Fakultät für Physik

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The dirty and clean dose concept: towards creating proton therapy treatment plans with a photon-like dose response
(2023-10-25) Heuchel, Lena; Hahn, Christian; Ödén, Jakob; Traneus, Erik; Wulff, Jörg; Timmermann, Beate; Bäumer, Christian; Lühr, Armin
Background: Applying tolerance doses for organs at risk (OAR) from photon therapy introduces uncertainties in proton therapy when assuming a constant relative biological effectiveness (RBE) of 1.1. Purpose: This work introduces the novel dirty and clean dose concept, which allows for creating treatment plans with a more photon-like dose response for OAR and, thus, less uncertainties when applying photon-based tolerance doses. Methods: The concept divides the 1.1-weighted dose distribution into two parts: the clean and the dirty dose. The clean and dirty dose are deposited by protons with a linear energy transfer (LET) below and above a set LET threshold, respectively. For the former, a photon-like dose response is assumed, while for the latter, the RBE might exceed 1.1. To reduce the dirty dose in OAR, a MaxDirtyDose objective was added in treatment plan optimization. It requires setting two parameters: LET threshold and max dirty dose level. A simple geometry consisting of one target volume and one OAR in water was used to study the reduction in dirty dose in the OAR depending on the choice of the two MaxDirtyDose objective parameters during plan optimization. The best performing parameter combinations were used to create multiple dirty dose optimized (DDopt) treatment plans for two cranial patient cases. For each DDopt plan, 1.1-weighted dose, variable RBE-weighted dose using the Wedenberg RBE model and dose-average LETd distributions as well as resulting normal tissue complication probability (NTCP) values were calculated and compared to the reference plan (RefPlan) without MaxDirtyDose objectives. Results: In the water phantom studies, LET thresholds between 1.5 and 2.5 keV/µm yielded the best plans and were subsequently used. For the patient cases, nearly all DDopt plans led to a reduced Wedenberg dose in critical OAR. This reduction resulted from an LET reduction and translated into an NTCP reduction of up to 19 percentage points compared to the RefPlan. The 1.1-weighted dose in the OARs was slightly increased (patient 1: 0.45 Gy(RBE), patient 2: 0.08 Gy(RBE)), but never exceeded clinical tolerance doses. Additionally, slightly increased 1.1-weighted dose in healthy brain tissue was observed (patient 1: 0.81 Gy(RBE), patient 2: 0.53 Gy(RBE)). The variation of NTCP values due to variation of α/β from 2 to 3 Gy was much smaller for DDopt (2 percentage points (pp)) than for RefPlans (5 pp). Conclusions: The novel dirty and clean dose concept allows for creating biologically more robust proton treatment plans with a more photon-like dose response. The reduced uncertainties in RBE can, therefore, mitigate uncertainties introduced by using photon-based tolerance doses for OAR.
Mode-multiplexing deep-strong light-matter coupling
(2024-02-28) Mornhinweg, Joshua; Diebel, Laura Katharina; Halbhuber, Maike; Prager, Michael; Riepl, Josef; Inzenhofer, Tobias; Bougeard, Dominique; Huber, Rupert; Lange, Christoph
Dressing electronic quantumstates with virtual photons creates exotic effects ranging from vacuum-field modified transport to polaritonic chemistry, and squeezing or entanglement of modes. The established paradigm of cavity quantum electrodynamics maximizes the light-matter coupling strength ΩR=ωc, defined as the ratio of the vacuumRabi frequency and the frequency of light, by resonant interactions. Yet, the finite oscillator strength of a single electronic excitation sets a natural limit to ΩR=ωc. Here, we enter a regime of record-strong light-matter interaction which exploits the cooperative dipole moments of multiple, highly non-resonant magnetoplasmon modes tailored by ourmetasurface. This creates an ultrabroadband spectrum of 20 polaritons spanning 6 optical octaves, calculated vacuum ground state populations exceeding 1 virtual excitation quantum, and coupling strengths equivalent to ΩR=ωc =3:19. The extreme interaction drives strongly subcycle energy exchange between multiple bosonic vacuum modes akin to high-order nonlinearities, and entangles previously orthogonal electronic excitations solely via vacuum fluctuations.
