A simulation framework for preclinical proton irradiation workflow.

The integration of proton beamlines with x-ray imaging/irradiation platforms has opened up possibilities for image-guided Bragg peak irradiations in small animals. Such irradiations allow selective targeting of normal tissue substructures and tumours. However, their small size and location pose challenges in designing experiments.

Yet anOther Dose Algorithm (YODA) for independent computations of dose and dose changes due to anatomical changes.

To assess the viability of a physics-based, deterministic and adjoint-capable algorithm for performing treatment planning system independent dose calculations and for computing dosimetric differences caused by anatomical changes.A semi-numerical approach is employed to solve two partial differential equations for the proton phase-space density which determines the deposited dose. Lateral hetereogeneities are accounted for by an optimized (Gaussian) beam splitting scheme.

Two-dimensional oxygen-diffusion modelling for FLASH proton therapy with pencil beam scanning-Impact of diffusive tissue properties, dose, dose rate and scan patterns.

Oxygen depletion is generally believed to play an important role in the FLASH effect-a differential reduction of the radiosensitivity of healthy tissues, relative to that of the tumour under ultra-high dose-rate (UHDR) irradiation conditions. In proton therapy (PT) with pencil-beam scanning (PBS), the deposition of dose, and, hence, the degree of (radiolytic) oxygen depletion varies both spatially and temporally. Therefore, the resulting oxygen concentration and the healthy-tissue sparing effect through radiation-induced hypoxia varies both spatially and temporally as well.

A Geant4 based simulation platform of the HollandPTC R&D proton beamline for radiobiological studies.

A Geant4 based simulation platform of the Holland Proton Therapy Centre (HollandPTC, Netherlands) R&D beamline (G4HPTC-R&D) was developed to enable the planning, optimisation and advanced dosimetry for radiobiological studies. It implemented a six parameter non-symmetrical Gaussian pencil beam surrogate model to simulate the R&D beamline in both a pencil beam and passively scattered field configuration. Three different experimental proton datasets (70 MeV, 150 MeV, and 240 MeV) of the pencil beam envelope evolution in free air and depth-dose profiles in water were used to develop a set of individual parameter surrogate functions to enable the modelling of the non-symmetrical Gaussian pencil beam properties with only the ProBeam isochronous cyclotron mean extraction proton energy as input.

Robustness analysis of CTV and OAR dose in clinical PBS-PT of neuro-oncological tumors: prescription-dose calibration and inter-patient variation with the Dutch proton robustness evaluation protocol.

. The Dutch proton robustness evaluation protocol prescribes the dose of the clinical target volume (CTV) to the voxel-wise minimum (VWmin) dose of 28 scenarios. This results in a consistent but conservative near-minimum CTV dose (D).

A hybrid multi-particle approach to range assessment-based treatment verification in particle therapy.

Particle therapy (PT) used for cancer treatment can spare healthy tissue and reduce treatment toxicity. However, full exploitation of the dosimetric advantages of PT is not yet possible due to range uncertainties, warranting development of range-monitoring techniques. This study proposes a novel range-monitoring technique introducing the yet unexplored concept of simultaneous detection and imaging of fast neutrons and prompt-gamma rays produced in beam-tissue interactions.

A probabilistic deep learning model of inter-fraction anatomical variations in radiotherapy.

. In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. To assess the need for adaptation, motion models can be used to simulate dominant motion patterns and assess anatomical robustness before delivery.

Deep learning-based segmentation of the thorax in mouse micro-CT scans.

For image-guided small animal irradiations, the whole workflow of imaging, organ contouring, irradiation planning, and delivery is typically performed in a single session requiring continuous administration of anaesthetic agents. Automating contouring leads to a faster workflow, which limits exposure to anaesthesia and thereby, reducing its impact on experimental results and on animal wellbeing. Here, we trained the 2D and 3D U-Net architectures of no-new-Net (nnU-Net) for autocontouring of the thorax in mouse micro-CT images.

