Description du projet
Des ondes sonores à la dynamique des bulles
L’échographie diagnostique utilise des ondes sonores à haute fréquence pour produire des images internes du corps. Dans le cas des maladies cardiovasculaires et du cancer, il est essentiel de disposer d’images de la vascularisation et des flux si l’on veut parvenir à surmonter les obstacles actuels en matière de diagnostic et de traitement. Cependant, les modalités d’imagerie clinique existantes offrent encore une résolution spatio-temporelle insuffisante. Pour résoudre ce problème, le projet Super-FALCON, financé par le CER, s’appuiera sur la dynamique non linéaire de nouveaux agents de contraste: les microbulles monodispersées. Grâce à l’apprentissage profond et aux simulations accélérées par processeur graphique, il reconstituera des images de nuages de bulles en super-résolution. Le projet élaborera également un nouveau modèle pour les bulles confinées et les utilisera comme capteurs non linéaires pour l’imagerie capillaire. L’objectif est de produire des connaissances fondamentales sur la dynamique des bulles confinées, la propagation inhomogène des ultrasons et les stratégies de déconvolution. Super-FALCON pourrait ainsi être à l’origine d’un changement de paradigme vers un traitement spécifique au patient.
Objectif
Our healthcare system is under unsustainable strain owing, largely, to cardiovascular diseases and cancer. For both, imaging vasculature and flow precisely is paramount to reduce costs while improving diagnosis and treatment. Specifically, the focus is on the multiscale aspects of shear, vorticity, pressure and capillary bed (10-200 μm vessels) structure and mechanics. However, this requires an imaging depth of ~10 cm with a resolution of ~50μm. Furthermore, velocities often exceed 1m/s, which requires a frame rate of ~1000 fps. Clinical imaging modalities have so far been hindered by insufficient spatiotemporal resolution and there is thus a dire need for new techniques.
Plane-wave ultrasound enhanced with contrast microbubbles outperforms all modalities in safety, cost, and speed, and is thus the ideal candidate to address this need. The strategy I propose in Super-FALCON harnesses the nonlinear dynamics of monodisperse microbubbles. In WP1, I will use deep learning and GPU-accelerated acoustic simulations to recover super-resolved (1/20th of the wavelength) bubble clouds. In WP2, I will create a new model for confined bubbles, and use them as nonlinear sensors for capillary imaging. In WP3, I will disentangle attenuation and scattering using (physics-informed) deep learning and correct for wave distortion. This is needed to apply the strategies from WP1 and 2 in deep tissue. Finally, in WP4, I will use automatic segmentation to integrate the fundamental results of WP1, 2 and 3 into a technology that I will scientifically assess on vascularized ex vivo livers.
With Super-FALCON, my ambition is to generate a long-term impact both scientifically and societally. I will produce new fundamental knowledge about confined bubble dynamics, inhomogeneous ultrasound propagation, and deconvolution strategies as well as new experimental methods for flow imaging and characterization. In healthcare, Super-FALCON could initiate a paradigm shift towards patient-specific treatment.
Champ scientifique
- natural sciencesphysical sciencesopticsmicroscopysuper resolution microscopy
- medical and health sciencesclinical medicinecardiologycardiovascular diseases
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencesphysical sciencesacousticsultrasound
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Thème(s)
Régime de financement
ERC - Support for frontier research (ERC)Institution d’accueil
7522 NB Enschede
Pays-Bas