Impact of range uncertainty on clinical distributions of linear energy transfer and biological effectiveness in proton therapy

In proton radiotherapy, range uncertainties can lead to differences between the clinically approved dose and that delivered to the patient. Likewise, the linear energy transfer (LET), which drives the relative biological effectiveness (RBE), is affected by range uncertainties. Clinical robust dose optimization ensures the delivery of the prescribed dose but not of a specific LET. In this study, the impact of range uncertainties on LET distributions in clinically robust dose-optimized treatment plans was quantified and potential biological implications in patients were assessed.
For each of six cancer patients (two brain, head-and-neck and prostate), two nominal treatment plans in pencil beam scanning mode were robustly dose-optimized using single- and multi-field optimization, respectively. Scenarios with range uncertainty of ± 3.5% were achieved by global rescaling of stopping-power ratios. Dose and LET distributions were recalculated using the nominal beam parameters and used to estimate the probability of radiation-induced toxicity.
The optimization technique had a minor impact on the results. For all patients, LET distributions in the target volume were rather homogeneous with average LET below 3.2 keV/µm and only a weak impact of range uncertainty was found. In contrast, LET hotspots (> 7 keV/µm) occurred in several organs at risk (OARs). Elevated and inhomogeneous LET distributions were organ- and patient-specific for OARs susceptible to range uncertainties. The observed changes in the probability for radiation-induced toxicity depended on OAR location and range uncertainty scenario.
Range uncertainties can substantially change LET values in OARs while the observed LET variation among all patients and scenarios was small in the CTV. The present findings support a constant RBE prescription in the CTV. However, unforeseen toxicity may occur in normal tissue due to elevated and inhomogeneous LET distributions caused by range uncertainty. We encourage LET-related objectives in robust optimization and consideration of range uncertainty in RBE assessment based on patient follow-up datasets.