Abstract

Histopathology of testicular tissue is considered to be the most sensitive tool to detect adverse effects on male reproduction. When assessing tissue damage, seminiferous epithelium needs to be classified into different stages to detect certain cell damages; but stage identification is a demanding task. The authors present a method to identify the 12 stages in mink testicular tissue. The staging system uses Gata-4 immunohistochemistry to visualize acrosome development and proved to be both intraobserver-reproducible and interobserver-reproducible with a substantial agreement of 83.6% (kappa=0.81) and 70.5% (kappa=0.67), respectively. To further advance and objectify this method, they present a computerized staging system that identifies these 12 stages. This program has an agreement of 52.8% (kappa 0.47) with the consensus staging by 2 investigators. The authors propose a pooling of the stages into 5 groups based on morphology, stage transition, and toxicologically important endpoints. The computerized program then reached a substantial agreement of 76.7% (kappa=0.69). The computerized staging tool uses local ternary patterns to describe the texture of the tubules and a support vector machine classifier to learn which textures correspond to which stages. The results have the potential to modernize the tedious staging process required in toxicological evaluation of testicular tissue, especially if combined with whole-slide imaging and automated tubular segmentation. Environ Toxicol Chem 2017;36:156-164. (c) 2016 The Authors. Environmental Toxicology and Chemistry Published by Wiley Periodicals, Inc. on behalf of SETAC.

Keywords

Male reproductive toxicology; Endocrine disruptor; Computational toxicology; Histopathology; Method

Published in

Environmental Toxicology and Chemistry
2017, Volume: 36, number: 1, pages: 156-164

SLU Authors

• Fakhrzadeh, Azadeh

  • Centre for Image Analysis, Swedish University of Agricultural Sciences
    

• Spörndly-Nees, Ellinor

  • Department of Animal Biosciences, Swedish University of Agricultural Sciences
    

• Ekstedt, Elisabeth

  • Department of Animal Biosciences, Swedish University of Agricultural Sciences
    

• Holm, Lena

  • Department of Animal Biosciences, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Computer Science
Pathobiology
Environmental Sciences


Publication identifier

DOI: https://doi.org/10.1002/etc.3517

Permanent link to this page (URI)

https://res.slu.se/id/publ/90935