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Digital quantification of fibrosis in liver biopsy sections: Description of a new method by Photoshop software
Author(s) -
DAHAB GAMAL M,
KHERIZA MOHAMED M,
ELBELTAGI HUSSIEN M,
FOUDA ABDELMOTAAL M,
ELDIN OSAMA A SHARAF
Publication year - 2004
Publication title -
journal of gastroenterology and hepatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.214
H-Index - 130
eISSN - 1440-1746
pISSN - 0815-9319
DOI - 10.1111/j.1440-1746.2004.03183.x
Subject(s) - medicine , biopsy , liver fibrosis , liver biopsy , software , medical physics , radiology , pathology , fibrosis , computer science , programming language
Background: The precise quantification of fibrous tissue in liver biopsy sections is extremely important in the classification, diagnosis and grading of chronic liver disease, as well as in evaluating the response to antifibrotic therapy. Because the recently described methods of digital image analysis of fibrosis in liver biopsy sections have major flaws, including the use of out‐dated techniques in image processing, inadequate precision and inability to detect and quantify perisinusoidal fibrosis, we developed a new technique in computerized image analysis of liver biopsy sections based on Adobe Photoshop software. Methods: We prepared an experimental model of liver fibrosis involving treatment of rats with oral CCl 4 for 6 weeks. After staining liver sections with Masson's trichrome, a series of computer operations were performed including (i) reconstitution of seamless widefield images from a number of acquired fields of liver sections; (ii) image size and solution adjustment; (iii) color correction; (iv) digital selection of a specified color range representing all fibrous tissue in the image and; (v) extraction and calculation. Results: This technique is fully computerized with no manual interference at any step, and thus could be very reliable for objectively quantifying any pattern of fibrosis in liver biopsy sections and in assessing the response to antifibrotic therapy. It could also be a valuable tool in the precise assessment of antifibrotic therapy to other tissue regardless of the pattern of tissue or fibrosis.