Session Item

As George Orwell once wrote: “the true genius is to create a problem and then sell the solution.” The latter might offer a too sarcastic view on developments in radiation oncology as indeed our discipline is characterized by the synergy between increasing accuracy & precision in dose delivery and improving knowledge in radiobiology. As such improvements can only be encouraged. However, truth be said, one cannot ignore some bias created by enthusiasm, focusing on innovation and neglecting clinical priorities, which brings to mind Monty Python’s hospital sketch on the “machine that goes ping”. With this presentation the author suggests a short “time-out”, stimulating a critical review on some of the innovations that emerged the last decades in view of what is important to our patients and what is an optimal balance within the current challenges that we face in health care economics. Much like MLC’s were claimed a necessity for IMRT a few decades ago; MRI-linacs are being introduced as a prerequisite for real-time adaptive radiation therapy, arguments are being generated to boost the advantages of proton beam therapy, real-time tumour tracking presented as the ultimate motion management, FLASH as a game changer, and radiomics and AI as the future of automation and decision making. One might argue that some decisions supporting clinical introduction of novel technology are driven by a “me-too” argumentation rather than clinical relevance. Developments must be multi-disciplinary in nature, process-oriented rather than device-oriented, risk- and evidence-based,  resource and risk optimised and flexible enough to cope with current and anticipated changes in oncology and health care. The multi-disciplinary radiation oncology community has an obligation to increase awareness and public confidence that radiation therapy is the most cost-effective cancer treatment (obviously, in optimal synergy with other cancer treatment modalities), and also that it is one of the safest medical specialties. New technology that is optimally implemented, appropriately applied and robustly assured will continue to support both of these messages.