An Algorithm for Efficient Metal Artifact Reductions in Permanent Seed

Purpose: In permanent seed implants, 60 to more than 100 small metal capsules are inserted in the prostate, creating artifacts in x-ray computed tomography (CT) imaging. The goal of this work is to develop an automatic method for metal artifact reduction (MAR) from small objects such as brachytherapy seeds for clinical applications.

Methods: The approach for MAR is based on the interpolation of missing projections by directly using raw helical CT data (sinogram). First, an initial image is reconstructed from the raw CT data. Then, the metal objects segmented from the reconstructed image are reprojected back into the sinogram space to produce a metal-only sinogram. The Steger method is used to determine precisely the position and edges of the seed traces in the raw CT data. By combining the use of Steger detection and reprojections, the missing projections are detected and replaced by interpolation of non-missing neighboring projections.

Results: In both phantom experiments and patient studies, the missing projections have been detected successfully and the artifacts caused by metallic objects have been substantially reduced. The performance of the algorithm has been quantified by comparing the uniformity between the uncorrected and the corrected phantom images. The results of the artifact reduction algorithm are indistinguishable from the true background value.

Conclusions: An efficient algorithm for MAR in seed brachytherapy was developed. The test results obtained using raw helical CT data for both phantom and clinical cases have demonstrated that the proposed MAR method is capable of accurately detecting and correcting artifacts caused by a large number of very small metal objects (seeds) in sinogram space. This should enable a more accurate use of advanced brachytherapy dose calculations, such as Monte Carlo simulations.