Ontology highlight
ABSTRACT: Purpose
Several [18F]Flortaucipir cutoffs have been proposed for tau PET positivity (T+) in Alzheimer's disease (AD), but none were data-driven. The aim of this study was to establish and validate unsupervised T+ cutoffs by applying Gaussian mixture models (GMM).Methods
Amyloid negative (A-) cognitively normal (CN) and amyloid positive (A+) AD-related dementia (ADRD) subjects from ADNI (n=269) were included. ADNI (n=475) and Geneva Memory Clinic (GMC) cohorts (n=98) were used for validation. GMM-based cutoffs were extracted for the temporal meta-ROI, and validated against previously published cutoffs and visual rating.Results
GMM-based cutoffs classified less subjects as T+, mainly in the A- CN (<3.4% vs >28.5%) and A+ CN (<14.5% vs >42.9%) groups and showed higher agreement with visual rating (ICC=0.91 vs ICC<0.62) than published cutoffs.Conclusion
We provided reliable data-driven [18F]Flortaucipir cutoffs for in vivo T+ detection in AD. These cutoffs might be useful to select participants in clinical and research studies.
SUBMITTER: Quattrini G
PROVIDER: S-EPMC10542510 | biostudies-literature | 2023 Sep
REPOSITORIES: biostudies-literature
Quattrini Giulia G Ferrari Clarissa C Pievani Michela M Geviti Andrea A Ribaldi Federica F Scheffler Max M Frisoni Giovanni B GB Garibotto Valentina V Marizzoni Moira M
European journal of nuclear medicine and molecular imaging 20230605 11
<h4>Purpose</h4>Several [<sup>18</sup>F]Flortaucipir cutoffs have been proposed for tau PET positivity (T<sup>+</sup>) in Alzheimer's disease (AD), but none were data-driven. The aim of this study was to establish and validate unsupervised T<sup>+</sup> cutoffs by applying Gaussian mixture models (GMM).<h4>Methods</h4>Amyloid negative (A<sup>-</sup>) cognitively normal (CN) and amyloid positive (A<sup>+</sup>) AD-related dementia (ADRD) subjects from ADNI (n=269) were included. ADNI (n=475) and ...[more]