Microglial activation in Alzheimer's disease: an (R)-[11C]PK11195 positron emission tomography study

AbstractInflammatory mechanisms, like microglial activation, could be involved in the pathogenesis of Alzheimer's disease (AD). (R)-[11C]PK11195 (1-(2-chlorophenyl)-N-methyl-N-1(1-methylpropyl)-3-isoquinolinecarboxamide), a positron emission tomography (PET) ligand, can be used to quantify microglial activation in vivo. The purpose of this study was to assess whether increased (R)-[11C]PK11195 binding is present in AD and mild cognitive impairment (MCI), currently also known as “prodromal AD.”MethodsNineteen patients with probable AD, 10 patients with prodromal AD (MCI), and 21 healthy control subjects were analyzed. Parametric images of binding potential (BPND) of (R)-[11C]PK11195 scans were generated using receptor parametric mapping (RPM) with supervised cluster analysis. Differences between subject groups were tested using mixed model analysis, and associations between BPND and cognition were evaluated using Pearson correlation coefficients.ResultsVoxel-wise statistical parametric mapping (SPM) analysis showed small clusters of significantly increased (R)-[11C]PK11195 BPND in occipital lobe in AD dementia patients compared with healthy control subjects. Regions of interest (ROI)-based analyses showed no differences, with large overlap between groups. There were no differences in (R)-[11C]PK11195 BPND between clinically stable prodromal AD patients and those who progressed to dementia, and BPND did not correlate with cognitive function.ConclusionMicroglial activation is a subtle phenomenon occurring in AD

First human case of tick-borne encephalitis virus infection acquired in the Netherlands, July 2016

In July 2016, the first autochthonous case of tick-borne encephalitis was diagnosed in the Netherlands, five days after a report that tick-borne encephalitis virus (TBEV) had been found in Dutch ticks. A person in their 60s without recent travel history suffered from neurological symptoms after a tick bite. TBEV serology was positive and the tick was positive in TBEV qRT-PCR. TBEV infection should be considered in patients with compatible symptoms in the Netherlands

Evaluation of reference tissue models for the analysis of [ 11C](R)-PK11195 studies

[11C](R)-PK11195 is a marker of activated microglia, which can be used to measure inflammation in neurologic disorders. The purpose of the present study was to define the optimal reference tissue model based on a comparison with a validated plasma input model and using clinical studies and Monte Carlo simulations. Accuracy and reproducibility of reference tissue models were evaluated using Monte Carlo simulations. The effects of noise and variation in specific binding, nonspecific binding and blood volume were evaluated. Dynamic positron emission tomography scans were performed on 13 subjects, and radioactivity in arterial blood was monitored online. In addition, blood samples were taken to generate a metabolite corrected plasma input function. Both a (validated) two-tissue reversible compartment model with K 1/k2 fixed to whole cortex and various reference tissue models were fitted to the data. Finally, a simplified reference tissue model (SRTM) corrected for nonspecific binding using plasma input data (SRTM pl_corr) was investigated. Correlations between reference tissue models (including SRTMpl_corr) and the plasma input model were calculated. Monte Carlo simulations indicated that low-specific binding results in decreased accuracy and reproducibility. In this respect, the SRTM and SRTMpl_corr performed relatively well. Varying blood volume had no effect on performance. In the clinical evaluation, SRTMpl_corr and SRTM had the highest correlations with the plasma input model (R 2=0.82 and 0.78, respectively). SRTMpl_corr is optimal when an arterial plasma input curve is available. Simplified reference tissue model is the best alternative when no plasma input is available

Daily variations in cerebral blood volume and consequences for quantitative PET studies

