Technical ArticleEmbedding Brain Tissue for Routine Histopathology: A Processing Step Worthy of Consideration in the Digital Pathology EraNelson, Bela G.; Patel, Ela; Arth, Dane; Nelson, Peter T. MD, PhDAuthor Information Department of Pathology and Laboratory Medicine, Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY The authors declare no conflict of interest. Reprints: Peter T. Nelson, MD, PhD, Department of Pathology, Division of Neuropathology, Room 311, Sanders-Brown Center on Aging, 800 South Limestone, University of Kentucky, Lexington, KY 40536-0230 (e-mail: [email protected]). Applied Immunohistochemistry & Molecular Morphology: November/December 2020 - Volume 28 - Issue 10 - p 791-793 doi: 10.1097/PAI.0000000000000832 Buy SDC Metrics Abstract The importance of technical quality for histopathologic examination has only increased in recent years with the expanding use of digital pathology. The University of Kentucky Alzheimer’s Disease Center (UK-ADC) Neuropathology Core has decades of experience with brain histopathology and has emphasized the importance of quantitative assessments of histopathologic hallmarks. Technical artifacts and nonuniform samples are challenging for high-throughput digital analyses after the slides have been scanned, so that methodological optimization may be helpful. We do not know of published literature that systematically reviews how different procedures at the various stages of tissue processing can impact the quality of the histopathologic preparations in human brain samples. We wanted to pass along our experience in the hope that it will help others to improve their results. Here we describe the UK-ADC method of embedding for neuropathologic evaluation and provide specific examples (with a comparison to another processing workflow) that help support the idea that the methods and tools used in the embedding process can alter the quality of the formalin-fixed paraffin-embedded histopathologic results. The process used at the UK-ADC has been successful for us, but results may vary in relation to each embedding machine and with other factors. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.