Collaborative Research: Interdisciplinary Center for Radiation Treatment Planning

合作研究：放射治疗规划跨学科中心

• 批准号: 0400294
• 负责人: Leyuan Shi
• 金额: $ 37.78万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-15 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0400294&HistoricalAwards=false
• 关键词: Collaborative; Research; Interdisciplinary; Center; Radiation

This collaborative research grant awarded to a multidisciplinary team aims to develop algorithmic tools and a corresponding cyberinfrastructure for the development, coordination, utilization, and dissemination of knowledge regarding the application of optimization-based inverse methods for radiation treatment planning. The PIs bring to this research cross-disciplinary proficiency in Industrial Engineering, Computer Sciences, and Radiation Oncology, building on their recent research in the areas of information technology, optimization, and treatment planning. The algorithm development is based on their newly developed methodologies including slicing approaches and the Nested Partitions framework. Along with the development of algorithms for Radiation Treatment Planning, the PIs also plan to develop a website that will provide an infrastructure to researchers worldwide for the development, coordination, utilization, and dissemination of optimization methods in Radiation Treatment Planning research. Approximately one million new cases of cancer are reported each year in the United States, with many times that number occurring worldwide. It is reported that more than 40 percent of people diagnosed with cancer in the US will undergo treatment with radiation therapy. Given the aging population, these numbers are expected to increase rapidly in coming years. It is expected that research results developed in this project will accelerate the development and understanding of efficient and effective automated Radiation Treatment Planning methods and software, resulting in clinical treatments of significantly higher quality, thereby enhancing both the quality of life and the longevity of cancer patients treated with radiation.

这项授予多学科团队的合作研究补助金旨在开发算法工具和相应的网络基础设施，以开发、协调、利用和传播有关应用基于优化的逆方法进行放射治疗规划的知识。PIs为这项研究带来了工业工程、计算机科学和放射肿瘤学的跨学科熟练程度，建立在他们在信息技术、优化和治疗规划领域的最新研究基础上。算法的开发是基于他们新开发的方法，包括切片方法和嵌套分区框架。随着放射治疗计划算法的开发，私人投资机构还计划开发一个网站，为世界各地的研究人员提供基础设施，以开发、协调、利用和传播放射治疗计划研究中的优化方法。美国每年报告的新癌症病例约为100万例，全球范围内的发病率是这个数字的许多倍。据报道，在美国，超过40%的确诊癌症患者将接受放射治疗。鉴于人口老龄化，这些数字预计将在未来几年迅速增长。预计该项目开发的研究成果将加速开发和了解高效和有效的自动放射治疗计划方法和软件，从而实现显著更高质量的临床治疗，从而提高接受放射治疗的癌症患者的生活质量和寿命。