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Context:
Organ transplantation is facing a growing shortage of grafts. Advances in surgical techniques have made transplantation a reference treatment for end-stage diseases, leading to an increase in the number of patients on waiting lists. This growing demand is not matched by an equivalent rise in donor numbers, which extends waiting times and increases patient mortality.
To address this shortage, so-called "marginal" organs from expanded criteria donors represent one avenue for broadening the pool of available grafts. These organs carry a higher risk of post-transplantation complications, however, which makes their assessment all the more important.
Currently, organ viability is evaluated through biopsy followed by histological analysis. This method has several limitations: results are sometimes obtained after the transplant has already taken place, pathological interpretation remains subjective, and the procedure is invasive by nature. There is therefore a need to develop an objective and faster assessment method, enabling surgeons to better select transplantable organs.
Thesis objectives:
Optical methods have the potential to address this challenge. Non-invasive, rapid, and compatible with intraoperative use, they allow continuous and quantitative monitoring of tissue condition without disrupting the transplantation protocol. The aim of this thesis is to develop such objective methods for assessing organ viability, in order to broaden the pool of transplantable organs and reduce rejections and graft failures linked to poor selection. This work will directly follow on from the thesis of Antoine Uzel (IGL/CREATIS, 2026), which laid the first groundwork for this type of assessment on the liver by developing two complementary approaches: near-infrared diffuse reflectance spectroscopy (NIR-DRS) for quantifying hepatic steatosis, with a particular focus on differentiating micro- and macrovesicular steatosis, and fluorescence spectroscopy for metabolic tissue monitoring through the study of endogenous fluorophores such as NADH, FAD, and vitamin A. Attention will also be given to implementing artificial intelligence methods to score organs based on optical measurements.
Supervision:
The supervision committee will bring together specialists from each component of this thesis project: clinical medical optics setup (Bruno Montcel, MAGICS team, CREATIS), machine learning for optics (Cédric Ray-Garreau, MAGICS team, CREATIS), data analysis (Michaël Sdika, MYRIAD team, CREATIS), as well as the company representative, specializing in biomedical optics, who carried out the initial work on the subject (Antoine Uzel, IGL engineer).
This work is part of the ITI Labcom project (Imaging for Transplantation Assisted by Artificial Intelligence), funded by the ANR, which structures the IGL/CREATIS collaboration over 5 years with the ultimate goal of commercializing organ viability assessment devices.
Candidate profile:
The person recruited will work on both the development and modelling of optical setups, signal processing, and data analysis. They will conduct laboratory characterization experiments as well as in vivo experiments on animal models, humans, and human organs under surgical conditions. The prerequisites are therefore those of a physicist and/or engineer with a specialization in modelling and/or data analysis, and a strong interest in interdisciplinary work in the medical and biomedical field.
Contact:
rh@icairgroup.com