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The current standard of care for locally advanced oesophageal cancer (EC) consists of a trimodality treatment comprising of neo-adjuvant chemoradiotherapy, followed by surgery, as supported by data from the phase III CROSS trial. However, this treatment is associated with high morbidity and mortality rates and overall survival is still disappointingly low. New technical developments in radiation treatment aim to improve tumor control while reducing post-operative complications and toxicity.

Amongst these technical developments are i) the integration of FDG-PET-CT and multiparametric MRI imaging in the delineation of target volumes and organ at risks, ii) motion management strategies such as 4DCT simulation, respiratory motion-based surface scanning and spirometry, iii) adaptive treatment by means of repeated imaging followed by recontouring and replanning or dose restoration, iv) new treatment delivery techniques such as MR-linac and proton therapy and v) the development of deep learning networks to select the optimal treatment modality and to support the treatment process.

While some of these techniques such as repeated 4D CT simulations have already been introduced in routine clinical practice, for many, clinical feasibility, usability and benefit have yet to be proven. Examples of large ongoing trials in which some of these new treatment strategies are being investigated are the phase III PROTECT trial, in which patients with locally advanced oesophageal cancer are randomised between photon therapy and proton therapy in the neoadjuvant setting, and the large MOMENTUM study that investigates the use of an MR-linac in an online adaptive workflow.