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.
Radiation therapy can cure patients with localized cancer, but a major limitation is that our treatments are based on the average patient. This program project will establish a framework for optimizing therapy based on the responses of individual patients. The methods developed and tested here will contribute to changing the paradigm within which cancer therapy is practiced, thus improving the efficacy and the safety of radiation therapy for al patients.
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