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Approach-specific, multi-GPU, multi-tool, high-realism neurosurgery simulation

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 9R44OD018334-03A1
Agency Tracking Number: R44OD018334
Amount: $1,932,231.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: 100
Solicitation Number: PAR09-220
Timeline
Solicitation Year: 2015
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-09-26
Award End Date (Contract End Date): 2017-05-31
Small Business Information
28 CORPORATE DRIVE
Clifton Park, NY 12065-8688
United States
DUNS: 010926207
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 ANDINET ENQUOBAHRIE
 (919) 969-6990
 andinet.enqu@kitware.com
Business Contact
 WILLIAM SCHROEDER
Phone: (518) 331-1177
Email: will.schroeder@kitware.com
Research Institution
N/A
Abstract

DESCRIPTION provided by applicant Approach specific Multi GPU Multi tool High realism Neurosurgery Simulation Surgical treatment of neurological diseases is complicated and requires advanced training However compressed internship schedules in hospitals creates a challenge to young surgeons to master techniques needed for such complex procedures Surgical simulators are powerful tools to provide advanced training for complex procedures accelerate the training of residents without a penalty in morbidity and mortality and improve skills where patient outcome clearly correlates with surgical experience Surgical simulation training has been proposed for nearly a decade and advancement in computing technology and algorithm development has now made it a more realistic training option Double blind validation studies have shown that surgical residents trained with a simulator systematically outperformed residents without such training in performing complex procedures such as laparoscopic cholecystectomies However despite demonstrated advantages of using simulation in conjunction with traditional frameworks simulation has only made limited inroads in surgical education particularly in the field of neurosurgery The overall goal of this proposal is to develop and evaluate an interactive neurosurgery simulator that is clinically realistic and well validated During Phase I we implemented a prototype interactive neurosurgery simulator for training medical students on the resection of deep seated tumors in the brain stem The simulator consists of a multi resolution sulcal separable meshing algorithm for pterional approach an efficient and physically realistic non linear model FEM formulation and GPU acceleration Our clinical collaborators deemed our Phase simulator a success for major components of tumor resection procedures However they also noted that it would benefit from consideration of vasculature as manipulation of vasculature is critical to tumor resection and many other neurosurgical procedures In this Phase project we propose to extend and refine our simulator with additional components required to simulate vasculature and build a simulator application for surgical treatment of arteriovenous malformations AVMs one of the most complex surgeries involving brain vasculature We will conduct a validity study of the neurosurgery simulator in collaboration with neurosurgeons in the Department of Neurosurgery at the University of North Carolina The interactive simulator that will be developed will facilitae training in neurosurgical procedures that are complicated and require advanced training This will translate to fewer operating room errors reduced patient morbidity and improved patient outcomes PUBLIC HEALTH RELEVANCE Approach specific Multi GPU Multi tool High realism Neurosurgery Simulation Surgical mistakes have catastrophic consequences Therefore surgeons use all tools available in their arsenal to avoid these errors Surgical simulation one such tool allows young residents and experts to practice and advance their surgical skills in a risk free environment This project aims to develop and validate an interactive simulator for neurosurgical procedures that are complicated and require advanced training This will translate to fewer operating room errors reduced patient morbidity and improved patient outcomes

* Information listed above is at the time of submission. *

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