New MRI technique spots signs of heart disease before symptoms emerge

Researchers with the University of Virginia Arlington are working to develop a new way of analyzing fat content around the heart. 

Epicardial adipose tissue is naturally present around our hearts, but in excess, it can lead to serious health risks, such as heart disease, heart failure, stroke and abnormal heartbeat. But it isn’t just the amount of fat surrounding the heart that matters—it's the type of fat as well. 

The team is developing an MRI technique that will allow them to more thoroughly analyze the composition of fat—saturated fatty acids, monounsaturated fatty acids and polyunsaturated fatty acids—surrounding the heart to identify individuals who may be at greater risk of cardiovascular complications even before they experience symptoms. In doing so, they’re hopeful that their work can lead to more proactive interventions that could slow the progression of heart disease. 

“Using this new MRI technique, we now for the very first time have the ability to know the composition of the fat that accumulates around the heart. This is important because depending on its makeup, the fat which surrounds the heart has the potential to release damaging substances directly into the heart muscle, leading to serious heart problems,” researcher Amit R. Patel, MD, a cardiologist and imaging expert at UVA Health and the University of Virginia School of Medicine, said in a release on the research. “With our ongoing research, we hope to show that we can convert the unhealthy fat which surrounds the heart to a more healthy type of fat with either diet and exercise or through the use of medications.” 

The MRI technique involves the use of a multi-echo radial gradient-echo sequence that allows for accelerated imaging of the heart. It can be captured in just one breath hold using a locally low-rank denoising technique to reconstruct undersampled images. The multi-echo images acquired are fitted with a multi-resonance complex signal model based on triglyceride characterization to map fatty acid composition. The accelerated technique helps overcome the issue of heart and lung motion during image acquisition. 

So far, the technique has been tested in the lab and in a handful of patients. The team is hopeful their technique will be further validated on larger groups of patients, ultimately leading to a better understanding of heart disease. 

“The ability to make these measurements in epicardial adipose tissue required the use of advanced computational methods that can extract the unique signature of saturated fatty acids from an overall noisy signal. Jack Echols, a biomedical engineering graduate student in my research lab, did outstanding work to develop these methods,” research leader Frederick H. Epstein, PhD, of UVA’s Department of Biomedical Engineering, added. “We’re excited to partner with cardiologists like Dr. Patel to explore clinical applications of this method and hope that this method ultimately leads to more precise treatments and better outcomes for patients with heart disease.” 

Learn more about the technique here.