A Machine Learning-Based Approach to Discrimination of Tauopathies Using [¹⁸ F]PM-PBB3 PET Images.

ABSTRACT:

Background

We recently developed a positron emission tomography (PET) probe, [¹⁸ F]PM-PBB3, to detect tau lesions in diverse tauopathies, including mixed three-repeat and four-repeat (3R + 4R) tau fibrils in Alzheimer's disease (AD) and 4R tau aggregates in progressive supranuclear palsy (PSP). For wider availability of this technology for clinical settings, bias-free quantitative evaluation of tau images without a priori disease information is needed.

Objective

We aimed to establish tau PET pathology indices to characterize PSP and AD using a machine learning approach and test their validity and tracer capabilities.

Methods

Data were obtained from 50 healthy control subjects, 46 patients with PSP Richardson syndrome, and 37 patients on the AD continuum. Ta

SUBMITTER: Endo H 

PROVIDER: S-EPMC9805085 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature