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Sex-specific Virtual Heart Technologies of Electrophysiology

Sex-specific Virtual Heart Technologies of Electrophysiology

Karli Gillette (ORCID: 0000-0002-0420-5375)
  • Grant DOI 10.55776/ESP592
  • Funding program ESPRIT
  • Status ongoing
  • Start January 1, 2024
  • End December 31, 2026
  • Funding amount € 316,037
  • E-mail

Disciplines

Biology (25%); Computer Sciences (25%); Clinical Medicine (25%); Mathematics (25%)

Keywords

    Cardiac Digital Twin, 12 lead ECG, Cardiovascular Disease, Precision Medicine, Computational Cardiology

Abstract

Cardiovascular diseases remain one of the most significant health challenges in Europe, claiming numerous lives every year. The current treatments, while effective for many, often adopt a one-size-fits-all approach. This means they don`t always consider individual differences, like whether the patient is male or female, which can influence how a person responds to a treatment and how a cardiovascular disease may develop. To improve the treatment of cardiovascular diseases, virtual heart technologies are promising new tools that allow for a more personalized and tailored approach in clinical medicine. Virtual heart technologies can come in the form of both calibrated virtual heart populations or cardiac digital twins, each of which offer unique benefits. Virtual heart populations are digital heart models representing a broad spectrum of people. They are immensely valuable for research purposes to better understand disease mechanisms and can help in designing better medical devices. Cardiac digital twins, on the other hand, are personalized digital replicas of an individual heart that can provide tailored diagnostics and treatment recommendations, ensuring the best possible care for specific patients. Current virtual heart technologies, however, are limited in that they do not yet account for the anatomical and functional differences between male and female hearts. Our objective is thus to be the leaders in developing virtual heart technologies, in the form of both cardiac digital twins and virtual heart populations, that account for sex-based differences in terms of both anatomy and function. Within this project specifically, we will develop virtual heart technologies from standard clinical data that are able to account for sex-specific variations in the clinical 12 lead ECG, a standard clinical tool, during a normal healthy heartbeat. First, we will generate virtual heart populations from clinical data and apply statistical techniques to ensure they accurately replicate the real-world variability in male and female hearts. With a clear understanding of these variations, we can then create personalized cardiac digital twins that reflect an individual`s unique heart characteristics. Lastly, the overall ability of the virtual heart technologies to behave like real human hearts will be evaluated. This research is novel because it will create virtual heart technologies, in the form of both cardiac digital twins and virtual heart populations, that will be able to replicate the anatomy and function of both male and female hearts. We would thus lay the groundwork for future work in using virtual heart technologies to gather insight into how differences between men and women may influence the mechanisms and development of cardiovascular diseases, as well as to create personalized and optimal treatments clinically.

Research institution(s)
  • Medizinische Universität Graz - 100%
Project participants
  • Daniel Scherr, Medizinische Universität Graz , national collaboration partner
International project participants
  • Rob Macleod, University of Utah School of Medicine - USA
  • Steven Niederer, King´s College London - United Kingdom

Research Output

  • 2 Publications
Publications
  • 2024
    Title A computational study on the influence of antegrade accessory pathway location on the 12-lead electrocardiogram in Wolff–Parkinson–White syndrome
    DOI 10.1093/europace/euae223
    Type Journal Article
    Author Gillette K
    Journal Europace
  • 2025
    Title Quantifying anatomically-based in-silico electrocardiogram variability for cardiac digital twins
    DOI 10.1016/j.compbiomed.2025.109930
    Type Journal Article
    Author Zappon E
    Journal Computers in Biology and Medicine
    Pages 109930
    Link Publication

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