title: Assessment of metal artifact reduction methods in pelvic CT.
abstract: OBJECTIVE
  Metal artifact reduction (MAR) produces images with improved quality potentially leading to confident and reliable clinical diagnosis and therapy planning. In this work, the authors evaluate the performance of five MAR techniques for the assessment of computed tomography images of patients with hip prostheses.
  
  
  METHODS
  Five MAR algorithms were evaluated using simulation and clinical studies. The algorithms included one-dimensional linear interpolation (LI) of the corrupted projection bins in the sinogram, two-dimensional interpolation (2D), a normalized metal artifact reduction (NMAR) technique, a metal deletion technique, and a maximum a posteriori completion (MAPC) approach. The algorithms were applied to ten simulated datasets as well as 30 clinical studies of patients with metallic hip implants. Qualitative evaluations were performed by two blinded experienced radiologists who ranked overall artifact severity and pelvic organ recognition for each algorithm by assigning scores from zero to five (zero indicating totally obscured organs with no structures identifiable and five indicating recognition with high confidence).
  
  
  RESULTS
  Simulation studies revealed that 2D, NMAR, and MAPC techniques performed almost equally well in all regions. LI falls behind the other approaches in terms of reducing dark streaking artifacts as well as preserving unaffected regions (p < 0.05). Visual assessment of clinical datasets revealed the superiority of NMAR and MAPC in the evaluated pelvic organs and in terms of overall image quality.
  
  
  CONCLUSIONS
  Overall, all methods, except LI, performed equally well in artifact-free regions. Considering both clinical and simulation studies, 2D, NMAR, and MAPC seem to outperform the other techniques.
authors.affiliation: Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX, The Netherlands.
authors.forename: Mehrsima
authors.initials: M
authors.lastname: Abdoli
authors.affiliation: Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva CH-1211, Switzerland.
authors.forename: Abolfazl
authors.initials: A
authors.lastname: Mehranian
authors.affiliation: Division of Radiology, Geneva University Hospital, Geneva CH-1211, Switzerland.
authors.forename: Angeliki
authors.initials: A
authors.lastname: Ailianou
authors.affiliation: Division of Radiology, Geneva University Hospital, Geneva CH-1211, Switzerland.
authors.forename: Minerva
authors.initials: M
authors.lastname: Becker
authors.affiliation: Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva CH-1211, Switzerland; Geneva Neuroscience Center, Geneva University, Geneva CH-1205, Switzerland; and Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen 9700 RB, The Netherlands.
authors.forename: Habib
authors.initials: H
authors.lastname: Zaidi
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D016477:Artifacts; D005260:Female; D006622:Hip Prosthesis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008670:Metals; D008875:Middle Aged; D010388:Pelvis / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed
chemical_list: D008670:Metals