Computational Tools for Adaptive Radiation Therapy

描述（由申请人提供）：分次间患者摆位不确定性和解剖结构变化被广泛认为是最大限度利用现代放射治疗技术（如调强放射治疗（IMRT））的主要限制因素之一。到目前为止，几乎所有的研究工作都集中在通过尝试更准确地重新定位患者来减少器官移动/变形的不良影响。在临床上，IMRT治疗计划优化和剂量递送仍然是两个解耦的步骤，几何不确定性考虑到人口为基础的边缘包围临床靶体积，这显着损害了放射治疗的成功。机载容积成像设备的出现为我们提供了一个有价值的工具，以获得三维甚至四维的几何模型的病人在治疗的立场，并允许自适应修改调强放射治疗计划在一个过程中。该项目的目标是开发图像引导自适应放射治疗（IGART）的计算工具，并显示IGART新范式的潜在临床影响。这项工作的基本假设是，IGART将大大降低射束靶向的不确定性，并提供所需的大幅改善的剂量分布，以实现更大的局部肿瘤控制，同时降低正常组织并发症的概率。该项目的具体目标是：（1）建立一种基于锥形束CT（CBCT）的剂量重建方法，用于计算分数和累积剂量;（2）建立IGART计划的动态闭环框架;（3）证明拟议IGART的潜在临床影响。该项目的执行将证明IGART是可实现的，并确定IGART相对于常规IMRT的改进水平。鉴于其显着的承诺，在最佳补偿interfractional几何不确定性以及剂量测定误差发生在以前的分数，该项目的成功完成，应导致癌症患者的护理大幅改善。 公共卫生相关性：目前，放射疗法治疗计划是基于患者的解剖模型从治疗前几天或甚至几周采集的计划CT图像产生的。大量研究表明，由于患者定位不确定性以及生理和临床因素，患者解剖结构每天都会发生显著变化。该项目旨在为放射治疗的新范例（称为图像引导自适应放射治疗（IGART））开发使能计算工具，以消除分次间解剖结构变化的影响。IGART通过根据患者在实际治疗位置采集的体积成像数据自适应调整射束参数来改进当前的放射治疗。

DESCRIPTION (provided by applicant): Interfractional patient setup uncertainty and anatomy change are widely recognized as one of the major limiting factors for maximum exploitation of modern radiation therapy techniques, such as intensity modulated radiation therapy (IMRT). Up to this point, almost all research efforts have been focused on reducing the adverse effects of organ movement/deformation by attempting to reposition the patient more accurately. Clinically, IMRT treatment plan optimization and dose delivery are still two decoupled steps, with the geometric uncertainties taking into account by population based margins encompassing the clinical target volume, which significantly compromises the success of radiation therapy. The recent advent of onboard volumetric imaging device provides a valuable tool for us to obtain 3D or even 4D geometric model of the patient in the treatment position and allows adaptive modification of IMRT plan during a course of treatment. The objective of this project is to develop enabling computational tools for image guided adaptive radiation therapy (IGART) and to show the potential clinical impact of the new paradigm of IGART. The underlying hypothesis of this work is that IGART will greatly reduce the uncertainty in beam targeting and provide substantially improved dose distributions required to achieve greater local tumor control while reducing the probability of normal tissue complications. Specific aims of the project are (1) to establish a cone beam CT (CBCT)-based dose reconstruction method for fractional and cumulative dose calculations; (2) to setup a dynamic closed-loop framework of IGART planning; and (3) to demonstrate the potential clinical impact of the proposed IGART. Execution of the project will demonstrate that the IGART is achievable and determine the level of improvement of IGART over the conventional IMRT. Given its significant promise in optimally compensating for interfractional geometric uncertainties as well as dosimetric errors incurred in previous fractions, successful completion of the project should lead to substantial improvement in cancer patient care. PUBLIC HEALTH RELEVANCE: Currently, a radiation therapy treatment plan is produced based on the patient's anatomical model from planning CT images acquired a few days or even weeks before treatment. Numerous investigations have revealed that there can be significant changes in the patient anatomy from day to day due to patient positioning uncertainties and physiologic and clinical factors. This project is aimed to develop enabling computational tools for a new paradigm of radiation therapy, referred to as image-guided adaptive radiation therapy (IGART), to eliminate the influence of inter-fractional anatomy change. IGART improves current radiation therapy by adaptively adjusting the beam parameters according to volumetric imaging data acquired with the patient in the actual treatment position.