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Hans Rabus

Publications and source records attributed to Hans Rabus.

At least 19 recordsLinked to original sources
arXiv2026

Prediction of biological radiation effects based on ionization clusters (nanodosimetry)

This article reviews approaches that link the formation of ionization clusters in nanometric volumes to radiobiological effectiveness. The corresponding models are presented using harmonized terminology and notation. They are categorized into three classes according to the most important, often implicit model rationale: (a) models that use a nanodosimetric weighting factor for biological effectiveness derived from frequency distributions of ionization clusters in a single target; (b) models that account for the synergistic effects of pairs of ionization clusters formed in different targets; (c) models that account for 'macroscopic' situations involving many nanometric targets and derive radiation quantities from the particle fluence. Further conceptual differences between the models and their underlying assumptions are discussed, such as the fact that some models are mechanistic while others only aim to elucidate correlations. Eventually, an attempt is made to identify the key open questions in this field that still need to be addressed.

physics.med-ph↗
arXiv2025

Active learning-based variance reduction for Monte Carlo simulations: A feasibility study for the nanodosimetry around a gold nanoparticle

Objective: This work presents a data-driven importance sampling-based variance reduction (VR) scheme inspired by active learning. The method is applied to the estimation of an optimal impact-parameter distribution in the calculation of ionization clusters around a gold nanoparticle (NP). Here, such an optimal importance distribution can not be inferred from principle. Approach: An iterative optimization procedure is set up that uses a Gaussian Process Sampler to propose optimal sampling distributions based on a loss function. The loss is constructed based on appropriate heuristics. The optimization code obtains estimates of the number of ionization clusters in shells around the NP by interfacing with a Geant4 simulation via a dedicated Transmission Control Protocol (TCP) interface. Main results: It is shown that the so-derived impact-parameter distribution easily outperforms the actual, uniform irradiation case. The results resemble those obtained with other VR schemes but do still slightly overestimate background contributions. Significance: While the method presented is a proof-of-principle, it provides a novel method of estimating importance distributions in ill-posed scenarios. The presented TCP interface described here is a simple and efficient method to expose compiled Geant4 code to other scripts, written for example, in Python.

physics.med-ph↗
arXiv2025

Cluster Dose Prediction in Carbon Ion Therapy: Using Transfer Learning from a Pretrained Dose Prediction U-Net

The cluster dose concept offers an alternative to the radiobiological effectiveness (RBE)-based model for describing radiation-induced biological effects. This study examines the application of a neural network to predict cluster dose distributions, with the goal of replacing the computationally intensive simulations currently required. Cluster dose distributions are predicted using a U-Net that was initially pretrained on conventional dose distributions. Using transfer learning techniques, the decoder path is adapted for cluster dose estimation. Both the training and pretraining datasets include head and neck regions from multiple patients and carbon ion beams of varying energies and positions. Monte Carlo (MC) simulations were used to generate the ground truth cluster dose distributions. The U-Net enables cluster dose estimation for a single pencil beam within milliseconds using a graphics processing unit (GPU). The predicted cluster dose distributions deviate from the ground truth by less than 0.35%. This proof-of-principle study demonstrates the feasibility of accurately estimating cluster doses within clinically acceptable computation times using machine learning (ML). By leveraging a pretrained neural network and applying transfer learning techniques, the approach significantly reduces the need for large-scale, computationally expensive training data.

physics.med-ph↗
arXiv2025

Cross-Section-Based Scaling Method for Material-Specific Cluster Dose Calculations -- A Proof of Concept

Cross-section data unavailability for non-water materials in track structure simulation software necessitates nanodosimetric quantity transformation from water to other materials. Cluster dose calculation transformation initially employed mass-density-based scaling - an approach resulting in a physically unrealistic material-independence of the cluster dose equation. This study introduces an alternative scaling method based on material-specific ionization cross-sections. The mean free path ratio of the materials for both the primary particles of the track structure simulation and for the secondary electrons served as the scaling factor. The approach was demonstrated through a cluster dose calculation for a carbon ion beam in a realistic head geometry and compared to the previous scaling method. The proposed cross-section-based scaling method resulted in a physically expected increase in cluster dose values for denser materials, which was not visible in the original scaling approach. The introduced scaling approach can be used to determine cluster dose distributions in heterogeneous geometries, a fundamental requirement for its integration into radiotherapy treatment planning frameworks.

