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10085 - CD3, Lymphocytic Colitis

INTRODUCTION
Microscopic colitis is a type of inflammation of the colon that causes non-bloody watery diarrhea and most often impacts middle-aged females. The condition can be distinguished into two types, lymphocytic and collagenous. The difference between the two types are minor; both are characterized by an increase in lymphocytes with collagenous colitis also having a thickened subepithelial collagen layer.
This APP is addressing lymphocytic colitis.

By quantifying the T-lymphocytes targeted by the CD3 marker in different tissue compartments, a diagnosis can be determined.

KEYWORD
Colon, colorectal, colitis, CD3, lymphocytic, collagenous, human, digital pathology, image analysis, quantitative.

METHODS
The APP detects the tissue regions and separates the intestinal glands and tissue border from the remaining tissue via edge detection based on Hematoxylin deconvolution. The brown CD3 positive stained and blue negative stained areas are then quantified and calculated within the three tissue regions.

QUANTITATIVE OUTPUT VARIABLES
The output variables obtained from this protocol are:

- % Positive (Tissue): The CD3 positive percentage in all tissue (area based calculation)

- % Positive (Border): The CD3 positive percentage in the tissue border (area based calculation)

- % Positive (Islets): The CD3 positive percentage in the intestinal glands (area based calculation)

AUXILIARY APPS (included)
ROI detect:
APP: "01 ROI detect"
This APP can be used for automatic and precise detection of tissue present in the image, thereby limiting the analysis to only occur within relevant tissue areas and not on the entire image.

STAINING PROTOCOL
There is no staining protocol available

ADDITIONAL INFORMATION
The APP utilizes the EngineTM and Viewer software modules, where EngineTM offers an execution platform to expand processing capability and speed of image analysis. Viewer gives a fast review together with several types of image adjustment properties ex. outlining of regions, annotations and direct measures of distance, curve length, radius, etc. 
By adding the AuthorTM module the APP can be customized to fit other purposes. AuthorTM offers a comprehensive and dedicated set of tools for creating new fit-for-purpose analysis APPs, and no programming experience is required.

REFERENCES
There are no references available.

RUO
FIGURE 1
FIGURE 1
The auxiliary APP “01 ROI detect” automatically outlines the relevant tissue on slide.
FIGURE 2
FIGURE 2
Next the intestinal glands and the tissue border is detected. The intestinal glands are marked with a red ROI, while the tissue border is marked with a blue ROI.
FIGURE 3
FIGURE 3
Close up of detected intestinal glands and the tissue border.
FIGURE 4
FIGURE 4
Final analysis result: CD3 positive (red) and CD3 negative tissue (blue) is identified. The APP outputs the percentage of CD3 positive area within each compartment, i.e. the intestinal glands and the tissue border. The APP also outputs the overall CD3 positive area on the slide.