119 Redundant tooth loss prior to head and neck radiotherapy 5 Extrapolation of the results described here is difficult since it is linked to the RT technique used (3D RT, IMRT or VMAT) and to the local experience in aspects of treatment planning with consequent differences in sparing of normal tissues. Therefore, in addition to properly assessing the tumor location and the location of the positive lymph nodes, good consultation with the radiation-oncologist remains of great clinical importance. Future research to define a true radiation dose cut-off point for ORN in the head and neck area is needed to achieve a potential further de-escalation in preventive measures with the result of a functional destruction of the masticatory organ. Thereby, it is important that it is clearly described whether the mean or the maximum dose must be used. Artificial intelligence (AI) algorithms using Deep Learning (DL) may be able to accurately predict the radiation dose for new patients, based on an input of cohorts of previously treated cases with imaging and dose to the teeth available. This would allow a fast and reliable dose-prediction based on CT imaging, without the need to await the results of the labor-intensive manual treatment planning process [38, 39].
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