Collaborative Research: Interdisciplinary Center for Radiation Treatment Planning

授予多学科团队的这项合作研究资助旨在开发算法工具和相应的网络基础设施，用于开发，协调，利用和传播有关应用基于优化的逆向方法进行放射治疗计划的知识。PI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能力，建立在他们最近在信息技术，优化和治疗计划领域的研究基础上。算法开发基于他们新开发的方法，包括切片方法和嵌套分区框架。 沿着放射治疗计划算法的开发，PI还计划开发一个网站，为全球研究人员提供基础设施，用于放射治疗计划研究中优化方法的开发、协调、利用和传播。在美国，每年大约有100万例新的癌症病例，而在世界范围内，这个数字是这个数字的许多倍。据报道，在美国，超过40%被诊断患有癌症的人将接受放射治疗。鉴于人口老龄化，预计这些数字在未来几年将迅速增加。预计该项目的研究成果将加速开发和理解高效和有效的自动化放射治疗计划方法和软件，从而显著提高临床治疗质量，从而提高放射治疗癌症患者的生活质量和寿命。

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.