Invasiveness modulation of glioma cells by copper complex-loaded nanoarchitectures.

Among the tumors with the highest lethality, gliomas are primary brain tumors associated with common recurrence inclined to metastasize along the neuraxis and occasionally out of the central nervous system. Even though metastasis is the main responsible for death in oncological patients, few dedicated treatments are approved. Therefore, the establishment of effective anti-metastasis agents is the final frontier in cancer research. Interestingly, some copper complexes have demonstrated promising efficacy as antimetastatic agents, but they may cause off-site effects such as the alteration of copper homeostasis in healthy tissues. Thus, the incorporation of copper-based antimetastatic agents in rationally designed nano-architectures can increase the treatment localization reducing the side effects. Here, copper complex loaded hybrid nano-architectures (CuLNAs) are presented and employed to assess the impact of an intracellular copper source on glioma cell invasiveness. The novel CuLNAs are fully characterized and exploited for cell migration modulation in a glioma cell line. The results demonstrate that CuLNAs significantly reduce cell migration without impairing cell proliferation compared to standard gold and copper NAs. A concomitant antimigratory-like regulation of the epithelial-to-mesenchymal transition genes confirmed these results, as the gene encoding for the epithelial protein E-cadherin was upregulated and the other explored mesenchymal genes were downregulated. These findings, together with the intrinsic behaviors of NAs, demonstrate that the inclusion of metal complexes in the nano-architectures is a promising approach for the composition of a family of agents with antimetastatic activity.

Lipid droplets and small extracellular vesicles: More than two independent entities.

Despite increasing knowledge about small extracellular vesicle (sEV) composition and functions in cell-cell communication, the mechanism behind their biogenesis remains unclear. Here, we reveal for the first time that sEV biogenesis and release into the microenvironment are tightly connected with another important organelle, Lipid Droplets (LDs). The correlation was observed in several human cancer cell lines as well as patient-derived colorectal cancer stem cells (CR-CSCs). Our results demonstrated that external stimuli such as radiation, pH, hypoxia or lipid-interfering drugs, known to affect the number of LDs/cell, similarly influenced sEV secretion. Importantly, through multiple omics data, at both mRNA and protein levels, we revealed RAB5C as a potential important molecular player behind this organelle connection. Altogether, the potential to fine-tune sEV biogenesis by targeting LDs could significantly impact the amount, cargos and properties of these sEVs, opening new clinical perspectives.

Analysis of hydrogen peroxide production in pure water: Ultrahigh versus conventional dose-rate irradiation and mechanistic insights.

BACKGROUND: Ultrahigh dose-rate radiation (UHDR) produces less hydrogen peroxide (H2O2) in pure water, as suggested by some experimental studies, and is used as an argument for the validity of the theory that FLASH spares the normal tissue due to less reactive oxygen species (ROS) production. In contrast, most Monte Carlo simulation studies suggest the opposite. PURPOSE: We aim to unveil the effect of UHDR on H2O2 production in pure water and its underlying mechanism, to serve as a benchmark for Monte Carlo simulation. We hypothesized that the reaction of solvated electrons ( e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ ) removing hydroxyl radicals (•OH), the precursor of H2O2, is the reason why UHDR leads to a lower G-value (molecules/100 eV) for H2O2 (G[H2O2]), because: 1, the third-order reaction between e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ and •OH is more sensitive to increased instantaneous ROS concentration by UHDR than a two-order reaction of •OH self-reaction producing H2O2; 2, e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ has two times higher diffusion coefficient and higher reaction rate constant than that of •OH, which means e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ would dominate the competition for •OH and benefit more from the inter-track effect of UHDR. Meanwhile, we also experimentally verify the theory of long-lived radicals causing lower G(H2O2) in conventional irradiation, which is mentioned in some simulation studies. METHODS AND MATERIALS: H2O2 was measured by Amplex UltraRed assay. 430.1 MeV/u carbon ions (50 and 0.1 Gy/s), 9 MeV electrons (600 and 0.62 Gy/s), and 200 kV x-ray tube (10 and 0.1 Gy/s) were employed. For three kinds of water (real hypoxic: 1% O2; hypoxic: 1% O2 and 5% CO2; and normoxic: 21% O2), unbubbled and bubbled samples with N2O, the scavenger of e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ , were irradiated by carbon ions and electrons with conventional and UHDR at different absolute dose levels. Normoxic water dissolved with sodium nitrate (NaNO3), another scavenger of e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ , and bubbled with N2O was irradiated by x-ray to verify the results of low-LET electron beam. RESULTS: UHDR leads to a lower G(H2O2) than conventional irradiation. O2 and CO2 can both increase G(H2O2). N2O increases G(H2O2) of both UHDR and conventional irradiation and eliminates the difference between them for carbon ions. However, N2O decreases G(H2O2) in electron conventional irradiation but increases G(H2O2) in the case of UHDR, ending up with no dose-rate dependency of G(H2O2). Three-spilled carbon UHDR does not have a lower G(H2O2) than one-spilled UHDR. However, the electron beam shows a lower G(H2O2) for three-spilled UHDR than for one-spilled UHDR. Normoxic water with N2O or NaNO3 can both eliminate the dose rate dependency of H2O2 production for x-ray. CONCLUSIONS: UHDR has a lower G(H2O2) than the conventional irradiation for both high LET carbon and low LET electron and x-ray beams. Both scavengers for e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ , N2O and NaNO3, eliminate the dose-rate dependency of G(H2O2), which suggests e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ is the reason for decreased G(H2O2) for UHDR. Three-spilled UHDR versus one-spilled UHDR indicates that the assumption of residual radicals reducing G(H2O2) of conventional irradiation may only be valid for low LET electron beam.

The potential of mixed carbon-helium beams for online treatment verification: a simulation and treatment planning study.

Objective.Recently, a new and promising approach for range verification was proposed. This method requires the use of two different ion species. Due to their equal magnetic rigidity, fully ionized carbon and helium ions can be simultaneously accelerated in accelerators like synchrotrons. At sufficiently high treatment energies, helium ions can exit the patient distally, reaching approximately three times the range of carbon ions at an equal energy per nucleon. Therefore, the proposal involves adding a small helium fluence to the carbon ion beam and utilizing helium as an online range probe during radiation therapy. This work aims to develop a software framework for treatment planning and motion verification in range-guided radiation therapy using mixed carbon-helium beams.Approach.The developed framework is based on the open-source treatment planning toolkit matRad. Dose distributions and helium radiographs were simulated using the open-source Monte Carlo package TOPAS. Beam delivery system parameters were obtained from the Heidelberg Ion Therapy Center, and imaging detectors along with reconstruction were facilitated by ProtonVDA. Methods for reconstructing the most likely patient positioning error scenarios and the motion phase of 4DCT are presented for prostate and lung cancer sites.Main results.The developed framework provides the capability to calculate and optimize treatment plans for mixed carbon-helium ion therapy. It can simulate the treatment process and generate helium radiographs for simulated patient geometry, including small beam views. Furthermore, motion reconstruction based on these radiographs seems possible with preliminary validation.Significance.The developed framework can be applied for further experimental work with the promising mixed carbon-helium ion implementation of range-guided radiotherapy. It offers opportunities for adaptation in particle therapy, improving dose accumulation, and enabling patient anatomy reconstruction during radiotherapy.

Cancer radioresistance is characterized by a differential lipid droplet content along the cell cycle.

BACKGROUND: Cancer radiation treatments have seen substantial advancements, yet the biomolecular mechanisms underlying cancer cell radioresistance continue to elude full understanding. The effectiveness of radiation on cancer is hindered by various factors, such as oxygen concentrations within tumors, cells' ability to repair DNA damage and metabolic changes. Moreover, the initial and radiation-induced cell cycle profiles can significantly influence radiotherapy responses as radiation sensitivity fluctuates across different cell cycle stages. Given this evidence and our prior studies establishing a correlation between cancer radiation resistance and an increased number of cytoplasmic Lipid Droplets (LDs), we investigated if LD accumulation was modulated along the cell cycle and if this correlated with differential radioresistance in lung and bladder cell lines. RESULTS: Our findings identified the S phase as the most radioresistant cell cycle phase being characterized by an increase in LDs. Analysis of the expression of perilipin genes (a family of proteins involved in the LD structure and functions) throughout the cell cycle also uncovered a unique gene cell cycle pattern. CONCLUSIONS: In summary, although these results require further molecular studies about the mechanisms of radioresistance, the findings presented here are the first evidence that LD accumulation could participate in cancer cells' ability to better survive X-Ray radiation when cells are in the S phase. LDs can represent new players in the radioresistance processes associated with cancer metabolism. This could open new therapeutic avenues in which the use of LD-interfering drugs might enhance cancer sensitivity to radiation.

