and low-usage participants will be contacted to address potential barriers to access.\nAnticipated Results & Significance: Our novel approach to surgical education could further advance surgical education by providing risk-free\, engaging\, and realistic training. Our platform offers a captivating and authentic environment\, which we expect will maintain trainees’ interest by allowing practice on relevant anatomy and strategies. This integration is only possible through our patient-specific modeling. The completed project will offer a VR simulation fully embedded into surgical education\, improving trainees’ familiarity\, preparedness\, and skills for live surgeries\, leading to heightened surgeon confidence in independent practice.\nReferences: (1) M. Pfandler et al.\, Spine J. 17\, 1352-1363 (2017); (2) A. Feeley et al.\, Injury. 52\, 1715-1720 (2021); (3) T. Chen et al.\, N. Am. Spine Soc. J. 6\, 100063 (2021); (4) G. Klein et al.\, in MICCAI\, Y. Cai et al.\, Eds.\, 2020\, pp. 15-28; (5) V. Sivan et al.\, 2023\, https://arxiv.org/abs/2302.02283v1; (6) C. Caldwell et al.\, World Congr. Med. Phys. & Biomed. Eng.\, 2015\, p. 2401; (7) T. Mahmood et al.\, World J Gastroenterol. 24\, 5439 (2018); (8) J. Harrop et al.\, Neurosurgery. 73\, 94-99 (2013); (9) M. Mahalingam\, E. Fasella\, Eff. Use Technol. Async. Learn.\, 2017.\nSupervisor Name: Michael Hardisty\nYear of Study: 2\nProgram of Study: MASc\nPowered by Calendly.com
URL:https://bme.utoronto.ca/event/graduate-student-seminar-series-yuyang-tony-jiao/
LOCATION:MS2158
CATEGORIES:Graduate Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20250905T162500
DTEND;TZID=America/Toronto:20250905T164000
DTSTAMP:20250905T200733Z
CREATED:20250905T180504Z
LAST-MODIFIED:20250905T200733Z
UID:10000598-1757089500-1757090400@bme.utoronto.ca
SUMMARY:Canceled: Graduate Student Seminar Series - Srdjan Sumarac
DESCRIPTION:Graduate Student Seminar Series\nPlease ensure you invite your Principal Investigator by adding their email via the ‘Add Guest’ button and they will also be notified of your presentation.\nLocation: MS2158 – 1 King’s College Circle\nPresentation Title: Multimodal physiomarker investigations to optimize deep brain stimulation therapy\nAbstract: Deep brain stimulation (DBS) is an established therapy for Parkinson’s disease when medication no longer controls motor symptoms. Conventional DBS delivers continuous stimulation without accounting for symptom state\, which can lead to overstimulation and stimulation-induced side effects. Since stimulation cannot adapt to symptoms\, patients often require lengthy and repeated reprogramming. These limitations motivate adaptive DBS systems that adjust stimulation in real time using brain-derived physiomarkers. This work examined electrophysiological signals recorded during DBS surgery in the subthalamic nucleus (STN) and globus pallidus internus (GPi). Neuronal firing rates showed disease-related changes but did not scale with symptom severity. In contrast\, beta oscillations correlated with motor impairment\, though their suppression during stimulation reduces their utility as control signals. Stimulation-evoked responses provided insight into how DBS engages basal ganglia circuits and suggested restoration of striatal–pallidal synaptic strength. An additional oscillatory response\, evoked recurrent neural activity (ERNA)\, reflected loop activity between STN and pallidum\, and ERNA features were associated with bradykinesia severity. Together\, these findings identify candidate physiomarkers and offer mechanistic insights to guide future adaptive DBS devices.\nSupervisor Name: Luka Milosevic\nYear of Study: 5\nProgram of Study: PhD\nCancellation Reason:\nPowered by Calendly.com
URL:https://bme.utoronto.ca/event/canceled-graduate-student-seminar-series-srdjan-sumarac/
LOCATION:MS2158
CATEGORIES:Graduate Seminar Series
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