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Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment.

ABSTRACT: Alzheimer's disease (AD) is a devastating and progressive neurodegenerative disease for which there is no cure. Mild cognitive impairment (MCI) is considered a prodromal stage of the disease. Molecular imaging with positron emission tomography (PET) allows for the in vivo visualisation and tracking of pathophysiological changes in AD and MCI. PET is a very promising methodology for differential diagnosis and novel targets of PET imaging might also serve as biomarkers for disease-modifying therapeutic interventions. This review provides an overview of the current status and applications of in vivo molecular imaging of AD pathology, specifically amyloid, tau, and microglial activation. PET imaging studies were included and evaluated as potential biomarkers and for monitoring disease progression. Although the majority of radiotracers showed the ability to discriminate AD and MCI patients from healthy controls, they had various limitations that prevent the recommendation of a single technique or tracer as an optimal biomarker. Newer research examining amyloid, tau, and microglial PET imaging in combination suggest an alternative approach in studying the disease process.

SUBMITTER: Chandra A

PROVIDER: S-EPMC6864887 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment.

Chandra Avinash A Valkimadi Polytimi-Eleni PE Pagano Gennaro G Cousins Oliver O Dervenoulas George G Politis Marios M

Human brain mapping 20190914 18

Alzheimer's disease (AD) is a devastating and progressive neurodegenerative disease for which there is no cure. Mild cognitive impairment (MCI) is considered a prodromal stage of the disease. Molecular imaging with positron emission tomography (PET) allows for the in vivo visualisation and tracking of pathophysiological changes in AD and MCI. PET is a very promising methodology for differential diagnosis and novel targets of PET imaging might also serve as biomarkers for disease-modifying therap ...[more]

PMID: 31520513

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Project description:Background Growing evidence indicates an association between cerebral microhemorrhages (MHs) and amyloid β accumulation in Alzheimer disease (AD), but to the knowledge of the authors the association with tau burden is unknown. Purpose To investigate the association between cerebral MH load and tau pathologic structure measured in healthy older individuals and individuals along the AD spectrum, stratified by using the A (amyloid β)/T (tau)/N (neurodegeneration) biomarker classification system. Materials and methods In this prospective cohort study, participants from the AD Neuroimaging Initiative were included (healthy control participants, participants with mild cognitive impairment, and participants with AD dementia; data from October 2005 to January 2019). T2*-weighted gradient-echo MRI was performed to quantify MH, fluorine 18 (18F) flortaucipir (AV-1451) PET was performed to quantify tau, and 18F-florbetaben/18F- florbetapir (AV45) PET was performed to quantify amyloid β to study associations of MH with regional and global tau and amyloid β load. Associations with cerebrospinal fluid (CSF) biomarkers (amyloid β1-42, total tau, phosphorylated tau 181) were also assessed. Analysis of covariance and Spearman rank correlation test for cross-sectional analysis and Wilcoxon signed rank test for longitudinal analyses were used, controlling for multiple comparisons (Bonferroni significance threshold, P < .008). Results Evaluated were 343 participants (mean age, 75 years ± 7; 186 women), including 205 participants who were A-TN- (mean age, 73 years ± 7; 115 women), 80 participants who were A+TN- (mean age, 76 years ± 7; 38 women), and 58 participants who were A+TN+ (mean age, 77 ± 8; 34 women). MH count was associated with global (Spearman ρ = 0.27; P = .004) and frontal (ρ = 0.27; P = .005) amyloid β load and global tau load (ρ = 0.31; P = .001). In a longitudinal analysis, MH count increased significantly over approximately 5 years in the entire cohort (T-1, 81 [range, 0-6 participants]; T0, 214 [range, 0-58 participants]; P < .001), in A+TN+ (T-1, 20 [range, 0-5 participants]; T0, 119 [range, 1-58 participants]; P < .001), A+TN- (T-1, 31 [range, 0-6 participants]; T0, 43 [range, 0-8 participants]; P = .03), and A-TN- (T-1, 30 [range, 0-4 participants]; T0, 52 [range, 0-6 participants]; P = .007). A higher MH count was associated with higher future global (ρ = 0.29; P = .008) and parietal (ρ = 0.31; P = .005) amyloid β and parietal tau load (ρ = 0.31; P = .005). Conclusion Cerebral microhemorrhage load is associated spatially with tau accumulation, both cross-sectionally and longitudinally. © RSNA, 2020 Online supplemental material is available for this article.

