Tau Positron Emission Tomography for Predicting Dementia in Individuals With Mild Cognitive Impairment.

Importance: An accurate prognosis is especially pertinent in mild cognitive impairment (MCI), when individuals experience considerable uncertainty about future progression. Objective: To evaluate the prognostic value of tau positron emission tomography (PET) to predict clinical progression from MCI to dementia. Design, Setting, and Participants: This was a multicenter cohort study with external validation and a mean (SD) follow-up of 2.0 (1.1) years. Data were collected from centers in South Korea, Sweden, the US, and Switzerland from June 2014 to January 2024. Participant data were retrospectively collected and inclusion criteria were a baseline clinical diagnosis of MCI; longitudinal clinical follow-up; a Mini-Mental State Examination (MMSE) score greater than 22; and available tau PET, amyloid-ß (Aß) PET, and magnetic resonance imaging (MRI) scan less than 1 year from diagnosis. A total of 448 eligible individuals with MCI were included (331 in the discovery cohort and 117 in the validation cohort). None of these participants were excluded over the course of the study. Exposures: Tau PET, Aß PET, and MRI. Main Outcomes and Measures: Positive results on tau PET (temporal meta-region of interest), Aß PET (global; expressed in the standardized metric Centiloids), and MRI (Alzheimer disease [AD] signature region) was assessed using quantitative thresholds and visual reads. Clinical progression from MCI to all-cause dementia (regardless of suspected etiology) or to AD dementia (AD as suspected etiology) served as the primary outcomes. The primary analyses were receiver operating characteristics. Results: In the discovery cohort, the mean (SD) age was 70.9 (8.5) years, 191 (58%) were male, the mean (SD) MMSE score was 27.1 (1.9), and 110 individuals with MCI (33%) converted to dementia (71 to AD dementia). Only the model with tau PET predicted all-cause dementia (area under the receiver operating characteristic curve [AUC], 0.75; 95% CI, 0.70-0.80) better than a base model including age, sex, education, and MMSE score (AUC, 0.71; 95% CI, 0.65-0.77; P = .02), while the models assessing the other neuroimaging markers did not improve prediction. In the validation cohort, tau PET replicated in predicting all-cause dementia. Compared to the base model (AUC, 0.75; 95% CI, 0.69-0.82), prediction of AD dementia in the discovery cohort was significantly improved by including tau PET (AUC, 0.84; 95% CI, 0.79-0.89; P < .001), tau PET visual read (AUC, 0.83; 95% CI, 0.78-0.88; P = .001), and Aß PET Centiloids (AUC, 0.83; 95% CI, 0.78-0.88; P = .03). In the validation cohort, only the tau PET and the tau PET visual reads replicated in predicting AD dementia. Conclusions and Relevance: In this study, tau-PET showed the best performance as a stand-alone marker to predict progression to dementia among individuals with MCI. This suggests that, for prognostic purposes in MCI, a tau PET scan may be the best currently available neuroimaging marker.

A comparison of visual assessment and semi-quantification for the diagnostic and prognostic use of [18F]flortaucipir PET in a memory clinic cohort.

