An efficient polyenergetic SART (pSART) reconstruction algorithm for quantitative myocardial CT perfusion.
PURPOSE: In quantitative myocardial CT perfusion imaging, beam hardening effect due to dense bone and high concentration iodinated contrast agent can result in visible artifacts and inaccurate CT numbers. In this paper, an efficient polyenergetic Simultaneous Algebraic Reconstruction Technique (pSART) was presented to eliminate the beam hardening artifacts and to improve the CT quantitative imaging ability. METHODS: Our algorithm made three a priori assumptions: (1) the human body is composed of several base materials (e.g., fat, breast, soft tissue, bone, and iodine); (2) images can be coarsely segmented to two types of regions, i.e., nonbone regions and noniodine regions; and (3) each voxel can be decomposed into a mixture of two most suitable base materials according to its attenuation value and its corresponding region type information. Based on the above assumptions, energy-independent accumulated effective lengths of all base materials can be fast computed in the forward ray-tracing process and be used repeatedly to obtain accurate polyenergetic projections, with which a SART-based equation can correctly update each voxel in the backward projecting process to iteratively reconstruct artifact-free images. This approach effectively reduces the influence of polyenergetic x-ray sources and it further enables monoenergetic images to be reconstructed at any arbitrarily preselected target energies. A series of simulation tests were performed on a size-variable cylindrical phantom and a realistic anthropomorphic thorax phantom. In addition, a phantom experiment was also performed on a clinical CT scanner to further quantitatively validate the proposed algorithm. RESULTS: The simulations with the cylindrical phantom and the anthropomorphic thorax phantom showed that the proposed algorithm completely eliminated beam hardening artifacts and enabled quantitative imaging across different materials, phantom sizes, and spectra, as the absolute relative errors were reduced from [-7.5%, 12.1%] for SART to [-0.1%, 0.1%] for pSART. When using low kVp spectra and high reference energies, pSART also showed improved reconstruction efficiency in terms of convergence speed compared to the conventional SART algorithm. The phantom experiment on a clinical CT scanner indicated that the quantitative advantage of pSART is realizable in experimental CT acquisition, as the absolute relative errors across material inserts were less than 0.4%. CONCLUSIONS: By incorporatinga priori information (material attenuation coefficients, x-ray source spectrum, and region type information) into the reconstruction process, the proposed pSART algorithm could effectively eliminate beam hardening artifacts, reconstruct the accurate attenuation coefficients for precise quantitative imaging, and accelerate the reconstruction process.
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