18F-Sodium Fluoride (18F-NaF) PET-CT Imaging to Identify Vulnerable Plaques in Patients With Diabetes

Overview

Coronary artery calcification is a sign of heart disease. A nuclear medicine PET-CT test using sodium fluoride (18F-NaF) radioisotope has been shown to help identify growing calcification plaques early on in the disease process. It is known that diabetic patients are at a high risk of developing premature coronary disease; the investigators intend to use this new technology to identify those patients at higher risk of developing coronary artery disease.

Diabetic patients are at very high risk of suffering premature coronary artery disease events compared to the general population. Whether pancreas transplant completely reverses the biochemical imbalances of diabetes mellitus and the high cardiovascular risk of these patients is unclear. Investigators in the field of imaging have been looking for ways to identify patients at greater risk of suffering events by searching for plaques in the cardiovascular system more likely to fracture and cause acute intravascular thrombosis (vulnerable plaques) with subsequent precipitation of acute events. Recent advances in PET-CT provide an opportunity to pursue such search with limited risk to the patient and high probability of success. CT scanning is used to identify vascular calcification -a marker of atherosclerosis- and PET imaging with 18F-NaF helps determine whether the calcification is actively accumulating calcium and phosphorus making it an actively growing plaque. PET imaging with 18F-NaF has been used in the setting of acute coronary syndromes to identify the most active and unstable plaques and in patients with severe aortic valve stenosis to follow the natural history of this disease. The investigators propose to perform PET-CT imaging with 18F-NaF in a pilot study of 100 patients chosen among the subjects followed in the outpatient diabetes clinics at the University of Alberta. The aim is to investigate the presence and extent of unstable plaques in ambulatory patients affected by diabetes, and to identify a set of clinical variables most likely to be associated with a large burden of disease. Since there are no published studies in this particular field it is impossible to make precise sample size calculations and these analyses must therefore be considered exploratory.

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