Computational Tools for Adaptive Radiation Therapy

描述(申请人提供)：部分患者设置的不确定性和解剖变化被广泛认为是最大限度地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运动/变形的不利影响。在临床上，调强放射治疗计划优化和剂量分配仍然是两个分离的步骤，几何不确定性通过包含临床靶区的基于人群的边际来考虑，这显著地影响了放射治疗的成功。最近出现的车载体积成像设备为我们提供了一个宝贵的工具来获得患者在治疗位置的3D甚至4D几何模型，并允许在治疗过程中自适应地修改调强放射治疗计划。该项目的目标是开发用于图像引导自适应放射治疗(IGART)的使能计算工具，并展示IGART新范式的潜在临床影响。这项工作的基本假设是，IGART将大大减少射束靶向的不确定性，并提供实现更好的局部肿瘤控制所需的显著改善的剂量分布，同时减少正常组织并发症的可能性。该项目的具体目标是(1)建立基于锥束CT(CBCT)的剂量重建方法，用于分数和累积剂量计算；(2)建立IGART规划的动态闭环框架；以及(3)展示拟议的IGART的潜在临床影响。该项目的实施将证明IGART是可实现的，并确定IGART相对于传统IMRT的改进程度。鉴于该项目在最佳补偿分数间几何不确定度以及先前分数中产生的剂量学误差方面的重大承诺，该项目的成功完成应该会大大改善癌症患者的护理。 与公共卫生相关：目前，放射治疗计划是基于患者的解剖模型，从治疗前几天甚至几周获得的计划CT图像中产生的。大量的研究表明，由于患者位置的不确定性以及生理和临床因素，患者的解剖结构每天都会发生重大变化。该项目旨在为一种新的放射治疗范式开发使能计算工具，称为图像引导自适应放射治疗(IGART)，以消除部分间解剖变化的影响。IGART根据患者在实际治疗位置获得的体积成像数据自适应地调整射束参数，从而改进了目前的放射治疗。

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.