Browsing by Author "Lou, Kai"
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Item A Phantom Study of In-beam PET Imaging for Proton Beam Range Verification(2013-12-17) Lou, Kai; Clark, John W., Jr.; Kelly, Kevin F.; Jacot, Jeffrey G.; Shao, YipingIn-beam PET imaging is an advanced image-based method to verify the proton beam range for proton therapy by measuring proton-induced positron activity distribution and activity range. This study investigates the feasibility, accuracy and precision of the activity range measurement with a high-performance compact PET prototype system for in-beam PET imaging. An experiment with a homogeneous PMMA phantom and several Monte Carlo simulation studies are conducted. The results have shown that the prototype PET can provide reasonably good images for the activity range measurement even with low count statistics; the accuracy of activity range measurement reaches sub-millimeter; 11C is the most dominating positron emission isotope contributing to the overall positron activity; the image quality and the precision of activity range measurement depend on the count statistics, and high count statistics leads to improved image quality and precision. Although the study is preliminary with simple system set-ups, it does provide interesting and important results which should lay the basis leading to future clinically relevant investigations.Item Feasibility of On-line Proton Beam Range Verification with Positron Emission Tomography Imaging(2015-12-18) Lou, Kai; Clark, Jr., John W.; Kelly, Kevin F.; Jacot, Jeffret G.; Shao, YipingPositron emission tomography (PET) imaging has been adopted clinically to verify proton beam range (BR) in proton therapy. Conventional approaches use off-line verification that verifies BR after delivery of full dose of a treatment fraction. This verification can be used to check the accuracy of current therapy retrospectively, but its effect suffers from potential target deviation between treatment fractions. In contrast, on-line verification can verify BR using a low dose proton beam and a short data acquisition time prior to administration of a treatment fraction. It could provide adequate information to verify or even revise the beam delivery for improving therapy targeting within a single treatment fraction. Nevertheless, a practical on-line verification has many unknowns and technical challenges. This thesis studies the feasibility of on-line BR verification with PET imaging from three aspects. First, it investigates the impact of count statistics on the accuracy and precision of BR verification. In general, on-line verification is hampered by low count statistics that degrade PET images and subsequently the accuracy and precision of BR verification. We used Monte Carlo simulation to understand the quantitative relationship between count statistics and the accuracy and precision of BR verification under various proton irradiation and PET imaging conditions. A mathematical model was also developed to study the impact of Poisson noise associated with PET images on BR verification. Second, it evaluates the effectiveness of existing algorithms and develops new approaches for improving the accuracy and precision of on-line BR verification. Important factors were identified, effective and efficient approaches were developed. By optimizing and applying these factors and approaches, it is feasible to substantially improve the accuracy and precision of on-line BR verification with the same proton dose and negligible extra processing time. Lastly, it investigates the feasibility of achieving on-line BR verification for proton brain therapy with Monte Carlo simulation, and proposes a new PET system configuration for on-line verification. It demonstrates that by using proper data correction and advanced algorithms, it is feasible to achieve 1-mm accuracy and precision of on-line BR verification with low proton dose and short data acquisition under different proton irradiation conditions.