Multi-Criteria IMRT Optimization

多标准 IMRT 优化

• 批准号: 7917353
• 负责人: THOMAS R. BORTFELD
• 金额: $ 27.75万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-07-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7917353
• 关键词: Algorithms; Area; Binding; Brain; Clinic; Clinical; Collimator; Complex; Complication; Conflict (Psychology); Data; Databases; Development Plans; Dimensions; Dose; Feedback; Funding; Generations; Goals; Head and neck structure; Hour; Housing; Human; Intensity-Modulated Radiotherapy; Intervention; Joints; Lead; Manuals; Maps; Methodology; Methods; Modeling; Normal tissue morphology; Pancreas; Patients; Physicians; Plant Leaves; Principal Component Analysis; Probability; Procedures; Process; Radiation; Radiation therapy; Resistance; Site; Solutions; Structure; Surface; System; Tail; Techniques; Technology; Testing; Time; Tissues; Weight; Work; base; cost; improved; interest; novel strategies; public health relevance; therapy development; tool; touchscreen; treatment planning; treatment site; tumor; usability

DESCRIPTION (provided by applicant): The overall long-term objective of this project is to incorporate clinical decisions through interactive feedback into the inverse treatment planning process for intensity-modulated radiotherapy. The hypotheses are that this will (i) make the inverse planning process more effective and (ii) increase the clinical relevancy of optimized plans, introducing better tradeoffs between target coverage and sparing of healthy tissues. The new approaches to tackle this problem include multi-criteria optimization techniques and an interactive plan navigation tool for searching a pre-calculated treatment plan database. The idea of multi-criteria optimization in treatment planning is that multiple planning criteria in different critical structures and in the target volume can be controlled simultaneously. In contrast, in current inverse planning algorithms a single objective (score function) is maximized or minimized. This conventional optimization gives only limited control of the planning result, and major manual plan tweaking using trial and error is often necessary. In the previous funding period the feasibility of the approach has been demonstrated in theoretical example cases and retrospective treatment planning studies. This showed the potential of the multi-criteria planning approach and a potential for improvement in some areas. The first aim of the current project is to improve the usability of the method. This will include a reduction of the dimensionality of the problem, to make the tradeoff decision easier and faster for the clinician. It will also include the generation of plan databases with minimal user intervention, and developments of the plan navigation approach. The second aim is to extend functionality. Hardware and delivery aspects will be incorporated. A means to interactively optimize beam orientations will be provided. Dose conformality will be included in the tradeoff discussion, and the user will be able to make tradeoff decisions based on alternative biologically motivated criteria. Finally, in aim 3, the hypothesis that the multi-criteria planning paradigm will lead to better treatment plans in less time will be tested in the clinic. This work has the potential to lead to clinically more suitable and more individualized radiation treatment plans, with better dose coverage of the tumor target volume and/or reduced radiation dose to surrounding healthy tissues. Furthermore, shorter treatment planning times will reduce the overall cost. PUBLIC HEALTH RELEVANCE: This work has the potential to lead to clinically more suitable and more individualized radiation treatment plans, with better dose coverage of the tumor target volume and/or reduced radiation dose to surrounding healthy tissues. Furthermore, shorter treatment planning times will reduce the overall cost.

描述（由申请人提供）：本项目的总体长期目标是通过互动反馈将临床决策纳入调强放疗的逆向治疗计划过程。假设这将（i）使逆向计划过程更有效，以及（ii）增加优化计划的临床相关性，从而在目标覆盖和健康组织的保留之间引入更好的权衡。解决这一问题的新方法包括多标准优化技术和用于搜索预先计算的治疗计划数据库的交互式计划导航工具。治疗计划中的多标准优化的思想是可以同时控制不同关键结构和靶体积中的多个计划标准。相反，在当前的逆规划算法中，单个目标（得分函数）被最大化或最小化。这种传统的优化只能对规划结果进行有限的控制，并且通常需要使用试错法进行主要的手动规划调整。在上一个资助期间，该方法的可行性已在理论示例病例和回顾性治疗计划研究中得到证明。这显示了多标准规划方法的潜力，以及在某些领域改进的潜力。当前项目的首要目标是提高该方法的可用性。这将包括降低问题的维度，使临床医生更容易和更快地做出权衡决定。它还将包括以最少的用户干预生成计划数据库，以及制定计划导航方法。第二个目标是扩展功能。硬件和交付方面将被纳入。将提供一种交互式优化射束方向的方法。剂量适形性将包括在权衡讨论中，用户将能够根据替代生物学动机标准做出权衡决定。最后，在目标3中，多标准计划范例将在更短的时间内产生更好的治疗计划的假设将在临床中进行测试。这项工作有可能带来临床上更合适、更个性化的放射治疗计划，更好地覆盖肿瘤靶区和/或减少对周围健康组织的辐射剂量。此外，更短的治疗计划时间将降低总成本。公共卫生关系：这项工作有可能导致临床上更合适和更个性化的放射治疗计划，更好的剂量覆盖肿瘤靶体积和/或减少周围健康组织的辐射剂量。此外，更短的治疗计划时间将降低总成本。