Unveiling the interplay of Mollow physics and perturbed free induction decay by nonlinear optical signals of a dynamically driven two-level system
(2024-05-13) Kaspari, Jan M.; Bracht, Thomas K.; Boos, Katarina; Kim, Sang Kyu; Sbresny, Friedrich; Müller, Kai; Reiter, Doris E.
Nonlinear optical signals in optically driven quantum systems can reveal coherences and thereby open up the possibility for manipulation of quantum states. While the limiting cases of ultrafast and continuous-wave excitation have been extensively studied, the time dynamics of finite pulses bear interesting phenomena. In this paper, we explore the nonlinear optical probe signals of a two-level system excited with a laser pulse of finite duration. In addition to the prominent Mollow peaks, the probe spectra feature several smaller peaks for certain time delays. Similar features have been recently observed for resonance fluorescence signals [K. Boos et al., Phys. Rev. Lett. 132, 053602 (2024)]. We discuss that the emergent phenomena can be explained by a combination of Mollow triplet physics and perturbed free induction decay effects, providing an insightful understanding of the underlying physics.
FLASH radiotherapy sparing effect on the circulating lymphocytes in pencil beam scanning proton therapy: impact of hypofractionation and dose rate
(2024-01-05) Galts, Antje; Hammi, Abdelkhalek
Purpose. The sparing effect of ultra-high dose rate (FLASH) radiotherapy has been reported, but its potential to mitigate depletion of circulating blood and lymphocytes (CL) has not been investigated in pencil-beam scanning-based (PBS) proton therapy, which could potentially reduce the risk of radiation-induced lymphopenia. Material and methods. A time-dependent framework was used to score the dose to the CL during the course of radiotherapy. For brain patients, cerebral vasculatures were semi-automatic segmented from 3T MR-angiography data. A dynamic beam delivery system was developed capable of simulating spatially varying instantaneous dose rates of PBS treatment plans, and which is based on realistic beam delivery parameters that are available clinically. We simulated single and different hypofractionated PBS intensity modulated proton therapy (IMPT) FLASH schemes using 600 nA beam current along with conventionally fractionated IMPT treatment plan at 2 nA beam current. The dosimetric impact of treatment schemes on CL was quantified, and we also evaluated the depletion in subsets of CL based on their radiosensitivity. Results. The proton FLASH sparing effect on CL was observed. In single-fraction PBS FLASH, just 1.5% of peripheral blood was irradiated, whereas hypofractionated FLASH irradiated 7.3% of peripheral blood. In contrast, conventional fractionated IMPT exposed 42.4% of peripheral blood to radiation. PBS FLASH reduced the depletion rate of CL by 69.2% when compared to conventional fractionated IMPT. Conclusion. Our dosimetric blood flow model provides quantitative measures of the PBS FLASH sparing effect on the CL in radiotherapy for brain cancer. FLASH Single treatment fraction offers superior CL sparing when compared to hypofractionated FLASH and conventional IMPT, supporting assumptions about reducing risks of lymphopenia compared to proton therapy at conventional dose rates. The results also indicate that faster conformal FLASH delivery, such as passive patient-specific energy modulation, may further enhance the sparing of the immune system.
