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News Center
Digital Heart Twin Improves Diagnosis and Treatment of Cardiac Arrhythmias
Millions of individuals around the globe suffer from cardiac arrhythmias. Traditionally, electrocardiography (ECG) has been used to detect premature ventricular contractions (PVCs), one of the most common types of arrhythmias. However, the accuracy of this method can be limited by anatomical variations among patients. Accurately identifying and treating cardiac arrhythmias continues to present significant challenges in cardiovascular medicine. Now, a collaboration between Spanish and German researchers and clinicians has introduced a new non-invasive technique to pinpoint the origin of PVCs. This innovative method combines electrocardiographic imaging (ECGI) with digital twins of the heart, significantly enhancing the precision with which the origin of these arrhythmias can be identified.
Developed by researchers at Valencia Polytechnic University (UPV, Valencia, Spain) which belongs to the COR-ITACA group, the system integrates ECGI with personalized heart simulations. To develop the new approach, the research team built a comprehensive database with over 600 simulations of cardiac arrhythmias, utilizing detailed anatomical models of both the torso and heart. From these simulations, they developed an algorithm that accurately identifies the arrhythmia focus, achieving an average accuracy of 7.8 mm, a significant improvement over the more than 30 mm error typically observed with conventional ECGI, all in a non-invasive manner. Additionally, the method was applied to a real clinical case involving a patient with an arrhythmia localized in the free wall of the left ventricle. Published in Computers in Biology and Medicine, the study demonstrated that the ECGI-based model combined with digital twins reduced the focus estimation error to 15.5 mm, well below the 36.7 mm error found with standard ECGI.
These results were shared at the EHRA 2025 Congress (European Heart Rhythm Association), one of Europe’s most prominent events on cardiac arrhythmias, held in Vienna, Austria. The COR-ITACA group at UPV is now leading a new project, EPICA+, which aims to expand this method to address a broader range of arrhythmias and implement it in clinical practice. The project will integrate ECGI with artificial intelligence (AI) and digital heart twins, bringing together a multidisciplinary team of engineers, clinicians, and data scientists. The team will leverage a database of over 1,000 patients and 20,000 computational models, with clinical trials involving 144 patients to validate the technology. The goal of the EPICA+ project is to improve treatment success rates and reduce costs by enhancing the precision of arrhythmia diagnosis and treatment.
"Our method can facilitate planning interventions, such as catheter ablation, by reducing the need for invasive scans and shortening intervention times,” said researcher Jorge Sánchez. “It could be integrated as a support tool in the preoperative planning of ablations. And it would be especially useful in complex cases where other techniques are more limited, such as in arrhythmias originating in the septum or at the base of the ventricle.”
http://www.comcn021.com/en/index.asp