Dosimetric study for breathing-induced motion effects in an abdominal pancreas phantom for carbon ion mini-beam radiotherapy.

BACKGROUND: Particle mini-beam therapy exhibits promise in sparing healthy tissue through spatial fractionation, particularly notable for heavy ions, further enhancing the already favorable differential biological effectiveness at both target and entrance regions. However, breathing-induced organ motion affects particle mini-beam irradiation schemes since the organ displacements exceed the mini-beam structure dimensions, decreasing the advantages of spatial fractionation. PURPOSE: In this study, the impact of breathing-induced organ motion on the dose distribution was examined at the target and organs at risk(OARs) during carbon ion mini-beam irradiation for pancreatic cancer. METHODS: As a first step, the carbon ion mini-beam pattern was characterized with Monte Carlo simulations. To analyze the impact of breathing-induced organ motion on the dose distribution of a virtual pancreas tumor as target and related OARs, the anthropomorphic Pancreas Phantom for Ion beam Therapy (PPIeT) was irradiated with carbon ions. A mini-beam collimator was used to deliver a spatially fractionated dose distribution. During irradiation, varying breathing motion amplitudes were induced, ranging from 5 to 15 mm. Post-irradiation, the 2D dose pattern was analyzed, focusing on the full width at half maximum (FWHM), center-to-center distance (ctc), and the peak-to-valley dose ratio (PVDR). RESULTS: The mini-beam pattern was visible within OARs, while in the virtual pancreas tumor a more homogeneous dose distribution was achieved. Applied motion affected the mini-beam pattern within the kidney, one of the OARs, reducing the PVDR from 3.78  ± $\pm$  0.12 to 1.478  ± $\pm$  0.070 for the 15 mm motion amplitude. In the immobile OARs including the spine and the skin at the back, the PVDR did not change within 3.4% comparing reference and motion conditions. CONCLUSIONS: This study provides an initial understanding of how breathing-induced organ motion affects spatial fractionation during carbon ion irradiation, using an anthropomorphic phantom. A decrease in the PVDR was observed in the right kidney when breathing-induced motion was applied, potentially increasing the risk of damage to OARs. Therefore, further studies are needed to explore the clinical viability of mini-beam radiotherapy with carbon ions when irradiating abdominal regions.

Spatially fractionated radiation therapy: a critical review on current status of clinical and preclinical studies and knowledge gaps.

Spatially fractionated radiation therapy (SFRT) is a therapeutic approach with the potential to disrupt the classical paradigms of conventional radiation therapy. The high spatial dose modulation in SFRT activates distinct radiobiological mechanisms which lead to a remarkable increase in normal tissue tolerances. Several decades of clinical use and numerous preclinical experiments suggest that SFRT has the potential to increase the therapeutic index, especially in bulky and radioresistant tumors. To unleash the full potential of SFRT a deeper understanding of the underlying biology and its relationship with the complex dosimetry of SFRT is needed. This review provides a critical analysis of the field, discussing not only the main clinical and preclinical findings but also analyzing the main knowledge gaps in a holistic way.

Linear Energy Transfer Measurements and Estimation of Relative Biological Effectiveness in Proton and Helium Ion Beams Using Fluorescent Nuclear Track Detectors.

PURPOSE: Our objective was to develop a methodology for assessing the linear energy transfer (LET) and relative biological effectiveness (RBE) in clinical proton and helium ion beams using fluorescent nuclear track detectors (FNTDs). METHODS AND MATERIALS: FNTDs were exposed behind solid water to proton and helium (4He) ion spread-out Bragg peaks. Detectors were imaged with a confocal microscope, and the LET spectra were derived from the fluorescence intensity. The track- and dose-averaged LET (LETF and LETD, respectively) were calculated from the LET spectra. LET measurements were used as input on RBE models to estimate the RBE. Human alveolar adenocarcinoma cells (A549) were exposed at the same positions as the FNTDs. The RBE was calculated from the resulting survival curves. All measurements were compared with Monte Carlo simulations. RESULTS: For protons, average relative differences between measurements and simulations were 6% and 19% for LETF and LETD, respectively. For helium ions, the same differences were 11% for both quantities. The position of the experimental LET spectra primary peaks agreed with the simulations within 9% and 14% for protons and helium ions, respectively. For the RBE models using LETD as input, FNTD-based RBE values ranged from 1.02 ± 0.01 to 1.25 ± 0.04 and from 1.08 ± 0.09 to 2.68 ± 1.26 for protons and helium ions, respectively. The average relative differences between these values and simulations were 2% and 4%. For A549 cells, the RBE ranged from 1.05 ± 0.07 to 1.47 ± 0.09 and from 0.89 ± 0.06 to 3.28 ± 0.20 for protons and helium ions, respectively. Regarding the RBE-weighted dose (2.0 Gy at the spread-out Bragg peak), the differences between simulations and measurements were below 0.10 Gy. CONCLUSIONS: This study demonstrates for the first time that FNTDs can be used to perform direct LET measurements and to estimate the RBE in clinical proton and helium ion beams.

