Radiation Oncology - Towards a mission-oriented approach to cancer

The Future Needs of External Beam Radiotherapy in Portugal Until 2040

AIMS

External beam radiotherapy (EBRT) is essential to offer an effective cancer treatment, but it needs to be accessible, well-timed, and high-quality. There is a global lack of radiotherapy infrastructure and investment that compromises the cancer outcomes. The authors aim to quantify the future needs of EBRT until 2040 to cover the future demand.

MATERIALS AND METHODS

Based on the Global Cancer Observatory estimate for new cancer cases in Portugal for 2040 it was calculated the optimal number of EBRT courses. The OUP is the proportion of new cancer cases that should receive EBRT at least once. In line with the International Atomic Energy Agency (IAEA) DIrectory of RAdiotherapy Centres and European SocieTy for Radiotherapy and Oncology - Health Economics in Radiation Oncology guidelines, we estimated the number of EBRT machines / Megavoltage (MV) units needed. Also, the authors followed the IAEA staffing guidelines.

RESULTS

The calculated median increase in the optimal number of EBRT courses for the year 2040 was found to be 18% when compared to the requirements in 2020. The projected number of optimal EBRT courses for 2040 was estimated to be approximately 34.000. Consequently, a range of 18 to 30 new EBRT machines/ MV units will need to be installed to adequately address the growing demand. To meet this demand, it is anticipated that a total of 28 to 46 radiation oncologists, 22 to 36 medical physicists, and 61 to 102 radiation therapists will be required.

CONCLUSION

The deficit of EBRT machines / MV units in Portugal will require a change in the cancer related - policies and an investment to offer full access to EBRT treatments.

A joint physics and radiobiology DREAM team vision - Towards better response prediction models to advance radiotherapy

Radiotherapy developed empirically through experience balancing tumour control and normal tissue toxicities. Early simple mathematical models formalized this practical knowledge and enabled effective cancer treatment to date. Remarkable advances in technology, computing, and experimental biology now create opportunities to incorporate this knowledge into enhanced computational models. The ESTRO DREAM (Dose Response, Experiment, Analysis, Modelling) workshop brought together experts across disciplines to pursue the vision of personalized radiotherapy for optimal outcomes through advanced modelling. The ultimate vision is leveraging quantitative models dynamically during therapy to ultimately achieve truly adaptive and biologically guided radiotherapy at the population as well as individual patient-based levels. This requires the generation of models that inform response-based adaptations, individually optimized delivery and enable biological monitoring to provide decision support to clinicians. The goal is expanding to models that can drive the realization of personalized therapy for optimal outcomes. This position paper provides their propositions that describe how innovations in biology, physics, mathematics, and data science including AI could inform models and improve predictions. It consolidates the DREAM team's consensus on scientific priorities and organizational requirements. Scientifically, it stresses the need for rigorous, multifaceted model development, comprehensive validation and clinical applicability and significance. Organizationally, it reinforces the prerequisites of interdisciplinary research and collaboration between physicians, medical physicists, radiobiologists, and computational scientists throughout model development. Solely by a shared understanding of clinical needs, biological mechanisms, and computational methods, more informed models can be created. Future research environment and support must facilitate this integrative method of operation across multiple disciplines.