After After
Before Before

10090 - Van Gieson, Collagenous Colitis

INTRODUCTION
Microscopic colitis is a type of inflammation of the colon that causes chronic non-bloody watery diarrhea. The disorder cannot be detected using normal colonoscopy, but is possible to detect by examining a biopsy of the colon tissue. Microscopic colitis can be distinguished into two subtypes, lymphocytic and collagenous. This APP addresses collagenous colitis, which is characterized by a thick layer of collagen in the colon tissue.

Thus, by quantifying the percentage of collagen in the colon tissue, a diagnosis can be determined.

KEYWORDS
Colon, colitis, collagenous, Van Gieson,  human, digital pathology, image analysis.

METHODS
The first image processing step involves an automated detection/outlining of colon tissue area, i.e. the region of interest (ROI) [See Figure 2]. The collagen border is subsequently detected inside the ROI [See Figure 4]. The collagen area is found [See Figure 5], and the percentage of collagen in the colon tissue is provided.

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

- CF Area #1: The total tissue area

- Area Collagen #1: The total collagen area

- Area Ratio Collagen: The ratio between the collagen area and the total tissue area

- Percentage Collagen: The percentage of collagen

AUXILIARY APPS (included)
ROI detection:
APP: “01 Detect ROI”
The auxiliary APP is 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.

WORKFLOW
Step 1: Load the auxiliary APP for ROI detection “01 Detect ROI”.

Step 2: Load the auxiliary APP for collagen border detection “02 Collagen Border”.

Step 3: Load the quantification protocol “03 Analyze”. This APP provides several output parameters such as “Area Collagen” and “Percentage Collagen”. 

Note: Manual editing of the detected borders (after step 2) or collagen (after step 3) may be necessary.

STAINING PROTOCOL
There is no staining protocol available.

ADDITIONAL INFORMATION
The APP utilizes the Visiopharm EngineTM and Viewer software modules, where EngineTM offers an execution platform to expand processing capability and speed of image analysis. The Visiopharm Viewer allows 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
1. Fiehn AM, Kristensson M, Engel U, Munck LK, Holck S, Engel PJH; Automated image analysis in the study of collagenous colitis, Clinical and Experimental Gastroenterology, April 2016.

RUO
Figure 1
Figure 1
Raw image of colon tissue.
Figure 2
Figure 2
Results of analysis with the Auxiliary APP: “01 Detect ROI”. The colon tissue area has clearly been outlined by a green dashed ROI.
Figure 3
Figure 3
Raw image showing the collagen border.
Figure 4
Figure 4
Results of analysis with the Auxiliary APP: “02 Collagen Border”. The collagen border is marked in red.
Figure 5
Figure 5
Results of analysis with the Auxiliary APP: “03 Analyze”. The collagen tissue is marked in red. The APP outputs the percentage of collagen in the colon tissue.