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Reproducibility of Regional Metabolic Covariance Patterns: Comparison of Four Populations

Department of Psychiatry, Columbia College of Physicians and Surgeons, New York
New York University School of Medicine, New York
Functional Brain Imaging Laboratory, North Shore University Hospital, Manhasset, New York, New York
Paul Scherrer Institute, Villengen, Switzerland

Correspondence: For correspondence or reprints contact: David Eidelberg, MD, Functional Brain Imaging Laboratory, North Shore University Hospital, 350 Community Dr., Manhasset, New York, 11030.

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 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.

Key Words: regional metabolic covariance patterns • FDG PET • Parkinson's disease

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