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Author Notes:

Corresponding Author: David Gutman, MD, PhD, Department of Biomedical, Informatics, Emory University School of Medicine, PAIS Building, 36, Eagle Row, Atlanta, GA, 30322 USA, Dgutman@emory.edu

We would like to especially acknowledge the Emory Alzheimer’s Disease Research Center (NIA P50 AG025688) and the technical assistance of Deborah Cooper.

Subjects:

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Clinical Neurology
  • Neurosciences
  • Pathology
  • Neurosciences & Neurology
  • Alzheimer's disease
  • Braak
  • CERAD
  • digital analysis
  • neuropathology
  • ALZHEIMERS ASSOCIATION GUIDELINES
  • MILD COGNITIVE IMPAIRMENT
  • WHOLE-SLIDE IMAGES
  • NATIONAL INSTITUTE
  • NEUROFIBRILLARY TANGLES
  • HUMAN BRAIN
  • DISEASE
  • DIAGNOSIS
  • DEMENTIA
  • PATHOLOGY

Applicability of digital analysis and imaging technology in neuropathology assessment

Tools:

Journal Title:

Neuropathology

Volume:

Volume 36, Number 3

Publisher:

, Pages 270-282

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Alzheimer's disease (AD) is a progressive neurological disorder that affects more than 30 million people worldwide. While various dementia-related losses in cognitive functioning are its hallmark clinical symptoms, ultimate diagnosis is based on manual neuropathological assessments using various schemas, including Braak staging, CERAD (Consortium to Establish a Registry for Alzheimer's Disease) and Thal phase scoring. Since these scoring systems are based on subjective assessment, there is inevitably some degree of variation between readers, which could affect ultimate neuropathology diagnosis. Here, we report a pilot study investigating the applicability of computer-driven image analysis for characterizing neuropathological features, as well as its potential to supplement or even replace manually derived ratings commonly performed in medical settings. In this work, we quantitatively measured amyloid beta (Aβ) plaque in various brain regions from 34 patients using a robust digital quantification algorithm. We next verified these digitally derived measures to the manually derived pathology ratings using correlation and ordinal logistic regression methods, while also investigating the association with other AD-related neuropathology scoring schema commonly used at autopsy, such as Braak and CERAD. In addition to successfully verifying our digital measurements of Aβ plaques with respective categorical measurements, we found significant correlations with most AD-related scoring schemas. Our results demonstrate the potential for digital analysis to be adapted to more complex staining procedures commonly used in neuropathological diagnosis. As the efficiency of scanning and digital analysis of histology images increases, we believe that the basis of our semi-automatic approach may better standardize quantification of neuropathological changes and AD diagnosis, ultimately leading to a more comprehensive understanding of neurological disorders and more efficient patient care.

Copyright information:

© 2016 Japanese Society of Neuropathology. This is the peer reviewed version of the following article, which has been published in final form. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

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