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IntroductionTau-positron emission tomography (PET) outcome data of patients with Alzheimer's disease (AD) cannot currently be meaningfully compared or combined when different tracers are used due to differences in tracer properties, instrumentation, and methods of analysis.MethodsUsing head-to-head data from five cohorts with tau PET radiotracers designed to target tau deposition in AD, we tested a joint propagation model (JPM) to harmonize quantification (units termed "CenTauR" [CTR]). JPM is a statistical model that simultaneously models the relationships between head-to-head and anchor point data. JPM was compared to a linear regression approach analogous to the one used in the amyloid PET Centiloid scale.ResultsA strong linear relationship was observed between CTR values across brain regions. Using the JPM approach, CTR estimates were similar to, but more accurate than, those derived using the linear regression approach.DiscussionPreliminary findings using the JPM support the development and adoption of a universal scale for tau-PET quantification.HighlightsTested a novel joint propagation model (JPM) to harmonize quantification of tau PET. Units of common scale are termed "CenTauRs". Tested a Centiloid-like linear regression approach. Using five cohorts with head-to-head tau PET, JPM outperformed linearregressionbased approach. Strong linear relationship was observed between CenTauRs values across brain regions.

ImportanceTau positron emission tomography (PET) tracers have proven useful for the differential diagnosis of dementia, but their utility for predicting cognitive change is unclear.ObjectiveTo examine the prognostic accuracy of baseline fluorine 18 (18F)-flortaucipir and [18F]RO948 (tau) PET in individuals across the Alzheimer disease (AD) clinical spectrum and to perform a head-to-head comparison against established magnetic resonance imaging (MRI) and amyloid PET markers.Design, setting, and participantsThis prognostic study collected data from 8 cohorts in South Korea, Sweden, and the US from June 1, 2014, to February 28, 2021, with a mean (SD) follow-up of 1.9 (0.8) years. A total of 1431 participants were recruited from memory clinics, clinical trials, or cohort studies; 673 were cognitively unimpaired (CU group; 253 [37.6%] positive for amyloid-β [Aβ]), 443 had mild cognitive impairment (MCI group; 271 [61.2%] positive for Aβ), and 315 had a clinical diagnosis of AD dementia (315 [100%] positive for Aβ).Exposures[18F]Flortaucipir PET in the discovery cohort (n = 1135) or [18F]RO948 PET in the replication cohort (n = 296), T1-weighted MRI (n = 1431), and amyloid PET (n = 1329) at baseline and repeated Mini-Mental State Examination (MMSE) evaluation.Main outcomes and measuresBaseline [18F]flortaucipir/[18F]RO948 PET retention within a temporal region of interest, MRI-based AD-signature cortical thickness, and amyloid PET Centiloids were used to predict changes in MMSE using linear mixed-effects models adjusted for age, sex, education, and cohort. Mediation/interaction analyses tested whether associations between baseline tau PET and cognitive change were mediated by baseline MRI measures and whether age, sex, and APOE genotype modified these associations.ResultsAmong 1431 participants, the mean (SD) age was 71.2 (8.8) years; 751 (52.5%) were male. Findings for [18F]flortaucipir PET predicted longitudinal changes in MMSE, and effect sizes were stronger than for AD-signature cortical thickness and amyloid PET across all participants (R2, 0.35 [tau PET] vs 0.24 [MRI] vs 0.17 [amyloid PET]; P < .001, bootstrapped for difference) in the Aβ-positive MCI group (R2, 0.25 [tau PET] vs 0.15 [MRI] vs 0.07 [amyloid PET]; P

