scholarly journals Predicting brain atrophy from tau pathology: A summary of clinical findings and their translation into personalized models

2021 ◽  
Author(s):  
Amelie Schäfer ◽  
Pavanjit Chaggar ◽  
Travis B Thompson ◽  
Alain Goriely ◽  
Ellen Kuhl

For more than 25 years, the amyloid hypothesis--the paradigm that amyloid is the primary cause of Alzheimer's disease--has dominated the Alzheimer's community. Now, increasing evidence suggests that tissue atrophy and cognitive decline in Alzheimer's disease are more closely linked to the amount and location of misfolded tau protein than to amyloid plaques. However, the precise correlation between tau pathology and tissue atrophy remains unknown. Here, we integrate multiphysics modeling and Bayesian inference to create personalized tau-atrophy models using longitudinal clinical images from the the Alzheimer's Disease Neuroimaging Initiative. For each subject, we infer three personalized parameters, the tau misfolding rate, the tau transport coefficient, and the tau-induced atrophy rate from four consecutive annual tau positron emission tomography scans and structural magnetic resonance images. Strikingly, the tau-induced atrophy coefficient of 0.13/year (95% CI: 0.097-0.189) was fairly consistent across all subjects suggesting a strong correlation between tau pathology and tissue atrophy. Our personalized whole brain atrophy rates of 0.68-1.68%/year (95% CI: 0.5-2.0) are elevated compared to healthy subjects and agree well with the atrophy rates of 1-3%/year reported for Alzheimer's patients in the literature. Once comprehensively calibrated with a larger set of longitudinal images, our model has the potential to serve as a diagnostic and predictive tool to estimate future atrophy progression from clinical tau images on a personalized basis.

2010 ◽  
Vol 31 (9) ◽  
pp. 1601-1605 ◽  
Author(s):  
Gabriela Spulber ◽  
Eini Niskanen ◽  
Stuart MacDonald ◽  
Oded Smilovici ◽  
Kewei Chen ◽  
...  

2021 ◽  
Vol 14 (2) ◽  
pp. 110
Author(s):  
Caitlin Jie ◽  
Valerie Treyer ◽  
Roger Schibli ◽  
Linjing Mu

Tauvid has been approved by the U.S. Food and Drug Administration (FDA) in 2020 for positron emission tomography (PET) imaging of adult patients with cognitive impairments undergoing evaluation for Alzheimer’s disease (AD) based on tau pathology. Abnormal aggregation of tau proteins is one of the main pathologies present in AD and is receiving increasing attention as a diagnostic and therapeutic target. In this review, we summarised the production and quality control of Tauvid, its clinical application, pharmacology and pharmacokinetics, as well as its limitation due to off-target binding. Moreover, a brief overview on the second-generation of Tau PET tracers is provided. The approval of Tauvid marks a step forward in the field of AD research and opens up opportunities for second-generation tau tracers to advance tau PET imaging in the clinic.


Author(s):  
Mei Tian ◽  
A. Cahid Civelek ◽  
Ignasi Carrio ◽  
Yasuyoshi Watanabe ◽  
Keon Wook Kang ◽  
...  

Abstract Purpose Positron emission tomography (PET) with the first and only tau targeting radiotracer of 18F-flortaucipir approved by FDA has been increasingly used in depicting tau pathology deposition and distribution in patients with cognitive impairment. The goal of this international consensus is to help nuclear medicine practitioners procedurally perform 18F-flortaucipir PET imaging. Method A multidisciplinary task group formed by experts from various countries discussed and approved the consensus for 18F-flortaucipir PET imaging in Alzheimer’s disease (AD), focusing on clinical scenarios, patient preparation, and administered activities, as well as image acquisition, processing, interpretation, and reporting. Conclusion This international consensus and practice guideline will help to promote the standardized use of 18F-flortaucipir PET in patients with AD. It will become an international standard for this purpose in clinical practice.


PLoS ONE ◽  
2015 ◽  
Vol 10 (10) ◽  
pp. e0140311 ◽  
Author(s):  
Aiko Ishiki ◽  
Nobuyuki Okamura ◽  
Katsutoshi Furukawa ◽  
Shozo Furumoto ◽  
Ryuichi Harada ◽  
...  

2020 ◽  
Vol 47 (13) ◽  
pp. 3165-3175 ◽  
Author(s):  
Denise Visser ◽  
Emma E. Wolters ◽  
Sander C. J. Verfaillie ◽  
Emma M. Coomans ◽  
Tessa Timmers ◽  
...  

Abstract Purpose We aimed to investigate associations between tau pathology and relative cerebral blood flow (rCBF), and their relationship with cognition in Alzheimer’s disease (AD), by using a single dynamic [18F]flortaucipir positron emission tomography (PET) scan. Methods Seventy-one subjects with AD (66 ± 8 years, mini-mental state examination (MMSE) 23 ± 4) underwent a dynamic 130-min [18F]flortaucipir PET scan. Cognitive assessment consisted of composite scores of four cognitive domains. For tau pathology and rCBF, receptor parametric mapping (cerebellar gray matter reference region) was used to create uncorrected and partial volume-corrected parametric images of non-displaceable binding potential (BPND) and R1, respectively. (Voxel-wise) linear regressions were used to investigate associations between BPND and/or R1 and cognition. Results Higher [18F]flortaucipir BPND was associated with lower R1 in the lateral temporal, parietal and occipital regions. Higher medial temporal BPND was associated with worse memory, and higher lateral temporal BPND with worse executive functioning and language. Higher parietal BPND was associated with worse executive functioning, language and attention, and higher occipital BPND with lower cognitive scores across all domains. Higher frontal BPND was associated with worse executive function and attention. For [18F]flortaucipir R1, lower values in the lateral temporal and parietal ROIs were associated with worse executive functioning, language and attention, and lower occipital R1 with lower language and attention scores. When [18F]flortaucipir BPND and R1 were modelled simultaneously, associations between lower R1 in the lateral temporal ROI  and worse attention remained, as well as for lower parietal R1 and worse executive functioning and attention. Conclusion Tau pathology was associated with locally reduced rCBF. Tau pathology and low rCBF were both independently associated with worse cognitive performance. For tau pathology, these associations spanned widespread neocortex, while for rCBF, independent associations were restricted to lateral temporal and parietal regions and the executive functioning and attention domains. These findings indicate that each biomarker may independently contribute to cognitive impairment in AD.


