Coherency image analysis to quantify collagen architecture: implications in scar assessment

Tristan Clemons, Michael Bradshaw, Priyanka Toshniwal, Nutan Chaudhari, Andrew Stevenson, Jessica Lynch, Mark Fear, Fiona Wood, Killugudi Swaminatha Iyer

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)


An important histological difference between normal, uninjured dermis and scar tissue such as that found in keloid scars is the pattern (morphological architecture) in which the collagen is deposited and arranged. In the uninjured dermis, collagen bundle architecture appears randomly organized (or in a basket weave formation), whereas in pathological conditions such as keloid scar tissue, collagen bundles are often found in whorls or in a hypotrophic scar collagen is more densely packed in a parallel configuration. In the case of skin, a scar disables the dermis, leaving it weaker, stiff and with a loss of optimal functionality. The absence of objective and quantifiable assessments of collagen orientation is a major bottleneck in monitoring progression of scar therapeutics. In this article, a novel quantitative approach for analyzing collagen orientation is reported. The methodology is demonstrated using collagen produced by cells in a model scar environment and examines collagen remodeling post-TGFβ stimulation in vitro. The method is shown to be reliable and effective in identifying significant coherency differences in the collagen deposited by human keloid scar cells. The technique is also compared for analysing collagen architecture in rat sections of normal, scarred skin and tendon tissue. Results demonstrate that the proposed computational method provides a fast and robust way of analyzing collagen orientation in a manner surpassing existing methods. This study establishes this methodology as a preliminary means of monitoring in vitro and in tissue treatment modalities which are expected to alter collagen morphology.
Original languageEnglish
Pages (from-to)9661-9669
Number of pages9
JournalRSC Advances
Issue number18
Publication statusPublished - 2018


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