Electron beam response corrections for an ultra-high-dose-rate capable diode dosimeter.

BACKGROUND: Ultra-high-dose-rate (UHDR) electron beams have been commonly utilized in FLASH studies and the translation of FLASH Radiotherapy (RT) to the clinic. The EDGE diode detector has potential use for UHDR dosimetry albeit with a beam energy dependency observed. PURPOSE: The purpose is to present the electron beam response for an EDGE detector in dependence on beam energy, to characterize the EDGE detector's response under UHDR conditions, and to validate correction factors derived from the first detailed Monte Carlo model of the EDGE diode against measurements, particularly under UHDR conditions. METHODS: Percentage depth doses (PDDs) for the UHDR Mobetron were measured with both EDGE detectors and films. A detailed Monte Carlo (MC) model of the EDGE detector has been configured according to the blueprint provided by the manufacturer under an NDA agreement. Water/silicon dose ratios of EDGE detector for a series of mono-energetic electron beams have been calculated. The dependence of the water/silicon dose ratio on depth for a FLASH relevant electron beam was also studied. An analytical approach for the correction of PDD measured with EDGE detectors was established. RESULTS: Water/silicon dose ratio decreased with decreasing electron beam energy. For the Mobetron 9 MeV UHDR electron beam, the ratio decreased from 1.09 to 1.03 in the build-up region, maintained in range of 0.98-1.02 at the fall-off region and raised to a plateau in value of 1.08 at the tail. By applying the corrections, good agreement between the PDDs measured by the EDGE detector and those measured with film was achieved. CONCLUSIONS: Electron beam response of an UHDR capable EDGE detector was derived from first principles utilizing a sophisticated MC model. An analytical approach was validated for the PDDs of UHDR electron beams. The results demonstrated the capability of EDGE detector in measuring PDDs of UHDR electron beams.

First Monte Carlo beam model for ultra-high dose rate radiotherapy with a compact electron LINAC.

BACKGROUND: FLASH radiotherapy based on ultra-high dose rate (UHDR) is actively being studied by the radiotherapy community. Dedicated UHDR electron devices are currently a mainstay for FLASH studies. PURPOSE: To present the first Monte Carlo (MC) electron beam model for the UHDR capable Mobetron (FLASH-IQ) as a dose calculation and treatment planning platform for preclinical research and FLASH-radiotherapy (RT) clinical trials. METHODS: The initial beamline geometry of the Mobetron was provided by the manufacturer, with the first-principal implementation realized in the Geant4-based GAMOS MC toolkit. The geometry and electron source characteristics, such as energy spectrum and beamline parameters, were tuned to match the central-axis percentage depth dose (PDD) and lateral profiles for the pristine beam measured during machine commissioning. The thickness of the small foil in secondary scatter affected the beam model dominantly and was fine tuned to achieve the best agreement with commissioning data. Validation of the MC beam modeling was performed by comparing the calculated PDDs and profiles with EBT-XD radiochromic film measurements for various combinations of applicators and inserts. RESULTS: The nominal 9 MeV electron FLASH beams were best represented by a Gaussian energy spectrum with mean energy of 9.9 MeV and variance (σ) of 0.2 MeV. Good agreement between the MC beam model and commissioning data were demonstrated with maximal discrepancy < 3% for PDDs and profiles. Hundred percent gamma pass rate was achieved for all PDDs and profiles with the criteria of 2 mm/3%. With the criteria of 2 mm/2%, maximum, minimum and mean gamma pass rates were (100.0%, 93.8%, 98.7%) for PDDs and (100.0%, 96.7%, 99.4%) for profiles, respectively. CONCLUSIONS: A validated MC beam model for the UHDR capable Mobetron is presented for the first time. The MC model can be utilized for direct dose calculation or to generate beam modeling input required for treatment planning systems for FLASH-RT planning. The beam model presented in this work should facilitate translational and clinical FLASH-RT for trials conducted on the Mobetron FLASH-IQ platform.

Mean dose rate in ultra-high dose rate electron irradiation is a significant predictor for O2consumption and H2O2yield.

Objective. The objective of this study was to investigate the impact of mean and instantaneous dose rates on the production of reactive oxygen species (ROS) during ultra-high dose rate (UHDR) radiotherapy. The study aimed to determine whether either dose rate type plays a role in driving the FLASH effect, a phenomenon where UHDR radiotherapy reduces damage to normal tissues while maintaining tumor control.Approach. Assays of hydrogen peroxide (H2O2) production and oxygen consumption (ΔpO2) were conducted using UHDR electron irradiation. Aqueous solutions of 4% albumin were utilized as the experimental medium. The study compared the effects of varying mean dose rates and instantaneous dose rates on ROS yields. Instantaneous dose rate was varied by changing the source-to-surface distance (SSD), resulting in instantaneous dose rates ranging from 102to 106Gy s-1. Mean dose rate was manipulated by altering the pulse frequency of the linear accelerator (linac) and by changing the SSD, ranging from 0.14 to 1500 Gy s-1.Main results. The study found that both ΔH2O2and ΔpO2decreased as the mean dose rate increased. Multivariate analysis indicated that instantaneous dose rates also contributed to this effect. The variation in ΔpO2was dependent on the initial oxygen concentration in the solution. Based on the analysis of dose rate variation, the study estimated that 7.51 moles of H2O2were produced for every mole of O2consumed.Significance. The results highlight the significance of mean dose rate as a predictor of ROS production during UHDR radiotherapy. As the mean dose rate increased, there was a decrease in oxygen consumption and in H2O2production. These findings have implications for understanding the FLASH effect and its potential optimization. The study sheds light on the role of dose rate parameters and their impact on radiochemical outcomes, contributing to the advancement of UHDR radiotherapy techniques.

