Asken, Breton M.

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I 2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I 2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I 2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I 2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I 2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Importance In vivo biomarkers for detecting neuropathologies from repetitive head impacts (RHI), including chronic traumatic encephalopathy (CTE), are needed. Objective To evaluate the utility of plasma phosphorylated tau 217 (p-tau217), assess its performance as a beta-amyloid (Aβ) biomarker in participants with RHI exposure at risk for CTE, and explore concordance with CTE neuropathology in a postmortem subsample. Design, Setting, and Participants This longitudinal, multicenter, case-control study used data from the Diagnostics, Imaging, and Genetics Network for the Objective Study and Evaluation of CTE (DIAGNOSE CTE) Research Project, collected from September 2016 to October 2023. Participants were former American football players (case participants) and asymptomatic men unexposed to RHI (control participants). A subsample had available neuropathologic data. Exposures RHI, traumatic encephalopathy syndrome (TES) diagnoses, and levels of CTE certainty. Main Outcomes and Measures Plasma p-tau217 (classified as positive [≥0.63 pg/mL], intermediate [0.40-0.62 pg/mL], and negative [<0.40 pg/mL]), Aβ–positron emission tomography (PET; 18 F-florbetapir; with Aβ-positive defined as a standardized uptake value ratio [SUVR] ≥1.10), and tau-PET ( 18 F-flortaucipir). TES diagnoses were assigned by multidisciplinary consensus conference. Analyses of postmortem brains controlled for age, race, and APOE ε4 status. Results Among 231 participants (mean [SD] age, 57.75 [8.25] years), 177 were former football players (117 professional and 60 college) and 54 were unexposed participants. Former football players had higher baseline mean (SD) p-tau217 concentrations than unexposed participants (0.35 [0.26] pg/mL vs 0.27 [0.14] pg/mL; P = .008), although this was driven by a higher proportion of Aβ-PET–positive participants among former players. Plasma p-tau217 increased over time across the sample (B = 0.207 [95% CI, 0.117-0.298]; P < .001), with no significant time × exposure group interactions. Among football players, p-tau217 showed no time × group interactions with TES diagnosis, TES-CTE certainty, or RHI metrics. Higher p-tau217 concentration correlated with higher global Aβ-PET SUVR (B = 0.058 [95% CI, 0.053-3.501; P = .01), with a few discordant cases (5 participants were p-tau217–negative and Aβ-PET–positive; 7 participants were p-tau217–positive and Aβ-PET–negative). P-tau217 had similar areas under the curve for projecting Aβ-PET positivity as cerebrospinal fluid (CSF) p-tau181/Aβ42 and CSF Aβ40/42 measures (p-tau217: AUC, 0.88 [95% CI, 0.80-0.96]; CSF p-tau181/Aβ42: AUC, 0.89 [95% CI, 0.79-1.00]; CSF Aβ40/42: AUC, 0.85 [95% CI, 0.72-0.98]). Among 9 brain donors, 6 had CTE (stages II-IV; none with Alzheimer disease). Seven had negative or intermediate p-tau217, concordant with Aβ-PET. Two p-tau217 outliers with stage III CTE had normal concentrations upon additional testing. Conclusions and Relevance The findings of this study suggest that plasma p-tau217 concentration is unlikely to be useful for the detection of CTE, but it does show utility for ruling out Aβ pathology in participants at risk for CTE.

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen's kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure 1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure 1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure 2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure 2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.