title: Reproducibility of regional metabolic covariance patterns: comparison of four populations.
abstract: In a previous [18F]fluorodeoxyglucose (FDG) PET study we analyzed regional metabolic data from a combined group of Parkinson's disease (PD) patients and healthy volunteers (N), using network analysis. By this method, we identified a unique pattern of regional metabolic covariation with an expression which accurately discriminated patients from healthy volunteers. To assess the reproducibility of this pattern as a potential marker for PD, we compared the pattern's topography with that of the disease-related covariance patterns identified in three other independent populations of patients with PD and healthy individuals studied in different PET laboratories.
  
  
  METHODS
  The following patient populations were studied: group A (original cohort: 22 PD, 20 N; resolution: 7.5 mm full width at half maximum [FWHM]); group B (18 PD, 12 N; resolution: 4.2 mm FWHM); group C (25 PD, 15 N; resolution: 8.0 mm FWHM); and group D (14 PD, 10 N; resolution: 10 mm FWHM). Region weights for the PD-related covariance pattern (PDRP) identified in the group A analysis were correlated with those for the disease-related patterns identified in the analyses of groups B, C and D. In addition, subject scores for the group A PDRP were computed prospectively for every individual in each of the study populations. PDRP scores for PD and N within each cohort were compared.
  
  
  RESULTS
  The PDRP topography identified in group A was highly correlated with each of the corresponding topographies identified in the other populations (r2 approximately 0.60, P < 0.0001). Prospectively computed subject scores for the group A PDRP significantly discriminated PD from N in each population (P < 0.004).
  
  
  CONCLUSIONS
  The PDRP topography identified previously in Group A is highly reproducible across patient populations and tomographs. Prospectively computed PDRP scores can accurately discriminate patients from controls in multiple populations studied with different tomographs. Brain network imaging with FDG PET can provide robust metabolic markers for the diagnosis of PD.
authors.affiliation: Department of Psychiatry, Columbia College of Physicians and Surgeons, New York, New York, USA.
authors.forename: J R
authors.initials: JR
authors.lastname: Moeller
authors.forename: T
authors.initials: T
authors.lastname: Nakamura
authors.forename: M J
authors.initials: MJ
authors.lastname: Mentis
authors.forename: V
authors.initials: V
authors.lastname: Dhawan
authors.forename: P
authors.initials: P
authors.lastname: Spetsieres
authors.forename: A
authors.initials: A
authors.lastname: Antonini
authors.forename: J
authors.initials: J
authors.lastname: Missimer
authors.forename: K L
authors.initials: KL
authors.lastname: Leenders
authors.forename: D
authors.initials: D
authors.lastname: Eidelberg
mesh_terms: D001921:Brain / Q000000981:diagnostic imaging; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D014055:Tomography, Emission-Computed / Q000592:standards*
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18