Positron emission tomography (PET) may increase the diagnostic accuracy and confirm the underlying neuropathologic changes of Alzheimer disease (AD). OBJECTIVE To determine the accuracy of antemortem [ 18 F]flortaucipir PET images for predicting the presence of AD-type tau pathology at autopsy. DESIGN, SETTING, AND PARTICIPANTS This diagnostic study (A16 primary cohort) was conducted from October 2015 to June 2018 at 28 study sites (27 in US sites and 1 in Australia). Individuals with a terminal illness who were older than 50 years and had a projected life expectancy of less than 6 months were enrolled. All participants underwent [ 18 F]flortaucipir PET imaging, and scans were interpreted by 5 independent nuclear medicine physicians or radiologists. Supplemental autopsy [ 18 F]flortaucipir images and pathological samples were also collected from 16 historically collected cases. A second study (FR01 validation study) was conducted from March 26 to April 26, 2019, in which 5 new readers assessed the original PET images for comparison to autopsy. MAIN OUTCOMES AND MEASURES [ 18 F]flortaucipir PET images were visually assessed and compared with immunohistochemical tau pathology. An AD tau pattern of flortaucipir retention was assessed for correspondence with a postmortem B3-level (Braak stage V or VI) pathological pattern of tau accumulation and to the presence of amyloid-β plaques sufficient to meet the criteria for high levels of AD neuropathological change. Success was defined as having at least 3 of the 5 readers above the lower bounds of the 95% CI for both sensitivity and specificity of 50% or greater. RESULTS A total of 156 patients were enrolled in the A16 study and underwent [ 18 F]flortaucipir PET imaging. Of these, 73 died during the study, and valid autopsies were performed for 67 of these patients. Three autopsies were evaluated as test cases and removed from the primary cohort (n = 64). Of the 64 primary cohort patients, 34 (53%) were women and 62 (97%) were white; mean (SD) age was 82.5 (9.6) years; and 49 (77%) had dementia, 1 (2%) had mild cognitive impairment, and 14 (22%) had normal cognition. Prespecified success criteria were met for the A16 primary cohort. The flortaucipir PET scans predicted a B3 level of tau pathology, with sensitivity ranging from 92.3% (95% CI, 79.7%-97.3%) to 100.0% (95% CI, 91.0%-100.0%) and specificity ranging from 52.0% (95% CI, 33.5%-70.0%) to 92.0% (95% CI, 75.0%-97.8%). A high level of AD neuropathological change was predicted with sensitivity of 94.7% (95% CI, 82.7%-98.5%) to 100.0% (95% CI, 90.8%-100.0%) and specificity of 50.0% (95% CI, 32.1%-67.9%) to 92.3% (95% CI, 75.9%-97.9%). The FR01 validation study also met prespecified success criteria. Addition of the supplemental autopsy data set and 3 test cases, which comprised a total of 82 patients and autopsies for both the A16 and FR01 studies, resulted in improved specificity and comparable overall accuracy. Among the 156 enrolled participants, 14 (9%) experienced at least 1 treatment-emergent adverse event. CONCL...

Using flortaucipir, Pontecorvo et al. reveal an increase in cortical tau over 18 months in Aβ+ but not Aβ- subjects, and an association between baseline tau and the magnitude of changes in tau and cognitive performance. The abundance and distribution of tau may influence both tau spreading and cognitive decline.

These findings may allow improved tracer-independent amyloid quantitation.

PET imaging of tau pathology in Alzheimer disease may benefit from the use of white matter reference regions. These regions have shown reduced variability compared with conventional cerebellar regions in amyloid imaging. However, they are susceptible to contamination from partial-volume blurring of tracer uptake in the cortex. We present a new technique, PERSI (Parametric Estimation of Reference Signal Intensity), for flortaucipir F 18 count normalization that leverages the advantages of white matter reference regions while mitigating potential partial-volume effects. Subjects with a clinical diagnosis of Alzheimer disease, mild cognitive impairment, or normal cognition underwent T1-weighted MRI and florbetapir imaging (to determine amyloid [Aβ] status) at screening and flortaucipir F 18 imaging at single or multiple time points. Flortaucipir F 18 images, acquired as 4 × 5 min frames 80 min after a 370-MBq injection, were motion-corrected, averaged, and transformed to Montreal Neurological Institute (MNI) space. The PERSI reference region was calculated for each scan by fitting a bimodal gaussian distribution to the voxel-intensity histogram within an atlas-based white matter region and using the center and width of the lower-intensity peak to identify the voxel intensities to be included. Four conventional reference regions were also evaluated: whole cerebellum, cerebellar gray matter, atlas-based white matter, and subject-specific white matter. SUVr (standardized uptake value ratio) was calculated for a statistically defined neocortical volume of interest. Performance was evaluated with respect to test-retest variability in a phase 2 study of 21 subjects (5-34 d between scans). Baseline variability in controls (SD of SUVr and ΔSUVr) and effect sizes for group differences (Cohen d; Aβ-positive impaired vs. Aβ-negative normal) were evaluated in another phase 2 study with cross-sectional data ( = 215) and longitudinal data ( = 142/215; 18 ± 2 mo between scans). PERSI showed superior test-retest reproducibility (1.84%) and group separation ability (cross-sectional Cohen d = 9.45; longitudinal Cohen d = 2.34) compared with other reference regions. Baseline SUVr variability and ΔSUVr were minimal in Aβ control subjects with no specific flortaucipir F 18 uptake (SUVr, 1.0 ± 0.04; ΔSUVr, 0.0 ± 0.02). PERSI reduced variability while enhancing discrimination between diagnostic cohorts. Such improvements could lead to more accurate disease staging and robust measurements of changes in tau burden over time for the evaluation of putative therapies.

Misinformation online poses a range of threats, from subverting democratic processes to undermining public health measures. Proposed solutions range from encouraging more selective sharing by individuals to removing false content and accounts that create or promote it. Here we provide a framework to evaluate interventions aimed at reducing viral misinformation online both in isolation and when used in combination. We begin by deriving a generative model of viral misinformation spread, inspired by research on infectious disease. By applying this model to a large corpus (10.5 million tweets) of misinformation events that occurred during the 2020 US election, we reveal that commonly proposed interventions are unlikely to be effective in isolation. However, our framework demonstrates that a combined approach can achieve a substantial reduction in the prevalence of misinformation. Our results highlight a practical path forward as misinformation online continues to threaten vaccination efforts, equity and democratic processes around the globe.