Examples of how the 3-D computer model would classify one patient at high risk for heart arrhythmia and another at low risk. [Johns Hopkins University]
Examples of how the 3-D computer model would classify one patient at high risk for heart arrhythmia and another at low risk. [Johns Hopkins University]

Implanting a small electrical defibrillation device near the heart to sense the onset of arrhythmia and jolt the heart back to a normal sinus rhythm can often be the difference between life and death for many cardiac patients. However, this invasive and costly technique does not come without its own set of health risks. Moreover, physicians are always questioning which patients truly need the device, as well as searching for the most optimal methodology to determine defibrillator candidates.

Now, an interdisciplinary team of researchers from Johns Hopkins University has developed a noninvasive 3-D virtual heart assessment tool to help doctors determine whether a particular patient faces the highest risk of a life-threatening arrhythmia and would benefit most from a defibrillator implant. Results from this new study showed that the digital approach yielded more accurate predictions than the imprecise blood pumping measurement now used by most physicians. 

“Our virtual heart test significantly outperformed several existing clinical metrics in predicting future arrhythmic events,” explained senior study author Natalia Trayanova, Ph.D., professor in the Department of Biomedical Engineering and Institute for Computational Medicine at Johns Hopkins University. “This noninvasive and personalized virtual heart risk assessment could help prevent sudden cardiac deaths and allow patients who are not at risk to avoid unnecessary defibrillator implantations.”

Dr. Trayanova and her colleagues assembled their results by using the distinctive magnetic resonance imaging (MRI) records of patients who had survived a heart attack but were left with damaged cardiac tissue that predisposes the heart to deadly arrhythmias. This blinded study involved data from 41 patients who had survived a heart attack and had an ejection fraction—a measure of how much blood is being pumped out of the heart—of less than 35%.

To protect against future arrhythmias, physicians typically recommend implantable defibrillators for all patients in this range—with all 41 patients in the study having received the implants because of their ejection fraction scores. But recent research has concluded that this score is a flawed measure for predicting which patients face a high risk of sudden cardiac death.

The findings from this study were published recently in Nature Communications in an article entitled “Arrhythmia Risk Stratification of Patients after Myocardial Infarction Using Personalized Heart Models.”

The Hopkins team postulated an alternative to these scores by using preimplant MRI scans of the recipients' hearts to build patient-specific digital replicas of the organs. Using computer-modeling techniques, the geometrical model of each patient's heart was assembled by incorporating representations of the electrical processes in the cardiac cells and the communication among cells. In some cases, the virtual heart developed an arrhythmia, and in others it did not.

The end result was a noninvasive way to gauge the risk of sudden cardiac death due to arrhythmia, dubbed VARP, for virtual-heart arrhythmia risk predictor. The method allowed the researchers to factor in the geometry of the patient's heart, the way electrical waves move through it, and the impact of scar tissue left by the earlier heart attack.

The new VARP results were compared to the defibrillator recipients' postimplantation records to determine how well the technology predicted which patients would experience the life-threatening arrhythmias that were detected and halted by their implanted devices. Patients who tested positive for arrhythmia risk by VARP were four times more likely to develop arrhythmia than those who tested negative. Furthermore, VARP predicted arrhythmia occurrence in patients four to five times better than the ejection fraction and other existing clinical risk predictors, both noninvasive and invasive.

“We demonstrated that VARP is better than any other arrhythmia prediction method that is out there,” Dr. Trayanova noted. “By accurately predicting which patients are at risk of sudden cardiac death, the VARP approach will provide the doctors with a tool to identify those patients who truly need the costly implantable device and those for whom the device would not provide any life-saving benefits.”

The researchers were excited by these early results and felt that further studies and a more nuanced VARP technique could be a useful alternative to the one-size-fits-all ejection fraction score.

“This is a ground-breaking proof-of-concept study for several reasons,” stated co-author Katherine Wu, M.D., associate professor in the Johns Hopkins School of Medicine. “As cardiologists, we obtain copious amounts of data about patients, particularly high-tech imaging data, but ultimately we use little of that information for individualized care. With the technique used in this study, we were able to create a personalized, highly detailed virtual 3-D heart, based on the patient's particular anatomy. Then, we were able to test the heart virtually to see how irritable it is under certain situations.”

Dr. Wu concluded by stating that “we could do all this without requiring the patient to undergo an invasive procedure. This represents a safer, more comprehensive, and individualized approach to sudden cardiac death risk assessment.”








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