Researchers from the Johns Hopkins University School of Medicine have developed a new magnetic resonance imaging technique that enables them to predict the prognosis for heart failure patients.
In a study published online in the Science Translational Medicine, the researchers, led by Robert Weiss, M.D., a cardiologist and professor of medicine at the Johns Hopkins, showed that energy metabolism within the heart, measured by MRI, is a significant predictor of clinical outcomes.
"It is difficult to predict which people with non-ischemic heart failure will do poorly and be at a higher risk of death," Weiss said in an announcement. "Having a more precise way to determine a patient's risk would enable us to identify high-risk people earlier and tailor their treatments more specifically. And with a new target--impaired energy metabolism--we can also open the door to developing and testing new therapies for heart failure."
For the study, the researchers measured energy metabolism in the hearts of 58 patients using MR spectroscopy. They examined how ATP (adenosine triphosphate)--the energy that powers heart muscle cells--interacts with the enzyme creatine kinase (CK), which maintains a constant energy supply in the beat heart.
"We found that the rate of energy metabolism in heart muscle was significantly lower in those heart failure patients whose conditions got worse and needed hospitalization, implantation of a ventricular assist device or a heart transplant, or had died from their weakened heart," co-lead study author Paul Bottomley, a professor and director of the Division of Magnetic Resonance Research at the Johns Hopkins, said. "We believe that the rate of ATP delivery to the cells by CK can be used along with established methods to better predict heart failure events and improve the timing of intensive interventions for patients."
The researchers said this method of measuring heart metabolism could be used along with other determinants of risk to provide a more accurate prognosis in heart failure patients, which can help doctors plan a better course of treatment for those patients.
To learn more:
- here's the study's abstract
- read the announcement