Light sterile neutrinos in the early universe: effects of altered dispersion relations and a coupling to axion-like dark matter
(2023-11-13) Hellmann, Dominik; Päs, Heinrich
We investigate the cosmological consequences of light sterile neutrinos with altered dispersion relations (ADRs) and couplings to an ultra-light, axion-like scalar field. In particular we study the impact on the number of additional, light, fermionic degrees of freedom and primordial nucleosynthesis. While the ADR leads to a new potential term in the Hamiltonian, the coupling to the scalar field results in a time dependent, effective mass contribution. We solve the quantum kinetic equations (QKEs) for the neutrino density matrix and find that in certain parameter regions both new physics effects can individually yield a suppressed population of sterile neutrino species and the correct observed amount of helium in nucleosynthesis. Combining both effects opens up new patches of parameter space excluded by experimental bounds applying to models featuring only one of the effects.
4D dosimetric-blood flow model: impact of prolonged fraction delivery times of IMRT on the dose to the circulating lymphocytes
(2023-07-12) Hammi, Abdelkhalek
To investigate the impact of prolonged fraction delivery of modern intensity-modulated radiotherapy (IMRT) on the accumulated dose to the circulating blood during the course of fractionated radiation therapy. We have developed a 4D dosimetric blood flow model (d-BFM) capable of continuously simulating the blood flow through the entire body of the cancer patient and scoring the accumulated dose to blood particles (BPs). We developed a semi-automatic approach that enables us to map the tortuous blood vessels of the surficial brain of individual patients directly from standard magnetic resonance imaging data of the patient. For the rest of the body, we developed a fully-fledged dynamic blood flow transfer model according to the International Commission on Radiological Protection human reference. We proposed a methodology enabling us to design a personalized d-BFM, such it can be tailored for individual patients by adopting intra- and inter-subject variations. The entire circulatory model tracks over 43 million BPs and has a time resolution of = 10−3 s. A dynamic dose delivery model was implemented to emulate the spatial and temporal time-varying pattern of the dose rate during the step-and-shoot mode of IMRT. We evaluated how different configurations of the dose rate delivery, and a time prolongation of fraction delivery may impact the dose received by the circulating blood (CB).Our calculations indicate that prolonging the fraction treatment time from 7 to 18 min will augment the blood volume receiving any dose from 36.1% to 81.5% during one single fraction. The results indicate that increasing the segment number has only a negligible effect on the irradiated blood volume, when the fraction time is kept identical. We developed a novel concept of customized 4D d-BFM that can be tailored to the hemodynamics of individual patients to quantify dose to the CB during fractionated radiotherapy. The prolonged fraction delivery and the variability of the instantaneous dose rate have a significant impact on the accumulated dose distribution during IMRT treatments. This impact should be considered during IMRT treatments design to reduce RT-induced immunosuppressive effects.
Data-driven ion-independent relative biological effectiveness modeling using the beam quality Q
(2023-05-08) Tian, Liheng; Lühr, Armin
Beam quality Q = Z2/E (Z = ion charge, E = energy), an alternative to the conventionally used linear energy transfer (LET), enables ion-independent modeling of the relative biological effectiveness (RBE) of ions. Therefore, the Q concept, i.e. different ions with similar Q have similar RBE values, could help to transfer clinical RBE knowledge from better-studied ion types (e.g. carbon) to other ions. However, the validity of the Q concept has so far only been demonstrated for low LET values. In this work, the Q concept was explored in a broad LET range, including the so-called overkilling region. The particle irradiation data ensemble (PIDE) was used as experimental in vitro dataset. Data-driven models, i.e. neural network (NN) models with low complexity, were built to predict RBE values for H, He, C and Ne ions at different in vitro endpoints taking different combinations of clinically available candidate inputs: LET, Q and linear-quadratic photon parameter αx/βx. Models were compared in terms of prediction power and ion dependence. The optimal model was compared to published model data using the local effect model (LEM IV). The NN models performed best for the prediction of RBE at reference photon doses between 2 and 4 Gy or RBE near 10% cell survival, using only αx/βx and Q instead of LET as input. The Q model was not significantly ion dependent (p > 0.5) and its prediction power was comparable to that of LEM IV. In conclusion, the validity of the Q concept was demonstrated in a clinically relevant LET range including overkilling. A data-driven Q model was proposed and observed to have an RBE prediction power comparable to a mechanistic model regardless of particle type. The Q concept provides the possibility of reducing RBE uncertainty in treatment planning for protons and ions in the future by transferring clinical RBE knowledge between ions.
