A wall-less Tissue Equivalent Proportional Counter as connecting bridge from microdosimetry to nanodosimetry

Calculation of alpha particle single-event spectra using a neural network

Introduction

A neural network was trained to accurately predict the entire single-event specific energy spectra for use in alpha-particle microdosimetry calculations.

Methods

The network consisted of 4 inputs and 21 outputs and was trained on data calculated using Monte Carlo simulation where input parameters originated both from previously published data as well as randomly generated parameters that fell within a target range. The 4 inputs consisted of the source-target configuration (consisting of both cells in suspension and in tissue-like geometries), alpha particle energy (3.97-8.78 MeV), nuclei radius (2-10 μm), and cell radius (2.5-20 μm). The 21 output values consisted of the maximum specific energy (zmax), and 20 values of the single-event spectra, which were expressed as fractional values of zmax. The neural network consisted of two hidden layers with 10 and 26 nodes, respectively, with the loss function characterized as the mean square error (MSE) between the actual and predicted values for zmax and the spectral outputs.

Results

For the final network, the root mean square error (RMSE) values of zmax for training, validation and testing were 1.57 x10-2, 1.51 x 10-2 and 1.35 x 10-2, respectively. Similarly, the RMSE values of the spectral outputs were 0.201, 0.175 and 0.199, respectively. The correlation coefficient, R2, was > 0.98 between actual and predicted values from the neural network.

Discussion

In summary, the network was able to accurately reproduce alpha-particle single-event spectra for a wide range of source-target geometries.

Energy imparted and ionisation yield at the nanometre scale: results for extended beams

The metrological problem of interpreting ionisation-based micro- and nanodosimetric measurements in terms of quantities proportional to energy imparted becomes particularly relevant when the sensitive volume (SV) size is in the nanometre range. At these scales, a constant W-value cannot be assumed, and the stochastics of the energy transfer per single collision could play a more important role. This problem was recently analysed by our group by means of track-structure Monte Carlo simulations with the Geant4-DNA code, finding a strong correlation between the energy imparted and ionisation yield also for SV diameters of 1 nm. As the previous study was limited to primary beams of radius zero crossing the sensitive sphere along its diameter, it is the aim of the present work to extend the analysis to beams with a radius larger than the dimensions of the SV, to better assess the role played by secondary electrons.

THE APPLICATION OF NEURAL NETWORK TECHNOLOGY BASED ON MEA-BP ALGORITHM IN THE PREDICTION OF MICRODOSIMETRIC QUALITIES

The most abundant products of the interaction between radiation and matter are low-energy electrons, and the collisions between these electrons and biomolecules are the main initial source of radiation-based biological damage. To facilitate the rapid and accurate quantification of low-energy electrons (0.1-10 keV) in liquid water at different site diameters (1-2000 nm), this study obtained ${\overline{y}}_{\mathrm{F}}$ and ${\overline{y}}_{\mathrm{D}}$data for low-energy electrons under these conditions. This paper proposes a back-propagation (BP) neural network optimized by the mind evolutionary algorithm (MEA) to construct a prediction model and evaluate the corresponding prediction effect. The results show that the ${\overline{y}}_{\mathrm{F}}$ and ${\overline{y}}_{\mathrm{D}}$ values predicted by the MEA-BP neural network algorithm reach a training precision on the order of ${10}^{-8}$. The relative error range between the prediction results of the validated model and the Monte Carlo calculation results is 0.03-5.98% (the error range for single-energy electrons is 0.1-5.98%, and that for spectral distribution electrons is 0.03-4.4%).

EURADOS STRATEGIC RESEARCH AGENDA 2020: VISION FOR THE DOSIMETRY OF IONISING RADIATION

Since 2012, the European Radiation Dosimetry Group (EURADOS) has developed its Strategic Research Agenda (SRA), which contributes to the identification of future research needs in radiation dosimetry in Europe. Continued scientific developments in this field necessitate regular updates and, consequently, this paper summarises the latest revision of the SRA, with input regarding the state of the art and vision for the future contributed by EURADOS Working Groups and through a stakeholder workshop. Five visions define key issues in dosimetry research that are considered important over at least the next decade. They include scientific objectives and developments in (i) updated fundamental dose concepts and quantities, (ii) improved radiation risk estimates deduced from epidemiological cohorts, (iii) efficient dose assessment for radiological emergencies, (iv) integrated personalised dosimetry in medical applications and (v) improved radiation protection of workers and the public. This SRA will be used as a guideline for future activities of EURADOS Working Groups but can also be used as guidance for research in radiation dosimetry by the wider community. It will also be used as input for a general European research roadmap for radiation protection, following similar previous contributions to the European Joint Programme for the Integration of Radiation Protection Research, under the Horizon 2020 programme (CONCERT). The full version of the SRA is available as a EURADOS report (www.eurados.org).

Roadmap for metal nanoparticles in radiation therapy: current status, translational challenges, and future directions

This roadmap outlines the potential roles of metallic nanoparticles (MNPs) in the field of radiation therapy. MNPs made up of a wide range of materials (from Titanium, Z = 22, to Bismuth, Z = 83) and a similarly wide spectrum of potential clinical applications, including diagnostic, therapeutic (radiation dose enhancers, hyperthermia inducers, drug delivery vehicles, vaccine adjuvants, photosensitizers, enhancers of immunotherapy) and theranostic (combining both diagnostic and therapeutic), are being fabricated and evaluated. This roadmap covers contributions from experts in these topics summarizing their view of the current status and challenges, as well as expected advancements in technology to address these challenges.

Biomedical Research Programs at Present and Future High-Energy Particle Accelerators

Biomedical applications at high-energy particle accelerators have always been an important section of the applied nuclear physics research. Several new facilities are now under constructions or undergoing major upgrades. While the main goal of these facilities is often basic research in nuclear physics, they acknowledge the importance of including biomedical research programs and of interacting with other medical accelerator facilities providing patient treatments. To harmonize the programs, avoid duplications, and foster collaboration and synergism, the International Biophysics Collaboration is providing a platform to several accelerator centers with interest in biomedical research. In this paper, we summarize the programs of various facilities in the running, upgrade, or construction phase.