Managing range and RBE variability in ART
The goal is to improve the safety and precision of proton therapy by managing variability in range and biological effectiveness.
Principal Investigator: Camilla Hanquist Stokkevåg
Team/collaborators: Kristian Smeland Ytre-Hauge (BioProton), Ilker Meric (NOVO)
Background
While a constant RBE of 1.1 is still used clinically, both experimental and computational studies have shown that the RBE is not fixed. It varies with factors such as LET, dose per fraction, tissue type, and biological endpoint. These variations are particularly relevant near the distal end of the proton beam, where LET increases and may lead to enhanced biological effect. If unaccounted for, this can result in unexpected normal tissue toxicity or insufficient tumor coverage.
Range uncertainties refer to the difference between where the proton beam is planned to stop and where it actually does. These discrepancies can be caused by factors such as CT calibration errors, variations in patient positioning, anatomical changes during treatment, and differences in tissue density. If the beam stops too early (undershoot), parts of the tumor may be underdosed. If it goes too far (overshoot), it can harm healthy tissue behind the tumor. Both situations can reduce treatment effectiveness or cause unintended side effects.
Goal
Improve the safety and precision of proton therapy by managing variability in range and biological effectiveness.
Approach
This WP focuses on integrating biological effectiveness and range monitoring into adaptive proton therapy. It investigates variability in RBE and LET during treatment and incorporates tools to track dose and range changes throughout therapy. RBE and LET evaluation will be implemented across adaptive workflows of increasing complexity, including approaches based on weekly repeat CTs, and daily CBCT-based planning. For each workflow, dose, LET, RBE, and range uncertainties will be calculated and accumulated over all treatment fractions.
Analyses will use the existing model framework developed in the BioProton project, applied to patient datasets from WP1 and WP2. This will support evaluation of biological dose effects and guide development of an optimization workflow using CBCT data.
In parallel, the WP will develop adaptive strategies that incorporate real-time range feedback during treatment. This will begin with a trigger-based system to pause delivery if recorded parameters fall outside defined thresholds, with the long-term goal of enabling rapid plan adaptation based on in vivo range signals.
Impact
Enhance treatment precision and safety by reducing risks from range and RBE variability in ART.