A novel method to assess collagen architecture in skin
© Osman et al.; licensee BioMed Central Ltd. 2013
Received: 14 January 2013
Accepted: 21 August 2013
Published: 26 August 2013
Texture within biological specimens may reveal critical insights, while being very difficult to quantify. This is a particular problem in histological analysis. For example, cross-polar images of picrosirius stained skin reveal exquisite structure, allowing changes in the basketweave conformation of healthy collagen to be assessed. Existing techniques measure gross pathological changes, such as fibrosis, but are not sufficiently sensitive to detect more subtle and progressive pathological changes in the dermis, such as those seen in ageing. Moreover, screening methods for cutaneous therapeutics require accurate, unsupervised and high-throughput image analysis techniques.
By analyzing spectra of images post Gabor filtering and Fast Fourier Transform, we were able to measure subtle changes in collagen fibre orientation intractable to existing techniques. We detected the progressive loss of collagen basketweave structure in a series of chronologically aged skin samples, as well as in skin derived from a model of type 2 diabetes mellitus.
We describe a novel bioimaging approach with implications for the evaluation of pathology in a broader range of biological situations.
KeywordsFast fourier transform Gabor filter Dermis Ageing Histology Collagen Basketweave Type 2 diabetes mellitus
The skin is composed of three principle layers; an outer protective epidermal barrier comprised largely of keratinocytes; a deeper layer of connective tissue dermis that confers strength and elasticity; and an underlying energy store, the sub-cuticular fat. The dermis is primarily composed of extracellular matrix (ECM) proteins, assembled into a meshwork of primarily collagen fibres . To date, 28 different types of collagen are known, which are categorized in eight subfamilies based on function, assembly and domain homology [2, 3]. Fibrillar collagens are the major ECM component, with collagen I and IV being the predominant dermal constituents . The dermis may be further subdivided into two discrete reticular and papillary layers. The reticular dermis consists of large, mature, well-organised collagen fibres in the lower layer of the dermis, interfacing with the subcutaneous fat. The papillary dermis is adjacent to the basement membrane, with thinner collagen fibres and a distinct collagen organisation .
In a healthy state, dermal collagen forms a ‘basketweave’ structure, with perpendicular collagen fibres intersecting at approximately 90° angles [6, 7]. This basketweave structure provides textural information regarding the skin and as a loss of collagen organisation characterises many different physiological situations, including ageing [8, 9], diabetes , scarring [11-13], fibrosis  and more specific diseases of connective tissue, such as Ehlers-Danlos syndrome , thus providing methods to assess texture in biological images has direct applications within dermatological research.
The ability to quantify collagen conformation in health and disease has important consequences for basic research, drug development and clinical diagnosis. For example, techniques facilitating accurate measurement of photo-damage, scarring, wound repair or other age-related damage are of value in determining the effectiveness of collagen repair therapies. Histological stains, such as picrosirius, effectively identify collagen in tissue specimens, and one may make qualitative assessments of ECM integrity from photomicrographs. However, unbiased image analysis methods are preferable. Segmentation-based methods have been described to assess collagen bundle thickness and orientation, although a degree of user intervention is required . More sophisticated unbiased methods exploit frequency domain transformation methods, or power spectral analysis tools.
Power spectral analysis estimates the power/energy variation of an image in different frequency sub-ranges, and is directly related to the autocorrelation of an image in that it describes how closely related two points in an image are as a function of their distance and orientation. The Fourier Transform, in particular the Fast Fourier Transform (FFT), has been used to estimate the power spectrum of images, and this approach was reported by several groups in measurements of bundle thickness and spacing, as well as collagen fibre orientation [9, 11, 12, 14, 17-19].
One particular variation of this approach, the Fourier zeroth-order maximum analysis, has been used to measure the orientation of collagen fibres . This method was extensively applied to a variety of different clinical situations, including identifying fibrosis in scleroderma , evaluating new treatments for hypertrophic scars and keloids [11, 12], and assessing the effectiveness of dermal substitutes in clinical trials . Initial attempts to utilise first-order maximum Fourier analysis required substantial observer input  but this approach was refined so that the user simply selected the area of interest for analysis and a measure of collagen orientation was calculated by determining stretch or elongation of the FFT spectrum . In this way, differences in bundle thickness, spacing and orientation in scar tissue compared to normal skin were measured.
Although the methods described above identify gross collagen changes associated with pathological states, they are not sufficiently sensitive to measure incremental changes in architecture seen in, for example, the progressive loss of basketweave with chronological age. A method to facilitate the quantification of textural information is, therefore, required. Gabor filters are known for their similarity to human visual system (HVS) models in interpreting image texture as they provide a multi-channel bank of filters capable of analysing images at different narrow spatial frequencies and orientations. The link between HVS and Gabor filters was established by the pioneering work of Daugman on image analysis/compression and iris recognition [20, 21]. It has since been successfully used for texture representation, segmentation and discrimination. Therefore, we sought to build on these published methods by combining Gabor filter and Fourier transform techniques to measure collagen fibre orientation in a series of images derived from picrosirius-stained mouse skin. Polarised light microscopy clearly reveals the basketweave structure of the dermis  and by initially applying a Gabor filter in eight angles to our images before creating a Fourier spectrum, we can generate a metric for collagen structure, indicating the integrity of the collagen basketweave. This provides increased sensitivity and decreased user input which is prone to human error and bias. To test the analysis platform we have measured the effect of chronological ageing in wild-type (WT) mice and assessed dermal integrity in a mouse model of type 2 diabetes. The improved performance of the Gabor analysis in mouse skin, which is notoriously difficult to analyze compared to human skin, confirms the superior nature of this platform for dermal structure analysis.
All procedures were conducted in accordance with the UK Government Animals (Scientific Procedures) Act 1986 and approved by the University of Buckingham Ethical Review Board. C57Bl6, type 2 diabetic Lepr db /Lepr db (db/db) mice on the C57BLKS/J background and control C57BLKS/J (Misty) mice were maintained on chow diets fed ad libitum under standard conditions (BeeKay Number 1, B&K Universal Ltd, Leeds, UK). Mice were obtained from Charles River (Manston, UK) aged 5-6wk. Wild-type C57 mice were killed at 3mth, 8mth, 12mth and 20mth of age and Misty and db/db mice were killed at 6wk, 3mth, 5mth, and 6mth of age. By 12wk db/db animals were hyperglycaemic and a meaningful model of human type II diabetes. Freely fed males were used for all studies, and tissues from at least 3 animals per group were studied.
Once animals were euthanized, dorsal skin biopsies were taken immediately and snap frozen in liquid nitrogen prior to storage at −80°C until all samples were ready for simultaneous processing to minimise artefacts. Samples were transferred into cold (4°C) 10% neutral buffered formalin, then fixed for 7-8 h at room temperature. This was followed by dehydration, clearing and wax immersion in an automated tissue processor as standard. Rectangular pieces of skin were placed on their sides in moulds such that sections would be cut orthogonal to the epidermal surface, before embedding in paraffin wax. 4 μm thick sections were cut using a rotary microtome with a knife angle of 35° and a clearance angle between 1° and 5°, before transfer to positively-charged glass slides. Haematoxylin and Eosin (H&E) staining was carried out as standard to confirm tissue integrity and orientation in all samples.
Data analysis was performed using GraphPad Prism 5.0 (GraphPad Software Inc, La Jolla, CA, USA). As the data exhibited a normal distribution (as determined by the D’Aostino and Pearson omnibus normality test), two-group tests, between db/db and Misty or papillary and reticular compartments, were carried out using Students’ t-test, otherwise one-way ANOVAs followed by Dunnett’s post-hoc analysis where the ANOVA demonstrated significance were performed. Where appropriate, Pearson’s Correlation analysis was performed (p < 0.05). For all tests: * p < 0.05; ** p < 0.01; *** p < 0.001; ****p < 0.0001.
Computational method development
Fourier transformation of skin images
Fourier transformation with Gabor filtering
The imaginary impulse response of the filter has a similar formula, but the cosine is replaced with the sine function. The FFT of such a Gabor function is two-shifted Gaussians at the location of the modulating frequency ω (for more detail see ). These properties inform the combined use of a family of Gabor filters parameterised in eight directions, followed by FFTs to investigate the quantification of distortion in the basketweave pattern of collagen structure seen in ageing or pathological states.
This generates a quantitative measure of basketweave integrity. If the ellipses in all directions are equal there is less order to the basketweave and equation 4 will result in a lower value, closer to 1. However, if the basketweave is intact, there will be a disproportionate amount of collagen in the 45° + 225°, and the 135° + 315° ellipses. This will result in large differences in the Nωn values and a resulting larger orientation index value (N).
Investigation of ageing skin
By quantifying the spectra resulting from FFT images, either with or without an eight directional Gabor filter, we sought to evaluate the ability of our methodology to provide an index of collagen organisation. The collagen basketweave is known to relax from middle age in humans, and in vivo analysis of collagen orientation in murine skin via multi-photon confocal microscopy demonstrated measureable alterations in collagen structure from 6-12mth . Furthermore, age-related decreases in collagen content, ECM fibre cross-linking, and dermal depth measurements are also detectable by 12mth [25-27].
