Digital neuropathology of neurodegenerative disorders: Foundations, research advances, and future directions

Abstract

A neuropathology examination after death remains the gold standard for differentiating between Alzheimer disease (AD) and AD and related dementias (ADRD). Increasing interest and familiarity with digital imaging highlights recent shifts to modernize pathology workflows by leveraging technology that automates imaging and analysis. This review provides an overview of digital pathology technologies and their associated infrastructure, available open-source and proprietary digital pathology software, relevant background on neurodegenerative histopathological features, and computational research. It further examines recent developments in digital pathology in neurodegenerative disease research with an emphasis on machine learning. We discuss evidence supporting how recently developed technologies and methodologies can enhance our understanding of histopathologic features of neurodegeneration and correlations of histopathologic features with cognitive performance and age at death. Finally, we review potential directions for neurodegenerative disease digital pathology research given trends in technological infrastructure development and other digital pathology research. HIGHLIGHTS: Provides a historical summary of digital pathology with respect to neuropathology. Examines key digital pathology technologies. Explores digital pathology applications in neurodegenerative disease and their contribution to research. Discusses the future of digital neuropathology.

Keywords: Alzheimer disease (AD); Alzheimer's disease and related dementias (ADRD); National Alzheimer's Coordinating Center; artificial intelligence (AI); brain banking; computer vision (CV); cross‐institutional collaboration; deep learning (DL); digital pathology; information technology; machine learning (ML); medical imaging; neurodegeneration; whole slide image (WSI).