Deep lEarning tooLs for selectIve iNtErnal rAdiation ThErapy of hepatic tumours – DELINEATE

Liver cancer is the sixth most common cancer in the world but the second leading cause of cancer mortality in men. Among the different types of liver cancer, some can be treated by selective internal radiation therapy (SIRT), which consists in injecting into the selected hepatic arteries yttrium-90 ß-radiation emitter microspheres. The project aims at improving SIRT treatments by bringing state-of-the-art deep learning methods to SIRT. First, a deep learning classification algorithm will be developed to predict the treatment response from the pre-treatment images to help the clinicians to optimise/adjust it. Then, a deep learning segmentation method will be trained and validated to enhance and automate the delineation of the liver and tumour volumes by using functional data on top of the anatomical ones. All the developed tools should improve the treatment planning and delivery, and therefore the response rate and patient survival time.