TH‐CD‐207A‐08: Simulated Real‐Time Image Guidance for Lung SBRT Patients Using Scatter Imaging

Purpose:To develop a comprehensive Monte Carlo-based model for the acquisition of scatter of patient anatomy in real-time, during lung treatment.Methods:During SBRT treatment, images of patient anatomy can be acquired from scattered radiation. To rigorously examine the utility of scatter for image guidance, a model is developed using MCNP code to simulate scatter of phantoms and lung cancer patients. The model is validated by comparing experimental and simulated of phantoms of different complexity. The differentiation between tissue types is investigated by imaging objects of known compositions (water, lung, and bone equivalent). A lung phantom, simulating materials and geometry encountered during lung treatments, is used to investigate image noise properties for various quantities of delivered radiation (monitor units(MU)). Patient scatter are simulated using the validated simulation model. 4DCT patient data is converted to an MCNP input geometry accounting for different tissue composition and densities. Lung phantom acquired with decreasing imaging time (decreasing MU) are used to model the expected noise amplitude in patient scatter images, producing realistic simulated patient scatter with varying temporal resolution.Results:Image intensity in simulated and experimental scatter of tissue equivalent objects (water, lung, bone) match within the uncertainty (∼3%). Lung phantom agree as well. Specifically, tumor-to-lung contrast matches within the uncertainty. The addition of random noise approximating quantum noise in experimental to simulated patient shows that scatter of lung tumors can provide in as fast as 0.5 seconds with CNR∼2.7.Conclusions:A scatter imaging simulation model is developed and validated using experimental phantom scatter images. Following validation, lung cancer patient scatter are simulated. These simulated patient demonstrate the clinical utility of scatter imaging for real-time tumor tracking during lung SBRT.