ICMUB: 229 600 €
Duration: 10/2021 – 54 months
Scientific Leader ICMUB: Benoît Presles
Description
Liver cancer is the sixth most common cancer but the second most deadly in humans. Some cancers can be treated by selective internal radiotherapy (SIRT), which involves selectively injecting yttrium-90-labelled beads into the hepatic arterial tree. The project aims to improve SIRT treatments by applying the latest deep learning methods in the literature. Firstly, a classification deep learning algorithm will be developed to predict the response to treatment from pre-treatment images and thus help clinicians to optimise/adjust the treatment. Secondly, a segmentation method will be trained and validated to improve and automate the delineation of tumour and liver volumes using functional data in addition to anatomical data. The tools developed should improve treatment planning and delivery, and hence the response rate and survival time.
Partners:
- Centre Hospitalier Universitaire (CHU) Dijon Bourgogne
- Centre Georges François Leclerc (CGFL)