An automated cone-beam CT dosimetric assessment pipeline for adaptive head and neck radiotherapy

Abstract Background and purpose: Adaptive radiotherapy (ART) is commonly used to mitigate effects of anatomical change during head and neck (H&N) radiotherapy. The process of identifying patients for ART can be subjective and resource-intensive. This feasibility project aims to design and validate a pipeline to automate the process and use it to assess the current clinical pathway for H&N treatments. Methods: The pipeline analysed patients’ on-set cone-beam CT (CBCT) scans to identify inter-fractional anatomical changes. CBCTs were converted into synthetic CTs, contours were automatically generated, and the original plan was recomputed. Each synthetic CT was evaluated against a set of dosimetric goals, with failed goals causing an ART recommendation. To validate pipeline performance, a ‘gold standard’ was synthesised by recomputing patients’ original plans on a rescan-CT acquired during treatment and identifying failed clinical goals. The pipeline sensitivity and specificity compared to this ‘gold standard’ were calculated for 12 ART patients. The pipeline was then run on a cohort of 12 ART and 14 non-ART patients, and its sensitivity and specificity were instead calculated against the clinical decision made. Results: The pipeline showed good agreement with the synthesised ‘gold standard’ with an optimum sensitivity of 0·83 and specificity of 0·67. When run over a cohort containing both ART and non-ART patients and assessed against the subjective clinical decision made, the pipeline showed no predictive power (sensitivity: 0·58, specificity: 0·47). Conclusions: Good agreement with the ‘gold standard’ gives confidence in pipeline performance and disagreement with clinical decisions implies implementation could help standardise the current clinical pathway.