TH-D-351-02: A Novel Digital Tomosynthesis (DTS) Reconstruction Method Using Prior Information and a Deformation Model

Purpose: Digital Tomosynthesis (DTS) is a quasi‐3D imaging technique which reconstructsimages from a limited angle of on‐board projections with significantly lower dose and shorter acquisition time than full cone‐beam CT(CBCT). However, DTS imagesreconstructed by the conventional filtered back projection method have low plane‐to‐plane resolution and can't provide full volumetric information for target localization. In this study, we developed a novel DTS reconstruction method using prior information and a deformation model to recover volumetric information. Method and Materials: A patient's previous CBCT or CT data were used as the prior information, and the new patient volume was considered as a deformation of the prior volume. The deformation fields were solved by minimizing bending energy and maintaining data fidelity. A nonlinear conjugate gradient method was used as the optimizer. The algorithm was tested using simulated projections of a Shepp‐Logan phantom, liver and head‐and‐neck patient data. The accuracy of the reconstruction was evaluated by comparing both pixel value and contour differences between DTS and CBCTimages.Results: In the liver patient study, the systematic and random errors for the live contour reconstructed using a 60‐degree scan angle were 0.5 and 1.6mm, respectively, showing the new organ volume was accurately reconstructed. The pixel signal‐to‐noise ratio (PSNR) for 60‐degree DTS reaches 23.5dB. In the head‐and‐neck patient study, the method using 60‐degree scan was able to reconstruct the 8.1 degree rotation of the bony structure with 0.0 degree error. The PSNR for 60‐degree DTS reaches 24.2dB. Conclusion: A novel reconstruction method was developed to reconstruct DTS images using prior information and a deformation model. Volumetric information was accurately obtained using a 60‐degree scan angle. Preliminary validation of the algorithm showed that it is both technically and clinically feasible for image‐guidance in radiation therapy. Partially supported by Grants from NIH and Varian Medical Systems.