A fibre tracking algorithm for volumetric microstructural data - application to tendons

Tendons are crucial connective tissues made almost entirely of bundles of long, near-parallel collagen fibrils, and are vitally important to skeletal stability and mechanical function. Tendon structure is typically quantified in 2D, whereas, in this work, we have used serial block face-scanning electron microscopy to image tendons in 3D. We present a custom fibre tracking algorithm (FTA), with which we have characterised the 3D microstructure of tendon. Currently available tools for fibre tracing were unsuitable for tracking large numbers of fibrils and handling imaging artefacts associated with EM. We have tracked fibrils through a representative tendon volume and measured their relative length, diameter, orientation, chirality, tortuosity and volume fraction, which are just some of the measurements it is possible to make with the FTA depending on the research question. This algorithm has been developed in a general way and can be applied to a range of biological research questions relating to tendon structure-function relationships, on topics such as ageing, disease, development and injury. The FTA is also applicable to other fibrous biological materials, as well as engineered materials and textiles; it is written using Python and is freely available to download. Statement of significance We have created an algorithm for tracking fibres in 3D image stacks and applied it to tendon tissue. Previous studies have examined tendon structure in 2D, whereas we have imaged tendons in 3D using volumetric electron microscopy. Currently available fibre tracing tools could not track the large numbers of fibres or tolerate the artefacts present in biological imaging data. Using our algorithm, we have re-constructed and characterised the geometrical properties of the collagen fibrils (length, width, alignment, area, location). This algorithm could help to answer questions in biology which relate tissue microstructure to function in areas such as ageing, disease, development and injury. It could also be used to study engineered materials and textiles and is available freely to download. (c) 2022 The Author(s). Published by Elsevier Ltd on behalf of Acta Materialia Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ )