The project's research involves development and deployment of an integrated and practical grid architecture for data driven intra-operative volumetric simulation of brain deformation during image guided therapy (IGT) and specifically for image guided neurosurgery (IGNS) to be employed in the operating room of the future. Preliminary work has resulted in a prototype dynamic data driven system, which resides locally in the operating room for IGNS that integrates data acquisition, surgical navigation, quantitative monitoring and enhanced real-time control. The proposed project will enable improvement in the safety and efficacy of brain tumor resection by extending the current system with a tightly coupled capability for interactively steered and adaptive data driven simulation of the dynamically shifting shape of the brain. Such simulation capability, integrated with real-time intra-operative data acquisition capability and real-time surgical resection, requires on-demand low latency fault tolerant robust and reliable access to remotely located significant compute capacity and data management resources from the operating room. Recent advances in grid infrastructure hold out the promise to pioneer such capability. The overall objective of this projectl is the development of a novel grid architecture integrating real- time data to allow intra-operative surgical decision-making and navigation during IGT. In addition this will provide database infrastructure for post-surgical analysis and modeling of data and image repositories. The project's information technology (IT) research is expected to have broad impact on clinical practice within a period of a few years.