physics.med-ph↗
arXiv2025

Exploring Machine Learning Models for Physical Dose Calculation in Carbon Ion Therapy Using Heterogeneous Imaging Data -- A Proof of Concept Study

Background: Accurate and fast dose calculation is essential for optimizing carbon ion therapy. Existing machine learning (ML) models have been developed for other radiotherapy modalities. They use patient data with uniform CT imaging properties. Purpose: This study investigates the application of several ML models for physical dose calculation in carbon ion therapy and compares their ability to generalize to CT data with varying resolutions. Among the models examined is a Diffusion Model, which is tested for the first time for the calculation of physical dose distributions. Methods: A dataset was generated using publicly available CT images of the head and neck region. Monoenergetic carbon ion beams were simulated at various initial energies using Geant4 simulation software. A U-Net architecture was developed for dose prediction based on distributions of material density in patients and of absorbed dose in water. It was trained as a Generative Adversarial Network (GAN) generator, a Diffusion Model noise estimator, and as a standalone network. Their performances were compared with two models from literature. Results: All models produced dose distributions deviating by less than 2% from that obtained by a full Monte Carlo simulation, even for a patient not seen during training. Dose calculation time on a GPU was in the range of 3 ms to 15 s. The resource-efficient U-Net appears to perform comparably to the more computationally intensive GAN and Diffusion Model. Conclusion: This study demonstrates that ML models can effectively balance accuracy and speed for physical dose calculation in carbon ion therapy. Using the computationally efficient U-Net can help conserve resources. The generalizability of the models to different CT image resolutions enables the use for different patients without extensive retraining.

physics.med-ph↗
arXiv2025

Do cell culturing influence the radiosensitizing effect of gold nanoparticles part 1: scrutinizing recent evidence for data consistency

In radiobiological experiments, the cells can either float in suspension or adhere to the walls of the sample holder. When irradiation is performed in the presence of dose modifying agents such as gold nanoparticles (AuNPs), the different shapes of the floating or adherent cells may imply a different dose to the nucleus, with biological consequences such as cell survival. Recently, it has been reported that the survival rate varies by up to a factor of 1.5 for the two cell geometries and by up to a factor of 2 for different orientation of the cells with respect to the incident beam. These results are examined in this paper and possible methodological issues are analyzed. This analysis shows that the simulation setup corresponds to the case of cells in the dose build-up region near the surface of a water phantom, where different depths result in different dose and survival probabilities. The validation of the simulations by comparison with experimental data is misleading, as the apparent agreement is due to a neglect of the quadratic term of the linear-quadratic survival model. The analysis further shows that the reported step-like changes between the survival predicted from the mean dose and the LEM could be explained by the fact that in the entire simulation only in one event an ionizing interaction of a photon took place in an AuNP. It is shown that the probability of this is in the permille range and that the total number of electrons leaving an AuNP, estimated from the reported electron spectrum, is three orders of magnitude higher than the value estimated from the expectation of photon interactions in the AuNPs. This contradiction would be resolved if the AuNP diameter in the simulations were a factor of 10 larger than intended. Another possible explanation for the discrepancies is a hidden bias in the simulation geometry, for example, if the distribution of AuNPs was non-uniform.

physics.med-ph↗
arXiv2025

Impact of metal nanoparticles on cell survival predicted by the local effect model for cells in suspension and tissue. Part 1: Theoretical framework

This work investigates the change in cell survival predicted by the local effect model (LEM) for an irradiated cell containing metal nanoparticles (MNPs) depending on the distribution of neighboring cells and the uptake of MNPs into the cells. In this first part of the paper, the theoretical framework is described, which is based on analytical weighting functions for the energy deposition around a single metal nanoparticle and radially symmetric distributions of MNPs. The weighting functions allow calculation of the radial profile of the absorbed dose in the cell nucleus as well as the mean dose and the mean square of the dose in the nucleus. The latter two quantities determine cell survival according to the LEM. The weighting functions are applied to isolated cells in a localized MNP distribution, cells in solution, and densely packed cells in tissue. It is shown that only for the idealistic case of complete uptake of MNPs it is sufficient to consider an isolated cell, as this otherwise leads to a significant underestimation in more realistic situations. In the case of cells in tissue, the MNP concentration within the range of secondary particles around the cell must be taken into account. Different packing densities of the cells may lead to values differing by up to 30% for the mean dose in the cell nucleus, depending on the conceived scenario for the uptake of MNPs. The weighting function offers a versatile method for assessing cell survival under irradiation in the presence of MNPs by the LEM, which is more general than previously reported approaches.

