1. Overview of the research programme:
InSilicoHealth is an innovative Doctoral Network (DN) with the ambition to train a new generation of outstanding
Doctoral Candidates (DC) that will become effective translators of the rapidly evolving digital technology to tackle
existing and future challenges related with healthy ageing in Europe. The research focus of this DN lies in three
key domains: the brain, heart, and musculoskeletal (MSK) systems. In the realm of digital technology, InSilicoHealth
specifically focuses on virtual human twin (VHT) technology to enhance our understanding of the age-related adaptive
changes of the complex human body through predictive multi-scale simulations. The research methodology employs
knowledge-driven models enhanced by advanced data-driven inference techniques to optimize the health potential of
older individuals.
2. Individual PhD Project Information:
- Host institution
- UGent, Belgium
- Supervisory team
- Prof. Patrick Segers (PhD supervisor, UGent), Dr Mathias Peirlinck (PhD co-supervisor, TUDelft), Dr Annette
Caenen (PhD co-supervisor, UGent and KU Leuven), Dr Gunnar Hansen (secondment host, GE Vingmed). - Enrolment in Doctoral School
- Enrolled in the Department of Electronics and Information Systems of UGent and the Graduate School of Faculty
3mE (TUDelft).
3. PhD project description:
Shear wave elastography visualizes the heart using ultrasound at a high frame rate (up to 5 kHz – 100x the frame rate of conventional echocardiographic imaging), which allows for the detection of shear waves that travel along the cardiac wall. Shear waves can be induced naturally by mitral or aortic valve closure for example (see figure). An interesting property of these shear waves is that their propagation speed is intrinsically linked to the operational stiffness of the tissue in which they propagate. There is increasing and encouraging evidence to support the potential clinical use of shear wave elastography in heart diseases characterized by stiffening due to fibrosis, but its interpretation might be more complex. However, the fundamental wave physics underlying the natural shear wave measurements remain relatively unexplored. Additionally, the layered fiber structure of the myocardium makes the mechanical properties position- and direction dependent, and the cyclic function of the heart leads to time- and loading-dependent changes. The settings of the ultrasound machine itself and biological factors (e.g. age) can also affect the relationship between wave propagation speed and myocardial stiffness.
This PhD project will focus on building a three-dimensional multi-physics in silico health solution of the contracting heart to disentangle the relationship between wave propagation speed and myocardial stiffness in the ageing heart. The model will provide insights into the interaction of the different cofounding factors of cardiac shear wave elastography, which will allow to optimize shear wave post-processing tools and potentially propose new relevant biomarkers. Experimental data of shear wave imaging will be available in healthy volunteers and heart patients from the Cardiovascular Imaging and Dynamics lab at KU Leuven (co-promoter Annette Caenen) for validation of the model. The candidate will work closely with the Peirlinck lab at TU Delft (co-promoter Mathias Peirlinck) to exchange cardiac modeling expertise and with GE (Dr Gunnar Hansen) to support translation of the developed tools into the clinical settings. Daily activities will take place in the Institute of Biomedical Engineering and Technology at Ghent university.
4. Planned secondments:
- TUDelft: Focused on broadening the methodological portfolio of the DC for in silico modelling of the heart.
- GE Vingmed: Aimed to gain knowledge on state-of-the-art clinical ultrasound systems developed at GE, and the
possibility to directly translate some of the methodological developments from the DC’s research project into
this state-of-the-art technology.
5. Essential requirements:
- You have completed a master’s degree in biomedical engineering, mechanical engineering or applied physics or
possess corresponding qualifications that could provide a basis for successfully completing a doctorate. - Specialization in soft tissue biomechanics, continuum mechanics and/or ultrasound physics will be beneficial.
- You have a keen interest in modelling and simulation, ultrasound imaging and cardiology.
- You have proven your proficiency in English language equivalent to B2 level.
- You did not reside or carry out your main activity (work, studies, etc.) in the host institution’s country for
more than 12 months in the three years before 1st of January 2025. - You are ambitious, well organized, a team player, and have excellent communication skills.
- You can work independently and have a critical mindset.
- You are a pro-active and motivated person, eager to participate in network-wide training events, international
mobility, and public dissemination activities. - Previous experience in multi-physics modelling combining biomechanics with ultrasound physics, ventricle models,
synthetic Radiofrequent data for ultrasonic imaging, and/or finite element modelling of hemodynamics, wall
mechanics and shear wave propagation is not essential but considered a plus.
6. Application requirements:
- Curriculum vitae.
- Motivation Letter, including a clear indication of the preferred DC position(s) within InSilicoHealth Doctoral Network if the applicant postulates for multiple positions.
- Academic records (grades) for Bachelor and Master degrees.