Collaborative Research ITR/NGS: An Integrated Simulation Environment for High-Resolution Computational Methods in Electromagnetics with Biomedical Applications

合作研究 ITR/NGS：电磁学与生物医学应用高分辨率计算方法的集成仿真环境

• 批准号: 0324911
• 负责人: Timothy Warburton
• 金额: $ 2.25万
• 依托单位: University of New Mexico
• 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: 2004-01-15 至 2005-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0324911&HistoricalAwards=false
• 关键词: Collaborative; Research; ITR; NGS; Integrated; Collaborative; Research; ITR; NGS; Integrated

Current technologies for radiationbased treatment of cancerous tumors rely almost exclusively on diagnosticimages such as MRI and PET scans to enable a careful targeting of multiple high-intensity beams.However, the very complex nature of the penetration of radiation energy into the biological tissue makes such targeting difficult and error-prone, possibly even prohibiting radiative treatment due to the risk of damaging essential tissue in close proximity to the cancerous areas. Such issues are naturally of particular concern in relation to treatment of brain cancer.This project will conduct research on the development of a simulation environment which eventually will provide a virtual patient-specific model of the area of interest and an ability to accurately and efficiently model wave-propagation within such an environment, with the potential to ultimately provide the radiation specialist with an online tool for fine tuning the targeting of radiation energy and, at a future stage, perhaps even model the impact of the energy deposition and heat release on the tissue.The project will develop an environment comprising of (a) the cleaning and segmentation of MRI data, including data with noise sensitivity, (b) extraction of material data and construction of a patient-specific volume model of the target of interest, (c) the generation of high-order, curvilinear, finite elements grids, (d) full as well as reduced order modeling of the penetration/refraction of electromagnetic energy into the volume model, and (e) visualization and extraction of physiological data of interest. These different elements will be integrated into a flexible, stand-alone environment and will, as part of the development, be tested extensively on phantom data as well as real MRI data, possibly with added artificial noiseto explore robustness.The key developments will include new image segmentation and cleaning algorithms, improved material models, the development of efficient high-order accurate computational schemes for wave-propagation, efficient methods for domain truncation, and tools for visualization and data extraction. These are all problems of generic importance with potential for impact well beyond the particular application being considered.

目前用于基于辐射治疗癌性肿瘤的技术几乎完全依赖于诸如MRI和PET扫描等诊断图，以仔细靶向多个高强度光束。但是，辐射能量渗透到生物组织中的渗透能量非常复杂的性质，即靶向困难和差异性的辐射治疗，可能会因癌症而造成癌症的风险，从而使辐射性治疗造成癌症的危险。此类问题自然是与脑癌治疗有关的特别关注。该项目将对开发模拟环境进行研究，最终将提供一种虚拟患者特定的感兴趣领域的模型，并具有在这种环境中准确有效地对波浪进行准确有效地模型的能力，并有可能最终在网上发行能量的能量和范围的范围，甚至可以在线启动范围，甚至可以在线启动范围，甚至可以在线启动范围。 tissue.The project will develop an environment comprising of (a) the cleaning and segmentation of MRI data, including data with noise sensitivity, (b) extraction of material data and construction of a patient-specific volume model of the target of interest, (c) the generation of high-order, curvilinear, finite elements grids, (d) full as well as reduced order modeling of the penetration/refraction of electromagnetic energy into the volume model, and （e）可视化和提取感兴趣的生理数据。这些不同的要素将集成到一个灵活的独立环境中，并将作为开发的一部分进行广泛的测试，对幻影数据和实际MRI数据进行广泛的测试，可能会随着添加的人工Noiseto探索鲁棒性，包括新的图像段和清洁算法，改进的材料模型，有效地取得了高度的效果，以实现高度的计算范围。截断和可视化和数据提取的工具。这些都是通用重要性的问题，具有影响远远超出所考虑的特定应用的潜力。