|Courtesy of Johns Hopkins (Click to enlarge)|
The standard of care for assessing the risk of recurrent arrhythmia may be on the verge of shifting. The current approach is typically based on somewhat imprecise blood pumping measurements. But Johns Hopkins University researchers have published results showing that their 3-D virtual heart assessment tool is more accurate than that approach.
Ultimately, this could help physicians better determine which patients are at highest risk of a life-threatening arrhythmia. That would also mean a more precise indicator for determining who requires a defibrillator--a technology that's not without risks and problems that is commonly implanted when doctors fear the recurrence of a life-threatening arrhythmia.
|Natalia Trayanova, JHU professor of biomedical engineering|
"Our virtual heart test significantly outperformed several existing clinical metrics in predicting future arrhythmic events," said Natalia Trayanova, Johns Hopkins professor of biomedical engineering and lead author on the study, in a statement. "This non-invasive 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." She holds appointments at both Johns Hopkins' Whiting School of Engineering and its School of Medicine.
The research team formed predictions based on the MRI records of 41 patients who had survived a heart attack, but were left with damaged cardiac tissue that can lead to arrhythmias. Each patient had an ejection fraction measure of less than 35%; this is a measure of how much blood is being pumped out of the heart. With measurements in this range, physicians would typically recommend an implantable defibrillator. If fact, all 41 patients received the implants.
They then used MRI scans from before the patients had received the defibrillator to build patient-specific digital replicas of their hearts. The replica incorporated the electrical processes in the cardiac cells, as well as the communication among cells.
In some of the virtual cases, some developed an arrhythmia, while others didn't. These results were compared to the patient's post-defibrillator records to determine how predictive the virtual-heart arrhythmia risk predictor (VARP) had worked.
Patients who had an arrhythmia risk according to VARP were four times more likely to develop an arrhythmia than those who has tested negative. In addition, VARP predicted arrhythmia occurrence in patients four to five times better than the ejection fraction and other existing clinical risk predictors.
Now that the proof-of-concept study is complete, the researchers are working to confirm their results in larger groups of heart patients.
"We demonstrated that VARP is better than any other arrhythmia prediction method that is out there," Trayanova said. "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."