A Novel Diagnostic Tool: from Structural Health Monitoring to Tissue Quality Prediction

As quality of life constantly improves, the average lifespan will continue to increase. The bad news is that tissue degradation due to wear and tear in an aged body is inevitable and is different from person to person. Fortunately recent advances in sciences and technology have enabled us to work towards personalised medicine this approach calls for a collective effort of researchers from a vast spectrum of specialised subjects. This project, by an interdisciplinary team from four different UK Universities with distinct areas of expertise, aims to predict patient-specific tissue quality which is essential in devising treatments plans. While our primary concern in this study is the bone tissue, the developed framework will apply to other tissues having porous or complex microstructure.

To achieve the aim of the project, we have to overcome a few challenges. Firstly we need better mathematical models to extract the tissue microstructure accurately and automatically and also reliable mathematical methods for comparing two different samples from either a normal image (say with 1024 x 1024 pixels) or a 3D image containing shapes and embedded complex structures. Although one would expect that existing softwares can do these tasks, the reality is that these tasks are harder than we think as the images from a realistic scan contains noise. To counter noise, we use a novel mathematical technique called the variational method that actually constructs an energy quantity involving the whole image and minimises it. In doing so, a noise-free reconstruction is obtained and the precise location of the underlying tissue is identified. This project will develop efficient and robust models to extract local features only. Similarly we can construct different energies to compare two images in the so-called co-registration problem. Our new idea is to use more mathematical approaches and less statistical estimation ideas to achieve more accuracy and robustness. The CMIT research centre at Liverpool specialises in a range of mathematical models for different problem scenarios. Secondly once imaging extracts microstructural geometry, our team from Edinburgh and Heriot-Watt will develop and use a computational mechanics approach to evaluate the tissues' material properties. Since tissue quality depends on what its microstructure looks like, answers to questions such as: is it very porous, are different solid parts poorly connected and are most of the pores aligned in the same direction, should indicate how strong the tissue is. We will examine these microstructures and then conduct range of mechanical tests on the computer so as to obtain properties that tell us when and how the tissue will get damaged or fail. We then study how the microstructural geometry relates to the mechanical behaviour. We will use a process called homogenisation that will enable prediction of properties at macro (tissue) level from knowledge of micro level. Homogenisation to predict tissue failure has not been attempted before and presents a major challenge. Finally, the predicted properties must be validated from a combination of imaging and bespoke in-vitro experimentation. The validation process, to be done in Durham, will evaluate the accuracy of our models and provide model refinements. Once validated, our methodology can be used with confidence as a tool to evaluate tissue properties straight from images.

Thus the proposed project contains both technical and advanced mathematical components and real applications in scenarios where non-invasive imaging is applicable. With imaging technology getting better, cheaper and more wide-spread, the prospects for novel applications of this work are immense.

The economic and societal impacts of our proposed research are as follows.

Economic Impact. Currently the combined cost of hospital and social care for patients with a hip fractures alone amounts to more than £1.73 billion per year. Tissue degradation due to wear and tear in an ageing population is inevitable. Understanding the progression of the disease process and the effectiveness of curative strategies are important. Providing treatments that are specific to a patient's tissue quality are becoming essential to healthcare. This study will lead to treatments optimised for specific patients. The pharmaceutical industry has huge financial investment in developing drugs that can maintain or modify tissue health. With respect to bone, the drugs work by either inhibiting bone resorption, stimulating bone formation or by a combination of mechanisms which have yet to be fully elucidated. Anti-resorption drugs (bisphosphonates) are being used extensively and have been shown to maintain bone density but result in brittle fractures. Understanding of structural and mechanical determinants of bone quality will help the pharmaceutical industry target relevant biological processes. The orthopaedic implant industries will benefit from this project in terms of extensive experimental data on ex-vivo tissues, computational simulations and scientific insights that focus in particular on how microstructural change influence tissue macroscopic biomechanical behaviour. Periprosthetic bone loss is common with total joint replacements; therefore, we expect this impact to continue to be facilitated with our long-term collaborative partners and new parties to perform proof-of-principle trials.

Societal Impact. There is considerable concern in the society with respect to morbidity and mortality associated with bone diseases. For example, UK based research has shown mortality of 18% at 3 months following a hip fracture (www.nos.org.uk). It has also been shown that patients who survive are extremely limited in their daily living activities. Use of optimum treatments will result in a lower morbidity. Recent years have seen rapid advances in imaging technologies. Image acquisition technologies are likely to further advance forward in a major way and non-invasive and harmless imaging of live tissue structures may well become a reality. There is also considerable ongoing research that aims to derive increasing amount of information using imaging methods currently employed on patients (X-rays, CT-scans). Once it becomes clear which parameters affect bone quality it may even be possible to derive this information from images obtained from currently employed techniques. This will immediately lead to new and further follow-up work along the project approaches and the work will result in a fully interactive diagnostic tool.
This study has the advantage of having several pieces of visually displayable components such as images from scans, segmented features, co-registered features, and distribution of material properties and micro-structures of tissues. We propose to develop enlarged models of bone microstructure using 3D printing systems that are now readily available. We will use these to engage the public at annual Science Festivals. We believe that these will not only raise awareness of tissue quality (and how activities such as exercise can help maintain it), but also generate interest in the community fascinated by bio-mimic systems.