Background and aim: Although fractional cerebral blood volume (Vb) can easily be included as a separate parameter in full compartmental analysis of PET studies, it is more difficult to account for in simplified analyses. In a previous study a significant change in distribution volume of (R)-[11C]verapamil from morning to afternoon scans was found using Logan analysis, but compartmental analysis revealed that this difference could be attributed solely to differences in Vb [1]. The aim of the present study was to verify whether there is indeed significant daily variation in Vb. Methods: Whole brain grey matter Vb of 73 scans (51 (R)-[11C]PK11195, 12 (R)-[11C]verapamil and 10 [11C]R116301 scans) was related to scan start time retrospectively. (R)-[11C]verapamil and [11C]R116301 scans were part of a test-retest protocol, with the same volunteer being scanned twice on the same day at 10:30 and 15:00 h. All 60 min dynamic scans were acquired in 3D mode following administration of 370 MBq of tracer. A metabolite corrected arterial plasma input function was obtained using continuous arterial sampling together with discrete manual samples. A co-registered segmented T1-weighted MRI scan was used to define whole brain grey matter regions of interest. Data were analysed using single ((R)-[11C]verapamil) or two ((R)-[11C]PK11195, [11C]R116301) tissue compartment models, including Vb as a fit parameter. Differences in Vb between morning and afternoon scans were assessed using two-tailed t-tests. Results: In all scans, whole brain grey matter Vb could be determined with a standard error of less than 10%. A shown in table 1, a significant decrease in blood volume between morning and afternoon scans in the same subject was found for both (R)-[11C]verapamil and [11C]R116301. In addition, a significant difference in Vb between morning and afternoon (R)-[11C]PK11195 scans was found. Conclusion: For all three tracers, a decrease of ∼10% in average Vb was found from morning to afternoon scans. This decrease could not be attributed to blood sampling in the morning scan itself, as the effect was also seen in (R)-[11C]PK11195 scans where subjects underwent only a single scan. As demonstrated previously, a decrease in Vb during the day may lead to erroneous Results: when it is not included as a fit parameter [1]. This effect should be considered especially in challenge studies where successive scans may be acquired during the day

Performance of a Modified Supervised Cluster Algorithm for Extracting Reference Region Input Functions from (R)-[C-11]PK11195 Brain PET Studies

(R)-[11C]PK11195 is widely used as radiotracer for imaging activated microglia in the brain using positron emission tomography (PET). Recently, for quantification of specific binding, a supervised cluster analysis (SVCA) approach to extract the reference tissue input function has been reported. This method uses a database of six predefined kinetic classes (SVCA6). In the present study SVCA was modified to enhance performance of the algorithm. The modified SVCA first applies an anatomical mask to include brain tissue only. In this manner a smaller number of kinetic classes can be used (n = 4, SVCA4), potentially improving accuracy and precision. The purpose of this study was to evaluate the performance of SVCA4. To this end 60 min dynamic (R)-[ 11C]PK11195 studies of 9 AD subjects and 9 healthy controls were acquired, including continuous arterial blood sampling. A reference tissue time activity curve (TAC) was extracted from these scans using SVCA6, SVCA4 and a cerebellar region of interest(ROI).All reference TACs were fitted to a 2 tissue compartment plasma input model, including blood volume fraction, with volume of distribution (VT) as outcome parameter. VT obtained using SVCA4 and cerebellum showed better (i.e. less) intersubject and intergroup variability than when using SVCA6. Moreover, reference tissue input based quantification of (R)-[ 11C]PK11195 binding in a target region (thalamus) showed better correlation with plasma input kinetic analysis when using SVCA4 rather than SVCA6 or cerebellum. However, use of SVCA4 results in a blood volume related upward bias in combination with SRTM. The latter may be resolved by using a reference tissue model with blood volume fraction corrections. It is concluded that SVCA4 is more accurate and precise than SVCA6. Use of cerebellar ROI may still be used in combination with SRTM, but provides a more conservative measure of binding

Optimization of supervised cluster analysis for extracting reference tissue input curves in (R)-[C-11]PK11195 brain PET studies

