About
Regan Shanahan is a third-year medical student at the University of Pittsburgh School of Medicine. Before attending medical school, she graduated from Boston University with degrees in Neurobiology, Public Health, and Political Science. She is engaged in neurotrauma and clinical spine surgery research. Regan is passionate about leveraging new technology to advance equitable patient outcomes and increasing female representation in Neurosurgery. In her free time, she enjoys riding her Peleton, reading memoirs, and cooking for her friends.
Projects
- Advancing Long Segment Spinal Fusion Precision: Harnessing Segmentation Software and Augmented Reality to Optimize Pre-Operative Planning and Intraoperative Rod Bending
- Augmented Reality-Assisted Glycerol Rhizotomy: Utilization of AR for surgical guidance in glycerol rhizotomy procedures of trigeminal neuralgia
- AI Enhanced Automated CT Segmentation for Spinal Osteoporosis Evaluation: Machine learning based automated segmentation algorithms can reliably predict bone mineral density for several spine surgery applications
- Optimizing Cerebral Bypass Surgery with Augmented Reality: Using AR to optimize the pre-operative workflow for STA-MCA bypass surgery
- Endoscopic Streaming on HoloLens during Skull Base Surgery: The purpose of this project is to determine the efficacy of implementing live-streaming video feeds during image-guided surgery
Publications
Machine Learning in Spine Surgery: A Narrative Review
Sam Adida, Andrew Legarreta, , David McCarthy, Edward Andrews, Regan Shanahan, , , , , ,
Neurosurgery, 2024
[Article]
Machine Learning Analysis of CT Scans to Determine Vertebral Hounsfield Units Can Assess Osteoporosis as well as DEXA
Akshay Sankar, Michael Kann, Sam Adida, Jhair Colan, Shovan Bhatia, , Regan Shanahan, Nicolás Kass, Nikhil Sharma, Griffin Hurt, , , Jacob Biehl, David McCarthy, Edward Andrews, Andrew Legarreta
Congress of Neurological Surgeons 2024 Annual Meeting, 2024
Machine Learning Analysis of CT Scans Predicts Vertebral Compression Fractures
Sam Adida, Michael Kann, Akshay Sankar, Jhair Colan, Shovan Bhatia, , , Regan Shanahan, Nicolás Kass, Nikhil Sharma, David McCarthy, Andrew Legarreta, , Peter Gerszten, Jacob Biehl, Edward Andrews
Congress of Neurological Surgeons 2024 Annual Meeting, 2024
Posters
Machine Learning-Derived Hounsfield Units from Preoperative CT Better Predicts Subsequent Adjacent-Level Fractures After Kyphoplasty Than DEXA Scans
Michael Kann, Sam Adida, Akshay Sankar, Jhair Colan, Shovan Bhatia, , , Regan Shanahan, Nicolás Kass, Nikhil Sharma, Griffin Hurt, David McCarthy, Andrew Legarreta, , Jacob Biehl, Edward Andrews, Peter Gerszten
Congress of Neurological Surgeons 2024 Annual Meeting, 2024
The Applications of Machine Learning Based Automated Segmentation to Spinal CT Scans
Michael Kann, Akshay Sankar, Jhair Colan, Sam Adida, Nicolás Kass, Shovan Bhatia, Regan Shanahan, , Griffin Hurt, Nikhil Sharma, , , David McCarthy, Andrew Legarreta, Jacob Biehl, Edward Andrews
Congress of Neurological Surgeons 2024 Annual Meeting, 2024