Paddle-wheel mechanism in doped succinonitrile–glutaronitrile plastic electrolyte: a joint magnetic resonance, dielectric, and viscosimetry study of Li ion translational and molecular reorientational dynamics
(2023-03-16) Lansab, Sofiane; Grabe, Bastian; Böhmer, Roland
Mixtures of 60% SN (succinonitrile) and 40% GN (glutaronitrile) doped with LiTFSI or LiPF6 at different concentrations are investigated using dielectric spectroscopy. Room temperature conductivities up to 10−3 S cm−1 are measured along with an overall conductivity enhancement of almost five decades compared to pure SN. Additionally, the dynamics of the methylene (CD2) groups of SN and that of the Li+ ions within the mixture are studied in a wide temperature range using 2H and 7Li NMR relaxometry, respectively. Static-field-gradient proton NMR combined with viscosity measurements probe the molecular diffusion. GN addition and Li doping both enhance the electrical conductivity significantly, while leaving the reorientational motion within the matrix essentially unchanged. The times scales and thus the effective energy barriers characterizing the Li ion motion as well as the molecular reorientations are very similar in the liquid and in the plastic phases, findings that argue in favor of the presence of a paddle-wheel mechanism.
Towards reducing uncertainties in the applied effective dose for two specialized radiotherapy techniques
(2023) Heuchel, Lena; Lühr, Armin; Bäumer, Christian
Radiotherapy is a high-precision treatment of malignant diseases. However, for some specialized techniques, e.g., total body irradiation (TBI) and proton therapy, considerable uncertainties remain regarding the applied effective dose. For some TBI techniques, no CT-based treatment planning is performed, therefore 3D dose distributions are unavailable. For proton therapy, the relative biological effectiveness (RBE) compared to standard photon irradiation is variable and subject to high uncertainties, particularly at the end of the proton range. Clinically, however, a constant RBE of 1.1 is assumed, since precise knowledge of the RBE distribution in patients, and therefore of the applied biological effective dose, is lacking. Two surveys among German and European clinics were performed to analyze the current clinical practice for TBI and proton therapy, respectively. These surveys showed that participating centers wish for new and improved guidelines for treatment planning, but important tools for analyzing the needed clinical data are missing. Therefore, these necessary tools were developed and tested by performing in silico patient irradiation studies. For TBI, a Monte Carlo-based simulation workflow was developed allowing for 3D dose calculations for non-CT-based TBI techniques. For proton therapy, a novel concept was introduced allowing for the reduction of dose components associated with high RBE uncertainties.
