ITR: Collaborative Research - \(ASE\) - \(DMC\): DDDAS: A Novel Grid Architecture Integrating Real-Time Data and Intervention During Image Guided Therapy

ITR：协作研究 - (ASE) - (DMC)：DDDAS：在图像引导治疗期间集成实时数据和干预的新型网格架构

• 批准号: 0427183
• 负责人: Kim Baldridge
• 金额: $ 32.5万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-10-01 至 2007-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0427183&HistoricalAwards=false
• 关键词: ITR; Collaborative; Research; ASE; DMC

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.

该项目的研究涉及开发和部署一个集成和实用的网格架构，用于在图像引导治疗(IGT)过程中对脑变形进行数据驱动的术中体积模拟，并专门用于未来将在手术室使用的图像引导神经外科(IGNS)。初步工作已经形成了一个原型动态数据驱动系统，该系统驻留在IGNS的本地手术室，集成了数据采集、手术导航、定量监测和增强的实时控制。拟议的项目将通过扩展现有系统，使其具有紧密耦合的能力，以交互引导和自适应数据驱动的方式模拟动态变化的大脑形状，从而提高脑瘤切除的安全性和有效性。这种模拟能力与术中实时数据采集能力和实时手术切除能力相结合，需要从手术室按需、低延迟、容错、健壮和可靠地访问远程的大量计算能力和数据管理资源。网格基础设施的最新进展为开创这种能力提供了希望。该项目的总体目标是开发一种新的网格架构，集成实时数据，以便在IGT期间进行术中手术决策和导航。此外，这将为手术后分析和建模数据和图像储存库提供数据库基础设施。该项目的信息技术(IT)研究预计将在几年内对临床实践产生广泛影响。