Collins, Emily C.

Abstract Background The Joint Propagation Model (JPM)‐based CenTauR scale was recently introduced to harmonize tau‐PET quantification across different radiotracers. This study examined how CenTauR harmonization enhances the comparability of tau‐PET quantification across matched cohorts using different tracers. The evaluation focused on three key aspects: (1) comparing tau‐PET positivity rates as defined by CenTauR, (2) evaluating its diagnostic accuracy for symptomatic AD, and (3) analyzing longitudinal changes in tau‐PET rates over time. Method The JPM, developed by the CPAD‐led Tau PET Harmonization Working Group (Leuzy et al., Alzheimers Dement. 2024; Figure 1A), models relationships between anchor point subjects and head‐to‐head tau‐PET SUVR data onto the CenTauR scale, providing conversion equations for multiple tracers. JPM equations were applied to [ 18 F]flortaucipir SUVR (Meta‐temporal ROI) data from 561 cognitively impaired participants in the ADNI and OASIS‐3 studies. Using ROC analysis, we determined the CenTauR cut‐off for positivity (T+) that maximized the Youden index for discriminating between FDA‐approved positive/negative visual reads. Three separate cohorts, scanned using [ 18 F]flortaucipir (ADNI), [ 18 F]MK‐6240 (CPAS), and [ 18 F]RO‐948 (BioFINDER‐2), were matched 1:1 by age, MMSE, amyloid‐β, and clinical diagnosis. CenTauR‐based metrics were compared across these cohorts. Result A cut‐off of 18 CenTauRs was found to optimally classify [ 18 F]flortaucipir PET visual reads (Figure 1B). The matching procedure identified 1089 participants (363 per cohort). The frequency of T+ using the 18 CenTauRs cut‐off for the Meta‐Temporal ROI was highly comparable across tracers across groups, except for the Aβ‐positive cognitively unimpaired group, where variability was more pronounced due to a smaller sample size (Figure 2A). Similarly, tau‐PET discriminative accuracy for symptomatic AD vs controls remained similar across [ 18 F]flortaucipir and [ 18 F]MK‐6240 (Figure 2B). In a separate sample of 212 matched participants from ADNI ([ 18 F]flortaucipir) and AIBL ([ 18 F]MK‐6240) with baseline and 1‐year follow‐up tau‐PET scans, 1‐year change in CenTauRs was comparable (Figure 2C). An exploratory voxelwise transformation, utilizing the Meta‐Temporal conversion equation in a representative case scanned with both [ 18 F]flortaucipir and [ 18 F]MK‐6240, demonstrates the potential for voxelwise CenTauR harmonization (Figure 3). Conclusion These analyses suggest that CenTauR harmonization increases the comparability of tau‐PET data acquired with different tracers. Additional validation analyses with larger cohorts including other radiotracers ([ 18 F]PI‐2620) are underway.

Abstract Background The Joint Propagation Model (JPM)‐based CenTauR scale was recently introduced to harmonize tau‐PET quantification across different radiotracers. This study examined how CenTauR harmonization enhances the comparability of tau‐PET quantification across matched cohorts using different tracers. The evaluation focused on three key aspects: (1) comparing tau‐PET positivity rates as defined by CenTauR, (2) evaluating its diagnostic accuracy for symptomatic AD, and (3) analyzing longitudinal changes in tau‐PET rates over time. Method The JPM, developed by the CPAD‐led Tau PET Harmonization Working Group (Leuzy et al., Alzheimers Dement. 2024; Figure 1A), models relationships between anchor point subjects and head‐to‐head tau‐PET SUVR data onto the CenTauR scale, providing conversion equations for multiple tracers. JPM equations were applied to [¹⁸F]flortaucipir SUVR (Meta‐temporal ROI) data from 561 cognitively impaired participants in the ADNI and OASIS‐3 studies. Using ROC analysis, we determined the CenTauR cut‐off for positivity (T+) that maximized the Youden index for discriminating between FDA‐approved positive/negative visual reads. Three separate cohorts, scanned using [¹⁸F]flortaucipir (ADNI), [¹⁸F]MK‐6240 (CPAS), and [¹⁸F]RO‐948 (BioFINDER‐2), were matched 1:1 by age, MMSE, amyloid‐β, and clinical diagnosis. CenTauR‐based metrics were compared across these cohorts. Result A cut‐off of 18 CenTauRs was found to optimally classify [ 18 F]flortaucipir PET visual reads (Figure 1B). The matching procedure identified 1089 participants (363 per cohort). The frequency of T+ using the 18 CenTauRs cut‐off for the Meta‐Temporal ROI was highly comparable across tracers across groups, except for the Aβ‐positive cognitively unimpaired group, where variability was more pronounced due to a smaller sample size (Figure 2A). Similarly, tau‐PET discriminative accuracy for symptomatic AD vs controls remained similar across [ 18 F]flortaucipir and [ 18 F]MK‐6240 (Figure 2B). In a separate sample of 212 matched participants from ADNI ([¹⁸F]flortaucipir) and AIBL ([¹⁸F]MK‐6240) with baseline and 1‐year follow‐up tau‐PET scans, 1‐year change in CenTauRs was comparable (Figure 2C). An exploratory voxelwise transformation, utilizing the Meta‐Temporal conversion equation in a representative case scanned with both [¹⁸F]flortaucipir and [¹⁸F]MK‐6240, demonstrates the potential for voxelwise CenTauR harmonization (Figure 3). Conclusion These analyses suggest that CenTauR harmonization increases the comparability of tau‐PET data acquired with different tracers. Additional validation analyses with larger cohorts including other radiotracers ([¹⁸F]PI‐2620) are underway.

