An automated image processing method to quantify collagen fibre organization within cutaneous scar tissue

Standard approaches to evaluate scar formation within histological sections rely on qualitative evaluations and scoring, which limits our understanding of the remodelling process. We have recently developed an image analysis technique for the rapid quantification of fibre alignment at each pixel loc...

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Published inExperimental dermatology Vol. 24; no. 1; pp. 78 - 80
Main Authors Quinn, Kyle P., Golberg, Alexander, Broelsch, G. Felix, Khan, Saiqa, Villiger, Martin, Bouma, Brett, Austen Jr, William G., Sheridan, Robert L., Mihm Jr, Martin C., Yarmush, Martin L., Georgakoudi, Irene
Format Journal Article
LanguageEnglish
Published Denmark Blackwell Publishing Ltd 01.01.2015
Subjects
Animals
Automation
burns
Burns - metabolism
Cicatrix - pathology
collagen
Collagen - chemistry
Female
fibre alignment
image analysis
Image Processing, Computer-Assisted - methods
Pattern Recognition, Automated
Rats
Rats, Sprague-Dawley
Regeneration - physiology
scar remodelling
Trichomes - chemistry
Wound Healing
collagen
fibre alignment
image analysis
scar remodelling
burns
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Summary:Standard approaches to evaluate scar formation within histological sections rely on qualitative evaluations and scoring, which limits our understanding of the remodelling process. We have recently developed an image analysis technique for the rapid quantification of fibre alignment at each pixel location. The goal of this study was to evaluate its application for quantitatively mapping scar formation in histological sections of cutaneous burns. To this end, we utilized directional statistics to define maps of fibre density and directional variance from Masson's trichrome‐stained sections for quantifying changes in collagen organization during scar remodelling. Significant increases in collagen fibre density are detectable soon after burn injury in a rat model. Decreased fibre directional variance in the scar was also detectable between 3 weeks and 6 months after injury, indicating increasing fibre alignment. This automated analysis of fibre organization can provide objective surrogate endpoints for evaluating cutaneous wound repair and regeneration.
Bibliography:ArticleID:EXD12553
NIH - No. F32AR061933; No. R01EB007542
American Cancer Society - No. RSG-09-174-01-CCE
ark:/67375/WNG-1GR70LGM-8
istex:43E694F769CA251BB33BEF169ADA3A93B88B259C
Figure S1. Overview of the collagen analysis algorithm. Figure S2. Parametric analysis of variables used to quantify fiber density and directional variance. Figure S3. Masson's Trichrome, fiber density maps and directional variance maps from representative samples at each time point.
Shriners - No. #85120-BOS
SourceType-Other Sources-1
ObjectType-Article-2
content type line 63
ObjectType-Correspondence-1
ISSN:0906-6705
1600-0625
DOI:10.1111/exd.12553