Technology already developed at the University of Houston could lead to the early detection of heart attack risk. Researchers in computational medicine have found a way to possibly prevent some heart attacks.
Heart attacks can affect even the most active and athletic people. It’s estimated that about ten percent of the otherwise healthy population are vulnerable to heart attacks. University of Houston Computer Science Professor Ioannis Kakadiaris says that vulnerable population isn’t affected by clogged arteries, but by plaque in the blood vessels.
“The majority of the heart attacks are caused not by the gradual narrowing of the arteries, but some structures that are called plaques. And these plaques are nothing else but build-ups of cholesterol and fatty deposits in areas of the artery. Though most of the individuals will live many years with some plaques, the ones that we are examining are the ones that are unstable, inflamed and close to rupturing.”
When those plaque areas rupture, blood rushes to that part of the vessel, causing a blockage and subsequent heart attack. Doctors know that in areas of inflamed blood vessels, small arteries called vasa vasorum tend to grow and multiply. But there is currently no way to detect increased growth of vasa vasorum in the vessels. But Kakadiaris’ developed a method of using pre-existing ultrasound technology to detect the growth of vasa vasorum. A standard vascular ultrasound device is inserted into the vessels and tiny saline bubbles are injected into the vessel.
“We can see not only the structure of the vessel, but also activity in the vessel. We can see inflammation. What’s happening is, by injecting contrast agent, these nano-sized bubbles that find their way into the so-called vasa vasorum, that’s the small vessels that surround the plaque area, we can find out which areas of the plaque have new vessels formed.”
If doctors can detect new vasa vasorum, they can determine the level of risk to a patient and take preventive measures like placing a stent within the vulnerable vessel. Kakadiaris says this detection method has the potential to significantly impact cardiology. There’s also a further benefit to his graduate students.
“We are preparing a new breed of scientist that not only understands the concept of computer science, but they are well-versed on the medical problems, anatomy and physiology and they are able to apply their mathematical skills and their computer science skills to problems that have the potential of altering the people’s life.”
This detection method has already been tested in humans in Europe. In the US, human clinical trials are pending.