An online adaptive plan library approach for intensity modulated proton therapy for head and neck cancer.

Radiother Oncol

Erasmus MC Cancer Institute, Department of Radiation Oncology, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands; Holland Proton Therapy Center, Department of Medical Physics & Informatics, Delft, The Netherlands.

Published: November 2022

Background And Purpose: In intensity modulated proton therapy (IMPT), the impact of setup errors and anatomical changes is commonly mitigated by robust optimization with population-based setup robustness (SR) settings and offline replanning. In this study we propose and evaluate an alternative approach based on daily plan selection from patient-specific pre-treatment established plan libraries (PLs). Clinical implementation of the PL strategy would be rather straightforward compared to daily online re-planning.

Materials And Methods: For 15 head-and-neck cancer patients, the planning CT was used to generate a PL with 5 plans, robustly optimized for increasing SR: 0, 1, 2, 3, 5 mm, and 3% range robustness. Repeat CTs (rCTs) and realistic setup and range uncertainty distributions were used for simulation of treatment courses for the PL approach, treatments with fixed SR (fSR) and a trigger-based offline adaptive schedule for 3 mm SR (fSROfA). Daily plan selection in the PL approach was based only on recomputed dose to the CTV on the rCT.

Results: Compared to using fSR and fSROfA, the risk of xerostomia grade ≥ II & III and dysphagia ≥ grade III were significantly reduced with the PL. For 6/15 patients the risk of xerostomia and/or dysphagia ≥ grade II could be reduced by > 2% by using PL. For the other patients, adherence to target coverage constraints was often improved. fSROfA resulted in significantly improved coverage compared to PL for selected patients.

Conclusion: The proposed PL approach resulted in overall reduced NTCPs compared to fSR and fSROfA at limited cost in target coverage.

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Source
http://dx.doi.org/10.1016/j.radonc.2022.09.011DOI Listing

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