Microscopic Lesion Detection
Microscopic Lesion Detection - Related Videos
03:46
Detection of Bacterial Antibiotic Susceptibility Using a Stimulated Raman Scattering Microscope
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2026
Source: Zhang, M. et. al., Rapid Antimicrobial Susceptibility Testing by Stimulated Raman Scattering Imaging of Deuterium Incorporation in a Single Bacterium. J. Vis. Exp. (2022)This video demonstrates the application of stimulated Raman scattering microscopy to assess susceptibility to antibiotics by tracking deuterium-labeled metabolic activity. By monitoring carbon–deuterium signals, the method enables rapid detection of resistant and susceptible bacterial populations.
08:16
Comparative Lesions Analysis Through a Targeted Sequencing Approach
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2019
This article describes a method to identify clonal and subclonal alterations among different specimens from a given patient. Although the experiments described here focus on a specific tumor type, the approach is broadly applicable to other solid tumors.
06:43
Quantitative Analysis and Characterization of Atherosclerotic Lesions in the Murine Aortic Sinus
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Cited by 51 •
2013
We describe procedures to quantify and characterize atherosclerotic lesions in mouse models using precision sectioning of the aortic sinus and ascending aorta combined with histochemical and immunohistochemical analysis.
09:22
Sectioning Mammary Gland Whole Mounts for Lesion Identification
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Cited by 13 •
2017
We developed a method to successfully remove, process, section, and stain, for histopathological evaluation, mammary tissue that had originally been fixed on slides as whole mounts. This method may promote the collection and evaluation of mammary gland whole mounts in reproductive and developmental test guideline studies.
02:19
Microscopic Visualization of Bacterial Microlesions in Mouse Heart Tissue
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2026
Source: Brown, A. O., et al. Visualization of Streptococcus pneumoniae within Cardiac Microlesions and Subsequent Cardiac Remodeling. J. Vis. Exp. (2015).This video demonstrates the microscopic visualization of bacterial microlesions in mouse heart tissue. The heart of a mouse infected with Streptococcus pneumoniae is harvested, washed, and fixed before being processed to obtain coronal sections. These sections are stained with hematoxylin and eosin and examined under a microscope to visualize...
FAQs
The key cues are changes in nuclear appearance, disruption of normal cell organization, and alterations in local tissue architecture. Their value comes from evaluating these features together and comparing the suspected abnormal area with nearby tissue that provides a relevant background reference. This combined assessment helps separate a true lesion pattern from normal variation within the section.
Heterogeneity means that abnormal features may vary across different parts of the same tissue or lesion. As a result, detection should account for more than one microscopic pattern and should not rely on a single representative area. Recognizing this variation supports more complete lesion characterization and helps relate microscopic findings to differences in molecular or clinical observations.
Boundary assessment shows where abnormal tissue begins and ends relative to surrounding tissue. Clear or irregular transitions can provide useful information about the extent and local organization of a lesion, while variable boundaries may reflect tissue heterogeneity. Recording these patterns strengthens characterization and can support later comparisons with quantitative image measurements or other cancer-related findings.
A typical workflow begins with examination of tissue sections at cellular resolution, followed by inspection of nuclear features, cell organization, and local architecture. Suspected abnormal regions are then considered in relation to surrounding normal tissue, with attention to their extent and internal variation. The resulting observations can support consistent pathology review and downstream image-based analysis.
Microscopic observations can be correlated with molecular or clinical findings to examine whether particular tissue patterns occur alongside other disease-related characteristics. This connection adds context to the cellular and architectural assessment rather than treating morphology as an isolated observation. In cancer research, such correlations can help characterize lesions more comprehensively and guide investigation of biologically relevant patterns.
Consistent recognition of small abnormal patterns creates a foundation for comparing microscopic features across specimens or research conditions. When these observations are combined with quantitative image analysis and molecular or clinical information, they may help identify patterns useful for biomarker investigation. The approach therefore contributes to early disease characterization by linking visible tissue changes with measurable research outcomes.