PURPOSE: [18F]Flortaucipir PET is a powerful diagnostic and prognostic tool for Alzheimer's disease (AD). Tau status definition is mainly based in the literature on semi-quantitative measures while in clinical settings visual assessment is usually preferred. We compared visual assessment with established semi-quantitative measures to classify subjects and predict the risk of cognitive decline in a memory clinic population. METHODS: We included 245 individuals from the Geneva Memory Clinic who underwent [18F]flortaucipir PET. Amyloid status was available for 207 individuals and clinical follow-up for 135. All scans were blindly evaluated by three independent raters who visually classified the scans according to Braak stages. Standardized uptake value ratio (SUVR) values were obtained from a global meta-ROI to define tau positivity, and the Simplified Temporo-Occipital Classification (STOC) was applied to obtain semi-quantitatively tau stages. The agreement between measures was tested using Cohen's kappa (k). ROC analysis and linear mixed-effects models were applied to test the diagnostic and prognostic values of tau status and stages obtained with the visual and semi-quantitative approaches. RESULTS: We found good inter-rater reliability in the visual interpretation of tau Braak stages, independently from the rater's expertise (k>0.68, p<0.01). A good agreement was equally found between visual and SUVR-based classifications for tau status (k=0.67, p<0.01). All tau-assessment modalities significantly discriminated amyloid-positive MCI and demented subjects from others (AUC>0.80) and amyloid-positive from negative subjects (AUC>0.85). Linear mixed-effect models showed that tau-positive individuals presented a significantly faster cognitive decline than the tau-negative group (p<0.01), independently from the classification method. CONCLUSION: Our results show that visual assessment is reliable for defining tau status and stages in a memory clinic population. The high inter-rater reliability, the substantial agreement, and the similar diagnostic and prognostic performance of visual rating and semi-quantitative methods demonstrate that [18F]flortaucipir PET can be robustly assessed visually in clinical practice.

ATN profile classification across two independent prospective cohorts.

Background: The ATN model represents a research framework used to describe in subjects the presence or absence of Alzheimer's disease (AD) pathology through biomarkers. The aim of this study was to describe the prevalence of different ATN profiles using quantitative imaging biomarkers in two independent cohorts, and to evaluate the pertinence of ATN biomarkers to identify comparable populations across independent cohorts. Methods: A total of 172 subjects from the Geneva Memory Clinic and 113 volunteers from a study on healthy aging at the University Hospital of Zurich underwent amyloid (A) and tau (T) PET, as well as T1-weigthed MRI scans using site-specific protocols. Subjects were classified by cognition (cognitively unimpaired, CU, or impaired, CI) based on clinical assessment by experts. Amyloid data converted into the standardized centiloid scale, tau PET data normalized to cerebellar uptake, and hippocampal volume expressed as a ratio over total intracranial volume ratio were considered as biomarkers for A, T, and neurodegeneration (N), respectively. Positivity for each biomarker was defined based on previously published thresholds. Subjects were then classified according to the ATN model. Differences among profiles were tested using Kruskal-Wallis ANOVA, and between cohorts using Wilcoxon tests. Results: Twenty-nine percent of subjects from the Geneva cohorts were classified with a normal (A-T-N-) profile, while the Zurich cohort included 64% of subjects in the same category. Meanwhile, 63% of the Geneva and 16% of the Zurich cohort were classified within the AD continuum (being A+ regardless of other biomarkers' statuses). Within cohorts, ATN profiles were significantly different for age and mini-mental state examination scores, but not for years of education. Age was not significantly different between cohorts. In general, imaging A and T biomarkers were significantly different between cohorts, but they were no longer significantly different when stratifying the cohorts by ATN profile. N was not significantly different between cohorts. Conclusion: Stratifying subjects into ATN profiles provides comparable groups of subjects even when individual recruitment followed different criteria.

Prognostic value of imaging-based ATN profiles in a memory clinic cohort.

PURPOSE: The ATN model represents a research framework used to classify subjects based on the presence or absence of Alzheimer's disease (AD) pathology through biomarkers for amyloid (A), tau (T), and neurodegeneration (N). The aim of this study was to assess the relationship between ATN profiles defined through imaging and cognitive decline in a memory clinic cohort. METHODS: One hundred-eight patients from the memory clinic of Geneva University Hospitals underwent complete clinical and neuropsychological evaluation at baseline and 23 ± 5 months after inclusion, magnetic resonance imaging, amyloid and tau PET scans. ATN profiles were divided into four groups: normal, AD pathological change (AD-PC: A + T-N-, A + T-N +), AD pathology (AD-P: A + T + N-, A + T + N +), and suspected non-AD pathology (SNAP: A-T + N-, A-T-N + , A-T + N +). RESULTS: Mini-Mental State Examination (MMSE) scores were significantly different among groups, both at baseline and follow-up, with the normal group having higher average MMSE scores than the other groups. MMSE scores changed significantly after 2 years only in AD-PC and AD-P groups. AD-P profile classification also had the largest number of decliners at follow-up (55%) and the steepest global cognitive decline compared to the normal group. Cox regression showed that participants within the AD-P group had a higher risk of cognitive decline (HR = 6.15, CI = 2.59-14.59), followed by AD-PC (HR = 3.16, CI = 1.17-8.52). CONCLUSION: Of the different group classifications, AD-P was found to have the most significant effect on cognitive decline over a period of 2 years, highlighting the value of both amyloid and tau PET molecular imaging as prognostic imaging biomarkers in clinical practice.