physics.med-ph↗
arXiv2025

Evaluation of the uncertainty in calculating nanodosimetric quantities due to the use of different interaction cross sections in Monte Carlo track structure codes

This study evaluates the uncertainty in nanodosimetric calculations caused by variations in interaction cross sections within Monte Carlo Track Structure (MCTS) simulation codes. Nanodosimetry relies on accurately simulating particle interactions at the molecular scale. Different MCTS codes employ distinct physical models and datasets for electron interactions in liquid water, a surrogate for biological tissues. The paper focuses on the Ionization Cluster Size Distribution (ICSD) generated by electrons of varying energies in nanometric volumes. Seven MCTS codes were tested using their native cross sections and a common dataset derived from averaging data used in the participating codes. The results reveal significant discrepancies among the codes in ICSDs and derived biologically relevant nanodosimetric quantities such as mean ionization numbers (M1) and probabilities of obtaining two or more ionizations (F2). The largest variations were observed for low-energy electrons, where the contribution from interaction cross sections dominates the overall uncertainties. For instance, M1 values for ICSDs of electron of 20 eV can differ by around 45 % (RSD) and 34 % (RSD) was found for F2 values of ICSDs of electrons of 50 eV. Using common cross sections substantially reduced the discrepancies, suggesting that cross section datasets are the primary source of variability. Finally, estimates of deoxyribonucleic acid (DNA) damage using the PARTRAC code highlight tht cross section variations have a non-negligible impact simulated biological outcomes, particularly for double-strand breaks (DSBs) Indeed, despite the fact that many other parameters in the simulation that can greatly differ from one code to another, the different interaction cross-sections studied in this work can lead to differences in the number of DSBs calculated with the PARTRAC code of up to 15%.

physics.med-ph↗
arXiv2024

On a revised concept of an event that allows linking nanodosimetry and microdosimetry in nanometric sites with macroscopic dosimetry

This work reviews the concepts of an event used in micro- and nanodosimetry and analyzes how single event distributions could theoretically be derived from probability distributions related to interactions of the primary particle which produce secondary electrons. It is shown that the corresponding mathematical expressions of conditional ionization cluster size distributions are alike those for the single event frequency distribution of energy imparted, particularly when all tracks are considered which intersect the volume in which interactions of the primary particle can result in energy deposits in the site. Track structure simulations of proton with energies between 1 MeV and 100 MeV are used to study how the occurrence of events depends on site size, beam radius, and proton energy. The range of impact parameters of particle tracks that contribute to energy imparted in a site appears not to depend on whether any energy deposits or only energy deposits by ionizations are considered. Since there is no longer a one-to-one correspondence between tracks passing a site and the occurrence of an event, it is proposed to use the fluence for which on average one event occurs as a substitute for single events. For protons, the product of this fluence and the site cross section or the average number of tracks necessary for an event shows an interesting dependence on site size and particle energy with asymptotic values close to unity for large sites and proton energies below 10 MeV. For a proton energy of 1 MeV, a minimum of the number of tracks is observed for sites between 5 nm and 10 nm diameter. The relative differences between the numbers of track per event on average obtained with different options of Geant4-DNA are in the order of 10 % and illustrate the need for further investigations into cross-section datasets and their uncertainties.

