Tissue Characterization Analysis
Tissue Characterization Analysis - Related Videos
07:46
Isolation, Characterization, and Purification of Macrophages from Tissues Affected by Obesity-related Inflammation
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Cited by 15 •
2017
This protocol allows a researcher to isolate and characterize tissue-resident macrophages in various hallmark inflamed tissues extracted from diet-induced models of metabolic disorders.
04:49
Characterization of Macrophage Extracellular Traps in Mouse Lung Tissue Samples
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2025
In this video, we describe a protocol for the immunostaining and confocal microscopy-based visualization of macrophage extracellular traps (METs) in murine lung tissue. Tissue-resident macrophages are characterized by the expression of the macrophage-specific F4/80 surface glycoprotein marker, while METs are visualized by labeling the MET markers matrix metalloproteinase 9, citrullinated histone H3, and extracellular chromatin.
11:10
Micro-Mechanical Characterization of Lung Tissue Using Atomic Force Microscopy
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Cited by 127 •
2011
The stiffness of the extracellular matrix strongly influences multiple behaviors of adherent cells. Matrix stiffness varies spatially throughout a tissue, and undergoes modification in various disease conditions. Here we develop methods to characterize spatial variations in stiffness in normal and fibrotic mouse lung tissue using atomic force microscopy microindentation.
08:18
Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples
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Cited by 4 •
2023
Multiplexed barcoding image analysis has recently improved the characterization of the tumor microenvironment, permitting comprehensive studies of cell composition, functional state, and cell-cell interactions. Herein, we describe a staining and imaging protocol using the barcoding of oligonucleotide-conjugated antibodies and cycle imaging, which allows for the use of a high-dimensional image analysis technique.
07:07
Biomechanical Characterization of Human Soft Tissues Using Indentation and Tensile Testing
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Cited by 111 •
2016
Tissue biomechanics is important for maintaining cell shape and function and for determining phenotype. This report demonstrates non-destructive mechanical protocols for characterizing elastic and viscoelastic properties of human soft tissues, which can be directly applied to tissue-engineered substrates to allow a close matching of engineered materials to native tissue.
FAQs
Different tissue properties provide complementary evidence. Signal intensity reflects how tissue appears in imaging data, while elasticity describes mechanical behavior. Cellular organization and biochemical content add structural and compositional information, and contrast-agent behavior can reveal differences in tissue response. Combining these features helps distinguish tissue regions more reliably than relying on a single measurement alone.
The analysis compares measured patterns across tissue types and regions. Areas affected by tumors, fibrosis, inflammation, or ischemia may differ from normal tissue in signal, elasticity, cellular organization, biochemical composition, or contrast behavior. Interpreting these differences within imaging, histological, or spectroscopic data supports classification of tissue changes rather than treating every region as biologically equivalent.
Quantitative measurements convert tissue features into values that can be compared across regions, tissue types, examinations, or clinical assessments. This approach can improve diagnostic consistency by reducing reliance on subjective pattern recognition. It also supports more personalized medical decisions when tissue characteristics are evaluated alongside the patient’s disease status and treatment needs.
Each data source emphasizes different aspects of tissue biology. Imaging can provide measurable regional patterns, histology can show cellular organization, and spectroscopy can contribute information about biochemical content. Using these sources together creates a broader characterization of tissue composition and structure, which can strengthen interpretation when one type of measurement does not fully describe a pathological region.
A typical workflow begins by collecting imaging, histological, or spectroscopic data from the tissue of interest. Researchers then evaluate measurable features such as signal intensity, elasticity, cellular organization, biochemical content, or contrast-agent behavior. Finally, they compare the resulting patterns across tissue types and interpret whether regions are normal, damaged, or associated with disease.
Clinical teams can apply the analysis when they need to identify or evaluate pathological tissue changes. Supported uses include investigating tumors, fibrosis, inflammation, and ischemia, as well as contributing to diagnosis and treatment planning. Because tissue features can be measured over time, the approach can also help monitor disease progression and response to therapy.
The resulting measurements can help clinicians compare suspicious or abnormal regions with other tissue types and recognize patterns associated with disease. This information may support diagnostic assessment, treatment planning, and longitudinal evaluation during therapy. In clinical research, quantitative characterization can also promote more consistent interpretation and contribute to decisions tailored to individual tissue findings.