Ultrafast coherent lattice dynamics coupled to spins in the van der Waals antiferromagnet FePS3
(2023) Mertens, Fabian; Cinchetti, Mirko; Akimov, Ilya
2D materials, like the antiferromagnetic van der Waals semiconductors FePS3 studied in this work, open up new possibilities for technological applications due to the unique interaction of their magnetization with electronic, optical, and mechanical properties. Furthermore, they provide the potential to study magnetism and magnetization dynamics in reduced dimensions. Up do date, the coherent control of the magnetization of these materials has barely been studied. Our research addresses this gap by using ultrashort light pulses. In this context, time-resolved studies can give an insight into the evolution of the light-induced dynamics, which essentially require a dedicated experimental setup. In this thesis, we present a comprehensive study on the development and application of a table-top laser setup designed for magneto-optical pump-probe experiments and adaptable for the investigation of microscopic samples. The system employs two optical parametric amplifiers, with a tunable photon-energy range of 0.5 eV - 3.5 eV for both the pump and the probe beam. Remarkable is the high pump amplitude modulation rate at 50 % of the laser repetition rate, realized via the integration of an electro-optical modulator, blocking every second pump pulse. Combined with a high-frequency digitizer, performing single pulse detection, our system can achieve a high sensitivity, down to 50 µdeg of the probe polarization rotation. The setup can apply magnetic fields of up to ±9 T, and voltages in the kV regime while providing a temperature control between 4 K-420 K. The functionality of the setup’s systems is demonstrated by performing static Kerrrotation and ultrafast demagnetization measurements in a cobalt single crystal as a function of the most important experimental parameters. The major part of this thesis is dedicated to our studies on a coherent optical lattice mode of terahertz frequency triggered by femtosecond laser pulses in the antiferromagnetic van der Waals semiconductor FePS3 . This specific 3.2 THz phonon mode shows a close relation to the antiferromagnetic order, as it vanishes above the Néel temperature and hybridizes with a magnon mode in the presence of a magnetic field. We investigate it as a function of sample temperature, probe polarization, excitation photon energy and externally applied magnetic fields. The resonant excitation of a crystal-field split electronic ..-.. transition efÏciently pumps the displacive excitation process of the mode, while the magnetic linear dichroism is identified as the magneto-optical effect, which reflects the phonon mode in the probe rotation. By applying magnetic fields of up to 9 T we can generate and observe the coherent hybridized phonon-magnon mode, thus exploiting the hybridization to excite coherent spin-dynamics. Furthermore, we investigate the coherent phonons in the bulk form of FePS3 and in an exfoliated flake with a thickness of 380 nm.
Modulation of the transient magnetization of an EuO/Co bilayer by controlled optical excitation
(2023) Mönkebüscher, David; Cinchetti, Mirko; Müller, Martina
Der ferromagnetische Halbleiter Europiummonoxid (EuO) gilt als vielversprechender Kandidat für neuartige spintronische Anwendungen, da er ein großes magnetisches Moment und starke magneto-optische Effekte mit isolierenden Eigenschaften vereint. Obwohl EuO mit T_C = 69 K die höchste Curie-Temperatur unter den Europiumchalkogeniden aufweist, ist sie für kommerzielle Anwendungen zu niedrig. Viele Ansätze zur Erhöhung von T_C, wie zum Beispiel die Dotierung mit Gd-Ionen oder epitaktische Verformung, wurden bereits erfolgreich untersucht. Jedoch basieren sie alle auf einer Veränderung der Stöchiometrie und Leitfähigkeit des Seltenerdoxids. Das Ausnutzen des Proximity-Effektes könnte eine alternative Herangehensweise für das starke Erhöhen der magnetischen Ordnungstemperatur von EuO darstellen, die gleichzeitig dessen intrinsischen Eigenschaften bewahrt. Dieser Effekt beruht auf der Kopplung an einen Ferromagneten mit hoher Curie-Temperatur und ist in der Literatur für ähnliche System bereits demonstriert worden. In dieser Arbeit wird ein EuO/Co-Zweischichtsystem dünner Filme mittels des statischen und zeitaufgelösten