Image Analysis-Based Approaches for Scoring Mouse Models of Colitis

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.

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