Predicting regional tau accumulation with machine learning-based tau-PET and advanced radiomics.

ABSTRACT:

Introduction

Alzheimer's disease is partially characterized by the progressive accumulation of aggregated tau-containing neurofibrillary tangles. Although the association between accumulated tau, neurodegeneration, and cognitive decline is critical for disease understanding and clinical trial design, we still lack robust tools to predict individualized trajectories of tau accumulation. Our objective was to assess whether brain imaging biomarkers of flortaucipir-positron emission tomography (PET), in combination with clinical and genomic measures, could predict future pathological tau accumulation.

Methods

We quantified the disease profile of participants (N = 276) using a comprehensive set of descriptors, including clinical/demographic (age, diagnosis, amyloid status,

SUBMITTER: Rathore S 

PROVIDER: S-EPMC11694527 | biostudies-literature | 2024 Oct-Dec

REPOSITORIES: biostudies-literature