Enabling a quantitative approach to cardiovascular disease diagnostics

Challenge

Over a third of all deaths in the EU are caused by disorders of the heart or blood vessels collectively described as cardiovascular disease (CVD), making it the leading cause of mortality. As well as the significant social toll, CVD is also estimated to cost the EU economy around €210 billion a year. The current ‘gold standard’ method to diagnose CVD, and hence direct appropriate treatment, is through measuring the blood flow or ‘perfusion’ in affected organs and tissue using Positron Emission Tomography (PET). In this technique a radionuclide is injected into a patient and the perfusion monitored using a PET scanner. From this scan, an image or cardiac perfusion map is derived which is used to make clinical decisions. The assessment of PET perfusion is usually performed quantitatively using specific cut-off thresholds by visual inspection or by describing the image intensity, however the measurement uncertainties affecting the perfusion values are not taken into account in the interpretation of the perfusion images. The expertise of the clinicians interpreting image maps can also add an additional source of error. This can lead to significant variation in results using the imaging technique applied at different centres or between this and alternative imaging techniques. In clinical practice, these factors can lead to false diagnoses, patient distress and unnecessary treatments.