Revolutionizing High-precision Non-invasive Brain Treatments with Advanced Numerical Modeling

**Revolutionizing High-Precision Non-Invasive Brain Treatments with Advanced Numerical Modeling**:

- Réf **ABG-129115**
- Sujet de Thèse
- 04/03/2025
- Financement public/privé
- ICube (UMR 7357)
- Lieu de travail- Strasbourg - Grand Est - France
- Intitulé du sujet- Revolutionizing High-Precision Non-Invasive Brain Treatments with Advanced Numerical Modeling
- Champs scientifiques- Biotechnologie
- Numérique
- Santé, médecine humaine, vétérinaire
- Mots clés- transcranial ultrasound, treatment targeting, numerical optimization

**Description du sujet**:
Transcranial Focused Ultrasound (tFUS) is a groundbreaking technology that can treat neurological conditions like Parkinson’s disease, epilepsy, and even enable targeted drug delivery—without invasive surgery. However, accurately focusing ultrasound waves deep inside the brain is challenging, especially without the use of expensive MRI guidance. Current alternatives lack real-time verification, making treatments less precise and potentially less effective.

This project aims to develop a new, cost-effective method for pinpointing the ultrasound focal spot using a combination of acoustic sensors and advanced numerical modeling. By leveraging mathematical optimization techniques, we will create patient-specific computational models of the brain’s complex, heterogeneous structure. These models will predict how ultrasound waves travel through different tissue types, enabling real-time adjustments for precise targeting.

Our approach includes two key innovations. First, we will develop an inverse optimization framework to refine estimates of the brain’s acoustic properties, using data from an array of transcranial acoustic sensors. Second, we will implement nonlinear numerical methods to iteratively adjust the ultrasound beam’s focus, ensuring it reaches the intended target with high accuracy. These techniques will replace the current trial-and-error approach, significantly improving treatment safety and efficiency.

**Prise de fonction**:

- 01/10/2025

**Nature du financement**:

- Financement public/privé

**Précisions sur le financement**:

- Par audition

**Présentation établissement et labo d'accueil**:

- ICube (UMR 7357)

**The Engineering science, computer science and imaging laboratory**

Created in 2013, the laboratory brings together researchers of the University of Strasbourg, the CNRS (French National Center for Scientific Research), the ENGEES and the INSA of Strasbourg in the fields of engineering science and computer science, with imaging as the unifying theme.

The laboratory is a member of the Carnot Telecom & Société numérique institute, thanks to its close relationship with Telecom Physique Strasbourg.

**Site web**:
**Intitulé du doctorat**:

- Doctorat de l'université de Strasbourg

**Pays d'obtention du doctorat**:

- France

**Etablissement délivrant le doctorat**:

- UNIVERSITE DE STRASBOURG

**Ecole doctorale**:

- Mathématiques, sciences de l'information et de l'ingénieur

We are looking for a motivated graduate student with a passion for interdisciplinary research and problem-solving. This project sits at the intersection of computational modeling, biomedical engineering, and medical physics, offering an exciting opportunity to develop cutting-edge methods for non-invasive brain treatments.

Interdisciplinary mindset - Ability to integrate knowledge from physics, engineering, and medical imaging.

Strong problem-solving skills - Creativity and critical thinking to tackle complex challenges in ultrasound-based therapies.

Programming experience - Familiarity with Python, MATLAB, C++, or similar languages for computational modeling and data analysis.

Mathematical and computational abilities - Interest in numerical methods, optimization, and inverse problems.

Understanding of wave propagation - Basic knowledge of acoustics or ultrasound physics (or a willingness to learn).

Experimental curiosity - Enthusiasm for validating models with real-world data, including working with sensors and imaging systems.- 21/04/2025