Performance of two supervised cluster analysis (SVCA) algorithms for extracting reference tissue curves was evaluated to improve quantification of dynamic (R)-[(11)C]PK11195 brain positron emission tomography (PET) studies. Reference tissues were extracted from images using both a manually defined cerebellum and SVCA algorithms based on either four (SVCA4) or six (SVCA6) kinetic classes. Data from controls, mild cognitive impairment patients, and patients with Alzheimer's disease were analyzed using various kinetic models including plasma input, the simplified reference tissue model (RPM) and RPM with vascular correction (RPMV(b)). In all subject groups, SVCA-based reference tissue curves showed lower blood volume fractions (V(b)) and volume of distributions than those based on cerebellum time-activity curve. Probably resulting from the presence of specific signal from the vessel walls that contains in normal condition a significant concentration of the 18 kDa translocation protein. Best contrast between subject groups was seen using SVCA4-based reference tissues as the result of a lower number of kinetic classes and the prior removal of extracerebral tissues. In addition, incorporation of V(b) in RPM improved both parametric images and binding potential contrast between groups. Incorporation of V(b) within RPM, together with SVCA4, appears to be the method of choice for analyzing cerebral (R)-[(11)C]PK11195 neurodegeneration studies

SPM analysis of parametric (R)-[11C]PK11195 binding images: Plasma input versus reference tissue parametric methods

(R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (Vd) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. Vd images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K1/k2 (blood-brain barrier transport and non-specific binding)

Evaluation of methods for generating parametric (R)-[11C]PK11195 binding images

Activated microglia can be visualised using (R)-[11C]PK11195 (1-[2-chlorophenyl]-N-methyl-N-[1-methyl-propyl]-3-isoquinoline carboxamide) and positron emission tomography (PET). In previous studies, various methods have been used to quantify (R)-[11C]PK11195 binding. The purpose of this study was to determine which parametric method would be best suited for quantifying (R)-[11C]PK11195 binding at the voxel level. Dynamic (R)-[11C]PK11195 scans with arterial blood sampling were performed in 20 healthy and 9 Alzheimer's disease subjects. Parametric images of both volume of distribution (Vd) and binding potential (BP) were obtained using Logan graphical analysis with plasma input. In addition, BP images were generated using two versions of the basis function implementation of the simplified reference tissue model, two versions of Ichise linearisations, and Logan graphical analysis with reference tissue input. Results of the parametric methods were compared with results of full compartmental analysis using nonlinear regression. Simulations were performed to assess accuracy and precision of each method. It was concluded that Logan graphical analysis with arterial input function is an accurate method for generating parametric images of Vd. Basis function methods, one of the Ichise linearisations and Logan graphical analysis with reference tissue input provided reasonably accurate and precise estimates of BP. In pathological conditions with reduced flow rates or large variations in blood volume, the basis function method is preferred because it produces less bias and is more precise

Evaluation of reference regions for (R)-[11C]PK11195 studies in Alzheimer's disease and Mild Cognitive Impairment

Inflammation in Alzheimer's disease (AD) may be assessed using (R)-[ 11C]PK11195 and positron emission tomography. Data can be analyzed using the simplified reference tissue model, provided a suitable reference region is available. This study evaluates various reference regions for analyzing (R)-[11C]PK11195 scans in patients with mild cognitive impairment (MCI) and probable AD. Healthy subjects (n=10, 30±10 years and n=10, 70±6 years) and patients with MCI (n=10, 74±6 years) and probable AD (n=9, 71±6 years) were included. Subjects underwent a dynamic three-dimensional (R)-[11C]PK11195 scan including arterial sampling. Gray matter, white matter, total cerebellum and cerebrum, and cluster analysis were evaluated as reference regions. Both plasma input binding potentials of these reference regions (BPPLASMA) and corresponding reference region input binding potentials of a target region (BPSRTM) were evaluated. Simulations were performed to assess cluster analysis performance at 5% to 15% coefficient of variation noise levels. Reasonable correlations for BP PLASMA (R2=0.52 to 0.94) and BPSRTM (R 2=0.59 to 0.76) were observed between results using anatomic regions and cluster analysis. For cerebellum white matter, cerebrum white matter, and total cerebrum a considerable number of unrealistic BPSRTM values were observed. Cluster analysis did not extract a valid reference region in 10% of the scans. Simulations showed that potentially cluster analysis suffers from negative bias in BPPLASMA. Most anatomic regions outperformed cluster analysis in terms of absence of both scan rejection and bias. Total cerebellum is the optimal reference region in this patient category