Automated deep learning segmentation of neuritic plaques and neurofibrillary tangles in Alzheimer disease brain sections using a proprietary software.

ABSTRACT: Neuropathological diagnosis of Alzheimer disease (AD) relies on semiquantitative analysis of phosphorylated tau-positive neurofibrillary tangles (NFTs) and neuritic plaques (NPs), without consideration of lesion heterogeneity in individual cases. We developed a deep learning workflow for automated annotation and segmentation of NPs and NFTs from AT8-immunostained whole slide images (WSIs) of AD brain sections. Fifteen WSIs of frontal cortex from 4 biobanks with varying tissue quality, staining intensity, and scanning formats were analyzed. We established an artificial intelligence (AI)-driven iterative procedure to improve the generation of expert-validated annotation datasets for NPs and NFTs thereby increasing annotation quality by >50%. This strategy yielded an expert-validated annotati

SUBMITTER: Ingrassia L 

PROVIDER: S-EPMC11333827 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature