Optimization of High Dose Conformal Therapy

描述(由申请者提供)：癌症治疗现在被设计为统一治疗“普通”患者。“安全”剂量由最敏感的5%-15%的患者决定。然而，这种以人群为基础的方法也伴随着对肿瘤控制的低期望。同样，放射治疗被设计为统一治疗肿瘤，尽管我们从生物学和临床研究中知道，肿瘤对治疗有不同的反应。我们假设，将治疗前患者因素与适应策略相结合的治疗设计，使用第一部分治疗来评估肿瘤和正常组织的敏感性，将允许我们优化针对单个患者的治疗，而不是给予可能效果较差的总体平均治疗。该提案包括4个科学项目和综合行动计划内的4个共享资源核心：项目1和2将侧重于肝和肺内的肿瘤。这两个部位之所以被选作临床示范，是因为它们目前的控制率很低，而且由于所照射的正常组织器官的体积是毒性的关键因素，它们提供了一个很好的适应机会。我们将使用生理成像和其他方法来个体化正常组织中的剂量重新分配，以降低毒性，同时也将异质照射耐药肿瘤亚体积以改善结果。项目3将为肿瘤靶向和正常组织反应建立基于成像的方法的空间和时间精度。项目4将开发、调查和改进决策支持工具，以利用预测模型进行适应性治疗患者管理。核心A提供行政和统计支持，核心B将支持临床治疗计划和实施，核心C将提供所有成像数据的分析，核心D将处理软件设计。我们认为，我们正在开发一种新的放射治疗模式，并认识到世界上只有几个其他项目有能力开发一种系统，将毒性、成像、规划、交付和临床领导能力结合起来，根据每个人的特征和治疗反应安全地调整治疗。

DESCRIPTION (provided by applicant): Cancer treatments are now designed to uniformly treat the "average" patient. The "safe" dose is dictated by the most sensitive 5-15% of the patient population. However, this population-based approach is also accompanied by low expectations of tumor control. Similarly, radiation treatments have been designed to treat the tumor uniformly, although we know from biological and clinical studies that tumors have a heterogeneous response to treatment. We hypothesize that a treatment design that Integrates pretreatment patient factors with an adaptation strategy that uses the first part of treatment to assess tumor and normal tissue sensitivity will permit us to optimize therapy for the individual patient rather than giving a population-averaged treatment that is likely to be less effective. Thi proposal comprises 4 scientific Projects and 4 shared resource Cores within an integrated plan of action: Project 1 and 2 will focus on tumors within the liver and lung. These two sites were chosen for clinical demonstration as their current control rates are low and, as the volume of the harboring normal tissue organ irradiated is the critical factor in toxicity, they offer a great opportunity for adaptation. We will use physiological imaging and other methods to individualize dose redistribution in normal tissues to lower toxicity while also heterogeneously irradiating resistant tumor sub-volumes to improve outcome. Project 3 will establish the spatial and temporal precision of imaging-based methods for both tumor targeting and normal tissue response. Project 4 will develop, investigate, and improve decision support tools to take advantage of predictive models for adaptive therapy patient management. Core A provides administrative and statistical support, Core B will support the clinical therapy planning and delivery, Core C will provide analysis of all Imaging data and Core D will handle software design. We feel that we are developing a new paradigm for radiation therapy and recognize only a few other programs in the world with our ability to develop a system that combines biological assays of toxicity, imaging, planning, delivery, and clinical leadership to safely adapt therapy based on each individual's characteristics and response to therapy.