Objective
The discovery of the green fluorescence protein (GFP) and the parallel development of super-resolved fluorescence microscopy (2008 and 2014 Nobel Prizes) led to major breakthroughs in basic biology and medicine by enabling the visualization of the pathways of individual molecules inside living cells. While optical imaging is limited to studying thin specimens (<1mm) due to light scattering in tissue, the introduction of nanoscale gas vesicles (GVs) as the GFP for ultrasound provides an alternative to light for deep tissue cellular imaging. However, current ultrasound imaging methods are bound by the diffraction limit, leading to a resolution of ~100 m at an ultrasound frequency of 15 MHz. While this allows for the detection of cell populations, signals arising from individual cells cannot be isolated. With this project, my goal is to develop a new super-resolution method for cellular ultrasound imaging. The first application of this method will consist in characterizing cancer microenvironments.
The first research objective will be to develop a 3D super resolution method for cellular imaging that relies on nonlinear ultrasound imaging of engineered cells expressing GVs. To put this research effort in context, the grand challenge for super-resolution cellular ultrasound imaging would be to reach a resolution of 10 m which is the characteristic length of a single cell. The second research objective will consist in applying this imaging method to preclinical cancer research. The development of super resolution cellular imaging would provide a new tool for drug screening and treatment monitoring. To do so my project will be conducted on multi-cellular tumorous spheroid models.
The output of this project will be an new ultrasound imaging method for oncology and basic biology research. The successful completion of this project will equip biomedical researchers around the world with a tool to inspect cellular functions deep into opaque tissue.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesphysical sciencesopticsmicroscopysuper resolution microscopy
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- medical and health sciencesclinical medicineoncology
- natural sciencesphysical sciencesacousticsultrasound
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
2628 CN Delft
Netherlands