Imaging, such as positron emission tomography (PET) and echocardiography, is vital for diagnosing heart disease, but it can also be used in new ways to assess the progress of disease or treatment.
Tracking the Impact of Diabetes with PET
James Haley, a master’s candidate at the Heart Institute, presented work with a PET tracer that allowed his team to track how insulin treatment altered expression of a cellular receptor called the beta-adrenoceptor (beta-AR) in diabetic rats. Reductions in beta-AR expression are thought to contribute to the development of heart failure in diabetic patients.
The researchers found that diabetic rats had reduced tracer binding in all regions of the heart. After early insulin treatment, the tracer showed recovery of expression of two receptor subtypes affected by diabetes. Late insulin treatment recovered expression of only one of the two subtypes. A PET tracer such as this could potentially be used to track beta-AR expression in diabetic patients while under beta blocker therapy to control it.
Imaging High-Risk Carotid Plaques
In research that was runner-up for the CCC Trainee Research Award in clinical science, Myra Cocker, a post-doctoral researcher at the Heart Institute, tested whether a PET tracer could be used to measure inflammation and other immune system activity within plaques in the carotid artery.
She and her colleagues found that tracer uptake is related to the extent of inflammatory response within the plaques, as evaluated in patients after surgery. This imaging technique could possibly be used to non-invasively identify patients with carotid plaques at high risk of rupture and other adverse events.
Assessing Valve Function with 3-D Echo
Dr. Benjamin Sohmer, a cardiac anesthesiologist at the Heart Institute, demonstrated a novel way to determine how well an aortic valve’s leaflets come together (coaptation surface area), a measure of valve function for assessing whether a valve should be replaced.
Using its new 3-D transesophageal echocardiography procedure, the team was able to correctly determine the level of valve dysfunction in patients with either normal valves or moderate to severely dysfunctional valves. The next step will examine whether the technique can predict successful valve repair.