Project description:Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) are closely associated with Tau proteins accumulation. In this study, we aimed to implement radiomics analysis to discover high-order features from pathological biomarker and improve the classification accuracy based on Tau PET images. Two cross-racial independent cohorts from the ADNI database (121 AD patients, 197 MCI patients and 211 normal control (NC) subjects) and Huashan hospital (44 AD patients, 33 MCI patients and 36 NC subjects) were enrolled. The radiomics features of Tau PET imaging of AD related brain regions were computed for classification using a support vector machine (SVM) model. The radiomics model was trained and validated in the ADNI cohort and tested in the Huashan hospital cohort. The standard uptake value ratio (SUVR) and clinical scores model were also performed to compared with radiomics analysis. Additionally, we explored the possibility of using Tau PET radiomics features as a good biomarker to make binary identification of Tau-negative MCI versus Tau-positive MCI or apolipoprotein E (ApoE) ε4 carrier versus ApoE ε4 non-carrier. We found that the radiomics model demonstrated best classification performance in differentiating AD/MCI patients and NC in comparison to SUVR and clinical scores models, with an accuracy of 84.8 ± 4.5%, 73.1 ± 3.6% in the ANDI cohort. Moreover, the radiomics model also demonstrated greater performance in diagnosing AD than other methods in the Huashan hospital cohort, with an accuracy of 81.9 ± 6.1%. In addition, the radiomics model also showed the satisfactory classification performance in the MCI-tau subgroup experiment (72.3 ± 3.5%, 71.9 ± 3.6% and 63.7 ± 5.9%) and in the MCI-ApoE subgroup experiment (73.5 ± 4.3%, 70.1 ± 3.9% and 62.5 ± 5.4%). In conclusion, our study showed that based on Tau PET radiomics analysis has the potential to guide and facilitate clinical diagnosis, further providing evidence for identifying the risk factors in MCI patients.

Project description:Background: Mild cognitive impairment (MCI) is a condition with diverse causes and clinical outcomes that can be categorized into subtypes. [18F]THK5351 has been known to detect reactive astrogliosis as well as tau which is accompanied by neurodegenerative changes. Here, we identified heterogeneous groups of MCI patients using THK retention patterns and a graph theory approach, allowing for the comparison of risk of progression to dementia in these MCI subgroups. Methods: Ninety-seven participants including 60 MCI patients and individuals with normal cognition (NC, n = 37) were included and undertook 3T MRI, [18F]THK5351 PET, and detailed neuropsychological tests. [18F]Flutemetamol PET was also performed in 62 participants. We calculated similarities between MCI patients using their regional standardized uptake value ratio of THK retention in 75 ROIs, and clustered subjects with similar retention patterns using the Louvain method based on the modularity of the graph. The clusters of patients identified were compared with an age-matched control group using a general linear model. Dementia conversion was evaluated after a median follow-up duration of 34.6 months. Results: MCI patients were categorized into four groups according to their THK retention patterns: (1) limbic type; (2) diffuse type; (3) sparse type; and (4) AD type (retention pattern as in AD). Subjects of the limbic type were characterized by older age, small hippocampal volumes, and reduced verbal memory and frontal/executive functions. Patients of the diffuse type had relatively large vascular burden, reduced memory capacity and some frontal/executive functions. Co-morbidity and mortality were more frequent in this subgroup. Subjects of the sparse type were younger and declined only in terms of visual memory and attention. No individuals in this subgroup converted to dementia. Patients in the AD type group exhibited the poorest cognitive function. They also had the smallest hippocampal volumes and the highest risk of progression to dementia (90.9%). Conclusion: Using cluster analyses with [18F]THK5351 retention patterns, it is possible to identify clinically-distinct subgroups of MCI patients and those at greater risk of progression to dementia.

Dataset Information

Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment.

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Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment.

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