PurposeA substantial proportion of amyloid-β (Aβ)+ patients with clinically diagnosed Alzheimer's disease (AD) dementia and mild cognitive impairment (MCI) are tau PET-negative, while some clinically diagnosed non-AD neurodegenerative disorder (non-AD) patients or cognitively unimpaired (CU) subjects are tau PET-positive. We investigated which demographic, clinical, genetic, and imaging variables contributed to tau PET status.MethodsWe included 2338 participants (430 Aβ+ AD dementia, 381 Aβ+ MCI, 370 non-AD, and 1157 CU) who underwent [18F]flortaucipir (n = 1944) or [18F]RO948 (n = 719) PET. Tau PET positivity was determined in the entorhinal cortex, temporal meta-ROI, and Braak V-VI regions using previously established cutoffs. We performed bivariate binary logistic regression models with tau PET status (positive/negative) as dependent variable and age, sex, APOEε4, Aβ status (only in CU and non-AD analyses), MMSE, global white matter hyperintensities (WMH), and AD-signature cortical thickness as predictors. Additionally, we performed multivariable binary logistic regression models to account for all other predictors in the same model.ResultsTau PET positivity in the temporal meta-ROI was 88.6% for AD dementia, 46.5% for MCI, 9.5% for non-AD, and 6.1% for CU. Among Aβ+ participants with AD dementia and MCI, lower age, MMSE score, and AD-signature cortical thickness showed the strongest associations with tau PET positivity. In non-AD and CU participants, presence of Aβ was the strongest predictor of a positive tau PET scan.ConclusionWe identified several demographic, clinical, and neurobiological factors that are important to explain the variance in tau PET retention observed across the AD pathological continuum, non-AD neurodegenerative disorders, and cognitively unimpaired persons.

Alzheimer's disease (AD) is characterized by the spread of tau pathology throughout the cerebral cortex. This spreading pattern was thought to be fairly consistent across individuals, although recent work has demonstrated substantial variability in the population with AD. Using tau-positron emission tomography scans from 1,612 individuals, we identified 4 distinct spatiotemporal trajectories of tau pathology, ranging in prevalence from 18 to 33%. We replicated previously described limbic-predominant and medial temporal lobe-sparing patterns, while also discovering posterior and lateral temporal patterns resembling atypical clinical variants of AD. These 'subtypes' were stable during longitudinal follow-up and were replicated in a separate sample using a different radiotracer. The subtypes presented with distinct demographic and cognitive profiles and differing longitudinal outcomes. Additionally, network diffusion models implied that pathology originates and spreads through distinct corticolimbic networks in the different subtypes. Together, our results suggest that variation in tau pathology is common and systematic, perhaps warranting a re-examination of the notion of 'typical AD' and a revisiting of tau pathological staging.

BackgroundImaging biomarkers have the potential to distinguish between different brain pathologies based on the type of ligand used with PET. AV-45 PET (florbetapir, Amyvid™) is selective for the neuritic plaque amyloid of Alzheimer's disease (AD), while AV-133 PET (florbenazine) is selective for VMAT2, which is a dopaminergic marker.ObjectiveTo report the clinical, AV-133 PET, AV-45 PET, and neuropathological findings of three clinically diagnosed dementia patients who were part of the Avid Radiopharmaceuticals AV133-B03 study as well as the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND).MethodsThree subjects who had PET imaging with both AV-133 and AV-45 as well as a standardized neuropathological assessment were included. The final clinical, PET scan, and neuropathological diagnoses were compared.ResultsThe clinical and neuropathological diagnoses were made blinded to PET scan results. The first subject had a clinical diagnosis of dementia with Lewy bodies (DLB); AV-133 PET showed bilateral striatal dopaminergic degeneration, and AV-45 PET was positive for amyloid. The final clinicopathological diagnosis was DLB and AD. The second subject was diagnosed clinically with probable AD; AV-45 PET was positive for amyloid, while striatal AV-133 PET was normal. The final clinicopathological diagnosis was DLB and AD. The third subject had a clinical diagnosis of DLB. Her AV-45 PET was positive for amyloid and striatal AV-133 showed dopaminergic degeneration. The final clinicopathological diagnosis was multiple system atrophy and AD.ConclusionPET imaging using AV-133 for the assessment of striatal VMAT2 density may help distinguish between AD and DLB. However, some cases of DLB with less-pronounced nigrostriatal dopaminergic neuronal loss may be missed.

