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Upcoming Cardiovascular Grand Rounds Lectures 2021

Upcoming Cardiovascular Grand Rounds Lectures 2021

29 November 2021

3 December - Lucio Barile

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Sophie van de Walle winner Harry Crijns research Grant

Sophie van de Walle winner Harry Crijns research Grant

25 November 2021

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Carim Maastricht
Carim Maastricht

Aurore Lyon

Post doc

Dr Aurore Lyon graduated from Telecom ParisTech Engineering School in Paris (France) with a Master in Engineering, and from the University of Oxford (UK) with a Master in Computer Science. She obtained her PhD at the Department of Computer Science at the University of Oxford, working in the Computational Cardiovascular Science group. Her PhD focussed on using computational techniques for analysis, modelling and simulation of ECG signals for patient risk stratification in hypertrophic cardiomyopathy.

Since April 2018, she has been working at Maastricht University. Her current research focusses on cardiac electromechanics and the coupling from cellular electrophysiology to whole-heart mechanics and hemodynamics. Specific projects of research include electromechanical modelling, effect of exercise on cardiac pathologies such as ARVC or deformation imaging analysis in atrial fibrillation patients. Her interests lie in combining computer simulations with clinical data to better understand cardiac physiology (e.g. exercise) or disease mechanisms (e.g. arrhythmia).

 

Aurore-lyon

Department of Biomedical Engineering
Universiteitssingel 50, 6229 ER Maastricht
PO Box 616, 6200 MD Maastricht
Room number: H3.348

  • 2021
    • van Osta, N., Kirkels, F. P., van Loon, T., Koopsen, T., Lyon, A., Meiburg, R., Huberts, W., Cramer, M. J., Delhaas, T., Haugaa, K. H., Teske, A. J., & Lumens, J. (2021). Uncertainty Quantification of Regional Cardiac Tissue Properties in Arrhythmogenic Cardiomyopathy Using Adaptive Multiple Importance Sampling. Frontiers in physiology, 12, [738926]. https://doi.org/10.3389/fphys.2021.738926
    • Sutanto, H., & Lyon, A. (2021). Predicting the neuro-cardio-haemodynamic outcomes of sepsis and its pharmacological interventions: get to the future through numerical equations. The Journal of Physiology, 599(11), 2797-2799. https://doi.org/10.1113/JP281661
    • Lyon, A., van Mourik, M., Cruts, L., Heijman, J., Bekkers, S. C. A. M., Schotten, U., Crijns, H. J. G. M., Linz, D., & Lumens, J. (2021). Both beat-to-beat changes in RR-interval and left ventricular filling time determine ventricular function during atrial fibrillation. EP Europace, 23, I21-I28. https://doi.org/10.1093/europace/euaa387
    • van Osta, N., Kirkels, F., Lyon, A., Koopsen, T., van Loon, T., Cramer, M-J., Teske, A. J., Delhaas, T., & Lumens, J. (2021). Electromechanical substrate characterization in arrhythmogenic cardiomyopathy using imaging-based patient-specific computer simulations. EP Europace, 23, I153-I160. https://doi.org/10.1093/europace/euaa407
  • 2020
    • Sutanto, H., Lyon, A., Lumens, J., Schotten, U., Dobrev, D., & Heijman, J. (2020). Cardiomyocyte calcium handling in health and disease: Insights from in vitro and in silico studies. Progress in Biophysics & Molecular Biology, 157, 54-75. https://doi.org/10.1016/j.pbiomolbio.2020.02.008
    • Lyon, A., Dupuis, L. J., Arts, T., Crijns, H. J. G. M., Prinzen, F. W., Delhaas, T., Heijman, J., & Lumens, J. (2020). Differentiating the effects of β-adrenergic stimulation and stretch on calcium and force dynamics using a novel electromechanical cardiomyocyte model. American Journal of Physiology-heart and Circulatory Physiology, 319(3), H519-H530. https://doi.org/10.1152/ajpheart.00275.2020
    • van Osta, N., Lyon, A., Kirkels, F., Koopsen, T., van Loon, T., Cramer, M. J., Teske, A. J., Delhaas, T., Huberts, W., & Lumens, J. (2020). Parameter subset reduction for patient-specific modelling of arrhythmogenic cardiomyopathy-related mutation carriers in the CircAdapt model. Philosophical Transactions of the Royal Society A: mathematical Physical and Engineering Sciences, 378(2173), [20190347]. https://doi.org/10.1098/rsta.2019.0347
    • Hermans, B. J. M., Bennis, F. C., Vink, A. S., Koopsen, T., Lyon, A., Wilde, A. A. M., Nuyens, D., Robyns, T., Pison, L., Postema, P. G., & Delhaas, T. (2020). Improving long QT syndrome diagnosis by a polynomial-based T-wave morphology characterization. Heart Rhythm, 17(5), 752-758. https://doi.org/10.1016/j.hrthm.2019.12.020
  • 2019
    • Lyon, A., Mincholé, A., Bueno-Orovio, A., & Rodriguez, B. (2019). Improving the clinical understanding of hypertrophic cardiomyopathy by combining patient data, machine learning and computer simulations: A case study. Morphologie, 103(343), 169-179. https://doi.org/10.1016/j.morpho.2019.09.001
    • Minchole, A., Camps, J., Lyon, A., & Rodriguez, B. (2019). Machine learning in the electrocardiogram. Journal of Electrocardiology, 57, S61-S64. https://doi.org/10.1016/j.jelectrocard.2019.08.008
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