Exploration of differentiability in a proton computed tomography simulation framework.

Objective.Gradient-based optimization using algorithmic derivatives can be a useful technique to improve engineering designs with respect to a computer-implemented objective function. Likewise, uncertainty quantification through computer simulations can be carried out by means of derivatives of the computer simulation. However, the effectiveness of these techniques depends on how 'well-linearizable' the software is. In this study, we assess how promising derivative information of a typical proton computed tomography (pCT) scan computer simulation is for the aforementioned applications.Approach.This study is mainly based on numerical experiments, in which we repeatedly evaluate three representative computational steps with perturbed input values. We support our observations with a review of the algorithmic steps and arithmetic operations performed by the software, using debugging techniques.Main results.The model-based iterative reconstruction (MBIR) subprocedure (at the end of the software pipeline) and the Monte Carlo (MC) simulation (at the beginning) were piecewise differentiable. However, the observed high density and magnitude of jumps was likely to preclude most meaningful uses of the derivatives. Jumps in the MBIR function arose from the discrete computation of the set of voxels intersected by a proton path, and could be reduced in magnitude by a 'fuzzy voxels' approach. The investigated jumps in the MC function arose from local changes in the control flow that affected the amount of consumed random numbers. The tracking algorithm solves an inherently non-differentiable problem.Significance.Besides the technical challenges of merely applying AD to existing software projects, the MC and MBIR codes must be adapted to compute smoother functions. For the MBIR code, we presented one possible approach for this while for the MC code, this will be subject to further research. For the tracking subprocedure, further research on surrogate models is necessary.

The DRESDEN PLATFORM is a research hub for ultra-high dose rate radiobiology.

The recently observed FLASH effect describes the observation of normal tissue protection by ultra-high dose rates (UHDR), or dose delivery in a fraction of a second, at similar tumor-killing efficacy of conventional dose delivery and promises great benefits for radiotherapy patients. Dedicated studies are now necessary to define a robust set of dose application parameters for FLASH radiotherapy and to identify underlying mechanisms. These studies require particle accelerators with variable temporal dose application characteristics for numerous radiation qualities, equipped for preclinical radiobiological research. Here we present the DRESDEN PLATFORM, a research hub for ultra-high dose rate radiobiology. By uniting clinical and research accelerators with radiobiology infrastructure and know-how, the DRESDEN PLATFORM offers a unique environment for studying the FLASH effect. We introduce its experimental capabilities and demonstrate the platform's suitability for systematic investigation of FLASH by presenting results from a concerted in vivo radiobiology study with zebrafish embryos. The comparative pre-clinical study was conducted across one electron and two proton accelerator facilities, including an advanced laser-driven proton source applied for FLASH-relevant in vivo irradiations for the first time. The data show a protective effect of UHDR irradiation up to [Formula: see text] and suggests consistency of the protective effect even at escalated dose rates of [Formula: see text]. With the first clinical FLASH studies underway, research facilities like the DRESDEN PLATFORM, addressing the open questions surrounding FLASH, are essential to accelerate FLASH's translation into clinical practice.

Uncertainty-aware spot rejection rate as quality metric for proton therapy using a digital tracking calorimeter.

