This is a curated repository of awesome Cardiac Digital Twin resources. Research and industry leverage cardiac digital twins to simulate and predict individualized responses to interventions, aid in diagnosis and treatment planning, optimize therapy strategies, and personalize patient care.
Welcome to any contribute to make the resources more complehensive for beginner!
Cardiac digital twins are personalized virtual representations combining cardiac images, ECG, and other subject-specific information [1]. CDT workflows usually involve two stages, namely anatomical and functional twinnings, as shown in Fig. 1 [2]. We also provided a short history flow about the CDT (see Fig. 2), and you can read more details about this in [5].
Here, we summarize the representative research teams and organizations in the computational cardiology and electrocardiography. Note that we may only list one PI name, but there may be more than one PI in a team/ lab. Furthermore, some amazing labs/ PIs have not included in this table as I did not find they have a official lab name.
- Living Heart Project: Dassault Systèmes (Steven M. Levine)
- John’s Digital Twin: Siemens Healthineers
- EDITH: European Virtual Human Twin
- Virtual Physiological Human (VPH) Projects: Virtual Physiological Human Institute, Belgium
- iHEART: An Integrated Heart Model for the Simulation of the Cardiac Function
- preDiCT: A major EU-funded project to make computer models of cardiac electrophysiology for drug safety prediction.
- EPSRC digital twins.
- Corify Care: A spain company focusing on changing the paradigm of treatment of atrial fibrillation patients by allowing personalised treatments.
- CardioInsight (Medtronic, USA)
- Vivo (Catheter Precision)
- EP Solutions SA
- openCARP: an open-access cardiac electrophysiology simulator.
- Life x: an open source library for high performance finite element simulations of multiphysics, multiscale and multidomain problems.
- Paper ECG Digitization Tool: allow users to upload scanned ECGs to extract the digital signals (ECG pre-processing might be required) [3].
- Chaste: an open source C++ library for computational physiology and biology [4].
- Alya: a multi-scale, multi-physics cardiac simulation code.
- ECGSIM: an interactive tool for studying the genesis of QRST waveforms [5].
- MonoAlg3D_C: an open-source high-performance GPU solver to numerically solve the monodomain equation.
- Eikonal model based ECG simulator: an open-source fast Eikonal model based simulator (check the function eikonal_ecg).
- Reaction Eikonal model based ECG simulator: an open-source fast Reaction Eikonal model based simulator.
- Chaste: Chaste (Cancer, Heart and Soft Tissue Environment) is a general purpose simulation package aimed at multi-scale, computationally demanding problems arising in biology and physiology.
- Cardioid: Cardioid is a cardiac multiscale simulation suite spanning from subcellular mechanisms up to simulations of organ-level clinical phenomena. The suite contains tools for simulating cardiac electrophysiology, cardiac mechanics, torso-ECGs, cardiac meshing and fiber generation tools.
- NeuroKit: NeuroKit2 is a user-friendly package providing easy access to advanced biosignal processing routines. Researchers and clinicians without extensive knowledge of programming or biomedical signal processing can analyze physiological data with only two lines of code.
- Thunderbolt.jl: a modular shared-memory high-performance framework for multiscale cardiac multiphysics.
- EP simulator: Basic courses of cardiac electrophysiology.
- openCARP tutorials: Basic courses of cardiac electrophysiology.
- Mathematical Matters of the Heart: written by Prof. Gary Mirams.
- EDGAR database: public dataset for the application and validation of ECGI techniques.
- MyoFit46: paired high-density surface ECGI and cardiac MRI.
- UK Biobank: paired cine MRI and 12-lead ECG data.
- Virtual cohort of four chamber heart from KCL: 24 four-chamber hearts, built from heart failure patients.
- MedalCare-XL: 16,900 healthy and pathological synthetic 12 lead ECGs obtained via ECG simulation.
- Update: Now featuring a podcast – Taking a look at Digital Twin Technology: a new frontier in personalised healthcare.
- Digital twin heart – Computer model for an optimized therapy success.
- Your Personal Virtual Heart | Natalia Trayanova | TEDxJHU.
- Heart research, AI and digital twins.
- Personalized Cardiology Powered by AI and Computational Modeling - Prof Natalia Trayanova (JHU)
- A mathematical microscope for non-invasive heart diagnostics
- 31 Mar, 2023: Virtual You: how digital twins will transform medicine
- 4 Feb, 2019: FDA approved clinical trial for the utility of computer simulations driving atrial ablation procedure
- 17 Sep, 2015: Personalized heart models for surgical planning
[1]: Corral-Acero, Jorge, et al. "The ‘Digital Twin’to enable the vision of precision cardiology." European heart journal 41.48 (2020): 4556-4564. link
[2]: Li, Lei, et al. "Towards Enabling Cardiac Digital Twins of Myocardial Infarction Using Deep Computational Models for Inverse Inference." IEEE Transactions on Medical Imaging (2024). link
[3]: Wu, Huiyi, et al. "A fully-automated paper ECG digitisation algorithm using deep learning." Scientific Reports 12.1 (2022): 20963. link
[4]: Mirams, Gary R., et al. "Chaste: an open source C++ library for computational physiology and biology." PLoS computational biology 9.3 (2013): e1002970. link
[5]: Van Oosterom, Allan, and T. F. Oostendorp. "ECGSIM: an interactive tool for studying the genesis of QRST waveforms." Heart 90.2 (2004): 165-168. link
[6]: Li, Lei, et al. Solving the Inverse Problem of Electrocardiography for Cardiac Digital Twins: A Survey, IEEE Reviews in Biomedical Engineering (2024). link