Abnormal regional brain function in Parkinson's disease: truth or fiction?
Normalization of regional measurements by the global mean is commonly employed to minimize inter-subject variability in functional imaging studies. This practice is based on the assumption that global values do not substantially differ between patient and control groups. In this issue of NeuroImage, Borghammer and colleagues challenge the validity of this assumption. They focus on Parkinson's disease (PD) and use computer simulations to show that lower global values can produce spurious increases in subcortical brain regions. The authors speculate that the increased signal observed in these areas in PD is artefactual and unrelated to localized changes in brain function. In this commentary, we summarize what is currently known of the relationship between regional and global metabolic activity in PD and experimental parkinsonism. We found that early stage PD patients exhibit global values that are virtually identical to those of age-matched healthy subjects. SPM analysis revealed increased normalized metabolic activity in a discrete set of biologically relevant subcortical brain regions. Because of their higher variability, the corresponding absolute regional measures did not differ across the two groups. Longitudinal imaging studies in this population showed that the subcortical elevations in normalized metabolism appeared earlier and progressed faster than did focal cortical or global metabolic reductions. The observed increases in subcortical activity, but not the global changes, correlated with independent clinical measures of disease progression. Multivariate analysis with SSM/PCA further confirmed that the abnormal spatial covariance structure of early PD is dominated by these subcortical increases as opposed to network-related reductions in cortical metabolic activity or global changes. Thus, increased subcortical activity in PD cannot be regarded as a simple artefact of global normalization. Moreover, stability of the normalized measurements, particularly at the network level, makes these metabolic indices suitable as imaging biomarkers of PD progression and the treatment response.
Ma
Yilong
Y
Center for Neurosciences, The Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, NY 11030, USA.
Tang
Chengke
C
Moeller
James R
JR
Eidelberg
David
D
D000328:Adult; D016477:Artifacts; D001921:Brain / Q000098:blood supply* / Q000000981:diagnostic imaging*; D002560:Cerebrovascular Circulation; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000000981:diagnostic imaging*; D049268:Positron-Emission Tomography / Q000379:methods*; D012016:Reference Values; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity