Characterising the progression of normal wound repair is an important step in understand- ing the causes and consequences of pathological healing. Although normal cutaneous wound healing is commonly described as a series of discrete steps, in fact there is significant over- lap of the cellular, molecular and mechanical processes involved. Even when studying an individual aspect of the healing process, the ability to make observations and take measure- ments at high spatial and temporal resolution is hugely beneficial. Whilst this is relatively easy to implement using in vitro systems, experiments involving animal models or human participants typically collect sparse data sets that characterise healing at discrete positions in space and time. Given the financial costs and ethical considerations associated with in vivo studies, it is important to glean as much information from each experiment as possible.
A range of techniques may be implemented either to collect data at high temporal resolu- tion or to exploit sparse datasets to provide additional insights. Non-invasive imaging is a technique commonly used in the clinic to assess wound size at regular intervals during healing, whereas histology is most widely used in murine studies [33, 145]. In Chapter 2 we evaluate one such non-invasive technology in the context of murine experimental wounds, to establish whether a 3D imaging approach is suitable to make repeated measurements of mouse wounds. Mathematical models of epidermal healing, which may be used to interpo- late between sparse observational data points, providing additional insight into intermediate healing dynamics, are reviewed in Chapter 3. Whilst both continuous and discrete computa- tional representations of cutaneous healing have been implemented to study a range of repair processes, rigorous comparison of different computational systems has not been undertaken.
Therefore, in Chapter 4 we present three relatively simple models of normal epidermal repair, and investigate some of their key assumptions in detail. The use of sparse histolog- ical data to inform model formulation and parameterisation is also explored, and a novel technique for capturing a wider temporal region in a single histology image is assessed. In Chapter 5 the importance of continuous representation of not only cell and biochemical con- centrations, but their orientations in the dermis, is illustrated in a continuous model of scar tissue formation. Finally, the potential of using these three key approaches – non-invasive imaging, histological observation and mathematical modelling (Figure 1.2) – in combination to radically enhance our understanding of mammalian cutaneous healing is evaluated, and the next steps required to achieve this, are presented in Chapter 6.
Figure 1.2: An illustration of modelling approaches to wound healing. Top left: Cross section through a murine wound at 5 days post wounding; blue - DAPI; yellow - tet histone GFP; green - integrin-α6; red - Plet 1. Top right: Describing the system with either an agent or differential equation based approach. Bottom left: A schematic of the principal biological interactions. Bottom right: A typical partial differential equation description of the density of epidermal cells.
Chapter 2
An evaluation of a novel method
for murine cutaneous wound
measurement
2.1
Introduction
Characterising how wound size changes over time is a prerequisite for understanding normal skin repair and healing disorders. Wound measurement is considered a key part of clinical wound evaluation, and studies suggest that the wound healing trajectory (changes to wound size over time) may be used to monitor and predict progression towards healing, as well as to predict the effectiveness of therapeutic agents [40, 36, 37]. Research has therefore been undertaken to evaluate the wound measurement techniques available, finding that non- invasive, objective measurement strategies are preferable in clinical practice [36]. Many clinical and biomedical studies of wound healing involve creating surgical wounds of known initial size that are monitored over a time course [146, 147, 148, 34, 149, 150, 151, 33]. Objective wound measurements would therefore also be beneficial in these fields; however, limited work has been undertaken to assess the suitability of the various clinical techniques when applied to experimental wounds.
When measuring wounds, be they clinical or experimental, it is advantageous if the method employed is non-invasive, convenient, reliable and accurate [152]. For carefully controlled
cohorts of patients or experimental subjects can be analysed rapidly; for murine models in which wounds heal quickly, measurements may need to be taken daily or more frequently, necessitating a technique that is not too time consuming. Reliability requires that the method used is well-defined, produces consistent results when applied repeatedly, and that inter-operator variation is low. Finally, a successful wound measurement technique must be accurate in quantifying the size of the wound.
The sizes of experimental wounds are commonly measured using calipers [146, 147, 148, 149, 150, 151]. Whilst convenient, this technique can disrupt the wound, particularly if depth measurements are required. Two-dimensional estimations are also problematic as wound size is frequently calculated by multiplying length by width, which does not take irregular wound shapes into account [36]. This issue may be overcome by tracing the wound border onto acetate and quantifying its area by counting squares on a pre-printed grid (manual planimetry), or using digital planimetry whereby measurement of the tracing is automated [153]. Whilst more amenable to two-dimensional measurements than callipers or rulers, the planimetry technique may disrupt the wound bed during tracing. Planimetry may also be less effective for smaller wounds and highly curved surfaces, such as those found in mouse models or small experimental wounds created on human arms [152, 154].
Recently, a 3D camera system known as LifeViz was developed and tested in the contexts of pre-operative breast measurement [155], quantification of facial and dental measurements [156], assessment of skin legions and carcinomas [157], monitoring paediatric burns [158] and the measurement of experimental wounds in human trial subjects [33]. Another assessment of the agreement between measurement using the LifeViz system and digital planimetry applied the technology to paediatric burn wounds; however, these are much larger than murine experimental wounds and the study did not investigate whether measurements are replicable [159]. The clinical study used the LifeViz camera to measure excisional wounds in human trial participants, an application that is similar to murine experiments; however, data was presented describing changes to wound size over time with no investigation of the accuracy or reliability of the technique [33]. Additionally, although many wound heal- ing experiments are conducted on human patients or trial subjects, there is a large body of work using animal models to investigate healing phenomena, particularly using mice [146, 147, 148, 34, 149, 150, 54, 151]. Key differences between murine studies and clinical investigations include the smaller size of subjects and wounds, faster healing rates and ad- ditional considerations of handling when working with mice. It is therefore important that new technologies for healing assessment are assessed in the context of murine wound healing if they are to be applied to this area. This study evaluates the 3D camera system as a tool
specifically for quantifying murine wound healing, systematically assessing its invasiveness, convenience, reliability and accuracy.