LAUSR

PURPOSE The constrained One-Step Spectral CT Image Reconstruction (cOSSCIR) algorithm with a non-convex alternating direction method of multipliers (ADMM) optimizer is proposed for addressing CT metal artifacts caused by beam hardening, noise, and photon starvation. The quantitative performance of cOSSCIR is investigated through a series of photon-counting CT simulations. METHODS cOSSCIR directly estimates basis material maps from photon-counting data using a physics-based forward model that accounts for beam hardening. The cOSSCIR optimization framework places constraints on the basis maps, which we hypothesize will stabilize the decomposition and reduce streaks caused by noise and photon starvation. Another advantage of cOSSCIR is that the spectral data need not be registered, so that a ray can be used even if some energy window measurements are unavailable. Photon-counting CT acquisitions of a virtual pelvic phantom with low-contrast soft tissue texture and bilateral hip prostheses were simulated. Bone and water basis maps were estimated using the cOSSCIR algorithm and combined to form a virtual monoenergetic image for evaluation of metal artifacts. The cOSSCIR images were compared to a 'two-step' decomposition approach that first estimated basis sinograms using a maximum likelihood algorithm and then reconstructed basis maps using an iterative total variation constrained least squares optimization (MLE+TVmin ). Images were also compared to a nonspectral TVmin reconstruction of the total number of counts detected for each ray with and without Normalized Metal Artifact Reduction (NMAR) applied. The simulated metal density was increased to investigate the effects of increasing photon starvation. The quantitative error and standard deviation in regions of the phantom were compared across the investigated algorithms. The ability of cOSSCIR to reproduce the soft-tissue texture, while reducing metal artifacts, was quantitatively evaluated. RESULTS Noiseless simulations demonstrated convergence of the cOSSCIR and MLE+TVmin algorithms to the correct basis maps in the presence of beam hardening effects. When noise was simulated, cOSSCIR demonstrated quantitative error of -1 HU, compared to 2 HU error for the MLE+TVmin algorithm and -154 HU error for the nonspectral TVmin +NMAR algorithm. For the cOSSCIR algorithm, the standard deviation in the central iodine ROI was 20 HU, compared to 299 HU for the MLE+TVmin algorithm, 41 HU for the MLE+TVmin +Mask algorithm that excluded rays through metal, and 55 HU for the nonspectral TVmin +NMAR algorithm. Increasing levels of photon starvation did not impact the bias or standard deviation of the cOSSCIR images. cOSSCIR was able to reproduce the soft-tissue texture when an appropriate regularization constraint value was selected. CONCLUSIONS By directly inverting photon-counting CT data into basis maps using an accurate physics-based forward model and a constrained optimization algorithm, cOSSCIR avoids metal artifacts due to beam hardening, noise, and photon starvation. The cOSSCIR algorithm demonstrated improved stability and accuracy compared to a two-step method of decomposition followed by reconstruction. This article is protected by copyright. All rights reserved.