Neuroinflammation predicts disease progression in progressive supranuclear palsy.

INTRODUCTION: In addition to tau pathology and neuronal loss, neuroinflammation occurs in progressive supranuclear palsy (PSP). However, the prognostic value of the in vivo imaging markers for these processes in PSP remains unclear. We test the primary hypothesis that baseline in vivo imaging assessment of neuroinflammation in subcortical regions predicts clinical progression in patients with PSP. METHODS: Seventeen patients with PSP-Richardson's syndrome underwent a baseline multimodal imaging assessment, including [11C]PK11195 positron emission tomography (PET) to index microglial activation, [18F]AV-1451 PET for tau pathology and structural MRI. Disease severity was measured at baseline and serially up to 4 years with the Progressive Supranuclear Palsy Rating Scale (PSPRS) (average interval of 5 months). Regional grey-matter volumes and PET ligand binding potentials were summarised by three principal component analyses (PCAs). A linear mixed-effects model was applied to the longitudinal PSPRS scores. Single-modality imaging predictors were regressed against the individuals' estimated rate of progression to identify the prognostic value of baseline imaging markers. RESULTS: PCA components reflecting neuroinflammation and tau burden in the brainstem and cerebellum correlated with the subsequent annual rate of change in the PSPRS. PCA-derived PET markers of neuroinflammation and tau pathology correlated with regional brain volume in the same regions. However, MRI volumes alone did not predict the rate of clinical progression. CONCLUSIONS: Molecular imaging with PET for microglial activation and tau pathology can predict clinical progression in PSP. These data encourage the evaluation of immunomodulatory approaches to disease-modifying therapies in PSP and the potential for PET to stratify patients in early phase clinical trials.

Dopamine release in dissociable striatal subregions predicts the different effects of oral methylphenidate on reversal learning and spatial working memory.

Previous data suggest that methylphenidate can have variable effects on different cognitive tasks both within and between individuals. This is thought to be underpinned by inverted U-shaped relationships between cognitive performance and dopaminergic activity in relatively separate fronto-striatal circuits and reflected by individual differences in trait impulsivity. Direct evidence for this is currently lacking. In this study, we demonstrate for the first time that therapeutic doses of oral methylphenidate administered to young healthy subjects result in different sized changes in D(2)/D(3) receptor availability in different regions of the human striatum and that the change in receptor availability within an individual subregion predicts cognitive performance on a particular task. Methylphenidate produced significantly different effects on reversal learning and spatial working memory tasks within individuals. Performance on the reversal learning task was predicted by the drug-induced change in D(2)/D(3) receptor availability in postcommissural caudate, measured using [(11)C]-raclopride radioligand PET imaging, whereas performance on the spatial working memory task was predicted by changes in receptor availability in the ventral striatum. Reversal learning performance was also predicted by subjects' trait impulsivity, such that the most impulsive individuals benefited more from methylphenidate, consistent with this drug's beneficial effects on cognition in attention deficit hyperactivity disorder.

A combined microdialysis and FDG-PET study of glucose metabolism in head injury.

BACKGROUND: Microdialysis continuously monitors the chemistry of a small focal volume of the cerebral extracellular space. Positron emission tomography (PET) establishes metabolism of the whole brain but only for the scan's duration. This study's objective was to apply these techniques together, in patients with traumatic brain injury, to assess the relationship between microdialysis (extracellular glucose, lactate, pyruvate, and the lactate/pyruvate (L/P) ratio as a marker of anaerobic metabolism) and PET parameters of glucose metabolism using the glucose analogue [(18)F]-fluorodeoxyglucose (FDG). In particular, we aimed to determine the fate of glucose in terms of differential metabolism to pyruvate and lactate. MATERIALS AND METHODS: Microdialysis catheters (CMA70 or CMA71) were inserted into the cerebral cortex of 17 patients with major head injury. Microdialysis was performed during FDG-PET scans with regions of interest for PET analysis defined by the location of the gold-tipped microdialysis catheter. Microdialysate analysis was performed on a CMA600 analyser. FINDINGS: There was significant linear relationship between the PET-derived parameter of glucose metabolism (regional cerebral metabolic rate of glucose; CMRglc) and levels of lactate (r = 0.778, p < 0.0001) and pyruvate (r = 0.799, p < 0.0001), but not with the L/P ratio. CONCLUSION: The results suggest that in this population of patients, glucose was metabolised to both lactate and pyruvate, but was not associated with an increase in the L/P ratio. This suggests an increase in glucose metabolism to both lactate and pyruvate, as opposed to a shift towards anaerobic metabolism.

