title: Digital tomosynthesis of hand joints for arthritis assessment.
abstract: The two principal forms of hand arthritis, rheumatoid arthritis (RA) and osteoarthritis (OA) have large clinical and economic costs. Radiography has been shown to be a useful tool to assess the condition of the disease. A hand radiograph, however, is a two-dimensional projection of a three-dimensional object. In this report we present the results of a study that applied digital tomosynthesis to hand radiography in order to extract three-dimensional outcome measures that should be more sensitive to arthritis progression. The study was performed using simulated projection radiographs created using micro computed tomography (microCT) and a set of five dry-bone hand skeletons. These simulated projection images were then reconstructed into tomographic slices using the matrix inversion tomosynthesis (MITS) algorithm. The accuracy of the tomosynthesis reconstruction was evaluated by comparing the reconstructed images to a gold standard created using the microCT data. A parameter from image registration science, normalized mutual information, provided a quantifiable figure of merit. This study examined the effects of source displacement, number of reconstructed planes, number of acquisitions, noise added to the gray scale images, and errors in the location of a fiducial marker. We also optimized the reconstruction as a function of two variables k and alpha, that controlled the mixing of MITS with conventional shift-and-add tomosynthesis. A study using hand delineated joint margins demonstrated that MITS images provided a better measurement of average joint space width. We found good agreement between the MITS slices and the true planes. Both joint margins and trabecular structure were visible and the reconstructed slices showed additional structures not visible with the standard projection image. Using hand-delineated joint margins we compared the average joint space width of the gold standard slices to the MITS and projection images. A root-mean square deviation (RMSD), calculated for this comparison, gave RMSDproj = 0.18 mm and RMSDMITS = 0.14 mm for the projection and MITS images, respectively. We have demonstrated the potential of digital tomosynthesis for imaging of the hand to assess arthritic changes. We have also developed a methodology that can be used to optimize the technique and have studied the issues that will control the feasibility of clinical implementation.
authors.affiliation: Osteoporosis and Arthritis Research Group, Department of Radiology, University of California, San Francisco, San Francisco, California 94143, USA. jduryea@bwh.harvard.edu
authors.forename: J
authors.initials: J
authors.lastname: Duryea
authors.forename: J T
authors.initials: JT
authors.lastname: Dobbins
authors.forename: J A
authors.initials: JA
authors.lastname: Lynch
mesh_terms: D001168:Arthritis / Q000000981:diagnostic imaging*; D016477:Artifacts; D005384:Finger Joint / Q000000981:diagnostic imaging*; D006225:Hand / Q000000981:diagnostic imaging; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008662:Metacarpophalangeal Joint / Q000000981:diagnostic imaging; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012016:Reference Values; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity