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INTRODUCTION: Capillary dysfunction, characterized by disturbances in capillary blood flow distribution, might be an overlooked factor in the development of Alzheimer's disease (AD). This study investigated microvascular blood flow in preclinical and prodromal AD individuals. METHODS: Using dynamic susceptibility contrast magnetic resonance imaging and positron emission tomography, we examined alterations in microvascular circulation and levels of Aβ deposition in two independent cohorts of APOE ε4 carriers. RESULTS: Capillary dysfunction was elevated in both prodromal and preclinical AD individuals compared to age‐matched controls. Additionally, the prodromal group exhibited higher levels of capillary dysfunction compared to the preclinical group. DISCUSSION: These findings suggest that capillary dysfunction can be detected at the preclinical stage of AD and indicates a worsening of capillary dysfunction throughout the AD continuum. Understanding the interaction between capillary dysfunction and Aβ could provide insights into the relationship between cardiovascular risk factors and the development of AD. Highlights: Alzheimer's disease (AD) is associated with disturbances in microvascular circulation.Capillary dysfunction can be detected in preclinical AD.As cognitive symptoms progress in prodromal AD, capillary dysfunction worsens.Capillary dysfunction may impede the clearance of beta‐amyloid (Aβ).Capillary dysfunction might contribute to the development of AD. [ABSTRACT FROM AUTHOR]

Background: Activated microglia is present in both Alzheimer's subjects (AD) and mild cognitive impairment (MCI) subjects and can be visualised by both pathological evaluation and in‐vivo imaging studies. It has been established that neuroinflammation plays a vital role in Alzheimer's trajectory and disruption in structural and functional connectivity is also a key event in Alzheimer's disease. However, the mechanism by which microglial activation influence brain structural and functional connectivity remains to be elucidated. 11C‐PBR28 PET is a marker of translocator protein (TSPO) reflecting microglial activation and 18F‐Flutematemol PET is a marker of amyloid deposition. Method: 25 amnestic MCI and 17 healthy controls (HC) were recruited and underwent T1‐weighted, diffusion tensor and resting‐state functional MRI, 11C‐PBR28 and 18F‐Flutemetamol PET scans. 11C‐PBR28 and 18F‐Flutemetamol scans were analysed using target‐to‐cerebellar ratio. Tract‐Based Spatial Statistics was performed on DTI scans. RS‐fMRI scans were analysed using medial prefrontal cortex (MPFC) as a seed. The relationship between tracer uptake and structural integrity of white matter tracts or brain functional connectivity with MPFC was analysed using linear regression corrected for age and gender. Result: MCI cohort showed significantly decreased functional connectivity between MPFC and posterior cingulate and precuneous regions. Cortical 11C‐PBR28 uptake but not 18F‐Flutemetamol was negatively correlated with FA in the corpus callosum, bilateral inferior frontal‐occipital fasciculi and inferior longitudinal fasciculi. MPFC 11C‐PBR28 uptake was correlated with increased MPFC functional connectivity to anterior frontal regions and reduced connectivity to posterior frontal, temporal, parietal and cingulate regions; while frontal amyloid load was correlated with reduced MPFC connectivity with frontal and temporal cortices. Regression analysis with both 18F‐Flutemetamol and 11C‐PBR28 demonstrated that MPFC 11C‐PBR28 was significantly associated MPFC connectivity with posterior frontal, parietal and cingulate regions. Conclusion: The findings suggest that MPFC microglial activation is associated with increased functional connectivity with the nearby regions and decreased connectivity with the distal regions to MPFC in MCI subjects. Findings from DTI analysis showed negative correlation with structural integrity of the long fibre tracts which are connecting distal regions. These findings suggest that neuroinflammation is involved in the structural and functional connectivity disruption and probably remodelling in AD trajectory. [ABSTRACT FROM AUTHOR]

Background: To investigate whether neuroinflammation and β‐amyloid (Aβ) deposition influence brain structural and functional connectivity in Alzheimer's spectrum, we conducted a cross‐sectional multimodal imaging study and interrogated the associations between imaging biomarkers of neuroinflammation, Aβ deposition, brain connectivity and cognition. Method: 58 participants (25 MCI, 16 AD dementia and 17 healthy controls) were recruited and scanned with 11C‐PBR28 and 18F‐flutemetamol PET, T1‐weighted, diffusion tensor and resting‐state functional MRI. Brain structural and functional connectivity were assessed by global white matter integrity and functional topology metrics, while neuroinflammation and Aβ deposition were evaluated by 11C‐PBR28 and 18F‐flutemetamol uptake, respectively. Changes of the biomarkers were compared between diagnostic groups and robust regression analyses at both voxel and regional level were performed on Aβ positive patients, who were considered to be representative of Alzheimer's continuum. Result: Increased 11C‐PBR28 and 18F‐flutemetamol uptake, decreased FA values, impaired small‐worldness and local efficiency of functional network were observed in the AD cohort. In Aβ‐positive patients, cortical 11C‐PBR28 uptake correlated with decreased structural integrity and network local efficiency independent of 18F‐flutemetamol uptake and cortical thickness. Network structural integrity and cortical thickness correlated with functional metrics, including small‐worldness and local efficiency, which were all associated with cognition. Conclusion: Our findings suggest that cortical neuroinflammation may lead to disruption of structural and functional brain network independent of amyloid deposition and cortical atrophy, which in turn can lead to cognitive impairment in AD. [ABSTRACT FROM AUTHOR]

Background: There is growing evidence that microglial activation plays a crucial role in the early pathological changes reported in Alzheimer's disease (AD). Multimodal neuroimaging can be used to detect micro‐ and macrostructural alterations together with molecular imaging to quantify metabolism and proteins expression. Diffusivity map, reflecting neuronal integrity, can be derived from diffusion‐weighted imaging, and is thought to be increased in AD following pathological alterations. We hypothesised that changes in diffusivity could be colocalized with microglial activation at different stages of the disease. Method: 56 patients (mean age=70.4, SD=8.5) cognitively normal (CN, n=15), with mild cognitive impairment (MCI, n=28) and with AD (n=12) were included in this study. All participants underwent diffusion tensor imaging (DTI), amyloid PET ([18F]flutemetamol) and TSPO PET ([11C]PBR28). DTI data were processed with FSL v.6.0 to compute mean diffusivity (MD) maps. Standard uptake ratio (SUVR) values were calculated in SPM12 to identify the amyloid deposition and microglial activation within cortical regions. Amyloid status (Aβ‐positive/Aβ‐negative) was determined from processed data using a cerebellar gray matter ratio with a binding value greater than the CN mean+2SD. Z score maps of MD and [11C]PBR28 SUVR were computed using CN amyloid negative participants as reference. Z score maps were then correlated using SPM8 and the BPM toolbox. Significance was set at a threshold of p<0.05 with an extended threshold of 50 voxels. Result: We found a significant positive correlation clusters between MD and PBR28‐SUVR Z score maps (higher diffusivity correlated with higher microglial activation) in MCI amyloid negative subjects in the temporal lobe (coordinates: 28 ‐3 ‐32, corrected p<0.001, k=7363). In MCI amyloid positive subjects, we found positive correlation in the parietal lobe (coordinates: ‐47 ‐41 39, corrected p=0.008, k=5712). Conclusion: We found colocalized diffusivity and microglial changes in the early stage of the disease, in the temporal lobe of MCI amyloid negative participants and in later stages of the disease, in the parietal lobe of MCI amyloid positive participants. These results suggest the potential of DTI diffusivity and microglial activation imaging in detecting early neuronal damage occurring in dementia. [ABSTRACT FROM AUTHOR]

Background: There is growing evidence that pathological changes in Alzheimer's disease (AD) begin several years before the symptom onset. Neuroimaging approaches can be used to detect microstructural alterations in the early stages of neurodegeneration using diffusion‐weighted MRI. Cortical grey matter mean diffusivity (cMD) is thought to be increased in AD following pathological alterations resulting in disrupted neuronal function, neuronal death and cellular atrophy. We hypothesised that changes in MD could be detected early in the disease progression and that they would be correlated with structural imaging biomarkers. Method: 72 patients (mean age=69.1, SD=9.2) cognitively normal (CN, n=21) and with mild cognitive impairment (MCI, n=51) were included in this study. All participants underwent T1‐weighted MPRAGE MRI, diffusion tensor imaging (DTI) and PET amyloid ([18F]flutemetamol). Regional cortical thickness was measured on T1‐MPRAGE using FreeSurfer v.6.0. DTI data were processed with FSL v.6.0 to compute MD maps. Standard uptake ratio (SUVR) values were calculated in SPM12 to identify the amyloid deposition within cortical regions. Amyloid status (Aβ‐positive/Aβ‐negative) was determined from processed data using a cerebellar gray matter reference to create target‐to‐cerebellar ratio. Subjects were considered positive with an uptake value of greater than mean+2SD of the control subjects. Student's t‐test were used to compare imaging modalities between CN and MCI participants. Pearson's correlation coefficients were calculated to assess the relationship between imaging modalities. Result: There was a significantly increased MD in MCI compared to CN participants in hippocampus (p=0.0213) and in medial temporal lobe (p=0.033). There were no significant group differences neither in whole brain mean cortical thickness (p=0.6984) nor in temporal cortical thickness (p=0.0923). Interestingly, when splitting subjects based on their amyloid status, we found that whole brain MD was significantly negatively correlated with whole brain cortical thickness in amyloid negative (CN+MCI amyloid negative, p<0.001) but not in amyloid positive (CN+MCI amyloid positive, p=0.99). Conclusion: We found that changes in gray matter diffusivity could be detected in the early stages of AD pathology. We also found that there is a direct relationship between MD and structural changes (i.e. cortical thickness) only before amyloid deposition suggesting that MD provides information about early microstructural changes before macrostructural changes. [ABSTRACT FROM AUTHOR]

Background: Neuroinflammation has been established as a key component of Alzheimer's pathology. Numerous cross‐sectional studies have found associations between neuroinflammatory markers and neuronal damage in AD, suggesting neuroinflammation as a potential drive force of disease progression. However, there have been debate on whether neuroinflammation has a causal effect on disease progression. Here we questioned whether neuroinflammation is predictive of future cognitive decline in early stage of the disease. Method: 21 MCI patients were recruited and had baseline T1‐MRI and 11C‐PBR28 scans. Patients were followed up for at least one year (mean follow‐up period 3.1±1.3 years) and had mini‐mental state examinations (MMSE) at each visit. 19 of them had baseline 18F‐Flutemetamol PET, 11 had 18F‐AV1451 scans. 18F‐AV1451 and 11C‐PBR28 SUVR in the medial temporal lobe were measured, while PCA analyses were performed to evaluate uptakes in the neocortex for all 3 tracers. Principle components of temporal lobe volumetric measurements were computed as the neurodegeneration marker. A linear growth model was fitted for each subjects using all available time points, giving the intercept and slope of individual cognition trajectory. Age, intercept, 11C‐PBR28, and T1 MRI markers were then put into linear models to predict slope, and a backward model selection procedure was conducted. To further validate that neuroinflammation is not just a mediator of amyloid and tau pathologies, we further included amyloid and tau markers in the sub‐cohorts and inspected the final model. Result: The average baseline MMSE was 28±1.9 in the study cohort and the average annual change of MMSE was ‐0.46. We found 11C‐PBR28 SUVR in neocortex and MMSE intercept, but not temporal cortical thickness, were predictive of the slope of MMSE decline. In subgroups where 18F‐Flutemetamol and 18F‐AV1451 SUVRs were included respectively, we found neocortical amyloid and tau load were also predictive of MMSE slope, while 11C‐PBR28 SUVR remained its significance in the models. Conclusion: Our findings suggest that neuroinflammation is an independent factor that drives disease progression and cognitive decline in early stage of AD. Molecular imaging biomarkers may better predict patients' outcome as they detect underlying biological processes. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD), dementia with Lewy bodies, frontotemporal dementia (FTD), and Huntington's disease (HD) are the main neurodegenerative causes of dementia. Causes and mechanisms of these diseases remain elusive. Neuroinflammation is increasingly emerging as an important pathological factor in their development. Positron emission tomography (PET) using [ 11 C]PK11195 represents a method of visualizing the microglial component of neuroinflammation via the translocator protein (TSPO) and we discuss the valuable insights this has yielded in neurodegenerative diseases. We discuss the limitations of this method and the development of second generation TSPO PET ligands which hope to overcome these limitations. We also discuss other methods of visualizing neuroinflammation and review the state of current dementia treatments targeted at neuroinflammation. It is our view that a multimodal investigation into neuroinflammation in AD, Parkinson's disease dementia, FTD and HD will yield valuable pathological insights which will usefully inform development of therapeutic targets and biomarkers. [ABSTRACT FROM AUTHOR]

Background: Microglial activation has been found surrounding amyloid plaques and neurofibrillary tangles in brains of Alzheimer's subjects. In‐vivo imaging using 11C‐PBR28 (a marker of translocator protein over expressed in activated microglia) has demonstrated significant correlation between both amyloid (18F‐Flutematemol PET) and tau deposition (18F‐AV1451 PET). However, it is not clear whether tau or amyloid predominantly influence microglial activation. Methods: 11C‐PBR28, 18F‐Flutematemol, 18F‐AV1451 PET scans were performed on clinically diagnosed mild cognitive impairment and Alzheimer's dementia patients (n=20). 90‐120 minute summed 18F‐Flutematemol, 80‐100 minute summed 18F‐AV1451 and 60‐90 minute summed 11C‐PBR28 images were created. Tracer uptake in cerebellar grey matter was then sampled and individual image was divided by cerebellar uptake. The images were then smoothed with 6mm FWHM and analysed. Multiple regression analysis was performed using by VoxelStats package with 11C‐PBR28 as dependent variable, and 18F‐Flutematemol, 18F‐AV1451 and age as independent variable. Correction for multiple comparison was applied based on random field theory. Results: In the current model, amyloid deposition was found to contribute to elevated microglial activation in the posterior part of the brain including bilateral temporal, occipital lobe and posterior cingulate. While tau deposition contributed to neuroinflammation in wide‐spread areas covering bilateral frontal, temporal, parietal, occipital lobe and cingulate cortex. Conclusion: In the current model tau deposition had more unique contribution to microglial activation in MCI and AD cohort, suggesting that tau formation has a stronger association with microglial activation which is independent of amyloid deposition. [ABSTRACT FROM AUTHOR]

Background: Microglial activation plays a significant role in neuroinflammation in the neurodegenerative process. Microglial activation is characterised by the over‐expression of a mitochondrial protein (TSPO), that can be targeted by PET Tracers. This study aims to evaluate the relationship between [18F]GE180 PET uptake and grey matter atrophy. Method: In this PET study, we evaluated microglial activation in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) using the novel TSPO ligand flutriciclamide ([18F]GE180). Forty‐eight participants have been assesed with [18F]GE180 PET using arterial input. Spectral analysis was used to generate parametric maps of the impulse response function at 90 minutes. Additionally, hippocampal volume analysis was performed on structural magnetic resonance images (MRIs). Result: In a group‐wise analysis a significant reduction in hippocampal volume was found between the AD and healthy controls cohorts. Hippocampal volume significantly negatively correlated with the IRF90 in the temporal lobe and occipital lobes as well as and composite region in AD patients compared to healthy controls. Conclusion: In this [18F]GE180 PET imaging study in AD/MCI cohort, we have demonstrated that there is hippocampal atrophy when [18F]GE180 PET goes up in AD patients. The results indicate that regional [18F]GE180 PET uptake has a close association with neurodegeneration of key memories processing centre. [ABSTRACT FROM AUTHOR]

Background: Microglial activation plays a significant role, and could be quantified using PET tracers targeting TSPO. We evaluated the use of Flutriciclamide PET tracer in a cohort of subject diagnosed with Alzheimer's Disease (AD) or Mild Cognitive Impairment (MCI), using spectral analysis Method: Twenty‐three subjects with AD, fourteen with MCI and eleven healthy controls (HC) underwent 3T MRI and Flutriciclamide PET with arterial input. Spectral analysis was used to create parametric maps, and IRF at 90 minutes was sampled for region of interest analysis. IRF90 parametric maps were also used for voxel‐wise SPM group analysis. Result: Mean ages were 70.65±6.2‐ for AD, 70.3±6‐ for MCI and 63.4±1.4‐ for HCs. MCI and AD were age‐matched. Significant difference was found in the MMSE scores between AD and MCI (mean and SD respectively 21.8±3.7‐ and 26.8±3‐, p<0.001) and between AD and HC (mean and SD of HC 28.9±1.4‐, p<0.001). Significant difference was found in the hippocampal volumes between AD and MCI (mean 2711±477 on the left and 2750±455 on the right for AD, and 3942±284 and 4048±394 for MCI, p<0.01) and between AD and HC (mean 3942±284 on the left and 4048±394 on the right for HC, p<0.001).Significant difference was also found between MCI and HC (p=0.01 for left hippocampus, p=0.02 for the right one). When evaluating the IRF90 flutriciclamide uptake, significantly higher uptake was found in the AD group compared to HC in temporal (p<0.01), parietal (p=0.012), occipital (p=0.03) lobes and composite brain (p=0.01). In the AD group, IRF90 was higher in temporal lobe when compared with MCI group (p=0.04). SPM group wise analysis showed significantly higher uptake in part of temporal, parietal and occipital regions in AD compared to HCs, and a smaller cluster including part of temporal and occipital lobes when comparing AD and MCI. Conclusion: Our study, conducted in a population with a clinical diagnosis of AD or MCI demonstrated higher widespread flutriciclamide uptake in the AD group compared with HC, and more limited difference between AD and MCI, and can be used quantify neuroinflammation. [ABSTRACT FROM AUTHOR]

Background Alzheimer's disease (AD) and Parkinson's disease (PD) are the two common neurodegenerative diseases characterized by progressive neuronal dysfunction in the presence of pathological microglial activation. Methods 10 AD, 10 mild cognitive impairment (MCI), 11 PD dementia (PDD), and 16 controls underwent magnetic resonance imaging, [11C](R)PK11195 (1-[2-chlorophenyl]-N-methyl-N-[1-methyl-propyl]-3-isoquinoline carboxamide), [11C]PIB (11C-Pittsburgh compound B), [18F]FDG-PET (18F-2-fluoro-2-deoxyglucose positron emission tomography) scans. Parametric images were interrogated using region of interest (ROI), biological parametric mapping (BPM) and statistical parametric mapping analysis, and neuropsychometric tests. Results Using BPM analysis, AD, MCI, and PDD subjects demonstrated significant correlation between increased microglial activation and reduced glucose metabolism (rCMRGlc). AD and MCI subjects also showed significant positive correlation between amyloid and microglial activation. Levels of cortical microglial activation were negatively correlated with Mini-Mental State Examination in both AD and PDD. Conclusion The significant inverse correlations between cortical levels of microglial activation and rCMRGlc in AD and PDD suggest cortical neuroinflammation may drive neuronal dysfunction in these dementias. [ABSTRACT FROM AUTHOR]