How should we model and evaluate breathing interplay effects in IMPT?

Breathing interplay effects in Intensity Modulated Proton Therapy (IMPT) arise from the interaction between target motion and the scanning beam. Assessing the detrimental effect of interplay and the clinical robustness of several mitigation techniques requires statistical evaluation procedures that take into account the variability of breathing during dose delivery. In this study, we present such a statistical method to model intra-fraction respiratory motion based on breathing signals and assess clinical relevant aspects related to the practical evaluation of interplay in IMPT such as how to model irregular breathing, how small breathing changes affect the final dose distribution, and what is the statistical power (number of different scenarios) required for trustworthy quantification of interplay effects.

A semi-supervised autoencoder framework for joint generation and classification of breathing.

Background And Objective: One of the main problems with biomedical signals is the limited amount of patient-specific data and the significant amount of time needed to record the sufficient number of samples needed for diagnostic and treatment purposes. In this study, we present a framework to simultaneously generate and classify biomedical time series based on a modified Adversarial Autoencoder (AAE) algorithm and one-dimensional convolutions. Our work is based on breathing time series, with specific motivation to capture breathing motion during radiotherapy lung cancer treatments.

Accurate assessment of a Dutch practical robustness evaluation protocol in clinical PT with pencil beam scanning for neurological tumors.

Background And Purpose: Scenario-based robust optimization and evaluation are commonly used in proton therapy (PT) with pencil beam scanning (PBS) to ensure adequate dose to the clinical target volume (CTV). However, a statistically accurate assessment of the clinical application of this approach is lacking. In this study, we assess target dose in a clinical cohort of neuro-oncological patients, planned according to the DUPROTON robustness evaluation consensus, using polynomial chaos expansion (PCE).

Fast and fully-automated multi-criterial treatment planning for adaptive HDR brachytherapy for locally advanced cervical cancer.

Purpose: To develop and evaluate a fast, automated multi-criterial treatment planning approach for adaptive high-dose-rate (HDR) intracavitary + interstitial brachytherapy (BT) for locally advanced cervical cancer.

Methods And Materials: Twenty-two previously delivered single fraction MRI-based HDR treatment plans (SF) were used to guide training of our in-house system for multi-criterial autoplanning, aiming for an autoplan quality superior to the training plans, while respecting the clinically desired "pear-shaped" dose distribution. Next, the configured algorithm was used to automatically generate treatment plans for 63 other fractions (SF).

Fast and accurate sensitivity analysis of IMPT treatment plans using Polynomial Chaos Expansion.

The highly conformal planned dose distribution achievable in intensity modulated proton therapy (IMPT) can severely be compromised by uncertainties in patient setup and proton range. While several robust optimization approaches have been presented to address this issue, appropriate methods to accurately estimate the robustness of treatment plans are still lacking. To fill this gap we present Polynomial Chaos Expansion (PCE) techniques which are easily applicable and create a meta-model of the dose engine by approximating the dose in every voxel with multidimensional polynomials.

Robustness Recipes for Minimax Robust Optimization in Intensity Modulated Proton Therapy for Oropharyngeal Cancer Patients.

Purpose: We aimed to derive a "robustness recipe" giving the range robustness (RR) and setup robustness (SR) settings (ie, the error values) that ensure adequate clinical target volume (CTV) coverage in oropharyngeal cancer patients for given gaussian distributions of systematic setup, random setup, and range errors (characterized by standard deviations of Σ, σ, and ρ, respectively) when used in minimax worst-case robust intensity modulated proton therapy (IMPT) optimization.

Methods And Materials: For the analysis, contoured computed tomography (CT) scans of 9 unilateral and 9 bilateral patients were used. An IMPT plan was considered robust if, for at least 98% of the simulated fractionated treatments, 98% of the CTV received 95% or more of the prescribed dose.