! INTERNSHIP FILLED !

! CLIQUER ICI POUR LA VERSION FRANÇAISE !

 

Download the internship proposal

Internship type

Master 2/last year engineering school internship

Duration

6 months from the beginning of 2024

Context

The Laboratoire d’Imagerie Biomédicale is developing 3D super-resolved ultrasound for intracerebral imaging applications. This approach is based on the imaging of ultrasound scatterers circulating in blood vessels, their sub-wavelength localization and tracking in order to reconstruct a 3D image that can potentially aid the diagnosis of many diseases involving the microcirculation [Chavignon et al. 2022]. Among other things, we are developing a new portable neuroscanner that could potentially contribute to the rapid diagnosis of strokes.

Initial preclinical studies on small animal models enabled us to classify the different types of stroke: ischemic (when a blood clot is present), and hemorrhagic (when blood effusion is present in the brain) [Chavignon et al. 2022]. Recently, we have extended these preclinical studies to large animal models to prove the efficacy and viability of transcranial 3D ULM when bone thickness is of the order of that of a human temporal bone [Coudert et al. 2023]. 3D ULM has enabled reconstruction of the microvascular network behind a skull to a depth of around 6 cm.

Objective

This internship involves enhancing the transcranial 3D ultrasound microbubble (ULM) processing of large animal model data and extending the processing to data obtained from patients who have suffered an ischemic stroke. In 2D, the algorithms developed by our team have been shared [Heiles, Chavignon et al. 2022] and improved upon by the international community, whether to enhance the microbubble signal or improve their tracking/trajectory [Leconte et al. 2023, Xing et al. 2023, Ghigo et al. 2023, Chen et al. 2022]. These new approaches need to be implemented in 3D and will pave the way for new neurovascular diagnostic methods.

Goals

The intern will have the following tasks:

• Understand the acquisition and post-processing to obtain 3D ULMs
• Expand the parameters of the echoes from the bubbles taken into account in the 3D ULM
• Participate in in-vivo studies

Expected competences

• Theory and practice in ultrasound and signal processing
• Theory and practice in biomedical engineering,
• Writing and exchanges in English,
• Willingness to evolve within multiple research environments (medical imaging laboratory) and multiple fields (acoustics, biomedical, in-vivo),
• Interest in applied research..

It is not required to master all these concepts perfectly but to want to understand them and use them quickly.

References

1. Couture, O., Hingot, V., Heiles, B., Muleki-Seya, P., & Tanter, M. (2018). Ultrasound localization microscopy and super-resolution: A state of the art. IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 65(8), 1304-1320.
2. Chavignon, A., Hingot, V., Orset, C., Vivien, D., & Couture, O. (2022). 3D transcranial ultrasound localization microscopy for discrimination between ischemic and hemorrhagic stroke in early phase. Scientific reports, 12(1), 1-11.
3. A. Coudert, L. Denis, A. Chavignon, C. Orset, D. Vivien, O. Couture, “Transcranial 3D Ultrasound Localization Microscopy in sheep brain”, (oral presentation, IEEE 2022), 2022
4. Heiles, B., Chavignon, A., Hingot, V., Lopez, P., Teston, E. and Couture, O., 2022. Performance benchmarking of microbubble-localization algorithms for ultrasound localization microscopy. Nature Biomedical Engineering, 6(5), pp.605-616.
5. Leconte, A., Porée, J., Rauby, B., Wu, A., Ghigo, N., Xing, P., … & Provost, J. (2023). A Tracking prior to Localization workflow for Ultrasound Localization Microscopy. arXiv preprint arXiv:2308.02724.
6. P. Xing, V. Perrot, A. Ulises Dominguez-Vargas, S.Quessy, N.Dancause, J. Provost, “Imaging of the Macaque Brain Microvasculature Using 3D Ultrasound Localizatioon Microscopy” “, (oral presentation, IEEE 2023), 2023
7. Ghigo, N., Ramos-Palacios, G., Bourquin, C., Xing, P., Wu, A., Cortés, N., … & Provost, J. (2023). Dynamic Imaging using any Ultrasound Localization Microscopy Dataset. arXiv preprint arXiv:2311.00648
8. Chen, X., Lowerison, M.R., Dong, Z., Han, A. and Song, P., 2022. Deep learning-based microbubble localization for ultrasound localization microscopy. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 69(4), pp.1312-1325.

Remuneration

Internship gratification

Contact

Olivier Couture – olivier.couture[at]sorbonne-universite.fr

Location

Laboratoire d’Imagerie Biomédicale (LIB) – 15 rue de l’École de Médecine 75006 Paris