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Both plasma tau phosphorylated at threonine-181 (pTau181) and tau PET show potential for detecting Alzheimer’s disease (AD) pathology and predicting clinical progression. In this study, we performed a head-to-head comparison between plasma pTau181 and tau PET along the AD continuum. Methods: We included participants from the Amsterdam Dementia Cohort who underwent 18F-flortaucipir (tau) PET and had a plasma sample biobanked within 12 mo from tau PET. Fifty subjective cognitive decline (SCD) participants (31 Ab-negative and 19 Ab-positive) and 60 Ab-positive participants with mild cognitive impairment (MCI) or dementia due to AD were included. A subset had 2-y longitudinal plasma pTau181 and tau PET available (n 5 40). Longitudinal neuropsychological test data covering 3.2 6 2.7 y from both before and after tau PET were available. Plasma pTau181 and tau PET were compared in their accuracies in discriminating between cognitive stage (MCI/AD vs. SCD) and preclinical Ab status (SCD Ab-positive vs. SCD Ab-negative), their associations with cross-sectional and longitudinal neuropsychological test performance, and their longitudinal changes over time. Results: When discriminating between preclinical Ab status, the area under the curve (AUC) for plasma pTau181 (0.83) and tau PET (entorhinal, 0.87; temporal, 0.85; neocortical, 0.67) were equally high (all DeLong P . 0.05), but tau PET outperformed plasma pTau181 in discriminating MCI/AD from SCD (AUC for plasma pTau181: 0.74; AUCs for tau PET: entorhinal, 0.89; temporal, 0.92; neocortical, 0.89) (all P, 0.01). Overall, tau PET showed stronger associations with cognitive decline and was associated with a wider variety of cognitive tests than plasma pTau181 (plasma pTau181, 20.02 . b, 20.12; tau PET, 20.01 . b, 20.22). Both plasma pTau181 and tau PET increased more steeply over time in MCI/AD than in SCD (P, 0.05), but only tau PET annual changes were associated with cognitive decline. Conclusion: Our results suggest that plasma pTau181 and tau PET perform equally well in identifying Ab pathology but that tau PET better monitors disease stage and clinical progression.

SummaryA significant number of COVID-19 patients develop ‘long COVID’, a condition defined by long-lasting debilitating, often neurological, symptoms. The pathophysiology of long COVID is unknown. Here we present in-vivo evidence of widespread neuroinflammation in long COVID, using a quantitative assessment, [18F]DPA-714 PET, in two long COVID patients. We reanalyzed historical data from three matched healthy control subjects, for comparison purposes. Both patients with long COVID had widespread increases in [18F]DPA-714 binding throughout the brain. Quantitative measures of binding (BPND values) were increased on average by 121% and 76%, respectively. This implicates profound neuroinflammation in the pathophysiology of long COVID.

Introduction: Empirical studies on effective communication for amyloid disclosure in mild cognitive impairment (MCI) are lacking. We aimed to study the impact of six communication strategies. Method: We performed a randomized controlled trial with seven randomly assigned, video-vignette conditions: six emphasizing a communication strategy and one basic condition. All showed a scripted consultation of a neurologist disclosing positive amyloid positron emission tomography (PET) scan results to an MCI patient. Healthy individuals (N = 1017; mean age ± SD 64 ± 8, 808 (79%) female) were instructed to imagine themselves in the video, answered questionnaires assessing information recall, emotional state, and behavioral intentions, and evaluate the physician/information. Results: “Risk best practice” resulted in highest free recall compared to other strategies (P

Purpose The purpose of this study is to develop and validate a 3D deep learning model that predicts the final clinical diagnosis of Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), mild cognitive impairment due to Alzheimer’s disease (MCI-AD), and cognitively normal (CN) using fluorine 18 fluorodeoxyglucose PET (18F-FDG PET) and compare model’s performance to that of multiple expert nuclear medicine physicians’ readers. Materials and methods Retrospective 18F-FDG PET scans for AD, MCI-AD, and CN were collected from Alzheimer’s disease neuroimaging initiative (556 patients from 2005 to 2020), and CN and DLB cases were from European DLB Consortium (201 patients from 2005 to 2018). The introduced 3D convolutional neural network was trained using 90% of the data and externally tested using 10% as well as comparison to human readers on the same independent test set. The model’s performance was analyzed with sensitivity, specificity, precision, F1 score, receiver operating characteristic (ROC). The regional metabolic changes driving classification were visualized using uniform manifold approximation and projection (UMAP) and network attention. Results The proposed model achieved area under the ROC curve of 96.2% (95% confidence interval: 90.6–100) on predicting the final diagnosis of DLB in the independent test set, 96.4% (92.7–100) in AD, 71.4% (51.6–91.2) in MCI-AD, and 94.7% (90–99.5) in CN, which in ROC space outperformed human readers performance. The network attention depicted the posterior cingulate cortex is important for each neurodegenerative disease, and the UMAP visualization of the extracted features by the proposed model demonstrates the reality of development of the given disorders. Conclusion Using only 18F-FDG PET of the brain, a 3D deep learning model could predict the final diagnosis of the most common neurodegenerative disorders which achieved a competitive performance compared to the human readers as well as their consensus.

