High-Throughput Computing for a Multi-Plan Framework in Radiotherapy

描述(由申请人提供)： 从直线加速器进行体外放射治疗(EBRT)或调强放射治疗(IMRT)的计算机计划是一个复杂的过程，涉及大量的输入数据和大量的决策变量。这种大规模的组合优化问题对于传统的方法来说是很难处理的，例如直接应用最好的商业算法，因此需要利用问题结构的专门方法。放射治疗计划(RTP)问题是多目标的，这使得问题变得更加复杂，也就是说，RTP优化过程必须考虑到向肿瘤提供适当剂量和避免向附近健康器官提供有害辐射这两个相互竞争的目标之间的权衡。该提案的目标是在RTP环境中通过秃鹰系统实现高吞吐量计算(HTC)，从而利用分布式计算。这一建议的具体目标是：1)开发一个嵌套分区(NP)框架，该框架指导使用HTC的最佳调强放疗传递参数的全球搜索过程。2)开发基于HTC的并行线性规划(LP)方法，有效地解决调强放射治疗中每组给定射束角度或射束孔径的剂量优化问题。(3)利用高吞吐量计算(HTC)环境和开发的NP/LP/分段框架，高效地为每个给定的患者病例生成多个计划。(4)将该多计划框架与决策支持系统(DSS)相结合，决策支持系统(DSS)包括计划表面模型、图形用户界面(GUI)和用于预测OAR并发症的机器学习工具，以帮助对所生成的治疗计划进行排序和选择。这项提案需要一个多学科的方法，最好是在宣布生物医学计算科学和技术创新计划的框架内进行。它汇集了一支跨学科的研究团队，他们拥有医学物理、数学编程、工业工程和临床放射肿瘤学方面的专业知识，这对利用HTC进行放射治疗的拟议多计划框架的开发至关重要。与公共卫生相关：这项提案的目标是为辐射输送的复杂治疗规划开发一个多维平台。它将开发新的算法，使之能够生成更好的治疗计划，并增加增加治疗计划速度的优势。此外，它将使医生能够预先知道相对于多个治疗目标的治疗计划的质量，并能够预先确定治疗并发症的情况。

DESCRIPTION (provided by applicant): Computerized planning for radiation delivery via either external beam radiation therapy (EBRT) or intensity- modulated radiation therapy (IMRT) from linear accelerators is a complex process involving a large amount of input data and vast numbers of decision variables. Such large-scale combinatorial optimization problems are typically intractable for conventional approaches such as the direct application of the best available commercial algorithms, and thus specialized methods that take advantage of problem structure are required. Radiation treatment planning (RTP) problems are further complicated by the fact that they are multi-objective, that is, the RTP optimization process must take into account a trade-off between the competing goals of delivering appropriate doses to the tumor and avoiding the delivery of harmful radiation to nearby healthy organs. The goal of this proposal is to harness distributive computing via the Condor system for High Throughput Computing (HTC) within an RTP environment. The specific aims for this proposal are: 1) To develop a Nested Partitions (NP) framework that guides a global search process for optimal IMRT delivery parameters using HTC. 2) To develop parallel HTC-based linear programming (LP) methods to efficiently solve the dose optimization problem in IMRT for each given set of beam angles or beam apertures. (3) To exploit a high-throughput computing (HTC) environment and the developed NP/LP/segmentation framework to efficiently generate multiple plans for each given patient case. (4) To couple this multi-plan framework with a decision support system (DSS) that includes planning surface models, a graphical-user-interface (GUI) and machine learning tools to prediction OAR complication in order to aid in the ranking and selection of the generated treatment plans. This proposal requires a multi-disciplinary approach that is best conducted within the framework of the Innovations in Biomedical Computational Science and Technology program announcement. It brings together an interdisciplinary team of investigators with expertise in medical physics, mathematical programming, industrial engineering and clinical radiation oncology that is crucial to the development of the proposed multi- plan framework using HTC in radiation therapy. PUBLIC HEALTH RELEVANCE: The goal of this proposal is to develop a multi-dimensional platform for sophisticated treatment planning of radiation delivery. It will develop novel algorithms that will enable generation of superior treatment plans with the added advantage of increasing the speed of treatment planning. Further, it will allow physicians to know beforehand the quality of the treatment plan relative to the multiple treatment objectives and be able to determine the treatment complication scenario beforehand.