Multi-Criteria IMRT Optimization
Multi-Criteria IMRT Optimization
批准号:
7688128
负责人:
THOMAS R. BORTFELD
金额:
$27.74万
依托单位国家:
美国
项目类别:
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-07-01 至 2012-07-31
关键词:
AlgorithmsAreaBindingBrainClinicClinicalCollimatorComplexComplicationConflict (Psychology)DataDatabasesDevelopment PlansDimensionsDoseFeedbackFundingGenerationsGoalsHead and neck structureHourHousingHumanIntensity-Modulated RadiotherapyInterventionJointsLeadManualsMapsMethodologyMethodsModelingNormal tissue morphologyPancreasPatientsPhysiciansPlant LeavesPrincipal Component AnalysisProbabilityProceduresProcessRadiationRadiation therapyResistanceSiteSolutionsStructureSurfaceSystemTailTechniquesTechnologyTestingTimeTissuesWeightWorkbasecostimprovedinterestnovel strategiespublic health relevancetherapy developmenttooltouchscreentreatment planningtreatment sitetumorusability
中文摘要
描述(由申请人提供):该项目的总体长期目标是通过互动反馈将临床决策纳入强度调节放射治疗的反向治疗计划过程中。假设这将(I)使反向计划过程更有效,(Ii)增加优化计划的临床相关性,在目标覆盖和节省健康组织之间引入更好的权衡。解决这一问题的新方法包括多准则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。治疗计划的多目标优化思想是在不同的关键结构和目标体积内同时控制多个计划标准。相比之下,在当前的逆向规划算法中,单一目标(得分函数)是最大化或最小化的。这种传统的优化只能对计划结果进行有限的控制,并且经常需要使用试错法对计划进行重大的手动调整。在前一个资助期,该方法的可行性已在理论范例、案例和回溯性治疗计划研究中得到证明。这表明了多标准规划方法的潜力和某些领域的改进潜力。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、更快地做出权衡决定。它还将包括在最大限度减少用户干预的情况下生成计划数据库,以及开发计划导航方法。第二个目标是扩展功能。硬件和交付方面将纳入其中。将提供一种交互优化波束方向的方法。剂量一致性将包括在权衡讨论中,用户将能够基于替代的生物激励标准做出权衡决定。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上得到验证。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,更好地覆盖肿瘤靶区体积和/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体成本。公共卫生相关性: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,更好地覆盖肿瘤靶区体积和/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体成本。
英文摘要
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.
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会议论文
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