Alzheimer's disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA.

BACKGROUND: 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer's disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. RESULTS: In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. CONCLUSION: rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA.

Serotonergic system in vivo with [11C]DASB PET scans in GTP-cyclohydrolase deficient dopa-responsive dystonia patients.

GTP-cyclohydrolase deficiency in dopa-responsive dystonia (DRD) patients impairs the biosynthesis of dopamine, but also of serotonin. The high prevalence of non-motor symptoms suggests involvement of the serotonergic pathway. Our study aimed to investigate the serotonergic system in vivo in the brain of`DRD patients and correlate this to (non-)motor symptoms. Dynamic [11C]DASB PET scans, a marker of serotonin transporter availability, were performed. Ten DRD, 14 cervical dystonia patients and 12 controls were included. Univariate- and network-analysis did not show differences in binding between DRD patients compared to controls. Sleep disturbances were correlated with binding in the dorsal raphe nucleus (all participants: rs = 0.45, p = 0.04; patients: rs = 0.64, p = 0.05) and participants with a psychiatric disorder had a lower binding in the hippocampus (all participants: p = 0.00; patients: p = 0.06). Post-hoc analysis with correction for psychiatric co-morbidity showed a significant difference in binding in the hippocampus between DRD patients and controls (p = 0.00). This suggests that psychiatric symptoms might mask the altered serotonergic metabolism in DRD patients, but definite conclusions are difficult as psychiatry is considered part of the phenotype. We hypothesize that an imbalance between different neurotransmitter systems is responsible for the non-motor symptoms, and further research investigating multiple neurotransmitters and psychiatry in DRD is necessary.

Feasibility of pharmacokinetic parametric PET images in scaled subprofile modelling using principal component analysis.

Scaled subprofile model using principal component analysis (SSM/PCA) is a multivariate analysis technique used, mainly in [18F]-2-fluoro-2-deoxy-d-glucose (FDG) PET studies, for the generation of disease-specific metabolic patterns (DP) that may aid with the classification of subjects with neurological disorders, like Alzheimer's disease (AD). The aim of this study was to explore the feasibility of using quantitative parametric images for this type of analysis, with dynamic [11C]-labelled Pittsburgh Compound B (PIB) PET data as an example. Therefore, 15 AD patients and 15 healthy control subjects were included in an SSM/PCA analysis to generate four AD-DPs using relative cerebral blood flow (R1), binding potential (BPND) and SUVR images derived from dynamic PIB and static FDG-PET studies. Furthermore, 49 new subjects with a variety of neurodegenerative cognitive disorders were tested against these DPs. The AD-DP was characterized by a reduction in the frontal, parietal, and temporal lobes voxel values for R1 and SUVR-FDG DPs; and by a general increase of values in cortical areas for BPND and SUVR-PIB DPs. In conclusion, the results suggest that the combination of parametric images derived from a single dynamic scan might be a good alternative for subject classification instead of using 2 independent PET studies.

Diagnostic performance of regional cerebral blood flow images derived from dynamic PIB scans in Alzheimer's disease.

