Reproducibility of regional metabolic covariance patterns: Comparison of four populations

James R. Moeller, Toshitaka Nakamura, Marc J. Mentis, Vijay Dhawan, Phoebe Spetsieres, Angelo Antonini, John Missimer, Klaus L. Leenders, David Eidelberg

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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 indifferent 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 ~ 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). Conclusion: 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.

Original languageEnglish
Pages (from-to)1264-1269
Number of pages6
JournalJournal of Nuclear Medicine
Volume40
Issue number8
Publication statusPublished - Aug 1999

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Parkinson Disease
Population
Healthy Volunteers
Fluorodeoxyglucose F18
Neuroimaging
Weights and Measures

Keywords

  • FDG PET
  • Parkinson's disease
  • Regional metabolic covariance patterns

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology

Cite this

Moeller, J. R., Nakamura, T., Mentis, M. J., Dhawan, V., Spetsieres, P., Antonini, A., ... Eidelberg, D. (1999). Reproducibility of regional metabolic covariance patterns: Comparison of four populations. Journal of Nuclear Medicine, 40(8), 1264-1269.

Reproducibility of regional metabolic covariance patterns : Comparison of four populations. / Moeller, James R.; Nakamura, Toshitaka; Mentis, Marc J.; Dhawan, Vijay; Spetsieres, Phoebe; Antonini, Angelo; Missimer, John; Leenders, Klaus L.; Eidelberg, David.

In: Journal of Nuclear Medicine, Vol. 40, No. 8, 08.1999, p. 1264-1269.

Research output: Contribution to journalArticle

Moeller, JR, Nakamura, T, Mentis, MJ, Dhawan, V, Spetsieres, P, Antonini, A, Missimer, J, Leenders, KL & Eidelberg, D 1999, 'Reproducibility of regional metabolic covariance patterns: Comparison of four populations', Journal of Nuclear Medicine, vol. 40, no. 8, pp. 1264-1269.
Moeller JR, Nakamura T, Mentis MJ, Dhawan V, Spetsieres P, Antonini A et al. Reproducibility of regional metabolic covariance patterns: Comparison of four populations. Journal of Nuclear Medicine. 1999 Aug;40(8):1264-1269.
Moeller, James R. ; Nakamura, Toshitaka ; Mentis, Marc J. ; Dhawan, Vijay ; Spetsieres, Phoebe ; Antonini, Angelo ; Missimer, John ; Leenders, Klaus L. ; Eidelberg, David. / Reproducibility of regional metabolic covariance patterns : Comparison of four populations. In: Journal of Nuclear Medicine. 1999 ; Vol. 40, No. 8. pp. 1264-1269.
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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 indifferent 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 ~ 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). Conclusion: 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.",
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