title: Metal artifact correction for x-ray computed tomography using kV and selective MV imaging.
abstract: OBJECTIVE
  The overall goal of this work is to improve the computed tomography (CT) image quality for patients with metal implants or fillings by completing the missing kilovoltage (kV) projection data with selectively acquired megavoltage (MV) data that do not suffer from photon starvation. When both of these imaging systems, which are available on current radiotherapy devices, are used, metal streak artifacts are avoided, and the soft-tissue contrast is restored, even for regions in which the kV data cannot contribute any information.
  
  
  METHODS
  Three image-reconstruction methods, including two filtered back-projection (FBP)-based analytic methods and one iterative method, for combining kV and MV projection data from the two on-board imaging systems of a radiotherapy device are presented in this work. The analytic reconstruction methods modify the MV data based on the information in the projection or image domains and then patch the data onto the kV projections for a FBP reconstruction. In the iterative reconstruction, the authors used dual-energy (DE) penalized weighted least-squares (PWLS) methods to simultaneously combine the kV/MV data and perform the reconstruction.
  
  
  RESULTS
  The authors compared kV/MV reconstructions to kV-only reconstructions using a dental phantom with fillings and a hip-implant numerical phantom. Simulation results indicated that dual-energy sinogram patch FBP and the modified dual-energy PWLS method can successfully suppress metal streak artifacts and restore information lost due to photon starvation in the kV projections. The root-mean-square errors of soft-tissue patterns obtained using combined kV/MV data are 10-15 Hounsfield units smaller than those of the kV-only images, and the structural similarity index measure also indicates a 5%-10% improvement in the image quality. The added dose from the MV scan is much less than the dose from the kV scan if a high efficiency MV detector is assumed.
  
  
  CONCLUSIONS
  The authors have shown that it is possible to improve the image quality of kV CTs for patients with metal implants or fillings by completing the missing kV projection data with selectively acquired MV data that do not suffer from photon starvation. Numerical simulations demonstrated that dual-energy sinogram patch FBP and a modified kV/MV PWLS method can successfully suppress metal streak artifacts and restore information lost due to photon starvation in kV projections. Combined kV/MV images may permit the improved delineation of structures of interest in CT images for patients with metal implants or fillings.
authors.affiliation: Department of Electrical Engineering, Stanford University, Stanford, California 94305.
authors.forename: Meng
authors.initials: M
authors.lastname: Wu
authors.affiliation: microDimensions GmbH, Munich 81379, Germany.
authors.forename: Andreas
authors.initials: A
authors.lastname: Keil
authors.affiliation: Varian Medical Systems, Inc., Palo Alto, California 94304.
authors.forename: Dragos
authors.initials: D
authors.lastname: Constantin
authors.affiliation: Varian Medical Systems, Inc., Palo Alto, California 94304.
authors.forename: Josh
authors.initials: J
authors.lastname: Star-Lack
authors.affiliation: Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332.
authors.forename: Lei
authors.initials: L
authors.lastname: Zhu
authors.affiliation: Department of Radiology, Stanford University, Stanford, California 94305.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Fahrig
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D003793:Dental Restoration, Permanent; D006615:Hip / Q000000981:diagnostic imaging; D016018:Least-Squares Analysis; D016014:Linear Models; D008670:Metals; D008954:Models, Biological; D019047:Phantoms, Imaging; D017785:Photons; D019736:Prostheses and Implants; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000379:methods*
chemical_list: D008670:Metals