A traffic light protocol workflow for image-guided adaptive radiotherapy in lung cancer patients

Djoya Hattu*, Jolein Mannens, Michel Öllers, Judith van Loon, Dirk De Ruysscher, Wouter van Elmpt

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


BACKGROUND AND PURPOSE: Image-guided radiotherapy using cone beam-CT (CBCT) images is used to evaluate patient anatomy and positioning before radiotherapy. In this study we analyzed and optimized a traffic light protocol (TLP) used in lung cancer patients to identify patients requiring treatment adaptation.

MATERIALS AND METHODS: First, CBCT review requests of 243 lung cancer patients were retrospectively analyzed and divided into 6 pre-defined categories. Frequencies and follow-up actions were scored. Based on these results, the TLP was optimized and evaluated in the same way on 230 patients treated in 2018.

RESULTS: In the retrospective study, a total of 543 CBCT review requests were created during treatment in 193/243 patients due to changed anatomy of lung (24%), change of tumor volume (24%), review of match (18%), shift of the mediastinum (15%), shift of tumor (15%) and other (4%). The majority of requests (474, 87%) did not require further action. In 6% an adjustment of the match criteria sufficed; in 7% treatment plan adaptation was required. Plan adaptation was frequently seen in the categories changed anatomy of lung, change of tumor volume and shift of tumor outside the PTV. Shift of mediastinum outside PRV and shift of GTV outside CTV (but inside PTV) never required plan adaptation and were omitted to optimize the TLP, which reduced the CBCT review requests by 23%.

CONCLUSIONS: The original TLP selected patients that required a treatment adaptation, but with a high false positive rate. The optimized TLP reduced the amount of CBCT review requests, while still correctly identifying patients requiring adaptation.

Original languageEnglish
Pages (from-to)152-158
Number of pages7
JournalRadiotherapy and Oncology
Early online date3 Sept 2022
Publication statusPublished - Oct 2022

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