title: The impact of reconstruction method on the quantification of DaTSCAN images.
abstract: OBJECTIVE
  Reconstruction of DaTSCAN brain studies using OS-EM iterative reconstruction offers better image quality and more accurate quantification than filtered back-projection. However, reconstruction must proceed for a sufficient number of iterations to achieve stable and accurate data. This study assessed the impact of the number of iterations on the image quantification, comparing the results of the iterative reconstruction with filtered back-projection data.
  
  
  METHODS
  A striatal phantom filled with (123)I using striatal to background ratios between 2:1 and 10:1 was imaged on five different gamma camera systems. Data from each system were reconstructed using OS-EM (which included depth-independent resolution recovery) with various combinations of iterations and subsets to achieve up to 200 EM-equivalent iterations and with filtered back-projection. Using volume of interest analysis, the relationships between image reconstruction strategy and quantification of striatal uptake were assessed.
  
  
  RESULTS
  For phantom filling ratios of 5:1 or less, significant convergence of measured ratios occurred close to 100 EM-equivalent iterations, whereas for higher filling ratios, measured uptake ratios did not display a convergence pattern. Assessment of the count concentrations used to derive the measured uptake ratio showed that nonconvergence of low background count concentrations caused peaking in higher measured uptake ratios. Compared to filtered back-projection, OS-EM displayed larger uptake ratios because of the resolution recovery applied in the iterative algorithm.
  
  
  CONCLUSIONS
  The number of EM-equivalent iterations used in OS-EM reconstruction influences the quantification of DaTSCAN studies because of incomplete convergence and possible bias in areas of low activity due to the nonnegativity constraint in OS-EM reconstruction. Nevertheless, OS-EM using 100 EM-equivalent iterations provides the best linear discriminatory measure to quantify the uptake in DaTSCAN studies.
authors.affiliation: Institute of Nuclear Medicine, UCLH NHS Foundation Trust and University College London, London, UK. john.dickson@uclh.nhs.uk
authors.forename: John C
authors.initials: JC
authors.lastname: Dickson
authors.forename: Livia
authors.initials: L
authors.lastname: Tossici-Bolt
authors.forename: Terez
authors.initials: T
authors.lastname: Sera
authors.forename: Kjell
authors.initials: K
authors.lastname: Erlandsson
authors.forename: Andrea
authors.initials: A
authors.lastname: Varrone
authors.forename: Klaus
authors.initials: K
authors.lastname: Tatsch
authors.forename: Brian F
authors.initials: BF
authors.lastname: Hutton
mesh_terms: D000465:Algorithms; D003342:Corpus Striatum / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D019047:Phantoms, Imaging; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D015899:Tomography, Emission-Computed, Single-Photon / Q000295:instrumentation / Q000379:methods*; D014326:Tropanes
chemical_list: D019275:Radiopharmaceuticals; D014326:Tropanes; C087552:2-carbomethoxy-8-(3-fluoropropyl)-3-(4-iodophenyl)tropane