BACKGROUND: In clinical practice, visual assessment of glucose metabolism images is often used for the diagnosis of Alzheimer's disease (AD) through 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) scans. However, visual assessment of the characteristic AD hypometabolic pattern relies on the expertise of the reader. Therefore, user-independent pipelines are preferred to evaluate the images and to classify the subjects. Moreover, glucose consumption is highly correlated with cerebral perfusion. Regional cerebral blood flow (rCBF) images can be derived from dynamic 11C-labelled Pittsburgh Compound B PET scans, which are also used for the assessment of the deposition of amyloid-ß plaques on the brain, a fundamental characteristic of AD. The aim of this study was to explore whether these rCBF PIB images could be used for diagnostic purposes through the PMOD Alzheimer's Discrimination Tool. RESULTS: Both tracer relative cerebral flow (R1) and early PIB (ePIB) (20-130 s) uptake presented a good correlation when compared to FDG standardized uptake value ratio (SUVR), while ePIB (1-8 min) showed a worse correlation. All receiver operating characteristic curves exhibited a similar shape, with high area under the curve values, and no statistically significant differences were found between curves. However, R1 and ePIB (1-8 min) had the highest sensitivity, while FDG SUVR had the highest specificity. CONCLUSION: rCBF images were suggested to be a good surrogate for FDG scans for diagnostic purposes considering an adjusted threshold value.

The influence of the winemaking process on the elemental composition of the Marselan red wine.

BACKGROUND: The elemental profile of the Marselan wine cycle was studied with a single ion-beam technique, namely particle-induced X-ray emission (PIXE). Samples were collected from all of the major stages involved in the wine cycle, including soil, vine plant, grape, and different stages of wine processing. RESULTS: The results show the influence of field practices on the elemental composition of leaves, branches, grapes, and soil. Mechanisms of element precipitation and elimination from the wine were identified through the changes in the elemental concentrations measured during the post-harvesting processes. The concentrations of some elements, such as Al, Si, K, and Ni, did not vary for grapes collected at different maturation stages. On the other hand, changes in the concentrations of Si, Cl, Ca, Cu, and K were observed right after the maceration and pressing processes in young wine. Finally, the reduction in the Cu concentration during the last stages of the wine cycle is related to its precipitation in the storage tanks. CONCLUSIONS: It was found that field practices and winemaking processes played distinct roles in the elemental composition of grapes and wine from different preparation stages. Moreover, PIXE proved to be a suitable analytical tool for the analysis of the whole wine cycle because it handles solid and liquid samples in a clean and straightforward manner. © 2019 Society of Chemical Industry.

Correction: Relative cerebral flow from dynamic PIB scans as an alternative for FDG scans in Alzheimer's disease PET studies.

[This corrects the article DOI: 10.1371/journal.pone.0211000.].

Relative cerebral flow from dynamic PIB scans as an alternative for FDG scans in Alzheimer's disease PET studies.

In Alzheimer's Disease (AD) dual-tracer positron emission tomography (PET) studies with 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) and 11C-labelled Pittsburgh Compound B (PIB) are used to assess metabolism and cerebral amyloid-ß deposition, respectively. Regional cerebral metabolism and blood flow (rCBF) are closely coupled, both providing an index for neuronal function. The present study compared PIB-derived rCBF, estimated by the ratio of tracer influx in target regions relative to reference region (R1) and early-stage PIB uptake (ePIB), to FDG scans. Fifteen PIB positive (+) patients and fifteen PIB negative (-) subjects underwent both FDG and PIB PET scans to assess the use of R1 and ePIB as a surrogate for FDG. First, subjects were classified based on visual inspection of the PIB PET images. Then, discriminative performance (PIB+ versus PIB-) of rCBF methods were compared to normalized regional FDG uptake. Strong positive correlations were found between analyses, suggesting that PIB-derived rCBF provides information that is closely related to what can be seen on FDG scans. Yet group related differences between method's distributions were seen as well. Also, a better correlation with FDG was found for R1 than for ePIB. Further studies are needed to validate the use of R1 as an alternative for FDG studies in clinical applications.