[18F]Flortaucipir is an FDA-approved tau-PET tracer that is increasingly utilized in clinical settings for the diagnosis of Alzheimer's disease. Still, a large-scale comparison of the in vivo PET uptake to quantitative post-mortem tau pathology and to other co-pathologies is lacking. Here, we examined the correlation between in vivo [18F]flortaucipir PET uptake and quantitative post-mortem tau pathology in corresponding brain regions from the AVID A16 end-of-life study (n = 63). All participants underwent [18F]flortaucipir PET scans prior to death, followed by a detailed post-mortem neuropathological examination using AT8 (tau) immunohistochemistry. Correlations between [18F]flortaucipir standardized uptake value ratios (SUVRs) and AT8 immunohistochemistry were assessed across 18 regions-of-interest (ROIs). To assess [18F]flortaucipir specificity and level of detection for tau pathology, correlations between [18F]flortaucipir SUVR and neuritic plaque score and TDP-43 stage were also computed and retention was further assessed in individuals with possible primary age-related tauopathy (PART), defined as Thal phase ≤ 2 and Braak stage I–IV. We found modest-to-strong correlations between in vivo [18F]flortaucipir SUVR and post-mortem tau pathology density in corresponding brain regions in all neocortical regions analyzed (rho-range = 0.61–0.79, p < 0.0001 for all). The detection threshold of [18F]flortaucipir PET was determined to be 0.85% of surface area affected by tau pathology in a temporal meta-ROI, and 0.15% in a larger cortical meta-ROI. No significant associations were found between [18F]flortaucipir SUVRs and post-mortem tau pathology in individuals with possible PART. Further, there was no correlation observed between [18F]flortaucipir and level of amyloid-β neuritic plaque load (rho-range = – 0.16–0.12; p = 0.48–0.61) or TDP-43 stage (rho-range = – 0.10 to – 0.30; p = 0.18–0.65). In conclusion, our in vivo vs post-mortem study shows that the in vivo [18F]flortaucipir PET signal primarily reflects tau pathology, also at relatively low densities of tau proteinopathy, and does not bind substantially to tau neurites in neuritic plaques or in individuals with PART. [ABSTRACT FROM AUTHOR]

Until recently, estimation of β-amyloid plaque density as a key element for identifying Alzheimer's disease (AD) pathology as the cause of cognitive impairment was only possible at autopsy. Now with amyloid-positron emission tomography (amyloid-PET) neuroimaging, this AD hallmark can be detected antemortem. Practitioners and patients need to better understand potential diagnostic benefits and limitations of amyloid-PET and the complex practical, ethical, and social implications surrounding this new technology. To complement the practical considerations, Eli Lilly and Company sponsored a Bioethics Advisory Board to discuss ethical issues that might arise from clinical use of amyloid-PET neuroimaging with patients being evaluated for causes of cognitive decline. To best address the multifaceted issues associated with amyloid-PET neuroimaging, we recommend this technology be used only by experienced imaging and treating physicians in appropriately selected patients and only in the context of a comprehensive clinical evaluation with adequate explanations before and after the scan.

Although amyloid imaging with PiB-PET ([C-11]Pittsburgh Compound-B positron emission tomography), and now with F-18-labeled tracers, has produced remarkably consistent qualitative findings across a large number of centers, there has been considerable variability in the exact numbers reported as quantitative outcome measures of tracer retention. In some cases this is as trivial as the choice of units, in some cases it is scanner dependent, and of course, different tracers yield different numbers. Our working group was formed to standardize quantitative amyloid imaging measures by scaling the outcome of each particular analysis method or tracer to a 0 to 100 scale, anchored by young controls (≤ 45 years) and typical Alzheimer's disease patients. The units of this scale have been named "Centiloids." Basically, we describe a "standard" method of analyzing PiB PET data and then a method for scaling any "nonstandard" method of PiB PET analysis (or any other tracer) to the Centiloid scale.

Neuropathologic heterogeneity is often present among Alzheimer disease (AD) patients. We sought to determine whether amyloid imaging measures of AD are affected by concurrent pathologies. Thirty-eight clinically and pathologically defined AD and 17 nondemented patients with quantitative florbetapir F-18 (F-AV-45) positron emission tomography (PET) imaging during life and postmortem histological β-amyloid quantification and neuropathologic examination were assessed. AD patients were divided on the basis of concurrent pathologies, including those with Lewy bodies (LBs) (n = 21), white matter rarefaction (n = 27), severe cerebral amyloid angiopathy (n = 11), argyrophilic grains (n = 5), and TAR DNA binding protein-43 inclusions (n = 18). Many patients exhibited more than 1 type of concurrent pathology. The ratio of cortical to cerebellar amyloid imaging signal (SUVr) and immunohistochemical β-amyloid load were analyzed in 6 cortical regions of interest. All AD subgroups had strong and significant correlations between SUVr and histological β-amyloid measures (p μ 0.001). All AD subgroups had significantly greater amyloid measures versus nondemented patients, and mean amyloid measures did not significantly differ between AD subgroups. When comparing AD cases with and without each pathology, AD cases with LBs had significantly lower SUVr measures versus AD cases without LBs (p = 0.002); there were no other paired comparison differences. These findings indicate that florbetapir-PET imaging is not confounded by neuropathological heterogeneity within AD.

