Fri 03 Feb 2017, 10:14:17

Scientists, including one of Indian origin, have discovered a new method to predict people at risk of developing blood clots in the heart, by using a supercomputer to create patient-specific models of the organ.
The critical factor is the degree to which the mitral jet - a stream of blood shot through the mitral valve - penetrates into the left ventricle of the heart, according to researchers from Johns Hopkins University and Ohio State University in the US.
If the jet does not travel deep enough into the ventricle, it can prevent the heart from properly flushing blood from the chamber, potentially leading to clots, strokes and other dangerous consequences.
The findings were based on simulations performed using the Stampede supercomputer at the Texas Advanced Computing Centre in the US and validated using patient datawho did and did not experience post-heart attack blood clots.The metric that characterises the jet penetration, called the E-wave propagation index (EPI), can be ascertained using standard diagnostic tools and clinical procedures that are currently used to assess patient risk of clot formation, but is much more accurate than current methods.
"The beauty of the index is that it doesn't require any additional measurements," said Rajat Mittal, professor of engineering at Johns Hopkins University."It simply reformulates echocardiogram data into a new metric," Mittal said.Predicting when a patient is in danger of developing a blood clot is challenging for physicians.
Patients recovering from a heart attack are frequently given anticoagulant drugs to prevent clotting, but these drugs have adverse side-effects.
Cardiologists currently use the ejection fraction - the percentage of blood flushed from the heart with each beat - as well as a few other factors, to predict which patients are at risk of a future clot.
For healthy individuals, 55 to 70 per cent of the volume of the chamber is ejected out of the left ventricle with every heartbeat.For those with heart conditions, the ejection fraction can be reduced to as low as 15 per cent and the risk of stagnation rises dramatically.
Researchers examined detailed measurements from 13 patients and used them to construct high-fidelity, patient-specific models of the heart.The models included fluid flow, physical structures and bio-chemistry.
"Because we understood the fluid dynamics in the heart using our computational models, we reached the conclusion that the ejection fraction is not a very accurate measure of flow stasis in the left ventricle," Mittal said.
"We showed very clearly that the ejection fraction is not able to differentiate a large fraction of these patient and stratify risk, whereas this e-wave propagation index can very accurately stratify who will get a clot and who will not," he said.
Heart attacks cause some deaths; others result from blood clots, frequently the result of a heart weakened by disease or a traumatic injury. Clots can occur whenever blood remains stagnant.
Since the chambers of the heart are the largest reservoirs of blood in the body, they are the areas most at risk for generating clots."This work cannot be done by simulating a single case. Having a large enough sample size to base conclusions on was essential for this research," Mittal said.
Mittal foresees a time where doctors will perform patient-specific heart simulations routinely to determine the best course of treatment.
However, hospitals would need systems hundreds of times faster than a current desktop computer to be able to figure out a solution locally in a reasonable timeframe.In addition to establishing the new diagnostic tool for clinicians, the research helps advance new, efficient computational models that will be necessary to make patient-specific diagnostics feasible.
"These research results are an important first step to move our basic scientific understanding of the physics of how blood flows in the heart to real-time predictions and treatments for the well-being of patients," said Ronald Joslin, NSF Fluid Dynamics programme director.