About the project

Liver and pancreatic cancers are among the most devastating cancers in the world. Even though their incidence is much lower than other carcinomas such as prostate or breast cancers, they are the second leading cancer-related death. Percutaneous ablations, such as radiofrequency or microwave ablation have shown their efficacy, in particular for hepatocellular carcinomas (HCC) located far from vital structures such as biliary tree or hepatic vein. However, HCC tumors located near vital blood vessels and pancreatic adenocarcinomas still suffer from a lack of efficient non surgical therapies.To overcome this therapeutic impasse, electroporation-based ablations (EPAs) combined with immunotherapy hold great promises. However these new ablation techniques are currently underused for deep-seated tumors due to their technical complexity, and the lack of quantitative criteria of treatment assessment. Grounded on a consortium gathering mathematicians, biologists, and interventional radiologists, the project MECI proposes to innovate percutaneous tumor ablations thanks to a combination of advanced computational modeling and machine learning approaches based on improved biological and clinical knowledges. The main challenge is to develop novel digital technologies to assist interventional radiologists in their practice of EPAs for deep seated tumors, with a specific focus on liver and pancreatic cancers. On the one hand, the computational assessment of EPAs will assist the operator during the ablation procedure, providing a real-time evaluation of the treated region. On the other hand, novel deep learning based radiomics signatures of the immune response to combinatorial EPAs and immunotherapy will provide an early quantification of the immune response after EPA. MECI paves the way of the digital optimisation of patient-dependent and evolutive percutaneous ablations combined with immunotherapy.

Cancer Plan Project N°21CM119_00

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Last publications with full text