Assessing Diabetes with Imaging
Diabetes and metabolic syndrome involve a range of end-organ complications. Frontline physicians have access to limited imaging data, and rely on non-specific blood and urine tests.
This project stems from an accelerating societal trend towards obesity, metabolic syndrome and diabetes, producing an epidemic of obesity-related disease, including multi-organ complications from diabetes. The surge in obesity is a healthcare priority. Over one third of the UK population, and 36% of year six children in deprived areas, have fatty liver disease. The challenge is dealing with the huge increase in incidence of the metabolic syndrome pathologies: Type 2 diabetes (T2D), fatty liver disease, steatohepatitis, heart disease and stroke.
This project concentrates on T2D, where there is dysfunction in multiple organs: pancreas, liver, spleen, kidneys, GI tract. Analysis of each organ and their combination contributes to the diagnosis. Estimated UK prevalence of T2D is 5.26%, with £8.8Bn associated direct health costs per year. In the UK, a first clinical visit for T2D typically results in Metformin and lifestyle advice, then subsequent decisions are left to the clinician, despite a multitude of options. A series of (6-monthly or yearly) follow-up visits inform the decision for dual or triple therapy in every T2D patient. Newer diabetic treatments are becoming available; but they cost 10 times more than Metformin.
There is a healthcare need to provide decision-support for clinicians, combining information from images and biomarkers, from multiple organs, to clarify recommendations for patients with (or at risk of) T2D. There is a pressing need for patient stratification, to identify the T2D patients who should be prescribed the newer, more expensive drugs and for empowerment of patients, in the form of a “health passport” of test results that patients own (similar to the “blue notes” for pregnancy or “red book” for children).
There is nothing on the market to address this growing need. The closest, by far, is Perspectum Diagnostic’s LiverMultiscan, an MRI method to stage fatty liver disease. Perspectum has developed a new MRI method, “Atlas” that in addition to the liver can quantify characteristics for each of the relevant T2D organs; pancreas, kidney, spleen, and aorta to diagnose cardiac complications. We have pilot data showing that MRI can: estimate portal hypertension (spleen); detect pancreatitis; and characterise kidney tissue. To support regulatory clearance, we will validate the technical development of “Atlas” with clinical data, both circulating biomarkers and imaging, at multiple hospital centres.
Based on the EU-funded Newcastle LITMUS programme to assess fatty liver disease, we will build a network of admitting and referring healthcare workers who treat diabetes, then develop algorithms with results made available to the GP and patients themselves depending on what they consent to, in adherence with GDPR.
The aim of this project is to better understand the impact of diabetes on different internal organs, so that we can determine which patients may benefit from different treatments. This will be achieved by collecting a database of data from patients with type 2 diabetes so that we can use advanced MRI image processing to identify patients with more advanced disease and patients with associated diseases in the liver, kidney or the heart.
- To create a databaseof 1000 patients with phenotypic mapping of organ dysfunction in type 2 diabetes.
- To determine the association of diabetes, organ involvement and future incidence of malignancy.
- To determine the association of phenotypes and future hospital admissions.
- To determine the impact of ethnicity, gender, genotype, renal function, liver inflammation, pancreatic fat and inflammation, splenic phenotype and aortic stiffness on clinical outcomes in a 1000-strong patient population who have type 2 diabetes.
- To optimise a new multi-organ protocol and associated analysis pipeline and software for multi-organ MRI, in liver, spleen, kidney, pancreas, aorta.