INTRODUCTION
Pulmonary fibrosis is the formation or development of excess fibrous connective tissue (fibrosis) in the lungs. Pulmonary fibrosis is a gradual exchange of normal lung parenchyma with fibrotic tissue, causing irreversible decrease in oxygen diffusion capacity. In addition, decreased compliance makes pulmonary fibrosis a restrictive lung disease. It is the main cause of restrictive lung disease that is intrinsic to the lung parenchyma. With Masson's trichrome, the collagen in a rat lung section is stained blue and therefore very easy to distinguish from other tissue types. A magnification of 5X and a random 50% sampling is sufficient for an accurate and robust estimation of the collagen to tissue ratio.

KEYWORDS
Pulmonary, Lung, Fibrosis, Collagen, quantitative, digital pathology, image analysis.

METHODS
The first image processing step involves a segmentation of the lung tissue from the background. This can be done automatically or manually depending on the complexity and quality of the image . As the collagen is quite distinct from the rest of the tissue, a threshold classifier is applied to a Red-Blue Contrast band. This segments the bluish collagen from the rest of the tissue].

QUANTITATIVE OUTPUT VARIABLES
The output variables of the analysis protocol includes:

- Area of collagen: The area of collagen

- Tissue area: The area of the analyzed tissue

- Collagen ratio = Area of collagen / Tissue area: Quantification of the fibrosis defined as the area of collagen relative to total tissue area


AUXILIARY APPS (included)
Auxiliary APPs are used for additional process steps, e.g. finding Region of Interest (ROI).

ROI Detect
This auxiliary APP '01 ROI Detect' can be used to automatically detect a ROI. The ROI is generated by distinguishing tissue from background.


STAINING PROTOCOL
There is no staining protocol available.


ADDITIONAL INFORMATION
The APP utilizes the Engine^TM and Viewer software modules, where Engine^TM 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 Author^TM module the APP can be customized to fit other purposes. Author^TM 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 currently no references.