(a) How does the project fit with the Imaging, Sensing and Analysis scope of Centre?
The project is based around the concept of using Raman Spectroscopy as a method to assess the quality
of organs prior to transplantation. The sensing is the measurement of metabolic profiles in an effort to
determine signatures of organ health. The analysis is in the local, automated processing of spectra in order
to reduce their complexity and communicate their contents in a way that quickly informs clinical decision
(b) What are the key academic and industrial research questions the project aims to answer?
· What are the spectroscopic signatures of liver health that improve decision making around
diagnosis and transplantation?
· What are the key elements of signal processing that allow a complex Raman spectrum to be used
as a tool in clinical decision making?
· How can a spectroscopic device be safely integrated into a clinical work flow?
(c) Where is the novelty of the project, and in what industrial / academic context?
· Using Raman spectroscopy to assess liver quality in a transplant setting.
· Measuring Raman spectra in the liver is complicated by the high background fluorescence of liver
tissue and a novel element of this project is using advanced device designs and advanced signal
processing algorithms to allow Raman spectra to be collected with a high enough signal to noise ratio. · Integrating sensing and analysis technology with normothermic perfusion (a technology used to provide better clinical outcomes for transplantation). (d) What is the methodology to be used, and what will the student actually be doing? Working with clinical samples from the transplant surgery and measuring metabolic profiles using Raman spectroscopy and NMR spectroscopy. Comparing spectroscopic profiles with well established markers of liver health e.g. immunohistopahology and blood gas analysis. Analysing the data using multivariate techniques in order to find signatures of health that improve the efficiency of donor liver use. Working out a pathway to clinical translation which includes integration of devices into clinical work flows and automated analysis of data. (e) What makes this a doctoral thesis project rather than a shorter piece of work? The successful candidate will benefit from training in a range of areas spanning physical chemistry, signal processing and clinical practice – this is not a skill-set that can be obtained without a significant investment of time. In such a challenging, multidisciplinary project a high level of problem solving and critical thought are required in order to advance the field to a point where the research has clinical utility. The challenge of taking a sensing technology to the point at which clinical utility can be demonstrated requires a great deal of careful experimental design, statistical analysis and problem solving and will require excellence in teamworking and communication in order to pull all strands of the project together.
A Masters level degree (MChem, MEng, MPhys, MSc) at 2.1 or equivalent.
Desire to work collegiately, be involved in outreach, undertake taught and professional skills study.
An interest in healthcare technologies