The course aims to : 

1.    Provide a broad understanding of key concepts and principles related to artificial intelligence (AI) applied in radiotherapy.
2.    Explore the challenges and opportunities of implementing and applying AI solutions in the radiation oncology clinic.
3.    Deliver knowledge on the state-of-the-art of current AI application in clinical practice within radiation oncology.
4.    Equip participants with the underlying knowledge to safely commission, perform quality assurance (QA), and apply AI technologies in the radiation oncology clinic.
5.    Enhance the ability to effectively use and interact with AI systems in the daily activities within the radiation oncology clinic.

Learning Outcomes

By the end of this course participants should :
1.    have a broad knowledge on the different concepts and principles of AI in radiotherapy
2.    recognize the challenges and opportunities of applying AI solutions in the radiation oncology clinic
3.    have knowledge on the state-of-the-art of current clinical AI applications in radiation oncology
4.    understand the basics underlying safe implementation, QA and the application of AI in the radiation oncology clinic
5.    understand how to effectively use and interact with AI in the radiation oncology clinic
 

Course Content

To be finalized

Course Design / Teaching methods

This course will be delivered using a blended learning approach, i.e. a combination of recorded online lectures and a live component with teaching lectures and hands-on sessions.
●    Online lectures will be delivered using the ESTRO Moodle, the ESTRO Virtual Learning Environment (VLE), where recorded presentations will be available for participants to join at a time that suits them before traveling to the on-site course.
●    The live component will consist of brief summaries from the recorded lectures with Q&A sessions, additional teaching lectures with case studies, hands-on sessions and time for multi-disciplinary discussion and interaction.

Prerequisites

This course is designed for participants with diverse backgrounds (e.g., RTTs, medical physicists, radiation oncologists, etc.). No previous experience with programming or artificial intelligence is required. All participants will be asked to bring a laptop to the course to participate in the hands-on sessions.

Course Directors

• Jennifer Dhont, Data Scientist, Institut Jules Bordet, Brussels (BE)
• Stine Korreman, Medical Physicist, Aarhus University, Aarhus (DK)

Faculty

• Wouter Crijns, Medical Physicist, KU Leuven, Leuven (BE)
• Ana Barragan Montero, Medical Physicist, Université Catholique de Louvain, Brussels (BE)
• Wouter van Elmpt, Medical Physicist, Maastricht University, Maasricht (NL)
• Elizabeth Forde, Radiation Therapy Technologist, Trinity College, Dublin (IE)
• Dave Fuller, Radiation Oncologist, MD Anderson Cancer Centre, Houston (US)
• Lise Thorsen, Radiation Oncologist, Aarhus University, Aarhus (DK)
• Eliana Vasquez Osorio, Computer Scientist, University of Manchester (UK)

Online contributors:

• Matteo Maspero, Medical Physicist, Universitair Medisch Centrum, Utrecht (NL)
• Lorenzo Placidi, Medical Physicist, Fondazione Policlinico Universitario Agostino Gemelli, Rome (IT)
• Davide Cusumano, Medical Physicist, Mater Olbia, Olbia (IT)
• Coen Hurkmans, Medical Physicist, Catharina Ziekenhuis, Eindhoven (NL)

Starhotels Majestic Torino

Corso Vittorio Emanuele II, 54

10123 Turin

Italy

The scientific programme is available here.

Membership

ESTRO members can order products at substantially reduced prices. To benefit from the member registration rate, you must subscribe for the ESTRO membership 2026 BEFORE registering to the course. To become an ESTRO member, benefit from the member registration rate and discover the many other member advantages, please visit the membership page.

Fees

* Members with specialty RadiationTherapist (RTT) may register at the In-Training fee

The fee includes the course material, coffees, lunches, and the social event.

Advance registration & payment are required.

Access to homework and/or course material will become available upon receipt of full payment.

Insurance and cancellation

Participants are strongly advised to take out their own personal insurance policy. ESTRO does not accept liability for individual medical, travel or personal accidents or incidents. Participants are strongly advised to take insurance policies to cover flight and accommodation cancellation penalties. ESTRO will not refund any travel or accommodation expenses.

For any cancellation made by the course participant, ESTRO School Events Cancellation Policy will be followed and all stated penalty fees will be applied.

Reduced fees

Members from emerging countries may register at a preferential rate of 350 Euro. Emerging country fee applies to individuals from low-income and lower-middle-income economies according to the World Bank listing here.

Additionally, all specialties from the following countries can benefit from this preferential rate: Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Hungary, Macedonia, Moldova, Montenegro, Romania, Russian Federation, Serbia, Turkey, Ukraine.  In addition, medical physicists from Cyprus can email education@estro.org to apply for this fee.

The preferential rate of 350 Euro is granted automatically when you click on the  BOOK NOW  button and the three conditions below are met:

1. Only ESTRO members for 2026 are eligible (please make sure your 2026 membership is in order before you click on the BOOK NOW  button)
2. Only one course per person per year can be subsidized by ESTRO
3. Sponsored candidates are not entitled to reduced fees (the invoicing address has to be the one of the participant)  

 Please note:

• We can only guarantee a certain number of reduced fees per course
• Application deadlines are the same as early registration fees