2008 ◽  
Vol 4 ◽  
pp. T547-T547
Author(s):  
Wiesje M. Van der Flier ◽  
Jasper Sluimer ◽  
Femke H. Bouwman ◽  
Hugo Vrenken ◽  
Marinus A. Blankenstein ◽  
...  

2021 ◽  
Vol 11 (4) ◽  
pp. 465
Author(s):  
Sohee Park ◽  
Minyoung Oh ◽  
Jae Kim ◽  
Jae-Hong Lee ◽  
Young Yoon ◽  
...  

The recent advance of positron emission tomography (PET) tracers as biomarkers in Alzheimer’s disease (AD) provides more insight into pathophysiology, preclinical diagnosis, and further therapeutic strategies. However, synergistic processes or interactions between amyloid and tau deposits are still poorly understood. To better understand their relationship in focal brain changes with clinical phenotypes, we focused on region-specific or atypical AD characterized by focal clinical presentations: Posterior cortical atrophy (PCA) and logopenic variant of primary progressive aphasia (lpvPPA). We compared three different PET images with 18F–THK–5351 (tau), 18F–Florbetaben (amyloid beta, Aβ), and 18F–Fluorodeoxyglucose (glucose metabolism) to investigate potential interactions among pathologies and clinical findings. Whereas the amyloid accumulations were widespread throughout the neocortex, tau retentions and glucose hypometabolism showed focal changes corresponding to the clinical features. The distinctly localized patterns were more prominent in tau PET imaging. These findings suggest that tau pathology correlates more closely to the clinical symptoms and the neurodegenerative processes than Aβ pathology in AD.


2013 ◽  
Vol 34 (8) ◽  
pp. 1996-2002 ◽  
Author(s):  
Josephine Barnes ◽  
Owen T. Carmichael ◽  
Kelvin K. Leung ◽  
Christopher Schwarz ◽  
Gerard R. Ridgway ◽  
...  

2019 ◽  
Author(s):  
Maura Malpetti ◽  
Rogier A. Kievit ◽  
Luca Passamonti ◽  
P. Simon Jones ◽  
Kamen A. Tsvetanov ◽  
...  

AbstractTau pathology, neuroinflammation, and neurodegeneration are key aspects of Alzheimer’s disease. Understanding whether these features predict cognitive decline, alone or in combination, is crucial to develop new prognostic measures and enhanced stratification for clinical trials. Here, we studied how baseline assessments of in vivo tau pathology (measured by [18F]AV-1451 PET), neuroinflammation (indexed via [11C]PK11195 PET) and brain atrophy (derived from structural MRI) predicted longitudinal cognitive changes in patients with Alzheimer’s disease pathology. Twenty-six patients (n=12 with clinically probable Alzheimer’s dementia and n=14 with amyloid positive Mild Cognitive Impairment) and 29 healthy controls underwent baseline assessment with [18F]AV-1451 PET, [11C]PK11195 PET, and structural MRI. Cognition was examined annually over the subsequent 3 years using the revised Addenbrooke’s Cognitive Examination. Regional grey-matter volumes, [18F]AV-1451 and [11C]PK11195 binding were derived from fifteen temporo-parietal regions characteristically affected by Alzheimer’s disease pathology. A Principal Component Analysis (PCA) was used on each imaging modality separately, to identify the main spatial distributions of pathology. A Latent Growth Curve model was applied across the whole sample on longitudinal cognitive scores to estimate the rate of annual decline in each participant. We regressed the individuals’ estimated slope of cognitive decline on the neuroimaging components and examined univariable models with single-modality predictors, and a multi-modality model of prediction, to identify the independent and combined prognostic value of the different neuroimaging markers.PCA identified a single component for the grey-matter atrophy, while two components were found for each PET ligand: one weighted to the anterior temporal lobe, and another weighted to posterior temporo-parietal regions. Across the whole-sample, the single-modality models indicated significant correlations between the slope of cognitive decline and the first component of each imaging modality. In patients, both stepwise backward elimination and Bayesian model selection revealed an optimal predictive model that included both components of [18F]AV-1451 and the first (i.e., anterior temporal) component for [11C]PK11195. However, the MRI-derived atrophy component and demographic variables were excluded from the optimal predictive model of cognitive decline. We conclude that temporo-parietal tau pathology and anterior temporal neuroinflammation predict cognitive decline in patients with symptomatic Alzheimer’s disease pathology. This indicates the added value of PET biomarkers in predicting cognitive decline in Alzheimer’s disease, over and above MRI measures of brain atrophy and demographic data. Our findings also support the strategy for targeting tau and neuroinflammation in disease-modifying therapy against Alzheimer’s Disease.


Sign in / Sign up

Export Citation Format

Share Document