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Optimization models and techniques for radiation treatment planning applied to Leksell Gamma KnifeRTM Perfexion(TM)

机译:适用于Leksell Gamma KnifeRTM Perfexion(TM)的放射治疗计划优化模型和技术

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摘要

Radiation treatment planning is a process through which a certain plan is devised in order to irradiate tumors or lesions to a prescribed dose without posing surrounding organs to the risk of receiving radiation. A plan comprises a series of shots at different positions with different shapes. The inverse planning approach which we propose utilizes certain optimization techniques and builds mathematical models to come up with the right location and shape, for each shot, automating the whole process. The models which we developed for Perfexion(TM) unit (Elekta, Stockholm, Sweden), in essence, have come to the assistance of oncologists in automatically locating isocentres and defining sector durations. Sector duration optimization (SDO) and sector duration and isocentre location optimization (SDIO) are the two classes of these models. The SDO models, which are, in fact, variations of equivalent uniform dose optimization model, are solved by two nonlinear optimization techniques, namely Gradient Projection and our home-developed Interior Point Constraint Generation. In order to solve SDIO model, a commercial optimization solver has been employed. This study undertakes to solve the isocentre selection and sector duration optimization. Moreover, inverse planning is evaluated, using clinical data, throughout the study. The results show that automated inverse planning contributes to the quality of radiation treatment planning in an unprecedentedly optimal fashion, and significantly reduces computation time and treatment time.
机译:放射治疗计划是一个过程,通过该过程可以制定一定的计划,以便将肿瘤或病变照射到规定剂量,而不会使周围器官受到辐射的风险。计划包括在不同位置以不同形状拍摄的一系列镜头。我们提出的逆向计划方法利用了某些优化技术,并建立了数学模型以针对每个镜头提供正确的位置和形状,从而使整个过程自动化。从本质上讲,我们为Perfexion(TM)单元(Elekta,斯德哥尔摩,瑞典)开发的模型已在肿瘤学家的协助下自动定位等中心并定义扇区持续时间。扇区持续时间优化(SDO)和扇区持续时间及等中心位置优化(SDIO)是这些模型的两类。 SDO模型实际上是等效均匀剂量优化模型的变体,它是通过两种非线性优化技术来解决的,即梯度投影和我们自己开发的“内部点约束生成”。为了求解SDIO模型,已采用了商用优化求解器。这项研究致力于解决等中心选择和扇区持续时间优化问题。此外,在整个研究过程中,将使用临床数据评估逆向计划。结果表明,自动化的逆计划以前所未有的最佳方式为放射治疗计划的质量做出了贡献,并显着减少了计算时间和治疗时间。

著录项

  • 作者

    Ghaffari, Hamid R.;

  • 作者单位

    University of Toronto (Canada).;

  • 授予单位 University of Toronto (Canada).;
  • 学科 Biomedical engineering.;Oncology.;Industrial engineering.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 117 p.
  • 总页数 117
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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