IntroductionA timely diagnosis of Alzheimer’s Disease (AD) in an early stage of dementia is important to support timely access to treatment, advice, and care. The aim of this study was to estimate the diagnostic accuracy of [18F]flutemetamol PET in addition to the usual diagnostic workup for the diagnosis of AD in a memory clinic population with young onset dementia by means of a panel reference-based etiology diagnosis.Methodsin an academic memory clinic early onset dementia cohort (n=211) the nosological diagnosis was set by usual diagnostic workup and after including [18F]flutemetamol amyloid PET in a stepwise approach. To assess the change in proportion correctly diagnosed, the diagnosis with and without [18F]flutemetamol PET was related to a panel-based reference standard, serving as gold standard, consisting of 3 neurologists who relied on available clinical information over 2-year follow-up (n=152; blinded for PET).ResultsThe panel majority nosology was set as a reference diagnosis in 122 participants, leaving 30 (20%) participants with no majority reached. In 107 (88%) cases post-PET was in line with the reference, and in 103 (84%) the pre-PET diagnosis was in line with the reference. The difference was 3.3% (95% CI -3.5% to 10.1%; p=0.424).Discussion[18F]flutemetamol PET did not significantly improve the diagnostic accuracy in young patients with dementia in an academic memory clinic setting. The secondary analyses provided several indications for future research in a narrower subsample of persons with (very) high diagnostic uncertainty and to assess patient relevant health outcomes.

Background Detecting subtle-to-moderate biomarker changes such as those in amyloid PET imaging becomes increasingly relevant in the context of primary and secondary prevention of Alzheimer’s disease (AD). This work aimed to determine if and when distribution volume ratio (DVR; derived from dynamic imaging) and regional quantitative values could improve statistical power in AD prevention trials. Methods Baseline and annualized % change in [11C]PIB SUVR and DVR were computed for a global (cortical) and regional (early) composite from scans of 237 cognitively unimpaired subjects from the OASIS-3 database (www.oasis-brains.org). Bland-Altman and correlation analyses were used to assess the relationship between SUVR and DVR. General linear models and linear mixed effects models were used to determine effects of age, sex, and APOE-ε4 carriership on baseline and longitudinal amyloid burden. Finally, differences in statistical power of SUVR and DVR (cortical or early composite) were assessed considering three anti-amyloid trial scenarios: secondary prevention trials including subjects with (1) intermediate-to-high (Centiloid > 20.1), or (2) intermediate (20.1 APOE-ε4 carriers only. Results Although highly correlated to DVR (ρ = .96), cortical SUVR overestimated DVR cross-sectionally and in annual % change. In secondary prevention trials, DVR required 143 subjects per arm, compared with 176 for SUVR. Both restricting inclusion to individuals with intermediate amyloid burden levels or to APOE-ε4 carriers alone further reduced sample sizes. For primary prevention, SUVR required less subjects per arm (n = 855) compared with DVR (n = 1508) and the early composite also provided considerable sample size reductions (n = 855 to n = 509 for SUVR, n = 1508 to n = 734 for DVR). Conclusion Sample sizes in AD secondary prevention trials can be reduced by the acquisition of dynamic PET scans and/or by restricting inclusion to subjects with intermediate amyloid burden or to APOE-ε4 carriers only. Using a targeted early composite only leads to reductions of sample size requirements in primary prevention trials. These findings support strategies to enable smaller Proof-of-Concept Phase II clinical trials to better streamline drug development.

Background The mechanism of synaptic loss in Alzheimer’s disease is poorly understood and may be associated with tau pathology. In this combined positron emission tomography (PET) and magnetoencephalography (MEG) study, we aimed to investigate spatial associations between regional tau pathology ([18F]flortaucipir PET), synaptic density (synaptic vesicle 2A [11C]UCB-J PET) and synaptic function (MEG) in Alzheimer’s disease. Methods Seven amyloid-positive Alzheimer’s disease subjects from the Amsterdam Dementia Cohort underwent dynamic 130-min [18F]flortaucipir PET, dynamic 60-min [11C]UCB-J PET with arterial sampling and 2 × 5-min resting-state MEG measurement. [18F]flortaucipir- and [11C]UCB-J-specific binding (binding potential, BPND) and MEG spectral measures (relative delta, theta and alpha power; broadband power; and peak frequency) were assessed in cortical brain regions of interest. Associations between regional [18F]flortaucipir BPND, [11C]UCB-J BPND and MEG spectral measures were assessed using Spearman correlations and generalized estimating equation models. Results Across subjects, higher regional [18F]flortaucipir uptake was associated with lower [11C]UCB-J uptake. Within subjects, the association between [11C]UCB-J and [18F]flortaucipir depended on within-subject neocortical tau load; negative associations were observed when neocortical tau load was high, gradually changing into opposite patterns with decreasing neocortical tau burden. Both higher [18F]flortaucipir and lower [11C]UCB-J uptake were associated with altered synaptic function, indicative of slowing of oscillatory activity, most pronounced in the occipital lobe. Conclusions These results indicate that in Alzheimer’s disease, tau pathology is closely associated with reduced synaptic density and synaptic dysfunction.