Simulation has made limited inroads in neurosurgery, despite validation studies demonstrating its advantages over traditional training. It has emphasized needle insertion and failed to address requirements of surgeons-in-training on most future caseloads. Existing simulators exhibit brain mesh that lacks separability about fissures, is insufficiently sparse to resolve large displacements interactively, and does not account for critical tissues. These simulators also have only modeled simple instruments. Our long-term objective is an interactive simulator that replicates most future cases of young surgeons, enabling hospitals faced with compressed internship schedules to accelerate training and improve skills where patient outcome correlates with surgical experience. This objective will be met by integrating a multi-resolution brain mesh that is sparse and sulcal-separable at the coarse level and descriptive at the fine level, biomechanics based on interactive nonlinear multi-grid finite elements, multi-tool interaction achieved through flexible haptics, and clinical requirements specified through surgical ontologies. Our hypothesis is that for interactive neurosurgery simulation to be relevant and technically feasible, anatomical modeling must be sufficiently descriptive in intra-surgical motion and tissue morphology, biomechanics must be faithful to tissue response, haptics must afford multi-tool interaction, and the system must meet clinical requirements reflecting the specific surgical approach and pathology.
Existing neurosurgery simulators fail to meet the needs of surgeons-in-training because the brain mesh model, needed for synthesizing biomechanical tissue response, as well as the haptic device, manipulated by the user to enter a gesture to the computer, are not descriptive enough, and because clinical specifications for simulation are insufficiently rigorous. Our long-term objective is an interactive simulator that replicates most future caseloads of young surgeons. This objective will be met by integrating 1) a multi-resolution brain mesh that is sparse and separable at brain fissures at the coarse level and descriptive of relevant tissues at the fine level, 2) biomechanics based on interactive nonlinear finite elements, 3) multi-tool interaction achieved through flexible haptics, and 4) clinical requirements specified through surgical ontologies based on the specific approach and pathology.
| Lee, Huai-Ping; Audette, Michel; Joldes, Grand Roman et al. (2012) Neurosurgery Simulation Using Non-linear Finite Element Modeling and Haptic Interaction. Proc SPIE Int Soc Opt Eng 8316:83160H |
| Wu, Xunlei; Yao, Jianhua; Enquobahrie, Andinet et al. (2012) Integration of a Multigrid ODE solver into an open medical simulation framework. Conf Proc IEEE Eng Med Biol Soc 2012:3090-3 |
| Audette, Michel A; Rivière, Denis; Law, Charles et al. (2011) Approach-specific multi-grid anatomical modeling for neurosurgery simulation with public-domain and open-source software. Proc SPIE Int Soc Opt Eng 7964: |
