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Cardiovascular diseases are the leading cause of death globally, but an EMPIR project has provided a new tool to fight these disorders
Cardiovascular disease covers a range of disorders of the heart or blood vessels including angina and heart attacks. According to EUROSTAT over a third of all deaths in the EU each year are caused by heart disease, making it the leading cause of mortality. This takes a significant social toll and in addition the European Heart Network estimates it to cost the EU economy around 210 billion Euro a year.
One of the main tools used to identify this disease, and hence direct treatment, is cardiovascular magnetic resonance (CMR) imaging. In perfusion imaging the ‘blood support’ to the cardiac muscle through the blood vessels, is imaged via the body’s interaction with magnetic fields generated by a scanner.
CMR can produce detailed perfusion image maps, but correctly interpreting them is very much dependent on the expertise of the clinicians visually inspecting these images. A large study performed at Kings College London in the UK showed that operators of these with a low level of experience only correctly identified cardiovascular disease around 56% of the time, rising to around 66% for more experienced clinicians, and only the most experienced operators identified the correct diagnosis 86% of the time.
Now a recently completed EMPIR project Metrology for multi-modality imaging of impaired tissue perfusion (15HLT05, perfusimaging) has developed a new tool to improve the diagnosis of cardiovascular disease using these images. In a consortium including European metrology institutes (VSL, LNE, PTB, NPL) and Kings College London a new analysis software has been developed that can quantify perfusion values from the measured data and can assign an ‘uncertainty’ value to each pixel of a perfusion map using a Bayesian mathematical model.
This new software matches the signal intensity of each pixel in the image to the blood flow in that region and, using a reiterative approach, detects areas where groups of low intensity pixels cluster – indicating impaired blood flow to that region due to disease.
This means that, with the aid of the new analysis technique, a cardiovascular magnetic resonance operator with a low level of experience can make a more informed decision as the output of the analysis does not just provide a perfusion estimate but a measure of how reliable this estimate is.
Dr. Chiribiri who led the original KCL study and who has been deeply involved in the development of the software said:
”The new software tool for quantitative perfusion imaging allows an objective and reproducible assessment of the symptoms of the patients. It also enables the use of advanced imaging techniques outside academic centres, as the analysis is fully automated”.
In conjunction with an industrial partner, Kings College London is continuing to develop the analysis software for cardiovascular magnetic resonance scanners, which is now at an advanced stage with plans to integrate the software as a module directly into these devices or as a separate module that can be run on a PC or in the cloud.
The project was coordinated by Tobias Schäffter at Physikalisch-Technische Bundesanstalt (PTB), Germany:
“The development of new quantitative imaging approaches was only possible through the interdisciplinary interaction in the consortium allowing the translation new measurement and analysis techniques into clinical practice for the benefit of patients.”
This EMPIR project is co-funded by the European Union's Horizon 2020 research and innovation programme and the EMPIR Participating States.
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