physics.med-ph↗
arXiv2024

Radial dependence of ionization clustering around a gold nanoparticle

This work explores the enhancement of ionization clusters around a gold nanoparticle (NP), indicative of the induction of DNA lesions, a potential trigger for cell-death. Monte Carlo track structure simulations were performed to determine (a) the fluence of incident photons and electrons in water around a gold NP under charged particle equilibrium conditions and (b) the density of ionization clusters produced on average as well as conditional on the occurrence of at least one interaction in the nanoparticle using Associated Volume Clustering. Absorbed dose was determined for comparison with a recent benchmark intercomparison. Reported quantities are normalized to primary fluence, allowing to establish a connection to macroscopic dosimetric quantities. The modification of the electron fluence spectrum by the gold NP is minor and mainly occurs at low energies. The net fluence of electrons emitted from the NP is dominated by electrons resulting from photon interactions. Smaller NPs cause noticeable peaks in the conditional frequency of clusters at distances around 50 nm to 100 nm from the NP surface. The number of clusters per energy imparted is increased at distances of up to 150 nm, and accordingly the enhancement in clustering notably surpasses that of dose enhancement. This work highlights the necessity of nanodosimetric analysis and suggests increased ionization clustering near the nanoparticles due to the emission of low energy Auger electrons. Whereas the electron component of the radiation field plays an important role in determining the background contribution to ionization clustering and energy imparted, the dosimetric effects of nanoparticles are governed by the interplay of secondary electron production by photon interaction (including low energy Auger electrons) and their ability to leave the nanoparticle.

physics.med-ph↗
arXiv2024

Nanodosimetric investigation of the track structure of therapeutic carbon ion radiation. Part 2: Detailed radiation transport and track structure simulation

Previously reported nanodosimetric measurements of therapeutic-energy carbon ions penetrating simulated tissue have produced results that are incompatible with the predicted mean energy of the carbon ions in the nanodosimeter and previous experiments with lower energy monoenergetic beams. The purpose of this study is to explore the origin of these discrepancies. Detailed simulations using the Geant4 toolkit were performed to investigate the radiation field in the nanodosimeter and provide input data for track structure simulations, which were performed with a developed version of the PTra code. The Geant4 simulations show that with the narrow-beam geometry employed in the experiment, only a small fraction of the carbon ions traverse the nanodosimeter and their mean energy is between 12 % and 30 % lower than the targeted values. Only about one-third or less of these carbon ions hit the trigger detector. The track structure simulations indicate that the observed enhanced ionization cluster sizes are mainly due to coincidences with events in which carbon ions miss the trigger detector. In addition, the discrepancies observed for high absorber thicknesses of carbon ions traversing the target volume could be explained by assuming an increase in thickness or interaction cross-sections in the order of 1 %. The results show that even with strong collimation of the radiation field, future nanodosimetric measurements of clinical carbon ion beams will require large trigger detectors to register all events with carbon ions traversing the nanodosimeter. Energy loss calculations of the primary beam in the absorbers are insufficient and should be replaced by detailed simulations when planning such experiments. Uncertainties of the interaction cross-sections in simulation codes may shift the Bragg peak position.

physics.med-ph↗
arXiv2024

Nanodosimetric investigation of the track structure of therapeutic carbon ion radiation. Part 1: Measurement of ionization cluster size distributions

At the Heidelberg Ion-Beam Therapy Center, the track structure of carbon ions of therapeutic energy after penetrating layers of simulated tissue was investigated for the first time. Measurements were conducted with carbon ion beams of different energies and polymethyl methacrylate (PMMA) absorbers of different thicknesses to realize different depths in the phantom along the pristine Bragg peak. Ionization cluster size (ICS) distributions resulting from the mixed radiation field behind the PMMA absorbers were measured using an ion-counting nanodosimeter. Two different measurements were carried out: (i) variation of the PMMA absorber thickness with constant carbon ion beam energy and (ii) combined variation of PMMA absorber thickness and carbon ion beam energy such that the kinetic energy of the carbon ions in the target volume is constant. The data analysis revealed unexpectedly high mean ICS values compared to stopping power calculations and the data measured at lower energies in earlier work. This suggests that in the measurements the carbon ion kinetic energies behind the PMMA absorber may have deviated considerably from the expected values obtained by the calculations. In addition, the results indicate the presence of a marked contribution of nuclear fragments to the measured ICS distributions, especially if the carbon ion does not cross the target volume.

physics.med-ph↗
arXiv2024

Intercomparison exercise on Monte Carlo simulations of electron spectra and energy depositions by a single gold nanoparticle under X-ray irradiation

