Diagnostics Development Unit (DDU)
Integrated Non-Invasive Diagnosis
An overview of the project can be downloaded here (pdf 1MB).
This project is a collaboration between Medicine, Spcace Science and Atmospheric Chemistry at the University of Leicester. We focus on diagnosis in emergency care - an area of medicine where there is often not time to use conventional diagnostic methods and clinical decisions about treatment have to be made without the doctor having the full information about the patient's condition.
The non-invasive detection of disease. Correlation of measurements with traditional diagnosis, leading to derivation of disease symptoms and leading to bespoke 'Point of Care' devices.
Because invasive measurement/monitoring can be unpleasant, can lead to complications, infection and possible exposure to radiation. False positives and negatives can be produced and is conventional diagnostics can be time consuming with some results not being available for several days.
Will utilise the smell of disease, the look of disease and feeling the “pulse” using state of the art instrumentation installed in a resuscitation bay in the Emergency Department.
We provide a facility in which novel diagnostic and monitoring devices can be developed and tested. A large volume of patients with diverse medical conditions are available, as well as a large volume of ‘normals’. The facility will be available for clinical testing for Industry.
Located in the Accident and Emergency Department at Leicester Royal Infirmary the DDU provides an immediate adjacency between the instrument room (left of picture) and a resuscitation bay (right of picture).
A series of ports through the wall allow cables and tubes to pass from the instruments to the patient, but with maintainance of separation between the clinical and equipment areas. Data cabling links USB and data points each side of the wall.
Research studies can be carried out without interfering with normal clinical care, as the patient remains in a resuscitation area during monitoring. This also means that all severities of patient (from minor injuries to major illness) can be studied. Last year there were more than 150 000 patients treated in the Emergency Department - so almost all types of illness and injury can be studied.
It is a University inter-college project between Cardiovascular Sciences, Emergency Medicine, Infection, Immunity and Inflammation, Chemistry, Physics and Astronomy, Space Research Centre, and IT services.
Is it possible to build the equivalent of a ‘Star Trek’ style Medical Tricorder, or a series of them for different medical needs! Start by building “the medical bed in sick bay”.
- IR Imager: temperature distribution
- UV-VIS-NIR Spectrometers
- Hyper spectral imager (2nm resolution): spectral features, patient pallor
- Context Colour Imager
Breath and Other Gas Phase Analysis
- Mass Spectrometer and Spirometer: composition and volume
- Nitric Oxide Analyser
- Micro-cantilever polymer based detector (gas and fluid)
Body State via
- Thoracic Impedance Monitor
- Blood Flow Monitor
- Oxygenation Monitor
The Data Analysis Challenge
The data from the various instrumentation will be collected and archived in the form of derived and, where appropriate, raw data. Each instrument can be used in isolation, however, it is believed that in combination the data will allow, in principle, a disease/ metabolic state pheno-typing. The large amount of data will need a combined algorithm analysis and bio-informatics approach along with application of data mining techniques. The data from the instrumentation will be compared with data from conventional diagnostic methods to attempt to
derive non-invasive diagnostic markers of the disease state(s) under investigation. This project is looked upon as a long term project will full capability not achieved until after 3-5 years from initial commissioning in the clinical environment.
In the case that disease/metabolic phenotyping is not possible due to practical considerations such as obtaining data form real patients and variations between patients the individual instruments and instrumentation packages will produce data of clinical value.