Objective.Proton therapy is highly sensitive to range uncertainties due to the nature of the dose deposition of charged particles. To ensure treatment quality, range verification methods can be used to verify that the individual spots in a pencil beam scanning treatment fraction match the treatment plan. This study introduces a novel metric for proton therapy quality control based on uncertainties in range verification of individual spots.Approach.We employ uncertainty-aware deep neural networks to predict the Bragg peak depth in an anthropomorphic phantom based on secondary charged particle detection in a silicon pixel telescope designed for proton computed tomography. The subsequently predicted Bragg peak positions, along with their uncertainties, are compared to the treatment plan, rejecting spots which are predicted to be outside the 95% confidence interval. The such-produced spot rejection rate presents a metric for the quality of the treatment fraction.Main results.The introduced spot rejection rate metric is shown to be well-defined for range predictors with well-calibrated uncertainties. Using this method, treatment errors in the form of lateral shifts can be detected down to 1 mm after around 1400 treated spots with spot intensities of 1 × 107protons. The range verification model used in this metric predicts the Bragg peak depth to a mean absolute error of 1.107 ± 0.015 mm.Significance.Uncertainty-aware machine learning has potential applications in proton therapy quality control. This work presents the foundation for future developments in this area.

A theoretical study of H2 O2 as the surrogate of dose in minibeam radiotherapy, with a diffusion model considering radical removal process.

BACKGROUND: Minibeam radiation therapy (MBRT) is an innovative dose delivery method with the potential to spare normal tissue while achieving similar tumor control as conventional radiotherapy. However, it is difficult to use a single dose parameter, such as mean dose, to compare different patterns of MBRT due to the spatially fractionated radiation. Also, the mechanism leading to the biological effects is still unknown. PURPOSE: This study aims to demonstrate that the hydrogen peroxide (H2 O2 ) distribution could serve as a surrogate of dose distribution when comparing different patterns of MBRT. METHODS: A free diffusion model (FDM) for H2 O2 developed with Fick's second law was compared with a previously published model based on Monte Carlo & convolution method. Since cells form separate compartments that can eliminate H2 O2 radicals diffusing inside the cell, a term describing the elimination was introduced into the equation. The FDM and the diffusion model considering removal (DMCR) were compared by simulating various dose rate irradiation schemes and uniform irradiation. Finally, the DMCR was compared with previous microbeam and minibeam animal experiments. RESULTS: Compared with a previous Monte Carlo & Convolution method, this analytical method provides more accurate results. Furthermore, the new model shows H2 O2 concentration distribution instead of the time to achieve a certain H2 O2 uniformity. The comparison between FDM and DMCR showed that H2 O2 distribution from FDM varied with dose rate irradiation, while DMCR had consistent results. For uniform irradiation, FDM resulted in a Gaussian distribution, while the H2 O2 distribution from DMCR was close to the dose distribution. The animal studies' evaluation showed a correlation between the H2 O2 concentration in the valley region and treatment outcomes. CONCLUSION: DMCR is a more realistic model for H2 O2 simulation than the FDM. In addition, the H2 O2 distribution can be a good surrogate of dose distribution when the minibeam effect could be observed.

Radio-resistance of hypoxic tumors: exploring the effects of oxygen and x-ray radiation on non-small lung cancer cell lines.

BACKGROUND: Solid tumors are often riddled with hypoxic areas, which develops as a result of high proliferation. Cancer cells willingly adapt and thrive in hypoxia by activating complex changes which contributes to survival and enhanced resistance to treatments, such as photon radiation. Photon radiation primarily relies on oxygen for the production of reactive oxygen species to induce DNA damage. The present in-vitro study aimed at investigating the biochemical responses of hypoxic non-small cell lung cancer (NSCLC) cells, particularly the effects on the DNA damage repair systems contributing to more radioresistant phenotypes and their pro- and anti-oxidant potential, within the first 24 h post-IR. METHODS: NSCLC cell lines (H460, A549, Calu-1) were irradiated using varying X-ray doses under normoxia (21% O2) and hypoxia (0.1% O2). The overall cell survival was assessed by clonogenic assays. The extent of irradiation (IR)-induced DNA damage was evaluated by analyzing γ-H2AX foci induction and the altered expression of repair genes involved in non-homologous end joining and homologous recombination pathways. Moreover, cell-altered responses were investigated, including the nuclear and cytosolic hydrogen peroxide (H2O2) production, as well as the associated anti-oxidant potential, in particular some components related to the glutathione system. RESULTS: Analysis of clonogenic survival revealed an enhanced radioresistance of the hypoxic NSCLC cells associated with reduced DNA damage and a downregulation of DNA repair genes. Moreover, nuclear H2O2 levels were IR-induced in a dose-dependent manner only under normoxia, and directly correlated with the DNA double-strand breaks. However, the observed nuclear H2O2 reduction in hypoxia appeared to be unaffected by IR, thus highlighting a possible reason for the enhanced radioresistance of the hypoxic NSCLC cells. The cellular antioxidant capacity was upregulated by IR in both oxygen conditions most likely helping to counteract the radiation effect on the cytosolic H2O2. CONCLUSIONS: In conclusion, our data provide insight into the adaptive behavior of radiation-resistant hypoxic NSCLC cells, in particular their DNA repair and oxidative stress responses, which could contribute to lower DNA damage and higher cell survival rates following X-ray exposure. These findings may therefore help to identify potential targets for improving cancer treatment outcomes.

