title: Metallic implant geometry and susceptibility estimation using multispectral B0field maps.
abstract: To estimate the susceptibility and the geometry of metallic implants from multispectral imaging (MSI) information, to separate the metal implant region from the surrounding signal loss region.
  
  
  
  The susceptibility map of signal-void regions is estimated from MSI B0field maps using total variation (TV) regularized inversion. Voxels with susceptibility estimates above a predetermined threshold are identified as metal. The accuracy of the estimated susceptibility and implant geometry was evaluated in simulations, phantom, and in vivo experiments.
  
  
  
  The proposed method provided more accurate susceptibility estimation compared with a previous method without TV regularization, in both simulations and phantom experiments. In the phantom experiment where the actual implant was 40% of the signal-void region, the mean estimated susceptibility was close to the susceptibility in literature, and the precision and recall of the estimated geometry was 85% and 93%. In vivo studies in subjects with hip implants also demonstrated that the proposed method can distinguish implants from surrounding low-signal tissues, such as cortical bone.
  
  
  
  The proposed method can improve the delineation of metallic implant geometry by distinguishing metal voxels from artificial signal voids and low-signal tissues by estimating the susceptibility maps. Magn Reson Med 77:2402-2413, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
authors.affiliation: Department of Radiology, Stanford University, Stanford, California, USA.|Department of Electrical Engineering, Stanford University, Stanford, California, USA.
authors.forename: Xinwei
authors.initials: X
authors.lastname: Shi
authors.affiliation: Department of Radiology, Stanford University, Stanford, California, USA.
authors.forename: Daehyun
authors.initials: D
authors.lastname: Yoon
authors.affiliation: Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
authors.forename: Kevin M
authors.initials: KM
authors.lastname: Koch
authors.affiliation: Department of Radiology, Stanford University, Stanford, California, USA.|Department of Electrical Engineering, Stanford University, Stanford, California, USA.|Department of Bioengineering, Stanford University, Stanford, California, USA.
authors.forename: Brian A
authors.initials: BA
authors.lastname: Hargreaves
mesh_terms: D000465:Algorithms; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008670:Metals; D019736:Prostheses and Implants; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D008670:Metals
keywords: field map; metal implants; multispectral imaging; susceptibility artifacts; susceptibility mapping