Computational approaches, such as Monte Carlo (MC) radiation transport simulations, are used to estimate the dosimetric effects of GNPs, where results differing by orders of magnitudes have been reported by different investigators. This has motivated an intercomparison exercise, which was conducted as a joint activity of EURADOS Working Groups 6 "Computational Dosimetry" and 7 "Internal Dosimetry". The aim of this exercise was to determine the extent of such discrepancies between the results obtained by different researchers and different codes in a very simple simulation setup. Several individual EURADOS associate members and two code developer groups from outside Europe participated in this exercise applying seven different MC codes to perform the simulations of a simple defined geometry set-up of one single GNP irradiated in water by kilo-voltage X-rays. Two GNP diameters of 50 nm and 100 nm of were considered and two photon spectra as generated by X-ray tubes operated at 50 kV and 100 kV peak voltages. The geometry set-up and X-ray spectra were provided by the EURADOS task group. The participants were asked to determine for each combination of GNP size and X-ray spectrum the dose enhancement ratio (DER) of 10 nm-thick water shells up to 1000 nm and 1 $\mu$m-thick water shells up to 50 $\mu$m around the GNP. Furthermore, the electron spectra emitted from the GNP and the energy depositions in water shells around it were also to be reported. This EURADOS report summarizes the motivation and background for the exercise, the tasks to be solved, the codes used, the results reported by the participants, the consistency checks applied in their evaluation and a best estimates and uncertainty bands derived from the final results for the energy spectra of emitted electrons and the energy imparted in the vicinity of the GNP.

cond-mat.mtrl-sci↗
arXiv2023

Comment on "Investigation of the anisotropic distribution of microdosimetric quantities in the vicinity of X-ray-irradiated gold nanoparticles" by Derrien et al. [Radiation Physics and Chemistry 213, 111232 (2023)]

In their recent article, Derrien et al. (Derrien et al., 2023) study the anisotropy of microdosimetric quantities for spherical sites of several sizes placed around spherical gold nanoparticles of several diameters irradiated by monoenergetic photons. This comment points out that (1) the reported single event distributions of specific energy may be biased due to overcounting. (2) by considering only energy imparted by electrons produced in photon interactions in the nanoparticle, the magnitude of the anisotropy is overestimated by up to orders of magnitude with respect to an irradiation under conditions of secondary particle equilibrium.

physics.med-ph↗
arXiv2023

Article Commentary on "Microdosimetric and radiobiological effects of gold nanoparticles at therapeutic radiation energies" [T.M. Gray et al., IJRB 2023, 99(2), 308-317]

In the recently published article by T.M. Gray et al. "Microdosimetric and radiobiological effects of gold nanoparticles at therapeutic radiation energies" (IJRB 2023, 99(2), 308-317) results of Monte Carlo simulations and radiobiological assays on the dosimetric effects of gold nanoparticles were presented. This commentary points out that the results of the two parts of the study are in contradiction and that the predicted magnitude of dose enhancement and its dependence on the shape of the nanoparticle appear implausible. Possible reasons for these observations are discussed.

physics.med-ph↗
arXiv2023

Comment on "Comparing gold nano-particle enhanced radiotherapy with protons, megavoltage photons and kilovoltage photons: A Monte Carlo simulation" by Lin et al [Phys. Med. Biol. 59 (2014) 7675-7689]

In their article published in Phys. Med. Biol. 59 (2014) 7675-7689, Lin et al studied the dose enhancement of of gold nanoparticles (GNPs) for proton therapy, which they compared with the case of photon irradiation. This comment points out two caveats to the methodlogy used by Lin et al that may not be evident to readers and may contribute to confusion in the literature about the dose enhancement by gold nanoparticles.

physics.med-ph↗
arXiv2023

Comment on "Biological modeling of gold nanoparticle enhanced radiotherapy for proton therapy" by Lin et al. [Phys. Med. Biol. 60 (2015) 4149-4168]

In their article published in Phys. Med. Biol. 60 (2015) 4149-4168, Lin et al studied the radiosensitizing effect of gold nanoparticles (GNPs) using radiation transport simulations and a biological model for the survival of irradiated cells. This comment points out several caveats to the methodlogy used by Lin et al. that may not be evident to readers and may contribute to confusion in the literature about the radiation effects of gold nanoparticles. The two main caveats are the high mass fraction of gold considered and a potential problem with the modified local effect model used to predict cell survival.

physics.med-ph↗