Development and characterization of a versatile mini-beam collimator for pre-clinical photon beam irradiation.

BACKGROUND: Interest in spatial fractionation radiotherapy has exponentially increased over the last decade as a significant reduction of healthy tissue toxicity was observed by mini-beam irradiation. Published studies, however, mostly use rigid mini-beam collimators dedicated to their exact experimental arrangement such that changing the setup or testing new mini-beam collimator configurations becomes challenging and expensive. PURPOSE: In this work, a versatile, low-cost mini-beam collimator was designed and manufactured for pre-clinical applications with X-ray beams. The mini-beam collimator enables variability of the full width at half maximum (FWHM), the center-to-center distance (ctc), the peak-to-valley dose ratio (PVDR), and the source-to-collimator distance (SCD). METHODS: The mini-beam collimator is an in-house development, which was constructed of 10 ×  40 mm2 tungsten or brass plates. These metal plates were combined with 3D-printed plastic plates that can be stacked together in the desired order. A standard X-ray source was used for the dosimetric characterization of four different configurations of the collimator, including a combination of plastic plates of 0.5, 1, or 2 mm width, assembled with 1 or 2 mm thick metal plates. Irradiations were done at three different SCDs for characterizing the performance of the collimator. For the SCDs closer to the radiation source, the plastic plates were 3D-printed with a dedicated angle to compensate for the X-ray beam divergence, making it possible to study ultra-high dose rates of around 40 Gy/s. All dosimetric quantifications were performed using EBT-XD films. Additionally, in vitro studies with H460 cells were carried out. RESULTS: Characteristic mini-beam dose distributions were obtained with the developed collimator using a conventional X-ray source. With the exchangeable 3D-printed plates, FWHM and ctc from 0.52 to 2.11 mm, and from 1.77 to 4.61 mm were achieved, with uncertainties ranging from 0.01% to 8.98%, respectively. The FWHM and ctc obtained with the EBT-XD films are in agreement with the design of each mini-beam collimator configuration. For dose rates in the order of several Gy/min, the highest PVDR of 10.09 ± 1.08 was achieved with a collimator configuration of 0.5 mm thick plastic plates and 2 mm thick metal plates. Exchanging the tungsten plates with the lower-density metal brass reduced the PVDR by approximately 50%. Also, increasing the dose rate to ultra-high dose rates was feasible with the mini-beam collimator, where a PVDR of 24.26 ± 2.10 was achieved. Finally, it was possible to deliver and quantify mini-beam dose distribution patterns in vitro. CONCLUSIONS: With the developed collimator, we achieved various mini-beam dose distributions that can be adjusted according to the needs of the user in regards to FWHM, ctc, PVDR and SCD, while accounting for beam divergence. Therefore, the designed mini-beam collimator may enable low-cost and versatile pre-clinical research on mini-beam irradiation.

Human Cancer Cell Radiation Response Investigated through Topological Analysis of 2D Cell Networks.