BackgroundThe goal of this study was to examine cross-sectional and longitudinal associations between cognitive performance and beta amyloid (Aβ) load determined by florbetapir F18 positron emission tomography (PET) in nondemented oldest-old.MethodsThirteen nondemented (normal or cognitively impaired nondemented) participants (median age, 94.2 years) from The 90+ Study underwent florbetapir-PET scanning within 3 months of baseline neuropsychological testing. Amyloid load was measured with a semi-automated quantitative analysis of average cortical-to-cerebellar standardized uptake value ratio (SUVr) and a visual interpretation (Aβ- or Aβ+). Neuropsychological testing was repeated every 6 months.ResultsAt baseline, SUVr correlated significantly with tests of global cognition and memory. During follow-up (median, 1.5 years), the Aβ+ group had steeper declines on most cognitive tests, particularly global cognitive measures.ConclusionThis preliminary study suggests that greater amyloid load is associated with poorer cognition and faster cognitive decline in nondemented oldest-old. Amyloid load may identify individuals at increased risk of developing Alzheimer's disease.

ObjectivesFlorbetapir F 18 PET can image amyloid-β (Aβ) aggregates in the brains of living subjects. We prospectively evaluated the prognostic utility of detecting Aβ pathology using florbetapir PET in subjects at risk for progressive cognitive decline.MethodsA total of 151 subjects who previously participated in a multicenter florbetapir PET imaging study were recruited for longitudinal assessment. Subjects included 51 with recently diagnosed mild cognitive impairment (MCI), 69 cognitively normal controls (CN), and 31 with clinically diagnosed Alzheimer disease dementia (AD). PET images were visually scored as positive (Aβ+) or negative (Aβ-) for pathologic levels of β-amyloid aggregation, blind to diagnostic classification. Cerebral to cerebellar standardized uptake value ratios (SUVr) were determined from the baseline PET images. Subjects were followed for 18 months to evaluate changes in cognition and diagnostic status. Analysis of covariance and correlation analyses were conducted to evaluate the association between baseline PET amyloid status and subsequent cognitive decline.ResultsIn both MCI and CN, baseline Aβ+ scans were associated with greater clinical worsening on the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog (p < 0.01) and Clinical Dementia Rating-sum of boxes (CDR-SB) (p < 0.02). In MCI Aβ+ scans were also associated with greater decline in memory, Digit Symbol Substitution (DSS), and Mini-Mental State Examination (MMSE) (p < 0.05). In MCI, higher baseline SUVr similarly correlated with greater subsequent decline on the ADAS-Cog (p < 0.01), CDR-SB (p < 0.03), a memory measure, DSS, and MMSE (p < 0.05). Aβ+ MCI tended to convert to AD dementia at a higher rate than Aβ- subjects (p < 0.10).ConclusionsFlorbetapir PET may help identify individuals at increased risk for progressive cognitive decline.

