Lung cancer is the leading cause of cancer death in the United States. Radiation therapy is indicated for 40% of the unresectable cases. Studies demonstrate improved local control and overall survival with an escalation in dose from conventional treatments, but care must be taken to spare healthy tissue. In order to increase target dose and decrease normal tissue irradiation, a clear representation of the target at all points of treatment must be obtained. Obtaining a clear image is difficult though, because images of the thorax and abdominal regions are subject to artifacts and distortions due to respiratory motion. Retrospective gating of CT image data based on a measured respiratory waveform (4D-CT) has proven to be a viable option to reduce the impact of respiratory motion on CT image quality. The goal of this project was to optimize the process of obtaining a multi-slice, helical 4D-CT image set. Four different breathing instruction techniques were evaluated using three respiration monitoring devices. A new retrospective sorting method was developed and compared to other published gating methods. Image quality was quantitatively assessed under variable reconstruction and scanning parameters. Among the recorded respiration traces, the most consistent period resulted from audible instruction, while no statistical difference between techniques was found for consistency in amplitude. The novel percentage amplitude sorting method was superior to the established time-based sorting methods in that it could accurately handle irregularities in period and slope of the respiration motion functions. Faster rotation speeds were optimal when assessing 4D-CT image quality, while no significant differences were observed with a change of pitch. Use of retrospective gating showed improvement in image quality parameters of objects in motion, providing more evidence towards the benefits of 4D-CT.
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