magneto-optischen Kerr-Effekts (MOKE) untersucht, um einen Nachweis für eine erhöhte Curie-Temperatur von EuO aufgrund der Nähe zum Übergangsmetall Co zu finden. Des Weiteren wird der Einfluss von Co auf die Spindynamik von EuO untersucht. Statische Messungen der Hysterese der EuO/Co-Probe zeigen eine antiferromagnetische Kopplung zwischen den beiden ferromagnetischen Schichten. Aufgrund der Überlagerung des Signals beider Schichten übersteigt die Co-Hysterese einen möglichen Restbeitrag von EuO bei erhöhten Temperaturen. Zeitaufgelöste MOKE-Messungen zeigen eine transiente Verstärkung der EuO-Magnetisierung, die auch dann auftritt, wenn selektiv nur das Übergangsmetall angeregt wird. Dieses Verhalten wird auf die Erzeugung eines superdiffusven Spinstroms von Majoritätselektronen bei der Entmagnetisierung der Co-Schicht zurückgeführt. Der Spinstrom breitet sich in Richtung der EuO-Schicht aus, um deren 5d-Zustände zu besetzen, was zu einer ähnlichen Magnetisierungsverstärkung wie bei einer direkten Photoanregung des Seltenerdoxids führt. Die Beiträge beider Schichten zur transienten Spindynamik zeigen entgegengesetze Vorzeichen. Daher bietet die EuO/Co-Probe ein System, in dem die transiente Kerr-Rotation durch Variation externer Parameter wie der Probentemperatur, des angelegten Magnetfelds und der Pumpstrahlfluenz beeinflusst werden kann. Durch eine starke Anregung der Co-Schicht wird ihre Magnetisierung signifikant verringert, wodurch die Hysterese der EuO-Schicht bei transienten Hysteresemessungen zugänglich wird. Sie ist auch noch bei einer Temperatur von 300 K zu beobachten, was auf eine starke Erhöhung der magnetischen Ordnungstemperatur von EuO, bedingt durch die Nähe zu Co, hindeutet.
Small beams, fast predictions: a comparison of machine learning dose prediction models for proton minibeam therapy
(2022-10-30) Mentzel, Florian; Kröninger, Kevin; Lerch, M.; Nackenhorst, Olaf; Rosenfeld, A.; Tsoi, A. C.; Weingarten, Jens; Hagenbuchner, M.; Guatelli, S.
Background: Dose calculations for novel radiotherapy cancer treatments such as proton minibeam radiation therapy is often done using full Monte Carlo (MC) simulations. As MC simulations can be very time consuming for this kind of application, deep learning models have been considered to accelerate dose estimation in cancer patients. Purpose: This work systematically evaluates the dose prediction accuracy, speed and generalization performance of three selected state-of-the-art deep learning models for dose prediction applied to the proton minibeam therapy. The strengths and weaknesses of those models are thoroughly investigated, helping other researchers to decide on a viable algorithm for their own application. Methods: The following recently published models are compared: first, a 3D U-Net model trained as a regression network, second, a 3D U-Net trained as a generator of a generative adversarial network (GAN) and third, a dose transformer model which interprets the dose prediction as a sequence translation task. These models are trained to emulate the result of MC simulations. The dose depositions of a proton minibeam with a diameter of 800μm and an energy of 20–100 MeV inside a simple head phantom calculated by full Geant4 MC simulations are used as a case study for this comparison. The spatial resolution is 0.5 mm. Special attention is put on the evaluation of the generalization performance of the investigated models. Results: Dose predictions with all models are produced in the order of a second on a GPU, the 3D U-Net models being fastest with an average of 130 ms. An investigated 3D U-Net regression model is found to show the strongest performance with overall 61.0%±0.5% of all voxels exhibiting a deviation in energy deposition prediction of less than 3% compared to full MC simulations with no spatial deviation allowed. The 3D U-Net models are observed to show better generalization performance for target geometry variations, while the transformer-based model shows better generalization with regard to the proton energy. Conclusions: This paper reveals that (1) all studied deep learning models are significantly faster than non-machine learning approaches predicting the dose in the order of seconds compared to hours for MC, (2) all models provide reasonable accuracy, and (3) the regression-trained 3D U-Net provides the most accurate predictions.
