Sophie Glinton

Doctoral Researcher
Physical Sciences of Imaging in the Biomedical Sciences CDT 

Thesis project - "Developing Multispectral Topographic Imaging as a Tool for Pre-clinical and Clinical Imaging of Rheumatoid Joints"

Supervisors:
Dr Amy Naylor, Institute of Inflammation and Ageing
Dr Andrew Filer, Institute of Inflammation and Ageing
Professor Ela Claridge, School of Computer Science
Dr Iain Styles, School of Computer Science

Rheumatoid Arthritis is among the most prevalent autoimmune diseases and has a devastating effect, both individually and on healthcare resources. The patients adaptive immune system irreversibly becomes intolerant to molecules present in the joints, causing chronic pain, oedema, and inflammation. It is estimated that sufferers have an average lifetime loss of 12 years, and the majority are unable to work 10 years after diagnosis.

The Rheumatoid Joint exhibits increased angiogenesis, but is conversely also known to be hypoxic. Together with oedema, these factors represent clinical markers present early in disease, but that are not comprehensively addressed by the current available imaging techniques. Imaging options available for diagnosis and assessment are X-ray images of the bone structure, ultrasound tissue imaging, and where possible, MRI. Each of these imaging modalities has disadvantages and consequently diagnosis of Rheumatoid Arthritis is mainly based on clinical criteria such as joint scoring and blood tests.

There is clear potential for the development of an optical imaging system capable of grading the level of joint inflammation, hypoxia and oedema as these features are particularly relevant to the progression of the disease. Optical imaging is a non-ionizing approach, which quick to perform, and eliminates inter-operator variation, addressing several of the disadvantages affecting current imaging techniques. This project aims to build an optical imaging system capable of producing topographic parametric maps of joints in the hands of human patients.

The method used for this project draws from 2003, Claridge et al who developed an inverse method of calculation of tissue parameters and applied it to melanomas in the skin. The algorithm returned estimations for dermal melanin, collagen and blood concentration using the information encoded within their spectra. Employing the same methodology for this project will involve two separate stages. The first will concentrate on building up a model of the spectral properties of different tissue structures. Emitted spectra from light that has permeated a tissue vary depending on the relative concentrations of scatterers and absorbers. If the variations between different tissue types can be shown to produce unique spectral signatures, the inverse process can be applied and emitted spectra can be used to determine the structure of a tissue.

The basic system set up will include a multispectral illumination source and CCD cameras for reflected and transmitted light, enclosed to block external light. Instrument control and data acquisition will be implemented using LabView. An instrument like this, capable of producing parametric maps of hypoxia, inflammation, and oedema has the potential to inform diagnosis, pick up early symptoms of RA and monitor the long-term effects of treatment.