Dose Uncertainty Management and Probabilistic Planning

剂量不确定性管理和概率规划

• 批准号: 8256662
• 负责人: JEFFREY Vincent SIEBERS
• 金额: $ 31.09万
• 依托单位: VIRGINIA COMMONWEALTH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-04-16 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8256662
• 关键词: Acceleration; Accounting; Algorithms; Anatomy; Breathing; Cervix Uteri; Clinical; Collaborations; Complex; Complication; Coupled; Development; Dose; Ensure; Evaluation; Evaluation Indexes; Evaluation Methodology; Evolution; Goals; Image; Image Analysis; Individual; Intensity-Modulated Radiotherapy; Lung; Maps; Methods; Morphologic artifacts; Names; Normal tissue morphology; Organ; Outcome; Patients; Phase; Positioning Attribute; Probability; Process; Prostate; Public Health; Radiation; Radiation therapy; Research Personnel; Residual state; Structure; Techniques; Testing; Therapeutic; Three-Dimensional Imaging; Time; Treatment Effectiveness; Treatment outcome; Uncertainty; Variant; base; direct application; image guided therapy; image registration; improved; indexing; novel; population based; process optimization; programs; response; treatment planning; tumor

The evolution of radiation therapy treatment techniques coupled with improved targeting by 3D onboard imaging and real-time adaptive IMRT replanning makes possible the delivery of more conformal dose distributions to targets with substantially reduced margins in comparison with historical radiation therapy practice. A key component of image guided adaptive radiation therapy (IGART) is planning and tracking of dose distributions on multiple deforming presentations of the patient anatomy. Performing such complex dose calculations in the context of rapid IMRT optimization presents a number of scientific challenges. First dose computation on deforming anatomies may add dose uncertainties, which results in decreased treatment effectiveness. Secondly, optimal IGART application will require that accurate dose calculations be performed much more rapidly than is possible with present algorithms. Finally, even when onboard 3D imaging-based setup adjustments are applied, residual systematic and random uncertainties will remain and need to be considered during planning. The goals of this Project are: (1) To develop methods to evaluate and minimize dose errors and dose uncertainty introduced by adding dose distributions acquired at different presentations of the patient's anatomy so as to accurately quantify and ensure effective dose delivery for IGART. (2) To develop and validate efficient, accurate dose algorithms for use with deformed image sets so as to enable rapid plan re- optimization and plan re-evaluation for IGART. (3) To develop and compare methods to account for residual dosimetric and targeting uncertainties and errors during plan IMRT optimization for IGART treatment delivery. The long term objectives of this Program are to develop and implement optimal IGART methods, to use these methods to enable dose-per-fraction escalation, and to improve patient outcomes through delivery of highly conformal dose distributions with minimal dose uncertainty. This project will benefit public health by developing techniques that will improve quantification of radiation therapy doses delivered to patients throughout their course of radiation therapy as their anatomy changes due to responses to the treatment or other processes. The project will develop techniques to reduce the amount of normal tissues irradiated, thereby enabling a reduction in complication rates and improvement in control rates for patients treated with radiationtherapy.

放射治疗技术的发展以及机载3D靶向技术的改进