High Structural Stress and Presence of Intraluminal Thrombus Predict Abdominal Aortic Aneurysm 18F-FDG Uptake: Insights From Biomechanics.

BACKGROUND: Abdominal aortic aneurysm (AAA) wall inflammation and mechanical structural stress may influence AAA expansion and lead to rupture. We hypothesized a positive correlation between structural stress and fluorine-18-labeled 2-deoxy-2-fluoro-d-glucose (18F-FDG) positron emission tomography-defined inflammation. We also explored the influence of computed tomography-derived aneurysm morphology and composition, including intraluminal thrombus, on both variables. METHODS AND RESULTS: Twenty-one patients (19 males) with AAAs below surgical threshold (AAA size was 4.10±0.54 cm) underwent 18F-FDG positron emission tomography and contrast-enhanced computed tomography imaging. Structural stresses were calculated using finite element analysis. The relationship between maximum aneurysm 18F-FDG standardized uptake value within aortic wall and wall structural stress, patient clinical characteristics, aneurysm morphology, and compositions was explored using a hierarchical linear mixed-effects model. On univariate analysis, local aneurysm diameter, thrombus burden, extent of calcification, and structural stress were all associated with 18F-FDG uptake (P<0.05). AAA structural stress correlated with 18F-FDG maximum standardized uptake value (slope estimate, 0.552; P<0.0001). Multivariate linear mixed-effects analysis revealed an important interaction between structural stress and intraluminal thrombus in relation to maximum standardized uptake value (fixed effect coefficient, 1.68 [SE, 0.10]; P<0.0001). Compared with other factors, structural stress was the best predictor of inflammation (receiver-operating characteristic curve area under the curve =0.59), with higher accuracy seen in regions with high thrombus burden (area under the curve =0.80). Regions with both high thrombus burden and high structural stress had higher 18F-FDG maximum standardized uptake value compared with regions with high thrombus burdens but low stress (median [interquartile range], 1.93 [1.60-2.14] versus 1.14 [0.90-1.53]; P<0.0001). CONCLUSIONS: Increased aortic wall inflammation, demonstrated by 18F-FDG positron emission tomography, was observed in AAA regions with thick intraluminal thrombus subjected to high mechanical stress, suggesting a potential mechanistic link underlying aneurysm inflammation.

Integrated image analysis solutions for PET datasets in damaged brain.

OBJECTIVE: To identify and discuss the problems inherent in the processing of multiparametric functional imaging datasets from patients with acute brain injury, using "triple oxygen" positron emission tomography (PET) as an example. To present an integrated imaging solution for analysis of such datasets and report on its use in practice. METHODS: Structured analysis of the steps in image analysis for triple oxygen studies in patients with acute brain injury, subarachnoid haemorrhage and carotid artery disease was undertaken. Systematic identification of the drawbacks of conventional manual processing techniques, which make use of modules from different commercially available software packages was carried out. This analysis informed the construction of an image analysis gateway that addressed these issues. RESULTS: We describe an integrated image analysis gateway (PETAn) that provides for the automated integration of all processing steps, along with outputs that detail analysis stages, error logs and results. Implementation of PETAn allowed batch processing of clinical PET data sets, reduced the level of technical expertise required for analysis, improved the quality of results and achieved significant reductions in operator analysis time. CONCLUSIONS: While modules from several imaging software suites can be usefully combined to allow analysis of multiparametric PET data sets from patients with acute brain injury, sequential use of these modules for various steps in image analysis is fraught with difficulty. Careful automation and integration of these steps greatly facilitates the interrogation of information-rich data sets and increases research productivity.