Table of Contents

Liver cancers -and particularly hepatocellular carcinoma HCC- are among the most devastating cancers in the world with a constantly increasing prevalence. For these cancers electroporation percutaneous ablation (EPA) combined with immunotherapy holds great promises. However, this (relatively new) ablation technique combined with novel immune treatments suffers from a lack of quantitative criteria for the treatment assessment. Indeed, unlike monopolar radiofrequency ablations which mostly require only a single needle insertion and whose efficacy is directly linked to the temperature map, EPAs need 3 to even 8 needles, and the distribution of the electric field needs accurate and efficient computations still to be developed. In addition, the combination with immunotherapy suffers from a lack of quantitative imaging biomarkers (radiomics) to classify as soon as possible the patients.

The originality of the PhD project lies in proposing to develop innovative artificial intelligence-based mathematical and algorithmic methods designed to produce a novel deep learning based radiomics signatures of the immune response to combinatorial EPAs and immunotherapy designed to better quantify the immune response after EPA. The thesis may open new perspectives for the care of patients with liver tumors, and the proof of concept could be applied to pancreas or other cancers.

For a better knowledge of the proposed research subject:

[1] O. Gallinato, B. D. de Senneville, O. Séror, and C. Poignard. Numerical workflow of irreversible electroporation for deep-seated tumor. Physics in Medicine and Biology, 2019.

[2] L. Lafitte, R. Giraud, C. Zachiu, M. Ries, O. Sutter, A. Petit, O. Séror, C. Poignard, B. Denis de Senneville. Patch-based field-of-view matching in multi-modal images for electropora-tion-based ablations. Computerized Medical Imaging and Graphics, Vol. 84, (2020).

[3] O. Gallinato, B. Denis de Senneville, O. Séror, C. Poignard. Numerical Modelling Challenges for Clinical Electroporation Ablation Technique of Liver Tumors. Math. Model. Nat. Phenom., Vol. 15 (11), (2020)

Collaboration

The recruited person will be in connection with Prof. Séror, head of the Interventional Radiology Department of Avicenne Hospital-AP-HP. The thesis will benefit from the large database of more the 120 patients with HCC treated by electroporation by Prof Séror's team, as well as from the database of the ongoing clinical trial NIVOLEP combining EPA and nivolumab, led by Prof Séror and Nahon, both are PU-PH at Avicenne Hospital-APHP, and which includes currently about 50 patients.

Responsibilities

This thesis aims to develop fast numerical strategies to compute the electric field applied for electroporation and also to invent novel radiomics biomarkers of the response to EPAs combined with immunotherapy. The goal is to invent computational and DL-based robust biomarkers to give a feedback to the radiologists during the procedure and also to classify the patient immune response to these therapies of the future.

Main activities

  • Develop fast numerical strategies to compute the electric field applied for electroporation
  • Compare reduced order model strategy (whose principle is to build a numerical basis of solution on which the seek solution is projected) with deep learning strategy (which consists in performing a lot of numerical simulation to obtain a large numerical training data base. The aim is to investigate the efficiency of the two approaches for the specific application of liver and pancreas tumor treatment
  • Accelerate the computation using reduce order model and in parallel deep learning strategy based on a built numerical database
  • Invent novel radiomics biomarkers of the response to EPAs combined with immunotherapy

Additional activities

  • Write reports
  • Contribute to code development and interface

Examples of activities

For the applications, the thesis will provide two important information to medical doctors performing EPA:
* It will provide online electric field distribution by the most robust and rapid approach
* It will provide quantitative imaging criteria to classify the patients with respect to their immune response. Indeed, determining rapidly if a patient is a good responder or not to immunotherapy is a great challenge, because of the side effects and the cost of these therapies. At last, identifying at the early stage a patient relapse should improve the care of the patients., The student will benefit from the experience of the team MONC on the textural and shape features extraction with the Python software PapriK.

An important strength of the project lies in the tight and long-term collaboration of the PhD advisors with Prof. Séror, head of the Interventional Radiology Department of Avicenne Hospital-AP-HP. The 3 researchers have published more than 5 communications, including applied math, physical medicine and radiology journals and a joint patent is being written.

Clair Poignard currently leads a Plan Cancer project NUMEP (numep.math.cnrs.fr) and they have submitted recently another project on numerical approaches for electroporation liver ablation.

A propos d'Inria

Inria est l'institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 200 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3500 scientifiques pour relever les défis du numérique, souvent à l'interface d'autres disciplines. L'institut fait appel à de nombreux talents dans plus d'une quarantaine de métiers différents. 900 personnels d'appui à la recherche et à l'innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 180 start-up. L'institut s'efforce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie.
The MONC project-team aims at developing new mathematical models involving partial differential equations and statistical methods based on a precise biological and medical knowledge in order to build numerical tools based on available quantitative data about cancer. The goal is finally to be able to help clinicians and/or biologists to better understand, predict or control tumor growth and possibly evaluate the therapeutic response, in a clinical context or for pre-clinical studies. We plan to develop patient-specific approaches (mainly based on medical imaging) as well as population-type approaches in order to take advantage of available large data bases. We claim that our work may have a clinical impact that can change the way of handling certain pathologies., * The student should have a strong background in applied mathematics and/or computer science, with interests in medicine application.
* Programing skills high-level languages, such as Matlab and/or Python are required and C++ programing skills will be appreciated.

Languages

  • Good level of English in both oral and writing

Relational skills

  • Sociability and ability to interact with people from different scientific communities

Other valued appreciated

  • Basic knowledge in cell/cancer biology or medicine will be appreciated
  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Possibility of teleworking and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage

Rémunération

1982€ / month (before taxs) during the first 2 years, 2085€ / month (before taxs) during the third year.
Postuler
The recruited person will work within the Inria team MONC (Modeling in ONCology).

An important strength of the project lies in the tight and long-term collaboration of the PhD advisors with Prof. Séror, head of the Interventional Radiology Department of Avicenne Hospital-AP-HP. The 3 researchers have published more than 5 communications, including applied math, physical medicine and radiology journals and a joint patent is being written.



Source link