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An image analysis‐based method for quantification of chronic allograft damage index parameters
Author(s) -
LAURONEN JOUNI,
HÄYRY PEKKA,
PAAVONEN TIMO
Publication year - 2006
Publication title -
apmis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.909
H-Index - 88
eISSN - 1600-0463
pISSN - 0903-4641
DOI - 10.1111/j.1600-0463.2006.apm_350.x
Subject(s) - medicine , digital image analysis , atrophy , biopsy , urology , pathology , gastroenterology , computer science , computer vision
Chronic allograft damage index (CADI) is a semi‐quantitative histopathological score that predicts renal graft outcome. We aimed to develop an objective image analysis‐based method for quantification of CADI parameters. Thirty‐five kidney transplant biopsies were visually analyzed according to the original CADI criteria, and divided into normal, mildly, moderately and severely altered groups. Digital images of the same samples were then analyzed with IPLab software. Areas of inflammation and fibrosis measured using image analysis increased simultaneously with corresponding visual scores, although the difference between non‐inflamed and mildly inflamed groups was not statistically significant. Area of normal tubuli decreased in the images of samples with visually mild/moderate tubular atrophy and tended to be even smaller in the group with severe tubular atrophy. Image analysis‐based glomerular sclerosis score increased concurrently with increasing visual score. Mesangial matrix increase score in image analysis was greater in the samples with visually mild/moderate mesangial matrix increase score compared to those with normal glomeruli, and it was highest in the group with severe mesangial matrix increase. An image analysis‐based CADI scoring of renal allograft biopsies could provide more precise data for scientific studies, and help pathologists in renal allograft biopsy scoring.