Using a new computer model that simulates damaged heart tissue, a Johns Hopkins University undergraduate and his faculty advisors are refining a testing method that may give doctors a better tool for detecting coronary artery disease before a heart attack occurs. Their computer simulation has confirmed earlier findings that coronary artery disease causes irregular electrical activation of the cardiac muscle. If an electrocardiogram (ECG) can detect such irregularities, the researchers say, doctors will know that a patient needs treatment to prevent permanent heart damage.
The research focuses on a condition called myocardial ischemia, which occurs when heart tissue receives insufficient blood and begins to weaken. A conventional ECG test looks at the electrical activity of the entire heart and may not always detect ischemia. Specifically, a conventional ECG can miss small-scale changes such as the ones caused by ischemia during cardiac activation. These changes might be earlier signs and better markers of cardiac disease than the existing ones, but to detect them, an additional examination method is needed.
With this in mind, Mahesh Shenai, a 22-year-old senior from Bloomfield Hills, Mich., adapted a modern mathematical recipe and used it to monitor the electrical activity within modeled heart tissue to identify and locate patches of diseased cells. Shenai is lead author of an article describing these findings in the December 1999 issue of the Journal of Biological Systems. His co-authors are two Johns Hopkins faculty members who supervised his research: Boris Gramatikov, a research associate in the Department of Biomedical Engineering, and Nitish V. Thakor, a professor in the department.
"The whole idea is to detect the ischemia prior to the point where the damage is irreversible," said Shenai, who is pursuing a combined B.S.-M.S.E degree in biomedical engineering. "If it's detected early enough, proper intervention steps such as drug therapy, an angioplasty or cardiac bypass surgery can be taken to restore the heart to a healthy condition."
Further research and development is needed before these findings can be incorporated into clinical practice for use in emergency room examinations and long-term monitoring of heart disease patients. But Shenai's work is an important step toward that goal, his advisors say.
"A regular ECG doesn't always detect signs of ischemia," added Gramatikov. "So a patient may come to an emergency room with chest pains and then be sent home. But one in 20 of those who are sent home will develop a heart attack. So any new tools we can provide to identify heart problems at an early stage could have some impact."
Gramitkov said the research represented a strong effort by Shenai. "He's a very capable student and a very hard-working one," the faculty member said. "That's a good combination."
Shenai started with an existing computer model of a slab of healthy human heart tissue. "By manipulating the parameters," he said, "I was able to mimic patches of cells suffering from ischemia within the slab." The student researcher then measured the electrical activity within the model tissue slab and processed the results with a math recipe called the Wavelet Transform. Using the Wavelet allowed him to obtain a more refined analysis of the ECG signal and attribute the ECG changes to what was happening at the cellular level. This revealed which portions of the slab were diseased.
Shenai and his colleagues have begun following up by testing the technique on living tissue in the lab. The researchers also have applied their methods to ECGs from patients undergoing angioplasty. Ultimately, they hope to show that the new method can be used safely and accurately to detect early signs of heart disease in human patients.
Shenai's research was supported by a Provost's Undergraduate Research Award, given to selected Johns Hopkins undergraduates, and a Howard Hughes Fellowship.
Color Photos of Shenai and Gramatikov available; contact Phil Sneiderman
The above post is reprinted from materials provided by Johns Hopkins University. Note: Materials may be edited for content and length.
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