Clonogenic assays are routinely used to evaluate the response of cancer cells to external radiation fields, assess their radioresistance and radiosensitivity, estimate the performance of radiotherapy. However, classic clonogenic tests focus on the number of colonies forming on a substrate upon exposure to ionizing radiation, and disregard other important characteristics of cells such their ability to generate structures with a certain shape. The radioresistance and radiosensitivity of cancer cells may depend less on the number of cells in a colony and more on the way cells interact to form complex networks. In this study, we have examined whether the topology of 2D cancer-cell graphs is influenced by ionizing radiation. We subjected different cancer cell lines, i.e. H4 epithelial neuroglioma cells, H460 lung cancer cells, PC3 bone metastasis of grade IV of prostate cancer and T24 urinary bladder cancer cells, cultured on planar surfaces, to increasing photon radiation levels up to 6 Gy. Fluorescence images of samples were then processed to determine the topological parameters of the cell-graphs developing over time. We found that the larger the dose, the less uniform the distribution of cells on the substrate-evidenced by high values of small-world coefficient (cc), high values of clustering coefficient (cc), and small values of characteristic path length (cpl). For all considered cell lines, [Formula: see text] for doses higher or equal to 4 Gy, while the sensitivity to the dose varied for different cell lines: T24 cells seem more distinctly affected by the radiation, followed by the H4, H460 and PC3 cells. Results of the work reinforce the view that the characteristics of cancer cells and their response to radiotherapy can be determined by examining their collective behavior-encoded in a few topological parameters-as an alternative to classical clonogenic assays.

A likelihood-based particle imaging filter using prior information.

BACKGROUND: Particle imaging can increase precision in proton and ion therapy. Interactions with nuclei in the imaged object increase image noise and reduce image quality, especially for multinucleon ions that can fragment, such as helium. PURPOSE: This work proposes a particle imaging filter, referred to as the Prior Filter, based on using prior information in the form of an estimated relative stopping power (RSP) map and the principles of electromagnetic interaction, to identify particles that have undergone nuclear interaction. The particles identified as having undergone nuclear interactions are then excluded from the image reconstruction, reducing the image noise. METHODS: The Prior Filter uses Fermi-Eyges scattering and Tschalär straggling theories to determine the likelihood that a particle only interacts electromagnetically. A threshold is then set to reject those particles with a low likelihood. The filter was evaluated and compared with a filter that estimates this likelihood based on the measured distribution of energy and scattering angle within pixels, commonly implemented as the 3σ filter. Reconstructed radiographs from simulated data of a 20-cm water cylinder and an anthropomorphic chest phantom were generated with both protons and helium ions to assess the effect of the filters on noise reduction. The simulation also allowed assessment of secondary particle removal through the particle histories. Experimental data were acquired of the Catphan CTP 404 Sensitometry phantom using the U.S. proton CT (pCT) collaboration prototype scanner. The proton and helium images were filtered with both the prior filtering method and a state-of-the-art method including an implementation of the 3σ filter. For both cases, a dE-E telescope filter, designed for this type of detector, was also applied. RESULTS: The proton radiographs showed a small reduction in noise (1 mm of water-equivalent thickness [WET]) but a larger reduction in helium radiographs (up to 5-6 mm of WET) due to better secondary filtering. The proton and helium CT images reflected this, with similar noise at the center of the phantom (0.02 RSP) for the proton images and an RSP noise of 0.03 for the proposed filter and 0.06 for the 3σ filter in the helium images. Images reconstructed from data with a dose reduction, up to a factor of 9, maintained a lower noise level using the Prior Filter over the state-of-the-art filtering method. CONCLUSIONS: The proposed filter results in images with equal or reduced noise compared to those that have undergone a filtering method typical of current particle imaging studies. This work also demonstrates that the proposed filter maintains better performance against the state of the art with up to a nine-fold dose reduction.

Correlative Raman-Electron-Light (CREL) Microscopy Analysis of Lipid Droplets in Melanoma Cancer Stem Cells.

Among all neoplasms, melanoma is characterized by a very high percentage of cancer stem cells (CSCs). Several markers have been proposed for their identification, and lipid droplets (LDs) are among them. Different techniques are used for their characterization such as mass spectrometry, imaging techniques, and vibrational spectroscopies. Some emerging experimental approaches for the study of LDs are represented by correlative light-electron microscopy and by correlative Raman imaging-scanning electron microscopy (SEM). Based on these scientific approaches, we developed a novel methodology (CREL) by combining Raman micro-spectroscopy, confocal fluorescence microscopy, and SEM coupled with an energy-dispersive X-ray spectroscopy module. This procedure correlated cellular morphology, chemical properties, and spatial distribution from the same region of interest, and in this work, we presented the application of CREL for the analysis of LDs within patient-derived melanoma CSCs (MCSCs).

Deep learning-based 4D-synthetic CTs from sparse-view CBCTs for dose calculations in adaptive proton therapy.

