Patients at risk of having cardiac arrhythmias are often hard to identify, but to accurately decide whether to implant a cardioverter defibrillator can mean the difference between life and death. Implanting everyone suspected of potentially getting an arrhythmia is not particularly effective, expensive, and introduces new side effects and limitations for patients. Now researchers at Johns Hopkins University have developed computer models of real patient hearts that can predict chances of sudden cardiac death due to potential arrhythmias in order to help cardiologists decide whether to prescribe an implantable cardioverter defibrillator.
The retrospective proof-of-concept study involved data obtained from MRI scans of patient hearts soon after they suffered heart attacks. The data was used to create computer models of the patient hearts which were then made to beat in-silico, including exhibiting the electrical signals and connections that exist in real hearts.
The researchers showed that their models were considerably better at predicting outcomes than the commonly used ejection fracture measurement that estimates the amount of blood pushed out of the heart.
Study in Nature Communications: Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models…
Source: Johns Hopkins…