Importance Accumulation of amyloid plaque drives pathogenesis of Alzheimer disease (AD). Reduction of amyloid via amyloid-targeting therapies may result in clinical benefit. Objective To assess the correlation of posttreatment amyloid levels with clinical outcomes and biomarkers in AD. Design, Setting, and Participants This was a post hoc exploratory analysis from the randomized, placebo-controlled phase 3 trial, TRAILBLAZER-ALZ 2, conducted June 2020 through April 2023 at 277 medical research centers/hospitals in 8 countries. A total of 8240 participants aged 60 to 85 years with early symptomatic AD with amyloid and tau pathology based on positron emission tomography (PET) imaging were assessed for eligibility. Of these, 6504 participants were excluded predominantly due to inadequate amyloid or tau pathology. The current analysis included 1582 participants (766 in the donanemab group and 816 in the placebo group) with baseline and at least 1 posttreatment assessment. Data analysis took place from July 2024 to March 2025. Interventions Participants were randomized 1:1 to receive donanemab (700 mg for the first 3 doses and 1400 mg thereafter) or placebo intravenously every 4 weeks for up to 72 weeks, with outcomes assessed through 76 weeks. Main Outcomes and Measures Participants were categorized into 1 of 10 groups (deciles) based on their lowest amyloid value observed posttreatment. Clinical progression was assessed via changes in integrated Alzheimer’s Disease Rating Scale (iADRS) and Clinical Dementia Rating–Sum of Boxes (CDR-SB) scores. Plasma biomarkers measured included phosphorylated tau 217 (p-tau217), p-tau181, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). Correlations between the median amyloid level in each decile were assessed with 76-week least-squares mean changes in each outcome and biomarker. Results Analyses included 1582 participants, including 766 treated with donanemab and 816 with placebo. The mean (SD) age was 72.9 (6.2) years, and 900 participants (56.9%) were female. Participants who received donanemab had lower posttreatment amyloid values than those in the placebo group. Across the trial population, lower posttreatment amyloid levels were correlated with slower clinical progression as measured by iADRS score ( R 2 , 0.73 [95% CI, 0.37-0.97]) and CDR-SB score ( R 2 , 0.87 [95% CI, 0.70-0.97]) and with decreases in p-tau217 ( R 2 , 0.86 [95% CI, 0.73-0.97]), p-tau181 ( R 2 , 0.88 [95% CI, 0.77-0.97]), and GFAP ( R 2 , 0.87 [95% CI, 0.76-0.97]). There was no correlation between posttreatment amyloid value and NfL ( R 2 , 0.03 [95% CI, 0.00-0.54]). Conclusions and Relevance The findings in this secondary analysis of a randomized clinical trial demonstrating a correlation between posttreatment amyloid plaque level and clinical benefit support amyloid plaque removal as the mechanism of action for donanemab treatment and the level of amyloid plaque as a potential surrogate biomarker in amyloid-targeting therapies. Trial Registration ClinicalTrials.gov Identifier: NCT04437511

Abstract INTRODUCTION Tau‐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. METHODS Using 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. RESULTS A 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. DISCUSSION Preliminary findings using the JPM support the development and adoption of a universal scale for tau‐PET quantification. Highlights Tested 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.