A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam radiotherapy.

Objective.This study explores the use of neural networks (NNs) as surrogate models for Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LETd) of protons in proton-beam therapy based on the planned dose distribution and patient anatomy in the form of computed tomography (CT) images. As LETdis associated with variability in the relative biological effectiveness (RBE) of protons, we also evaluate the implications of using NN predictions for normal tissue complication probability (NTCP) models within a variable-RBE context.Approach.The predictive performance of three-dimensional NN architectures was evaluated using five-fold cross-validation on a cohort of brain tumor patients (n= 151). The best-performing model was identified and externally validated on patients from a different center (n= 107). LETdpredictions were compared to MC-simulated results in clinically relevant regions of interest. We assessed the impact on NTCP models by leveraging LETdpredictions to derive RBE-weighted doses, using the Wedenberg RBE model.Main results.We found NNs based solely on the planned dose distribution, i.e. without additional usage of CT images, can approximate MC-based LETddistributions. Root mean squared errors (RMSE) for the median LETdwithin the brain, brainstem, CTV, chiasm, lacrimal glands (ipsilateral/contralateral) and optic nerves (ipsilateral/contralateral) were 0.36, 0.87, 0.31, 0.73, 0.68, 1.04, 0.69 and 1.24 keV µm-1, respectively. Although model predictions showed statistically significant differences from MC outputs, these did not result in substantial changes in NTCP predictions, with RMSEs of at most 3.2 percentage points.Significance.The ability of NNs to predict LETdbased solely on planned dose distributions suggests a viable alternative to compute-intensive MC simulations in a variable-RBE setting. This is particularly useful in scenarios where MC simulation data are unavailable, facilitating resource-constrained proton therapy treatment planning, retrospective patient data analysis and further investigations on the variability of proton RBE.

Increased relative biological effectiveness and periventricular radiosensitivity in proton therapy of glioma patients.

PURPOSE: Currently, there is an intense debate on variations in intra-cerebral radiosensitivity and relative biological effectiveness (RBE) in proton therapy of primary brain tumours. Here, both effects were retrospectively investigated using late radiation-induced brain injuries (RIBI) observed in follow-up after proton therapy of patients with diagnosed glioma. METHODS: In total, 42 WHO grade 2-3 glioma patients out of a consecutive patient cohort having received (adjuvant) proton radio(chemo)therapy between 2014 and 2017 were eligible for analysis. RIBI lesions (symptomatic or clinically asymptomatic) were diagnosed and delineated on contrast-enhanced T1-weighted magnetic resonance imaging scans obtained in the first two years of follow-up. Correlation of RIBI location and occurrence with dose (D), proton dose-averaged linear energy transfer (LET) and variable RBE dose parameters were tested in voxel- and in patient-wise logistic regression analyses. Additionally, anatomical and clinical parameters were considered. Model performance was estimated through cross-validated area-under-the-curve (AUC) values. RESULTS: In total, 64 RIBI lesions were diagnosed in 21 patients. The median time between start of proton radio(chemo)therapy and RIBI appearance was 10.2 months. Median distances of the RIBI volume centres to the cerebral ventricles and to the clinical target volume border were 2.1 mm and 1.3 mm, respectively. In voxel-wise regression, the multivariable model with D, D × LET and periventricular region (PVR) revealed the highest AUC of 0.90 (95 % confidence interval: 0.89-0.91) while the corresponding model without D × LET revealed a value of 0.84 (0.83-0.86). In patient-level analysis, the equivalent uniform dose (EUD11, a = 11) in the PVR using a variable RBE was the most prominent predictor for RIBI with an AUC of 0.63 (0.32-0.90). CONCLUSIONS: In this glioma cohort, an increased radiosensitivity within the PVR was observed as well as a spatial correlation of RIBI with an increased RBE. Both need to be considered when delivering radio(chemo)therapy using proton beams.

Reduction of intrafraction pancreas motion using an abdominal corset compatible with proton therapy and MRI.

Background and purpose: Motion mitigation is of crucial importance in particle therapy (PT) of patients with abdominal tumors to ensure high-precision irradiation. Magnetic resonance imaging (MRI) is an excellent modality for target volume delineation and motion estimation of mobile soft-tissue tumors. Thus, the aims of this study were to develop an MRI- and PT-compatible abdominal compression device, to investigate its effect on pancreas motion reduction, and to evaluate patient tolerability and acceptance. Materials and methods: In a prospective clinical study, 16 patients with abdominal tumors received an individualized polyethylene-based abdominal corset. Pancreas motion was analyzed using time- and phase resolved MRI scans (orthogonal 2D-cine and 4D MRI) with and without compression by the corset. The pancreas was manually segmented in each MRI data set and the population-averaged center-of-mass motion in inferior-superior (IS), anterior-posterior (AP) and left-right (LR) directions was determined. A questionnaire was developed to investigate the level of patient acceptance of the corset, which the patients completed after acquisition of the planning computed tomography (CT) and MRI scans. Results: The corset was found to reduce pancreas motion predominantly in IS direction by on average 47 % - 51 % as found in the 2D-cine and 4D MRI data, respectively, while motion in the AP and LR direction was not significantly reduced. Most patients reported no discomfort when wearing the corset. Conclusion: An MRI- and PT-compatible individualized abdominal corset was presented, which substantially reduced breathing-induced pancreas motion and can be safely applied with no additional discomfort for the patients. The corset has been successfully integrated into our in-house clinical workflow for PT of tumors of the upper abdomen.