# External Validation of Joint Propagation Model‐Based Tau PET CenTauR units

## TL;DR

This study validates a new method to standardize tau PET scans across different tracers, improving comparison and consistency in Alzheimer's research.

## Contribution

The study externally validates the CenTauR harmonization method for tau PET quantification across multiple tracers.

## Key findings

- A CenTauR cut-off of 18 optimally classifies PET visual reads across tracers.
- Tau-PET discriminative accuracy for Alzheimer's remains consistent across different tracers.
- Longitudinal changes in CenTauRs are comparable across matched cohorts.

## Abstract

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.

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.

A cut‐off of 18 CenTauRs was found to optimally classify [18F]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 [18F]flortaucipir and [18F]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).

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.