Correlation of ageing with collagen structure
−0.999 to −0.209
−0.999 to 0.284
−0.999 to −0.276
−0.370 to 0.999
−0.574 to 0.997
−0.171 to 0.999
Loss of structure in diabetic skin
Analysis of picrosirius stained skin by FFT alone showed a decrease in basketweave integrity, as defined by an increase in the Orientation Index, between 6wk and 3mth (by which time mice were hyperglycaemic). After 3mths, this analysis suggested that no further loss of structure occurred. However, no statistically significant differences in dermal integrity discriminated diabetic and lean mouse skin at any time point (Figure 5C). Application of the Gabor filter revealed a progressive loss in dermal integrity, and the degradation seen by 6mth was consistent with the loss of cutaneous integrity that one would anticipate in diabetic animals. More importantly, inclusion of the Gabor filter allowed discrimination between lean and diabetic skin structure at each time point (Figure 5D). Interestingly, Misty skin appeared to have a more ordered basketweave structure compared to the C57Bl6 mice and this unexpected strain variation is a current avenue of investigation in our laboratory.
Diabetic correlation co-efficient calculations
−0.9999 to −0.8511
−0.8481 to 0.9905
−0.6437 to 0.9964
−0.8531 to 0.9901
Image analysis techniques that exploit the frequency domain are attractive as they generate spectra informed by texture. We have developed a methodology that can quantify the organised structure or texture within images. Due to the highly-organised basketweave conformation of healthy mammalian dermis being lost or at least compromised in pathological conditions, or with chronological age, the investigation of these pathological states should be tractable to image analysis. Indeed the loss of both fibrillar collagens and the well-organised collagen structure with increasing age has long been known [8, 9, 30], and loss of collagen organization in gross pathological states such as fibrosis (as assessed by FFT methods) were previously documented [6, 13, 19, 31]. However, these are untested with respect to more subtle changes in structure (which still have many pathological sequelae). Moreover, they are also untested in mouse tissue, in which the finer collagen structure is considerably more difficult to discern than in humans. FFT-based quantification of multi-photon microscopic images of mouse dermis has been reported, but this was not designed to specifically assess basketweave, and this technology is expensive and beyond the reach of many laboratories . A wide range of therapeutic and cosmetic interventions target skin structure, texture and function, and hence tools to determine incremental changes in the integrity of the collagen basketweave are needed. These analytical tools would be particularly attractive if they could extract information from images generated by routine or inexpensive laboratory equipment, rather than electron micrographs or confocal imaging.
Simple H&E stained images are informative (particularly if eosin auto-fluorescence is exploited), but they do not reveal collagen basketweave. Cross-polar images of picrosirius-stained histological skin sections are able to reveal collagen architecture, and relevant optics are inexpensive and retro-fit to many standard microscopes. We found that by applying a FFT to cross-polar photomicrographs, we were able to quantify a shift in collagen organisation in extreme age (i.e. in skin from 20mth old mice). However, incipient collagen changes went undetected in samples from one year old mice. To improve sensitivity, we decided to deploy a Gabor filter to improve edge detection prior to application of a FFT. This yields a more complex spectrum, but by quantifying pixel distributions in four planes we were able to create a sensitive collagen orientation index. In this way, we were able to detect subtle changes in collagen that were not revealed by FFT alone. Further testing revealed that 5° rotations of the images used in this study still facilitated discrimination between biological groups, although larger rotations that take the basketweave out of phase with the Gabor filter (i.e. 20-30°) result in a loss of sensitivity (not shown). This suggests that to ensure optimal performance of the algorithm, all images should be orientated in the same plane, as far as possible. Overall, our improved method enabled us to assess subtle age-related differences in the sub-compartments of the dermis and, more importantly, to quantify collagen damage in models of diabetes.
Our improved measurement of texture and divergence from regular structure in multiple planes provides superior measurement of collagen orientation in skin and thus is widely applicable to dermatological research. In addition, the combination of the Gabor filter and FFT is likely to have utility beyond the quantification of texture in skin and biological imaging as the fundamental principle of measuring divergence from a regular shape is of wider utility across scientific and mathematical disciplines.
A fully functioning version with example images and full instructions for our analysis platform is available to download from: http://webspace.buckingham.ac.uk/klanglands/.
This work made possible by a grant from the Cotswold Trust.
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