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Inflammatory Bowel Disease II: Crohn's Disease

Inflammatory Bowel Disease II: Crohn's Disease

Introduction
Inflammatory bowel disease, commonly known as IBD, refers to a collection of disorders that lead to persistent inflammation of the gastrointestinal tract. The two types of IBD are ulcerative colitis, which impacts the colon, and Crohn's disease, which can involve any part of the gastrointestinal segment.
Crohn's disease
Crohn's disease is a chronic, systemic inflammatory bowel disease (IBD) that predominantly affects the gastrointestinal tract. It is marked by...

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Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

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Published on: October 28, 2018

Cell Spatial Analysis in Crohn's Disease: Unveiling Local Cell Arrangement Pattern with Graph-based Signatures.

Shunxing Bao¹, Sichen Zhu², Vasantha L Kolachala³

¹Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA.

Proceedings of Spie--The International Society for Optical Engineering

|September 23, 2024

Summary

This summary is machine-generated.

Researchers analyzed cell arrangements in Crohn's disease (CD) tissue using Hematoxylin and Eosin (H&E) imaging. They found distinct spatial patterns in cell neighborhoods, highlighting data heterogeneity and variations between research sites.

Keywords:

Cell spatial analysis Crohn’s disease Pattern recognition

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Published on: January 7, 2019

Area of Science:

Gastroenterology
Computational Pathology
Bioinformatics

Background:

Crohn's disease (CD) is a chronic inflammatory condition impacting the gastrointestinal tract.
Assessing CD activity typically relies on histological analysis, focusing on neutrophil density in Hematoxylin and Eosin (H&E) stained tissues.
Current methods face challenges in capturing comprehensive morphometric and spatial cellular arrangement data.

Purpose of the Study:

To develop a novel computational approach for characterizing local cell spatial signatures in CD.
To analyze differences in cellular environments and spatial patterns between active CD patients and controls.
To investigate the impact of data heterogeneity and multi-institutional data on cell spatial arrangements.

Main Methods:

Characterization of six distinct cell types from H&E images.
Development of a 10-cell neighborhood matrix to represent local cell arrangements.
Application of t-SNE for non-linear spatial projection and Kernel Density Estimation for contour plotting.
Comparative analysis of spatial patterns between active CD and control groups.

Main Results:

Identification of heterogeneous nearest-neighbor patterns in cellular arrangements.
Observed distinct cell clustering tendencies, particularly in the rectal region.
Demonstrated variations in spatial distribution linked to data heterogeneity and research site.
Quantified differences in cellular environments associated with CD activity.

Conclusions:

Novel computational methods reveal distinct spatial cell arrangements in Crohn's disease.
Cellular microenvironment heterogeneity significantly influences spatial patterns in CD.
Inter-institutional data disparities necessitate careful consideration in multi-center studies.
The developed analysis pipeline offers a tool for deeper insights into CD pathogenesis.