Synthetic electrocardiograms for Brugada syndrome: from data generation to expert cardiologists evaluation
Year: 2025
Type: article
Abstract: Aims: Synthetic electrocardiograms (ECGs) for inherited cardiac diseases may overcome the issue related to data scarcity for artificial intelligence (AI)-based algorithms. This study aimed to evaluate experienced cardiologists' ability to differentiate synthetic and real Brugada ECGs. Methods and results: A total of 2244 ECG instances (50% synthetic generated by a generative adversarial network, 50% real Brugada patients' ECGs) were evaluated by 7 cardiologists, each with >15 years of experience. All ECGs were standard 12-lead recordings acquired with identical settings (paper speed 25 mm/s, amplitude 10 mm/mV) and randomly assigned without identifying markers. The examination was blinded and conducted in 2 rounds with at least 2 h gap between rounds to assess potential learning effects and intra-rater reliability. Each physician classified the recordings as 'real' or 'synthetic' without having any additional information. Performance metrics, including accuracy, sensitivity, specificity, and intra-rater reliability (Cohen's Kappa), were analyzed. Brugada syndrome (BrS) specialists' repeated evaluations were characterized by low accuracy (first round 40%, second round 42%), specificity (first round 22%, second round 26%) and sensitivity (first round 58%, second round 58%). Intra-rater reliability varied widely (Cohen's Kappa: -0.12 to 0.80). Conclusion: Synthetic Brugada ECGs cannot be adequately distinguished from real patients' ECGs by BrS specialists.
Institutions: University of Applied Sciences and Arts of Southern Switzerland, University of Zurich, University of Bern, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Hospital Sant Joan de Déu Barcelona, Universitat de Girona, Institut de Recerca Sant Joan de Déu, St George's Hospital, St George’s University Hospitals NHS Foundation Trust, City St George's, University of London, Hospital Clínic de Barcelona, Universitat de Barcelona, IRCCS Istituto Auxologico Italiano, University of Milano-Bicocca, Tel Aviv University, Hadassah Medical Center, Ente Ospedaliero Cantonale, Istituto Cardiocentro Ticino, Università della Svizzera italiana
Language: English
Topic: ECG Monitoring and Analysis
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,725
OpenAlex ID: W4409839814