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

Abstract

Additional supporting data may be found in the supplementary information of this article.Data S1. Purified mIL-31 from culture supernatants from transfected Free Style 293 cells was glycosylated. Western blotting analysis with Anti-H6 antibody or anti-IL-31 rabbit polyclonal antibodies showed the same staining pattern, although western blotting analysis is a semi-quantitative assay. Taken together, these results suggested that this purification method excluded most contaminants other than IL-31. Abstract: 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 trichromestained 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.

Rapid three-dimensional quantification of voxel-wise collagen fiber orientation

“…The local directional variance of orientation values within specific regions of an image, such as the ECM surrounding an epithelial structure, is an example of such a biomarker. We have previously found the collagen fiber directional variance defined within 2D images to be a useful metric in understanding the matrix's role in breast epithelial morphogenesis [33] and in localizing burn wounds [34]. By acquiring 3D orientation information, such assessments can be easily extended to the analysis of 3D image stacks, which provide a more thorough and accurate representation of cell-matrix interactions than 2D images.…”

“…As a result, pixel-specific fiber orientation information can be provided faster than pixel-wise Fourier analysis with comparable accuracy by an order of magnitude. This technique has been successfully applied for studying interactions between the matrix and human breast cells [33], and mapping scar formation in histological tissue sections [34,35]. Compared to edge detection algorithms that have been developed for rapidly detecting fiber orientation in micrographs, such as algorithms based on Sobel or Canny operators [36][37][38], this technique has improved accuracy.…”

Quantitative differentiation of normal and scarred tissues using second‐harmonic generation microscopy

“…In a parallel effort, we have developed an algorithm to rapidly and accurately detect fiber orientation (Quinn and Georgakoudi, 2013) and applied it to quantify fiber organization in cutaneous scar tissue (Quinn et al ., 2015). For the fiber density calculations, we select appropriate intensity thresholds determined by the Otsu’s method, which calculates the optimal threshold intensity by dividing the signal and background values so that their combined variance is minimal (Otsu, ’79; Provenzano et al ., 2006; D’Amore et al ., 2010).…”

Substrate modulus of 3D-printed scaffolds regulates the regenerative response in subcutaneous implants through the macrophage phenotype and Wnt signaling

“…In addition, expression of both types I and III collagen ( Col1A1 and Col3A1 ) measured by qRTPCR correlated with the histological findings, in which both Col1A1 and Col3A1 expression were greatest in 3D-24 scaffolds (Figure 3B-C). To compare differences in scarring between groups, the alignment of fibroblasts and deposited collagen fibers was evaluated as previously described [42]. Both quantitative (Figure 3D) and qualitative (Figure 3E) data illustrate alignment of the cells and extracellular matrix for each of the treatment groups.…”