Objective: We aimed to test whether region‐specific factors, including spatial expression patterns of the tau‐encoding gene MAPT and regional levels of amyloid positron emission tomography (PET), enhance connectivity‐based modeling of the spatial variability in tau‐PET deposition in the Alzheimer disease (AD) spectrum. Methods: We included 685 participants (395 amyloid‐positive participants within AD spectrum and 290 amyloid‐negative controls) with tau‐PET and amyloid‐PET from 3 studies (Alzheimer's Disease Neuroimaging Initiative, 18F‐AV‐1451‐A05, and BioFINDER‐1). Resting‐state functional magnetic resonance imaging was obtained in healthy controls (n = 1,000) from the Human Connectome Project, and MAPT gene expression from the Allen Human Brain Atlas. Based on a brain‐parcellation atlas superimposed onto all modalities, we obtained region of interest (ROI)‐to‐ROI functional connectivity, ROI‐level PET values, and MAPT gene expression. In stepwise regression analyses, we tested connectivity, MAPT gene expression, and amyloid‐PET as predictors of group‐averaged and individual tau‐PET ROI values in amyloid‐positive participants. Results: Connectivity alone explained 21.8 to 39.2% (range across 3 studies) of the variance in tau‐PET ROI values averaged across amyloid‐positive participants. Stepwise addition of MAPT gene expression and amyloid‐PET increased the proportion of explained variance to 30.2 to 46.0% and 45.0 to 49.9%, respectively. Similarly, for the prediction of patient‐level tau‐PET ROI values, combining all 3 predictors significantly improved the variability explained (mean adjusted R2 range across studies = 0.118–0.148, 0.156–0.196, and 0.251–0.333 for connectivity alone, connectivity plus MAPT expression, and all 3 modalities combined, respectively). Interpretation: Across 3 study samples, combining the functional connectome and molecular properties substantially enhanced the explanatory power compared to single modalities, providing a valuable tool to explain regional susceptibility to tau deposition in AD. ANN NEUROL 2024;95:274–287 [ABSTRACT FROM AUTHOR]

Background: Positron emission tomography (PET) imaging with [18F]flortaucipir allows for in‐vivo visualization of aggregated tau in Alzheimer's disease (AD). The FDA‐approved label for [18F]flortaucipir PET provides a standardized, clinically applicable definition of tau‐PET positivity by visual interpretation. Here, we studied the concordance between this visual interpretation and quantitative approaches employed in research. Method: We included 2692 participants (cognitively unimpaired [CU] and impaired [CI, MCI or AD dementia]) from four cohorts (Mayo Clinic Study of Aging and ADRC, ADNI, A4, and A05) with available [18F]flortaucipir PET (mean age: 70.2 y, 50.0% females). Three trained readers assessed each [18F]flortaucipir PET scan according to the FDA‐approved method. Visual reads were compared to an established approach for defining tau‐PET positivity based on SUVR values in a temporal meta‐ROI (Jack, et al. Alzheimers Dement. 2017). Previously defined "lenient" (SUVR = 1.22) and "conservative" (SUVR = 1.30) cut‐points were explored. In addition, visual reads were compared to tau‐PET positivity as defined by a scheme based on the expected spatial progression of tau pathology from the medial temporal lobe (MTL) to the temporal neocortex (NEO) (Ossenkoppele, et al. Nat Med. 2022; cut‐points: SUVRMTL = 1.30, SUVRNEO = 1.37). Result: Concordance between visual and quantitative approaches was limited (Figure 1): the "lenient" and MTL‐NEO methods yielded high rates of quantitative‐positive, visual‐negative scans (73‐52% and 26‐18% for CU and CI, respectively), while the "conservative" cut‐point failed to detect 45% and 13% of the CU and CI visual‐positive scans, respectively. The prevalence of tau‐PET positivity in Aβ‐negative individuals was highest with the "lenient" cut‐point (∼24%) and lowest with visual interpretation (∼3%) (Figure 2). Visual‐positive, quantitative‐negative individuals were more frequently Aβ‐positive than visual‐negative, quantitative‐positive individuals ("lenient": 86% vs 50%, p<0.001; "conservative": 87% vs 58%, p<0.001; MTL‐NEO: 85% vs 70%, p = 0.005). Among visually‐positive participants, 164 (28%) showed a tau deposition pattern that deviated from the expected MTL to NEO progression (Figure 3). Conclusion: Visual and quantitative methods for [18F]flortaucipir PET are non‐exchangeable. Tau‐PET positivity based on visual interpretation aligns better with Aβ‐pathology. A significant number of visually‐positive participants showed a pattern of tau accumulation that deviated from the expected stereotypical spatial progression and was not detected by standard quantitative methods. [ABSTRACT FROM AUTHOR]

Mechanisms of resilience against tau pathology in individuals across the Alzheimer's disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer's disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE -ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = −0.062, P = 0.032), higher education level (Stβinteraction = −0.072, P = 0.011) and higher intracranial volume (Stβinteraction = −0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE -ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer's disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences. [ABSTRACT FROM AUTHOR]