title: Visual-statistical interpretation of (18)F-FDG-PET images for characteristic Alzheimer patterns in a multicenter study: inter-rater concordance and relationship to automated quantitative evaluation.
abstract: OBJECTIVE
  The role of (18)F-FDG-PET in the diagnosis of Alzheimer disease is increasing and should be validated. The aim of this study was to assess the inter-rater variability in the interpretation of (18)F-FDG-PET images obtained in the Japanese Alzheimer's Disease Neuroimaging Initiative, a multicenter clinical research project.
  
  
  METHODS
  This study analyzed 274 (18)F-FDG-PET scans (67 mild Alzheimer disease, 100 mild cognitive impairment, and 107 normal cognitive) as baseline scans for the Japanese Alzheimer's Disease Neuroimaging Initiative, which were acquired with various types of PET or PET/CT scanners in 23 facilities. Three independent raters interpreted all PET images by using a combined visual-statistical method. The images were classified into 7 (FDG-7) patterns by the criteria of Silverman et al and further into 2 (FDG-2) patterns.
  
  
  RESULTS
  Agreement among the 7 visual-statistical categories by at least 2 of the 3 readers occurred in >94% of cases for all groups: Alzheimer disease, mild cognitive impairment, and normal cognitive. Perfect matches by all 3 raters were observed for 62% of the cases by FDG-7 and 76 by FDG-2. Inter-rater concordance was moderate by FDG-7 (κ = 0.57) and substantial in FDG-2 (κ = 0.67) on average. The FDG-PET score, an automated quantitative index developed by Herholz et al, increased as the number of raters who voted for the AD pattern increased (ρ = 0.59, P < .0001), and the FDG-PET score decreased as those for normal pattern increased (ρ = -0.64, P < .0001).
  
  
  CONCLUSIONS
  Inter-rater agreement was moderate to substantial for the combined visual-statistical interpretation of (18)F-FDG-PET and was also significantly associated with automated quantitative assessment.
authors.affiliation: From the Division of Molecular Imaging (T.Y., Y.I., T.N., M. Senda), Institute of Biomedical Research and Innovation, Kobe, Japan.
authors.forename: T
authors.initials: T
authors.lastname: Yamane
authors.forename: Y
authors.initials: Y
authors.lastname: Ikari
authors.forename: T
authors.initials: T
authors.lastname: Nishio
authors.forename: K
authors.initials: K
authors.lastname: Ishii
authors.forename: K
authors.initials: K
authors.lastname: Ishii
authors.forename: T
authors.initials: T
authors.lastname: Kato
authors.forename: K
authors.initials: K
authors.lastname: Ito
authors.forename: D H S
authors.initials: DH
authors.lastname: Silverman
authors.forename: M
authors.initials: M
authors.lastname: Senda
authors.forename: T
authors.initials: T
authors.lastname: Asada
authors.forename: H
authors.initials: H
authors.lastname: Arai
authors.forename: M
authors.initials: M
authors.lastname: Sugishita
authors.forename: T
authors.initials: T
authors.lastname: Iwatsubo
mesh_terms: D000465:Algorithms; D000544:Alzheimer Disease / Q000150:complications / Q000000981:diagnostic imaging*; D001185:Artificial Intelligence; D060825:Cognitive Dysfunction / Q000150:complications / Q000000981:diagnostic imaging*; D003627:Data Interpretation, Statistical; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007564:Japan; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
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