Innovative Digital Twin Technology Enhances Cardiac Arrhythmia Management

Cardiac arrhythmias affect millions globally, with over a million cases reported in Spain alone. The challenge of accurately diagnosing and treating these conditions has long posed difficulties for cardiovascular medicine.

A team from the Universitat Politècnica de València (UPV), part of the COR-ITACA group, has developed a groundbreaking non-invasive technique to pinpoint the sources of premature ventricular contractions (PVCs), one of the most common types of arrhythmias. This innovative approach integrates electrocardiographic imaging (ECGI) with digital twin technology, significantly improving the identification of arrhythmia origins.

The development of this method involved collaboration with various institutions, including the Gregorio Marañón General University Hospital, Corify Care S.L., Complutense University of Madrid, Autonomous University of Barcelona, the Center for Biomedical Research Network in Cardiovascular Diseases (CIBERCV), and the Institute of Biomedical Engineering at Karlsruhe Institute of Technology in Germany. The findings of this research were published in the journal Computers in Biology and Medicine.

Next week, the COR-ITACA team alongside Corify Care will present their findings at the European Heart Rhythm Association (EHRA) 2025 Congress.

Traditionally, PVCs are detected using standard electrocardiography (ECG), which can be limited by individual anatomical differences. According to the UPV team, while ECGI offers more detailed insights, it still struggles to accurately determine the precise origin of arrhythmias. The newly developed method addresses this limitation.

Researchers have created a 'digital twin' of the heart that more accurately replicates the electrical activities of the myocardium. This digital twin is built upon a database comprising over 600 simulations of cardiac arrhythmias, using intricate anatomical models of the torso and heart. An algorithm developed from these simulations allows for the localization of arrhythmia sources with an average accuracy of 7.8 mm, a significant improvement over the 30 mm error margin typically associated with conventional ECGI.

In clinical applications, the method was tested on a patient with an arrhythmia manifesting in the left ventricle's free wall. The digital twin model yielded an estimation error of 15.5 mm, considerably lower than the 36.7 mm error noted with standard ECGI.

This advancement could streamline procedures such as catheter ablation by minimizing invasive scans and reducing intervention durations. It may serve as a valuable tool in preoperative planning for ablation procedures, especially in complex cases where traditional techniques may fall short, such as arrhythmias originating from the septum or ventricle base.

The COR-ITACA group is also spearheading a new initiative named EPICA+, aiming to broaden the application of this method to various other arrhythmias and enhance its clinical use. The project seeks to merge ECGI with artificial intelligence and digital heart twins, enhancing the diagnosis and treatment of cardiac arrhythmias.

EPICA+ brings together a multidisciplinary team of engineers, clinicians, and data scientists, leveraging a database of over 1,000 patients and 20,000 computational models. Clinical trials with 144 patients will test the technology, striving to double the success rates of treatments while reducing costs.

This project signifies a pivotal advancement in Spanish research, addressing a critical issue in cardiovascular medicine and demonstrating how the integration of advanced technologies like artificial intelligence and computational modeling can enhance healthcare outcomes.