BACKGROUND: Time-resolved 4D cone beam-computed tomography (4D-CBCT) allows a daily assessment of patient anatomy and respiratory motion. However, 4D-CBCTs suffer from imaging artifacts that affect the CT number accuracy and prevent accurate proton dose calculations. Deep learning can be used to correct CT numbers and generate synthetic CTs (sCTs) that can enable CBCT-based proton dose calculations. PURPOSE: In this work, sparse view 4D-CBCTs were converted into 4D-sCT utilizing a deep convolutional neural network (DCNN). 4D-sCTs were evaluated in terms of image quality and dosimetric accuracy to determine if accurate proton dose calculations for adaptive proton therapy workflows of lung cancer patients are feasible. METHODS: A dataset of 45 thoracic cancer patients was utilized to train and evaluate a DCNN to generate 4D-sCTs, based on sparse view 4D-CBCTs reconstructed from projections acquired with a 3D acquisition protocol. Mean absolute error (MAE) and mean error were used as metrics to evaluate the image quality of single phases and average 4D-sCTs against 4D-CTs acquired on the same day. The dosimetric accuracy was checked globally (gamma analysis) and locally for target volumes and organs-at-risk (OARs) (lung, heart, and esophagus). Furthermore, 4D-sCTs were also compared to 3D-sCTs. To evaluate CT number accuracy, proton radiography simulations in 4D-sCT and 4D-CTs were compared in terms of range errors. The clinical suitability of 4D-sCTs was demonstrated by performing a 4D dose reconstruction using patient specific treatment delivery log files and breathing signals. RESULTS: 4D-sCTs resulted in average MAEs of 48.1 ± 6.5 HU (single phase) and 37.7 ± 6.2 HU (average). The global dosimetric evaluation showed gamma pass ratios of 92.3% ± 3.2% (single phase) and 94.4% ± 2.1% (average). The clinical target volume showed high agreement in D98 between 4D-CT and 4D-sCT, with differences below 2.4% for all patients. Larger dose differences were observed in mean doses of OARs (up to 8.4%). The comparison with 3D-sCTs showed no substantial image quality and dosimetric differences for the 4D-sCT average. Individual 4D-sCT phases showed slightly lower dosimetric accuracy. The range error evaluation revealed that lung tissues cause range errors about three times higher than the other tissues. CONCLUSION: In this study, we have investigated the accuracy of deep learning-based 4D-sCTs for daily dose calculations in adaptive proton therapy. Despite image quality differences between 4D-sCTs and 3D-sCTs, comparable dosimetric accuracy was observed globally and locally. Further improvement of 3D and 4D lung sCTs could be achieved by increasing CT number accuracy in lung tissues.

Changes in Radical Levels as a Cause for the FLASH effect: Impact of beam structure parameters at ultra-high dose rates on oxygen depletion in water.

The influence of different average and bunch dose rates in electron beams on the FLASH effect was investigated. The present study measures O2 content in water at different beam pulse patterns and finds strong correlation with biological data, strengthening the hypothesis of radical-related mechanisms as a reason for the FLASH effect.

Human lung-cancer-cell radioresistance investigated through 2D network topology.

Radiation therapy (RT) is now considered to be a main component of cancer therapy, alongside surgery, chemotherapy and monoclonal antibody-based immunotherapy. In RT, cancer tissues are exposed to ionizing radiation causing the death of malignant cells and favoring cancer regression. However, the efficiency of RT may be hampered by cell-radioresistance (RR)-that is a feature of tumor cells of withstanding RT. To improve the RT performance, it is decisive developing methods that can help to quantify cell sensitivity to radiation. In acknowledgment of the fact that none of the existing methods to assess RR are based on cell graphs topology, in this work we have examined how 2D cell networks, within a single colony, from different human lung cancer lines (H460, A549 and Calu-1) behave in response to doses of ionizing radiation ranging from 0 to 8 Gy. We measured the structure of resulting cell-graphs using well-assessed networks-analysis metrics, such as the clustering coefficient (cc), the characteristic path length (cpl), and the small world coefficient (SW). Findings of the work illustrate that the clustering characteristics of cell-networks show a marked sensitivity to the dose and cell line. Higher-than-one values of SW coefficient, clue of a discontinuous and inhomogeneous cell spatial layout, are associated to elevated levels of radiation and to a lower radio-resistance of the treated cell line. Results of the work suggest that topology could be used as a quantitative parameter to assess the cell radio-resistance and measure the performance of cancer radiotherapy.