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Alzheimer's Imaging Consortium.

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PubMed
Summary
This summary is machine-generated.

Positron emission tomography (PET) biomarkers for amyloid-β and tau predict brain pathology, but tau PET requires adjustments for outliers to accurately reflect tau neurofibrillary tangle distribution. Individualized tau PET metrics improve prediction of neuropathologic assessments.

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Area of Science:

  • Neuroimaging
  • Neuropathology
  • Alzheimer's Disease Research

Background:

  • The Harvard Aging Brain Study (HABS) investigates differences between normal aging and preclinical Alzheimer's Disease (AD).
  • Sixteen HABS participants donated their brains for neuropathologic assessment.
  • This study evaluates the predictive power of antemortem PET biomarkers for postmortem neuropathologic findings.

Purpose of the Study:

  • To compare antemortem PET biomarkers (amyloid-β and tau) with postmortem neuropathologic assessments.
  • To determine the correlation between PET imaging metrics and the burden/distribution of amyloid plaques and tau tangles.
  • To identify factors contributing to discrepancies between PET findings and neuropathology.

Main Methods:

  • Neuropathologic assessment of amyloid plaques (Thal phase/A score), tau tangles (Braak NFT stage/B score), and neuritic plaques (CERAD NP score/C score).
  • Amyloid-β PET (PiB) metrics included frontal, lateral temporal, parietal, and retrosplenial cortex (FLR) distribution volume ratio (DVR) and spatial extent (EXT).
  • Tau PET (flortaucipir, FTP) metrics included whole temporal, medial temporal lobe (MTL), and temporal neocortex (NEO-T) standardized uptake value ratios (SUVRs), analyzed bilaterally and laterally.

Main Results:

  • Amyloid-β PET (PiB) DVR and EXT significantly correlated with amyloid plaque (A) and CERAD (C) scores.
  • Initial tau PET (FTP) SUVRs did not significantly correlate with Braak (B) stage.
  • After removing outliers, whole temporal and NEO-T SUVRs correlated significantly with B score; lateralized SUVRs further strengthened these correlations.

Conclusions:

  • Amyloid-β PET metrics align well with amyloid plaque distribution and density.
  • Tau PET metrics correlate with tau tangle distribution only after accounting for outliers, suggesting PET-neuropathologic discrepancies are more common with tau.
  • Individualized tau PET metrics that account for heterogeneity in tauopathy are crucial for accurate prediction of neuropathologic assessments.