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The definition of tumor involved volumes in patients with head and neck cancer poses great challenges with the increasing use of highly conformal radiotherapy techniques eg, volumetric modulated arc therapy and intensity modulated proton therapy. The risk of underdosing the tumor might increase unless great care is taken in the process. The information gained from imaging is increasing with both PET and MRI becoming readily available for the definition of targets. The information gained from these techniques is indeed multidimensional as one often acquire data on eg, metabolism, diffusion, and hypoxia together with anatomical and structural information. Nevertheless, much work remains to fully exploit the available information on a patient-specific level. Multimodality target definition in radiotherapy is a chain of processes that must be individually scrutinized, optimized and quality assured. Any uncertainties or errors in image acquisition, reconstruction, interpretation, and delineation are systematic errors and hence will potentially have a detrimental effect on the entire radiotherapy treatment and hence; the chance of cure or the risk of unnecessary side effects. Common guidelines and procedures create a common minimum standard and ground for evaluation and development. In Denmark, the treatment of head and neck cancer is organized within the multidisciplinary Danish Head and Neck Cancer Group (DAHANCA). The radiotherapy quality assurance group of DAHANCA organized a workshop in January 2020 with participants from oncology, radiology, and nuclear medicine from all centers in Denmark, treating patients with head and neck cancer. The participants agreed on a national guideline on imaging for target delineation in head and neck cancer radiotherapy, which has been approved by the DAHANCA group. The guidelines are available in the Supplementary. The use of multimodality imaging is being recommended for the planning of all radical treatments with a macroscopic tumor. 2-[18F]FDG-PET/CT should be available, preferable in the treatment position. The recommended MRI sequences are T1, T2 with and without fat suppression, and T1 with contrast enhancement, preferable in the treatment position. The interpretation of clinical information, including thorough physical examination as well as imaging, should be done in a multidisciplinary setting with an oncologist, radiologist, and nuclear medicine specialist. [ABSTRACT FROM AUTHOR]

Purpose Radiation-induced mucositis is a serious side effect, which can jeopardize treatment compliance and influence patient weight during treatment. The aim of this study was to develop a mathematical model to predict the risk of severe mucositis. Methods 535 curative radiotherapy H&N cancer patients from one institution between 2011 and 2015 were included. Doses were 66, 68 or 76 Gy in 33, 34 or 56fx. Patients were treated with IMRT/VMAT and mucosal reactions were scored weekly during radiotherapy. The highest observed score was used as endpoint and dichotomised in stage two stages: milder than confluent mucositis vs. confluent mucositis and worse. DVH of the extended oral cavity (Brower et al.) was extracted from the TPS. Principal component analysis was used to uncouple the highly correlated dose metrics ( V 5 , … , V 75 ) . Predictors available for the logistic model were the first 5 principal dose components, gender, weekly low dose chemotherapy, radiosensitizer, treatment acceleration, age, smoking status, tumour site, and volume of extended oral cavity. Parameter selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) within the statistical package R. The LASSO tuning parameter was chosen using 10-fold cross validation and 95% confidence interval found with 2000 bootstraps. Results Gender, acceleration, current smoker, tumour in the vicinity of the oral cavity, radiosensitizer, and the two first principal dose components were selected as predictors using Lasso. Acceleration is a well-known risk factor while the tumour position indicates an increased risk beyond the prediction related to the oral cavity dose. The protective value of being male and current smoker is in line with previous findings of toxicity in oesophagus and lung. The risk related to dose is dominated by the PC1. The model calibration plot (predicted vs observed risk) show good agreement with the line of identity. The bootstrap adjusted area under the curve (AUC) was 0.77 (95% CI 0.73–0.81). Conclusions A robust logistic regression model for prediction of radiation induced mucositis of H&N has been developed, which can be used as risk assessment of mucosal toxicity during treatment plan optimisation. The AUC value of 0.77 is significantly larger than previous published models on mucositis. [ABSTRACT FROM AUTHOR]