Optimization of High Dose Conformal Therapy

描述（由申请人提供）：癌症治疗现在被设计为统一治疗“普通”患者。“安全”剂量由患者群体中最敏感的5-15%决定。然而，这种基于人群的方法也伴随着对肿瘤控制的低期望。同样，尽管我们从生物学和临床研究中得知，肿瘤对治疗有不同的反应，但放射治疗的目的是均匀地治疗肿瘤。我们假设，将预处理患者因素与使用治疗的第一部分来评估肿瘤和正常组织敏感性的适应策略相结合的治疗设计将使我们能够针对个体患者优化治疗，而不是给出可能效果较差的人群平均治疗。该提案包括综合行动计划中的4个科学项目和4个共享资源核心：项目1和项目2将侧重于肝和肺内肿瘤。选择这两个地点进行临床演示，是因为它们目前的控制率很低，并且由于受辐射的正常组织器官的体积是毒性的关键因素，因此它们提供了很好的适应机会。我们将使用生理成像和其他方法在正常组织中进行个体化剂量重新分配以降低毒性，同时也对耐药肿瘤亚体积进行异质性照射以改善结果。项目3将建立基于成像方法的肿瘤靶向和正常组织反应的时空精度。项目4将开发、调查和改进决策支持工具，以利用适应性治疗患者管理的预测模型。核心A提供管理和统计支持，核心B将支持临床治疗计划和交付，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。我们认为我们正在为放射治疗开发一种新的范例，并且认识到世界上只有少数其他项目有能力开发一种系统，该系统结合了毒性，成像，计划，交付和临床领导的生物分析，根据每个人的特征和对治疗的反应安全地适应治疗。

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.