Literature DB >> 25907770

Image Analysis-Based Approaches for Scoring Mouse Models of Colitis.

R Rogers1, J Eastham-Anderson1, J DeVoss2, J Lesch2, D Yan2, M Xu2, M Solon1, K Hotzel1, L Diehl1, J D Webster3.   

Abstract

Mouse models of inflammatory bowel disease are critical for basic and translational research that is advancing the understanding and treatment of this disease. Assessment of these mouse models frequently relies on histologic endpoints. In recent years, whole slide imaging and digital pathology-based image analysis platforms have become increasingly available for implementation into the pathology workflow. These automated image analysis approaches allow for nonbiased quantitative assessment of histologic endpoints. In this study, the authors sought to develop an image analysis workflow using a commercially available image analysis platform that requires minimal training in image analysis or programming, and this workflow was used to score 2 mouse models of colitis that are primarily characterized by immune cell infiltrates in the lamina propria. Although the software was unable to accurately and consistently segment hematoxylin and eosin-stained sections, automated quantification of CD3 immunolabeling resulted in strong correlations with the pathologist's score in all studies and allowed for the identification of 8 of the 9 differences among treatment groups that were identified by the pathologist. These results demonstrate not only the ability to incorporate solutions based on image analysis into the pathologist's workflow but also the importance of immunohistochemical or histochemical surrogates for the incorporation of image analysis in histologic assessments.
© The Author(s) 2015.

Entities:  

Keywords:  colitis; computer-assisted image analysis; computer-assisted image interpretation; digital pathology; inflammatory bowel disease; mouse models; pathology methods; whole-slide imaging

Mesh:

Substances:

Year:  2015        PMID: 25907770     DOI: 10.1177/0300985815579998

Source DB:  PubMed          Journal:  Vet Pathol        ISSN: 0300-9858            Impact factor:   2.221


  5 in total

1.  Digital Microscopy, Image Analysis, and Virtual Slide Repository.

Authors:  Famke Aeffner; Hibret A Adissu; Michael C Boyle; Robert D Cardiff; Erik Hagendorn; Mark J Hoenerhoff; Robert Klopfleisch; Susan Newbigging; Dirk Schaudien; Oliver Turner; Kristin Wilson
Journal:  ILAR J       Date:  2018-12-01

2.  The effect of lunasin from Indonesian soybean extract on histopatologic examination and cox-2 expression in dextran sodium sulfate-induced mice colon.

Authors:  Kusmardi Kusmardi; Nessa Nessa; Ari Estuningtyas; Aryo Tedjo
Journal:  Int J Physiol Pathophysiol Pharmacol       Date:  2018-12-25

3.  Antimicrobial peptide KR-32 alleviates Escherichia coli K88-induced fatty acid malabsorption by improving expression of fatty acid transporter protein 4 (FATP4)1.

Authors:  Heyuan Liu; Xiaoxuan Cao; Hong Wang; Jian Zhao; Xinxia Wang; Yizhen Wang
Journal:  J Anim Sci       Date:  2019-05-30       Impact factor: 3.159

4.  An Image Analysis Solution For Quantification and Determination of Immunohistochemistry Staining Reproducibility.

Authors:  Elizabeth A Chlipala; Christine M Bendzinski; Charlie Dorner; Raili Sartan; Karen Copeland; Roger Pearce; Faye Doherty; Brad Bolon
Journal:  Appl Immunohistochem Mol Morphol       Date:  2020-07

5.  Deep learning-based approach to the characterization and quantification of histopathology in mouse models of colitis.

Authors:  Soma Kobayashi; Jason Shieh; Ainara Ruiz de Sabando; Julie Kim; Yang Liu; Sui Y Zee; Prateek Prasanna; Agnieszka B Bialkowska; Joel H Saltz; Vincent W Yang
Journal:  PLoS One       Date:  2022-08-29       Impact factor: 3.752

  5 in total

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