Application of machine learning in glow curve deconvolution
(2023) Lienau, Evelin; Kröninger, Kevin; Westphal, Carsten
Routine dosimetry aims to estimate the radiation dose of occupationally exposed persons for a monitoring interval of one month. The Material Prüfungsamt NRW (MPA NRW) provides a thermoluminescence (TL) dosimeter based on LiF:Mg,Ti (TL-DOS). Thermal fading causes a time-dependent signal loss when using a TL dosimeter. This signal change is used to gain information about the irradiation event beyond the dose estimate, which can help to improve the radiation protection concept of occupationally exposed persons. In this work, multivariate analysis techniques for glow curve analysis using deep learning approaches are developed to estimate the irradiation day within a monitoring interval of 40 days with single-dose irradiation using a Cs-137 source with a prediction uncertainty of two days. To create a data basis for training the application of deep learning, over 10 000 measurements were performed in cooperation with the MPA NRW and the TL-DOS project. Furthermore, a technique to generate realistic glow curves based on generative adversarial networks (GANs) is presented, which makes it possible to expand the measured data set artificially and thus create a larger database for the deep learning approaches.
Microbeams - quick and dirty
(2023) Mentzel, Florian; Kröninger, Kevin; Lühr, Armin
Microbeam radiation therapy (MRT) is a promising yet preclinical radiotherapy treatment for several tumour diagnosis such as gliosarcoma and radioresistant melanoma for which even modern clinical treatments such as intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) yield poor outcome perspectives. The dose prediction during MRT treatment planning, as for most other novel radiotherapies, is mostly performed with very time-consuming Monte Carlo (MC) simulations. This slows down preclinical research processes and renders treatment plan optimization infeasible. In this thesis, several milestones for the introduction of a fast machine learning (ML) dose calculation method for MRT are presented. First, a 3D U-Net-based ML dose engine is developed using MC training data obtained with Geant4 simulations of a synchrotron broadbeam incident on different bone slab models and a simplified human head phantom as a proof of concept. The developed model is shown to produce dose predictions within less than 100ms which is substantially faster than the used MC simulations with up to 20hours and also the currently fastest approximative MRT dose prediction approach, called HybridDC, with approximately 30minutes. The model is also shown to be superior to a dose prediction approach using generative adversarial networks (GANs) and also a novel transformer-based ML model called Dose Transformer (DoTA), with which it is compared for application in proton minibeam radiation therapy (pMBRT) in a subsequent study. Secondly, the developed ML model and the MC simulations for data generation are extended to account for the spatially fractionated nature of MRT. For this, a novel MC scoring method is developed which is able produce separate dose estimations for the high-dose peak regions where the microbeams traverse the phantoms and the low-dose valley regions in-between those beams. Finally, the developed ML model and the MC scoring method are deployed in a first application of an ML dose prediction method in a preclinical MRT study in collaboration with the University of Wollongong, Australia, conducted at the Imaging and Medical Beamline (IMBL) at the Australian Synchrotron which aimed at treating rats after implanting gliosarcoma cells. It is shown that the ML model can be trained to provide unbiased dose estimations in complex target phantoms even when trained on high-noise MC data, in important finding for the acceleration of future developments of ML models as such datasets can be produced significantly faster. The ML predictions in the rat phantoms deviate at most 10% from the MC simulations, rendering the proposed model a suitable candidate for fast dose predictions during treatment plan optimization in the future.
Physics-based generative model of curvature sensing peptides; distinguishing sensors from binders
(2023-03-17) Hilten, Niek van; Methorst, Jeroen; Verwei, Nino; Risselada, Herre Jelger
Proteins can specifically bind to curved membranes through curvature-induced hydrophobic lipid packing defects. The chemical diversity among such curvature “sensors” challenges our understanding of how they differ from general membrane “binders” that bind without curvature selectivity. Here, we combine an evolutionary algorithm with coarse-grained molecular dynamics simulations (Evo-MD) to resolve the peptide sequences that optimally recognize the curvature of lipid membranes. We subsequently demonstrate how a synergy between Evo-MD and a neural network (NN) can enhance the identification and discovery of curvature sensing peptides and proteins. To this aim, we benchmark a physics-trained NN model against experimental data and show that we can correctly identify known sensors and binders. We illustrate that sensing and binding are phenomena that lie on the same thermodynamic continuum, with only subtle but explainable differences in membrane binding free energy, consistent with the serendipitous discovery of sensors.
