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    Biomedical Imaging and Instrumentation

    (D-148) ImageJ Plugin for Quantifying Biomarker Distribution along the Gastrointestinal Unit Axis: A Tool for Spatial Pathology Analysis

    Saturday, October 14, 2023
    9:30 AM – 10:30 AM PDT
    Location: Exhibit Hall - Row D - Poster # 148

      Presenting Author(s)

    • AD

      Arion Dey (he/him/his)

      Student
      Wake Forest University
      Aurora, Illinois, United States

      • Primary Investigator(s)

    • JW

      Jared Weis

      Assistant Professor
      Wake Forest University School of Medicine, United States

      • Last Author(s)

    • VW

      Victoria Weis

      Assistant Professor
      Wake Forest Institute for Regenerative Medicine, United States

      • Co-Author(s)

    • ME

      Michelle Ebu

      Student Researcher
      Wake Forest Institute for Regenerative Medicine, United States

    Introduction:: Histological staining is a mainstay of tissue assessment and is critical for understanding normal homeostasis and disease within the gastrointestinal tract. In the preclinical setting, tissue histology is widely used to assess normal development and homeostasis, disease initiation and progression, and impacts of experimental therapeutic approaches. This tissue analysis often includes histological stains and immunohistochemistry for the quantification of specific cell types or protein expression within the tissue architecture to identify potential changes in either the quantity or localization. This quantitative analysis of tissue staining is typically performed using coarse and time-consuming manual scoring assessments. Further, robust assessment of spatial dependence encoded within tissue staining patterns is often lacking in these quantitative measurements. This shortcoming is especially relevant in the analysis of the gastrointestinal epithelium, which is typically arranged in an ordered architecture with repeating epithelial units. Therefore, there is a compelling need within the GI biology field for a robust tool to analyze how immunostaining for markers of interest are expressed across the tissue landscape within the epithelial unit.  In this work, we developed a gastrointestinal-focused spatial pathology plugin to advance research in spatial analysis of GI epithelial tissues to quantify immunostaining markers in a tissue landscape through a spatial lens. Based on our previous closed-source custom-built software, this new ImageJ plugin is designed to analyze the quantitative spatial localization of user designated points-of-interest (i.e. positively stained cells) along the ordered architecture of the GI epithelial units. 

    Materials and Methods:: This new plugin was developed using ImageJ 1.53.o as the ImageJ version and was built using the Java programming language. The Java code was written in Eclipse Java Integrated Development Environment release 4.27.0, which is a development environment for Java code. The software relies on ImageJ and native Java utility packages to both interfaces directly with ImageJ and to take advantage of the variety of Java libraries for data processing. Being hosted in ImageJ allows for the user to benefit from ImageJ’s native image preprocessing tools and familiar interface. The workflow can be divided into four steps. The first step is the user uploading a GI unit’s image to analyze. The user can choose an output file for data or choose to have the plugin generate one for them. Next, the user is prompted to determine the GI epithelial unit’s base through a manual segmentation line. A similar process is then used for determining the top of the GI epithelial unit. Finally, the user has the option to either import previously identified point-of-interest coordinates utilizing ImageJ's intrinsic coordinate framework or perform manual annotations within ImageJ using the multipoint tool.

    Results, Conclusions, and Discussions::

    The data output consists of three readouts: 1) the centroid coordinates of user designated positive-stained locations, 2) the absolute distances of these centroids from each of the identified GI epithelial unit’s top and base landmarks to designate location along the GI epithelial unit axis, and 3) the normalized distances of these centroids (relative to the total height of the GI unit) to designate relative location along the GI unit axis. To further assess cellular localizations, this plugin also generates a histogram based on these data with average point-of-interest distances along the unit axis per GI epithelial unit. The information can be used to quantify total points-of-interest counts per GI epithelial unit, analyze the height localization (relative and absolute) of points-of-interest, and the average GI unit heights.This GI spatial pathology plugin is an important analysis tool that allows for more robust assessment of many biological mechanisms within the GI tract. These types of histological analyses could include EdU localization and migration distances, changes in localization of known cell types, and identification of new or rare expression patterns along the GI unit axis. Overall, this new open-source ImageJ plugin is a semi-automated user-friendly tool to provide important insights into spatial localization of tissue histology expression patterns within the GI structured architecture with streamlined post-processing pipelines for large-scale robust analysis.



    Acknowledgements (Optional): : This project was supported in part by the NIH/NLM (R25 LM014214) in the Department of Biomedical Engineering and Center for Biomedical Informatics at Wake Forest University School of Medicine. 

    These studies were supported by the Wake Forest Institute for Regenerative Medicine Pilot Award, NIH-NIDDK K01DK125633, American Gastroenterological Association Research Scholar Award in Health Disparities, and Wake Forest University School of Medicine Faculty Start-Up Funds.


     



    References (Optional): :

    [1] Wiegand, W. E. A platform for integrating development tools. IBM Systems Journal 43, 371–383 (2004).


    [2] Weis, V. G., Petersen, C. P., Weis, J. A., Meyer, A. R., Choi, E., Mills, J. C., & Goldenring, J. R. (2017). Maturity and age influence chief cell ability to transdifferentiate into metaplasia. American Journal of Physiology-Gastrointestinal and Liver Physiology, 312(1). https://doi.org/10.1152/ajpgi.00326.2016