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Updated: Jan 8, 2026

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451
Published on: April 18, 2025
Alzheimer's Imaging Consortium
Max McLachlan1, Brecca Bettcher1, Andrew K McVea1
1Waisman Center, University of Wisconsin-Madison, Madison, WI, USA.
Background:
Previous work in the Down syndrome (DS) population has revealed early and accelerated accumulation of Alzheimer's disease (AD) pathology when compared with neurotypical adults. Temporal models of [11C]PiB PET beta-amyloid (Aβ) trajectories aligned with the progression of [18F]flortaucipir neurofibrillary tau (NFT) burden through Braak-associated regions (Zammit 2023). These analyses were extended to a larger DS cohort that includes individuals who underwent Aβ imaging with [18F]florbetapir. This work investigated the temporal relationship between regional NFT burden and a standardized model of Aβ onset in the DS population.
Method:
282 participants with DS underwent longitudinal NFT and Aβ PET imaging (Table 1). PiB and florbetapir scans underwent Centiloid (CL) processing using a previously calibrated pipeline. Flortaucipir scans were realigned, summed 80-100 min, and warped into standard space. SUVR was calculated (inferior cerebellar grey reference) for Braak-associated NFT regions (described in Figure 1). Using the sampled iterative local approximation (SILA) method, the average rate of change was discretely sampled across the CL range, yielding a generalized model for amyloid progression. The estimated time-to-Aβ onset (or Aβ chronicity) was calculated for each participant by aligning their trajectories to the model. Flortaucipir SUVR and % Change were binned within discrete Aβ chronicity stages and fit to a linear mixed effects model for each region, using: SUVR or % Change ∼ Age+Sex+Scanner+APOE4+Chronicity Stage+Cognitive Status+(1|Participant) The model was used to estimate the influence of biological parameters and the relative time of significant NFT onset.
Result:
Across all NFT regions, participants with dementia had the highest flortaucipir SUVR and latest chronicity, followed by MCI (Figure 1). SUVR was significantly increased by the 0-5 years chronicity window in NFT I and II, while NFT III-VI were not significantly increased until 5-10 years (Figure 2). % Change was significantly increased in the 0-5 years chronicity window for NFT I and in the >10 years window for NFT III-VI. Scanner, cognitive status, and age effects were significant in each region.
Conclusion:
This work supports previous findings that NFT regions I-II demonstrate earlier increases to flortaucipir SUVR than other NFT regions when using a standardized temporal model for Aβ onset.
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