Quantum spin dynamics of quasi-one-dimensional Heisenberg-Ising magnets in a transverse field: confined spinons, E8 spectrum, and quantum phase transitions
(2022-12-07) Amelin, Kirill; Viirok, Johan; Nagel, Urmas; Rõõm, Toomas; Engelmayer, Johannes; Dey, Tusharkanti; Agung Nugroho, Agustinus; Lorenz, Thomas; Wang, Zhe
We report on high-resolution terahertz spectroscopic studies of quantum spin dynamics in the quasi-one-dimensional Ising-like ferromagnet CoNb2O6 and antiferromagnet BaCo2V2O8 as a function of an applied transverse magnetic field. In the ordered phases stabilized by inter-chain couplings, we reveal characteristics for confined spinon excitations, E8 dynamical spectrum, and field-induced quantum phase transitions. The connections between these characteristic dynamical features are found in the field-dependent evolution of the excitation spectra.
Comparing biological effectiveness guided plan optimization strategies for cranial proton therapy: potential and challenges
(2022-10-22) Hahn, Christian; Heuchel, Lena; Ödén, Jakob; Traneus, Erik; Wulff, Jörg; Plaude, Sandija; Timmermann, Beate; Bäumer, Christian; Lühr, Armin
Background: To introduce and compare multiple biological effectiveness guided (BG) proton plan optimization strategies minimizing variable relative biological effectiveness (RBE) induced dose burden in organs at risk (OAR) while maintaining plan quality with a constant RBE. Methods: Dose-optimized (DOSEopt) proton pencil beam scanning reference treatment plans were generated for ten cranial patients with prescription doses ≥ 54 Gy(RBE) and ≥ 1 OAR close to the clinical target volume (CTV). For each patient, four additional BG plans were created. BG objectives minimized either proton track-ends, dose-averaged linear energy transfer (LETd), energy depositions from high-LET protons or variable RBE-weighted dose (DRBE) in adjacent serially structured OARs. Plan quality (RBE = 1.1) was assessed by CTV dose coverage and robustness (2 mm setup, 3.5% density), dose homogeneity and conformity in the planning target volumes and adherence to OAR tolerance doses. LETd, DRBE (Wedenberg model, α/βCTV = 10 Gy, α/βOAR = 2 Gy) and resulting normal tissue complication probabilities (NTCPs) for blindness and brainstem necrosis were derived. Differences between DOSEopt and BG optimized plans were assessed and statistically tested (Wilcoxon signed rank, α = 0.05). Results: All plans were clinically acceptable. DOSEopt and BG optimized plans were comparable in target volume coverage, homogeneity and conformity. For recalculated DRBE in all patients, all BG plans significantly reduced near-maximum DRBE to critical OARs with differences up to 8.2 Gy(RBE) (p < 0.05). Direct DRBE optimization primarily reduced absorbed dose in OARs (average ΔDmean = 2.0 Gy; average ΔLETd,mean = 0.1 keV/µm), while the other strategies reduced LETd (average ΔDmean < 0.3 Gy; average ΔLETd,mean = 0.5 keV/µm). LET-optimizing strategies were more robust against range and setup uncertaintes for high-dose CTVs than DRBE optimization. All BG strategies reduced NTCP for brainstem necrosis and blindness on average by 47% with average and maximum reductions of 5.4 and 18.4 percentage points, respectively. Conclusions: All BG strategies reduced variable RBE-induced NTCPs to OARs. Reducing LETd in high-dose voxels may be favourable due to its adherence to current dose reporting and maintenance of clinical plan quality and the availability of reported LETd and dose levels from clinical toxicity reports after cranial proton therapy. These optimization strategies beyond dose may be a first step towards safely translating variable RBE optimization in the clinics.
Explanation, Reduction, Progress
(1987) Scheibe, Erhard

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