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.

Dynamic nomogram for long-term survival in patients with locally advanced oropharyngeal cancer after (chemo)radiotherapy.

PURPOSE: This study aimed to establish a nomogram for predicting overall survival (OS) in oropharyngeal cancer patients treated with curative (chemo)radiotherapy. MATERIALS AND METHODS: The dynamic nomogram was constructed on 273 patients with oropharyngeal squamous cell carcinoma treated in a Tertiary Head and Neck Cancer Unit. The clinical features that were previously reported to be associated with OS were analyzed. The performance of the nomogram was assessed using concordance index (C-index) and calibration curves. RESULTS: The nomogram incorporated three explanatory variables derived from a decision tree approach including HPV status, N classification according to 8th edition TNM and early response to (chemo)radiotherapy. The nomogram was capable to predict OS with a validation C-index of 0.768. The proposed stratification in risk groups allowed significant distinction between Kaplan-Meier curves for OS outcome (p < 0.0001). CONCLUSIONS: The nomogram provided an accurate evaluation of OS for oropharyngeal cancer patients treated with curative (chemo)radiotherapy.

Technical note: 9-month repositioning accuracy for functional response assessment in head and neck chemoradiotherapy.

The use of thermoplastic immobilisation masks in head and neck radiotherapy is now common practice. The accuracy of these systems has been widely studied, but always within the context and time frame of the radiation delivery-some 6-8 weeks. There is growing current interest in the use of functional imaging to assess the response to treatment, particularly in the head and neck. It is therefore of interest to determine the accuracy with which functional images can be registered to baseline CT over the extended periods of time used for functional response assessment: 3-6 months after radiotherapy. In this study, repeated contrast-enhanced diagnostic quality CT and mid-quality localisation CT from a positron emission tomography/CT scanner were available for five time points over a period of 9 months (before, during and up to 6 months after chemoradiotherapy) for a series of eight patients enrolled in a clinical pilot study. All images were acquired using thermoplastic immobilisation masks. The overall set-up accuracy obtained from this 9-month study of 5.5 ± 3.2 mm (1 standard deviation) and 1.9 ± 1.3° (1 standard deviation) is in agreement with published data acquired over 6-8 weeks. No statistically significant change in set-up error was seen with time. This work indicates that thermoplastic immobilisation masks can be used to accurately align multimodality functional image data for assessment of the response to treatment in head and neck patients over extended follow-up periods.