Imagine if your GP or consultant were able to show you, through a computerised model of yourself, the effects of potential treatments on your body.
That’s the vision of the Institute for Biomedical Imaging and Modelling (INSIGNEO), a new research institute set up by the University of Sheffield and Sheffield Teaching Hospitals NHS Foundation Trust.
Researchers at the Institute are developing models of different parts of the human body, which will ultimately build into a complete digital replica of a patient. Medical information, from details as simple as age and weight to more complex data taken from scans and x-rays, will be fed into the models to provide an overall picture of an individual patient’s condition, against which different treatments can then be tested.
Speaking today (March 8) at a press conference to launch UK National Science and Engineering Week, Director of INSIGNEO, Professor Alejandro Frangi, of the University’s Department of Mechanical Engineering, explained:
“By developing models of complete organ systems, such as the cardiovascular system, we can help clinicians predict whether a visible narrowing in a coronary artery, for example, is significant enough to cause constriction of blood supply, and whether the patient would benefit from having a stent fitted, or not. Although it is difficult to make these kinds of predictions on visual appearance alone, clinicians are often forced to do so, and quite frequently get it wrong. We prefer to consider not just the measurement of the narrowing, but to put it in context. Diseases such as atherosclerosis, which causes hardening of the arteries, are in fact multifactorial or systemic, and our models will enable doctors to handle illnesses like that in a more holistic way.”
The researchers are working first on developing models of the cardiac and the neuro-musculo-skeletal systems.
Examples of the areas already well advanced include:
- A model of the heart’s aortic valve to help clinicians decide, in cases of heart valve failure, when a valve will need repair without the need for invasive, and often inaccurate, tests. As artificial valves have a finite lifespan, the timing of repair is crucial. The model is personalised using data on heart rate and blood flow.
- A model of a cerebral aneurysm, already being piloted with patients, supports clinicians in predicting the likelihood of rupture, when treatment is necessary and what sort of treatment will work best. The model is personalised using data taken from X-ray or MRI scans, showing the shape of the aneurysm and blood flow dynamics
- A musculo-skeletal model to help predict likelihood of bone fracture in vulnerable elderly patients based on bone density data from scans and gait analysis to show forces exerted on the bones during movement. INSIGNEO will see researchers based in the Faculty of Engineering and the Faculty of Medicine, Dentistry and Health at the University working alongside clinicians from the NHS Foundation Trust and it is this link between research and clinical practice that is crucial for its success. The initial development of new models will benefit from a rich source of anonymised patient data on a range of conditions, and the collaboration will ensure that all developments are clinically relevant and can easily transfer into practice.
Consultant Clinical Scientist and Scientific Director at Sheffield Teaching Hospitals, Professor Wendy Tindale said: “There’s a desperate need to find new technologies that can help us improve the treatments we provide to patients, but too often developments by academics never cross over into clinical practice.
“What is different about INSIGNEO is the direct link between engineers, computer scientists, clinical researchers and practising clinicians. This ensures the models we develop will be relevant to, and therefore will be used in, the clinic.”
Artist’s impressions of a GP consultation in the future, showing a virtual digital replica of a patient: https://www.dropbox.com/gallery/6591781/1/VPH?h=d8406d
For a patient’s narrative to accompany the pictures: http://dl.dropbox.com/u/6591781/Yearly%20check%20narrative.pdf
Images by Luigi Lena, © 2007-2012 STEP Consortium