Linear Energy Transfer and Relative Biological Effectiveness Investigation of Various Structures for a Cohort of Proton Patients With Brain Tumors

Ana Vaniqui; Femke Vaassen; Dario Di Perri; Daniëlle Eekers; Inge Compter; Ilaria Rinaldi; Wouter van Elmpt; Mirko Unipan

doi:10.1016/j.adro.2022.101128

Linear Energy Transfer and Relative Biological Effectiveness Investigation of Various Structures for a Cohort of Proton Patients With Brain Tumors

Adv Radiat Oncol. 2022 Nov 26;8(2):101128. doi: 10.1016/j.adro.2022.101128. eCollection 2023 Mar-Apr.

Authors

Ana Vaniqui¹, Femke Vaassen¹, Dario Di Perri¹, Daniëlle Eekers¹, Inge Compter¹, Ilaria Rinaldi¹, Wouter van Elmpt¹, Mirko Unipan¹

Affiliation

¹ Department of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Centre, Maastricht, The Netherlands.

Abstract

Purpose: The current knowledge on biological effects associated with proton therapy is limited. Therefore, we investigated the distributions of dose, dose-averaged linear energy transfer (LET_d), and the product between dose and LET_d (DLET_d) for a patient cohort treated with proton therapy. Different treatment planning system features and visualization tools were explored.

Methods and materials: For a cohort of 24 patients with brain tumors, the LET_d, DLET_d, and dose was calculated for a fixed relative biological effectiveness value and 2 variable models: plan-based and phenomenological. Dose threshold levels of 0, 5, and 20 Gy were imposed for LET_d visualization. The relationship between physical dose and LET_d and the frequency of LET_d hotspots were investigated.

Results: The phenomenological relative biological effectiveness model presented consistently higher dose values. For lower dose thresholds, the LET_d distribution was steered toward higher values related to low treatment doses. Differences up to 26.0% were found according to the threshold. Maximum LET_d values were identified in the brain, periventricular space, and ventricles. An inverse relationship between LET_d and dose was observed. Frequency information to the domain of dose and LET_d allowed for the identification of clusters, which steer the mean LET_d values, and the identification of higher, but sparse, LET_d values.

Conclusions: Identifying, quantifying, and recording LET distributions in a standardized fashion is necessary, because concern exists over a link between toxicity and LET hotspots. Visualizing DLET_d or dose × LET_d during treatment planning could allow for clinicians to make informed decisions.