Radiation treatment (RT) for lung cancer is often limited to sub-therapeutic doses due to unintended toxicity to normal lung tissue. The long-term goal of the current application is to increase the therapeutic ratio in lung cancer, relevant to the mission of the National Cancer Institute, Specifically;current methods to assess potential toxicity of thoracic radiation for caner treatment are imprecise, inaccurate, and/or cumbersome. We hypothesize we can develop a physiologically relevant model for lung cancer patients to rapidly assess interventions for cancer treatment. The majority of lung cancer patients will receive RT along with some level of pulmonary toxicity;this is clearly a significant problem experienced by nearly 60,000 in the US annually. Currently, the complex inter-relationships between RT treatment and the changes in pulmonary function are poorly defined and based on subjective measures. We have developed a spatial and temporally variant approach to measure pulmonary function and compute lung changes in human subjects who have undergone radiation therapy. Based on observations from our preliminary data, our central hypothesis is: Spatial distributions of radiation induced pulmonary changes can be modeled and utilized for image- guided planning and therapy to improve pulmonary function preservation and hence the therapeutic ratio for lung cancer.
The aims of this proposal are to use quantitative imaging to characterize pulmonary biomechanics (SA1), build a model that predicts how these parameters change following RT (SA2), and use the model to improve therapy outcomes (SA3). Specifically, SA1 is to characterize the spatial and temporal nature of pulmonary function and establish baseline measurement reproducibility. SA2 is to establish objective models---based on pulmonary function indices, dosimetric, anatomic, and physiological relationships---that predict measured pulmonary function reduction following RT. Finally, SA3 is to clinically validate pulmonary function preservation models through a prospective study and determine if improved pulmonary function preservation can be achieved in subjects, relative to those treated without model information. We believe the proposed research will dramatically improve our basic understanding of lung physiology and its radiosensitivity. The repeat and post-RT imaging studies will be invaluable to the quantitative imaging community with registered 4D datasets and anatomical landmarks. We believe this will demonstrate the benefit of adding functional imaging into the RT workflow, and direct future experiments elucidating the mechanism of radiation damage in the lung.
The long-term goal of the current application is to increase the effectiveness of radiation therapy in treating lung cancer, by reducing its toxicity, and achieving greater killing of tumors by allowing for higher radiation doses. The majority of lung cancer patients will receive RT along with some level of pulmonary toxicity, experienced by nearly 60,000 in the US annually. Current methods to assess potential toxicity of radiation for lung are imprecise, inaccurate, and/or cumbersome. We propose to develop a technique to rapidly assess lung cancer patients prior to initiating treatment and improve our basic understanding of lung sensitivity to radiation doses.
|Du, Kaifang; Bayouth, John E; Ding, Kai et al. (2013) Reproducibility of intensity-based estimates of lung ventilation. Med Phys 40:063504|