Feedback-controlled dynamics of neuronal cells on directional surfaces.

The formation of neuronal networks is a complex phenomenon of fundamental importance for understanding the development of the nervous system. The basic process underlying the network formation is axonal growth, a process involving the extension of axons from the cell body and axonal navigation toward target neurons. Axonal growth is guided by the interactions between the tip of the axon (growth cone) and its extracellular environmental cues, which include intercellular interactions, the biochemical landscape around the neuron, and the mechanical and geometrical features of the growth substrate. Here, we present a comprehensive experimental and theoretical analysis of axonal growth for neurons cultured on micropatterned polydimethylsiloxane (PDMS) surfaces. We demonstrate that closed-loop feedback is an essential component of axonal dynamics on these surfaces: the growth cone continuously measures environmental cues and adjusts its motion in response to external geometrical features. We show that this model captures all the characteristics of axonal dynamics on PDMS surfaces for both untreated and chemically modified neurons. We combine experimental data with theoretical analysis to measure key parameters that describe axonal dynamics: diffusion (cell motility) coefficients, speed and angular distributions, and cell-substrate interactions. The experiments performed on neurons treated with Taxol (inhibitor of microtubule dynamics) and Y-27632 (disruptor of actin filaments) indicate that the internal dynamics of microtubules and actin filaments plays a critical role for the proper function of the feedback mechanism. Our results demonstrate that axons follow geometrical patterns through a contact-guidance mechanism, in which high-curvature geometrical features impart high traction forces to the growth cone. These results have important implications for our fundamental understanding of axonal growth as well as for bioengineering novel substrate to guide neuronal growth and promote nerve repair.

Axonal growth on surfaces with periodic geometrical patterns.

The formation of neuron networks is a complex phenomenon of fundamental importance for understanding the development of the nervous system, and for creating novel bioinspired materials for tissue engineering and neuronal repair. The basic process underlying the network formation is axonal growth, a process involving the extension of axons from the cell body towards target neurons. Axonal growth is guided by environmental stimuli that include intercellular interactions, biochemical cues, and the mechanical and geometrical features of the growth substrate. The dynamics of the growing axon and its biomechanical interactions with the growing substrate remains poorly understood. In this paper, we develop a model of axonal motility which incorporates mechanical interactions between the axon and the growth substrate. We combine experimental data with theoretical analysis to measure the parameters that describe axonal growth on surfaces with micropatterned periodic geometrical features: diffusion (cell motility) coefficients, speed and angular distributions, and axon bending rigidities. Experiments performed on neurons treated Taxol (inhibitor of microtubule dynamics) and Blebbistatin (disruptor of actin filaments) show that the dynamics of the cytoskeleton plays a critical role in the axon steering mechanism. Our results demonstrate that axons follow geometrical patterns through a contact-guidance mechanism, in which high-curvature geometrical features impart high traction forces to the growth cone. These results have important implications for our fundamental understanding of axonal growth as well as for bioengineering novel substrates that promote neuronal growth and nerve repair.

Variations of Elastic Modulus and Cell Volume with Temperature for Cortical Neurons.

Neurons change their growth dynamics and mechanical properties in response to external stimuli such as stiffness of the local microenvironment, ambient temperature, and biochemical or geometrical guidance cues. Here we use combined atomic force microscopy (AFM) and fluorescence microscopy experiments to investigate the relationship between external temperature, soma volume, and elastic modulus for cortical neurons. We measure how changes in ambient temperature affect the volume and the mechanical properties of neuronal cells at both the bulk (elastic modulus) and local (elasticity maps) levels. The experimental data demonstrate that both the volume and the elastic modulus of the neuron soma vary with changes in temperature. Our results show a decrease by a factor of 2 in the soma elastic modulus as the ambient temperature increases from room (25 °C) to physiological (37 °C) temperature, while the volume of the soma increases by a factor of 1.3 during the same temperature sweep. Using high-resolution AFM force mapping, we measure the temperature-induced variations within different regions of the elasticity maps (low and high values of elastic modulus) and correlate these variations with the dynamics of cytoskeleton components and molecular motors. We quantify the change in soma volume with temperature and propose a simple theoretical model that relates this change with variations in soma elastic modulus. These results have significant implications for understanding neuronal development and functions, as ambient temperature, cytoskeletal dynamics, and cellular volume may change with variations in physiological conditions, for example, during tissue compression and infections in vivo as well as during cell manipulation and tissue regeneration ex vivo.