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An international group of experts in pharmacokinetic modeling recommends a consensus nomenclature to describe in vivo molecular imaging of reversibly binding radioligands.

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To investigate the pathophysiology of fatigue in MS, we assessed cerebral glucose metabolism (CMR-Glu) in 47 MS patients using PET and 18F-fluorodeoxyglucose. Applying the Fatigue Severity Scale (FSS), we first compared MS patients with severe fatigue (MS-FAT, n = 19, FSS > 4.9) and MS patients without fatigue (MS-NOF, n = 16, FSS < 3.7) on a pixel-by-pixel basis using Statistical Parametric Mapping (SPM95). Second, we compared FSS values of all 47 patients covering the whole range of this scale with CMRGlu using an analysis of covariance (SPM95). In addition, we determined global CMRGlu by region-of-interest analysis. Sixteen healthy subjects served as control subjects (CON). Global CMRGlu was significantly lower in both MS groups compared with CON (CON 43.3 +/- 6.9 mumol/100 mL/min, MS-FAT 34.7 +/- 4.4, MS-NOF 35.4 +/- 4.5) but was not related to fatigue severity. Comparing the two MS groups, SPM95 analysis revealed predominant CMRGlu reductions bilaterally in a prefrontal area involving the lateral and medial prefrontal cortex and adjacent white matter, in the premotor cortex, putamen, and in the right supplementary motor area of MS-FAT. In addition, there were CMRGlu reductions in the white matter extending from the rostral putamen toward the lateral head of the caudate nucleus. FSS values were inversely related to CMRGlu in the right prefrontal cortex. CMRGlu in the cerebellar vermis and anterior cingulate was relatively higher in MS-FAT than in MS-NOF patients. CMRGlu of both regions showed positive correlations with FSS values. Our data suggest that fatigue in MS is associated with frontal cortex and basal ganglia dysfunction that could result from demyelination of the frontal white matter.

In normal humans, relationships between cognitive test performance and cortical structure have received little study, in part, because of the paucity of tools for measuring cortical structure. Computational morphometric methods have recently been developed that enable the measurement of cortical thickness from MRI data, but little data exist on their reliability. We undertook this study to evaluate the reliability of an automated cortical thickness measurement method to detect correlates of interest between thickness and cognitive task performance. Fifteen healthy older participants were scanned four times at two-week intervals on three different scanner platforms. The four MRI datasets were initially treated independently to investigate the reliability of the spatial localization of findings from exploratory whole-cortex analyses of cortical thickness-cognitive performance correlates. Next, the first dataset was used to define cortical ROIs based on the exploratory results that were then applied to the remaining three datasets to determine whether the relationships between cognitive performance and regional cortical thickness were comparable across different scanner platforms and Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Author ManuscriptNeuroimage. Author manuscript; available in PMC 2009 January 1. Published in final edited form as:Neuroimage. 2008 January 1; 39(1): 10-18. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript field strengths. Verbal memory performance was associated with medial temporal cortical thickness, while visuomotor speed/set-shifting was associated with lateral parietal cortical thickness. These effects were highly reliable-in terms of both spatial localization and magnitude of absolute cortical thickness measurements-across the four scan sessions. Brain-behavior relationships between regional cortical thickness and cognitive task performance can be reliably identified using an automated data analysis system, suggesting that these measures may be useful as imaging biomarkers of disease or performance ability in multi-center studies in which MRI data are pooled.