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Validation of An Iterative Tomosynthesis Algorithm for Low Dose On Board Cone Beam CT Patient Localization


E Izaguirre

E W Izaguirre1,2*, S G Price1,2, D Yang1, D Rangaraj1,2, (1) Washington University School of Medicine, Saint Louis, MO, (2) Nuclear Science and Engineering Institute, University of MO, Columbia, MO

SU-E-J-5 Sunday 3:00:00 PM - 6:00:00 PM Room: Exhibit Hall

Purpose: Cone beam CT (CBCT) is a well established technique to localize patients using bone and soft tissue anatomy. Current protocols are limited to one weekly CBCT due to the considerable imaging dose delivered to the patient. The purpose of this project is to develop and validate a low dose CBCT algorithm to reduce dose and imaging time of current 3D imaging localization procedures using a novel iterative tomosynthesis algorithm to allow daily CBCT for patient positioning and target localization.
Methods: The algorithm is based on the combination of a tomosynthesis filtered back propagation (TFBP) acquisition geometry algorithm and a maximum likelihood expectation maximization (MLEM) iterative reconstruction. Circular or arc acquisition trajectory, projection number, and angular projection position are optimized according to the anatomical treatment site and region of interest. The TFBP method provides the first 3D image estimate, and the MLEM improves its quality. In this study, we focused on head and neck treatment localization imaging.
Results: We studied the performance of our tomosynthesis algorithm imaging resolution on an anthropomorphic head and neck phantom to determine image quality as a function of dose reduction techniques. Reconstructed anatomy shows that a 1/8 dose reduction provides similar image quality and resolution as current CBCT protocols. Seven iterations show an optimal compromise between image quality and reconstruction time. Tomosynthesis images provide digitally reconstructed radiographs with similar resolution and contrast as full CBCT. We verified that the iterative process eliminates phantom images originated by the acquired sparse angular data projections.
Conclusions: We developed and validated an iterative algorithm for low dose cone beam CT based on circular or arc tomosynthesis geometries and iterative reconstruction techniques. The algorithm combines the strengths of both techniques to provide a novel low dose method to image patient anatomy for patient positioning and target localization.

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