Evaluating synthetic CT from deformable registration in directed adaptive radiotherapy for head and neck cancer
In brief
Synthetic CT predicts need for adaptive replanning with 92% accuracy
In a retrospective study of 12 head-and-neck patients, the DART workflow generated synthetic CTs that matched replanning CTs within 1% dose and 2 mm geometry, achieving over 95% gamma pass rates. Using a 2 Gy change threshold, the synthetic CT identified patients who required plan adaptation with 92% sensitivity and specificity, potentially sparing unnecessary imaging and replans.
- Journal
- Journal of applied clinical medical physics (Q2)
- Published
- 1 August 2026
- Study design
- Cohort / observational study
- Evidence level
- Level 3, Low (CEBM 3b)
- Authors
- Jessica Lye, Kartik Kumar, Benjamin Harris, Jarrod Prohasky, Leah McDermott, Simon Goodall, et al.
- PMID
- 42581625
- DOI
- 10.1002/acm2.70732
Why clinicians should know about it
- Picked for Medical Physics (top studies of the week, 16 August 2026).
Abstract
BACKGROUND AND PURPOSEL: Anatomical changes over the many weeks of radiotherapy for Head and Neck cancer patients can compromise the original treatment plan, potentially increase the risk of side effects and impact outcomes. It is difficult to decide, based on daily imaging alone, which patients will most benefit from adapted treatment plans. This work presents an automated approach to evidence-based assessment of treatment plan robustness to anatomy changes. METHODS: Directed Adaptive Radiotherapy (DART) generates a synthetic CT for calculating dose changes in the treatment planning system (TPS). The process first enhances the CBCT, then uses a double fusion to insert the smaller field-of-view CBCT into the larger CT. The double fusion captures both neck tilt and weight loss changes, to accurately capture the position of the head and related critical organs. The deformed CT and contours are sent to TPS for recalculation of the original plan and quantify dose changes. A retrospective study was undertaken using 12 H&N patients who had a replanning CT during their treatment. The quality of the dose distributions calculated on synthetic CT and deformed contours were evaluated, along with the sensitivity and specificity of the synthetic CT as a predictor for adaptation. RESULTS: The contour and dose comparison between synthetic CT and clinical replan CT showed good agreement. The average Dice Similarity Coefficient (DSC) was > 80% for all contours, except for the sub-mandibular (> 75%) and excluding cochlea. The average mean distance-to-agreement (MDA) was < 2 mm, and all MDAs were < 3 mm. The average DVH differences were within 1%, and all dose differences were within 3%. The total gamma passing rates were > 95%. Both the sensitivity and specificity of the synthetic CT for predicting the need for adaptation were 92%, based on a tolerance of 2 Gy change for both target coverage and OAR dose constraint limits. CONCLUSIONS: By quantifying the impact of anatomical changes on dose distributions, the DART process helps determine whether a patient would benefit from adaptive replanning. The DART method improves efficiency by reducing unnecessary imaging and replanning when the treatment remains robust against anatomy changes.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.