Suitability of propagated contours for adaptive replanning for head and neck radiotherapy

David Nash, Antony L. Palmer, Marcel van Herk, Alan McWilliam, Eliana Vasquez Osorio

Research output: Contribution to journalArticlepeer-review


Purpose: Adaptive radiotherapy relies on rapid recontouring for replanning. Contour propagation offers workflow efficiencies, but the impact of using unedited propagated OAR contours directly during re-optimisation is unclear. Methods: Plans for ten head and neck patients were created on the planning CT scan. OAR contours for the spinal cord, brainstem, parotids and larynx were then propagated to five shading-corrected CBCTs equally spaced throughout treatment using five commercial packages. Two reference contours were created on the CBCTs by (1) a clinician and (2) a geometric consensus from the propagated contours. Treatment plans were re-optimised on each CBCT for each set of contours, and the DVH statistic differences to the reference contours were calculated. The spread of DVH statistic differences between the 5th and 95th percentiles was quantified. Results: The spread of DVH statistic differences was 3.7 Gy compared to the clinician contour and 3.3 Gy compared to the consensus contour for the brainstem (and PRV) and 2.4 Gy and 2 Gy for the spinal cord (and PRV), across all 5 auto-contouring solutions. The parotids and larynx showed differences of 3.7 Gy compared to the clinician and 0.9 Gy to the consensus contour, with the larger difference for the clinician possibly caused by uncertainty in the clinician standard due to poor image quality on the CBCTs. Conclusions: Propagated OAR contours can be used safely for adaptive radiotherapy replanning, however, where organ doses are close to clinical tolerance then the contours should be reviewed for accuracy regardless of the propagation software used.

Original languageEnglish
Pages (from-to)66-72
Number of pages7
JournalPhysica Medica
Publication statusPublished - Oct 2022


  • Adaptive radiotherapy
  • Contour propagation
  • Deformable image registration
  • Non-rigid registration


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