Modulating Nucleus Oxygen Concentration by Altering Intramembrane Cholesterol Levels: Creating Hypoxic Nucleus in Oxic Conditions.

We propose a novel mechanism by which cancer cells can modulate the oxygen concentration within the nucleus, potentially creating low nuclear oxygen conditions without the need of an hypoxic micro-environment and suited for allowing cancer cells to resist chemo- and radio-therapy. The cells ability to alter intra-cellular oxygen conditions depends on the amount of cholesterol present within the cellular membranes, where high levels of cholesterol can yield rigid membranes that slow oxygen diffusion. The proposed mechanism centers on the competition between (1) the diffusion of oxygen within the cell and across cellular membranes that replenishes any consumed oxygen and (2) the consumption of oxygen in the mitochondria, peroxisomes, endoplasmic reticulum (ER), etc. The novelty of our work centers around the assumption that the cholesterol content of a membrane can affect the oxygen diffusion across the membrane, reducing the cell ability to replenish the oxygen consumed within the cell. For these conditions, the effective diffusion rate of oxygen becomes of the same order as the oxygen consumption rate, allowing the cell to reduce the oxygen concentration of the nucleus, with implications to the Warburg Effect. The cellular and nucleus oxygen content is indirectly evaluated experimentally for bladder (T24) cancer cells and during the cell cycle, where the cells are initially synchronized using hydroxeaurea (HU) at the late G1-phase/early S-phase. The analysis of cellular and nucleus oxygen concentration during cell cycle is performed via (i) RT-qPCR gene analysis of hypoxia inducible transcription factors (HIF) and prolyl hydroxylases (PHD) and (ii) radiation clonogenic assay every 2 h, after release from synchronization. The HIF/PHD genes allowed us to correlate cellular oxygen with oxygen concentration in the nucleus that is obtained from the cells radiation response, where the amount DNA damage due to radiation is directly related to the amount of oxygen present in the nucleus. We demonstrate that during the S-phase cells can become hypoxic in the late S-phase/early G2-phase and therefore the radiation resistance increases 2- to 3-fold.

Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks.

BACKGROUND: Proton computed tomography (pCT) and radiography (pRad) are proposed modalities for improved treatment plan accuracy and in situ treatment validation in proton therapy. The pCT system of the Bergen pCT collaboration is able to handle very high particle intensities by means of track reconstruction. However, incorrectly reconstructed and secondary tracks degrade the image quality. We have investigated whether a convolutional neural network (CNN)-based filter is able to improve the image quality. MATERIAL AND METHODS: The CNN was trained by simulation and reconstruction of tens of millions of proton and helium tracks. The CNN filter was then compared to simple energy loss threshold methods using the Area Under the Receiver Operating Characteristics curve (AUROC), and by comparing the image quality and Water Equivalent Path Length (WEPL) error of proton and helium radiographs filtered with the same methods. RESULTS: The CNN method led to a considerable improvement of the AUROC, from 74.3% to 97.5% with protons and from 94.2% to 99.5% with helium. The CNN filtering reduced the WEPL error in the helium radiograph from 1.03 mm to 0.93 mm while no improvement was seen in the CNN filtered pRads. CONCLUSION: The CNN improved the filtering of proton and helium tracks. Only in the helium radiograph did this lead to improved image quality.

Lipid Droplet Biosynthesis Impairment through DGAT2 Inhibition Sensitizes MCF7 Breast Cancer Cells to Radiation.

Breast cancer is the most frequent cancer in women worldwide and late diagnosis often adversely affects the prognosis of the disease. Radiotherapy is commonly used to treat breast cancer, reducing the risk of recurrence after surgery. However, the eradication of radioresistant cancer cells, including cancer stem cells, remains the main challenge of radiotherapy. Recently, lipid droplets (LDs) have been proposed as functional markers of cancer stem cells, also being involved in increased cell tumorigenicity. LD biogenesis is a multistep process requiring various enzymes, including Diacylglycerol acyltransferase 2 (DGAT2). In this context, we evaluated the effect of PF-06424439, a selective DGAT2 inhibitor, on MCF7 breast cancer cells exposed to X-rays. Our results demonstrated that 72 h of PF-06424439 treatment reduced LD content and inhibited cell migration, without affecting cell proliferation. Interestingly, PF-06424439 pre-treatment followed by radiation was able to enhance radiosensitivity of MCF7 cells. In addition, the combined treatment negatively interfered with lipid metabolism-related genes, as well as with EMT gene expression, and modulated the expression of typical markers associated with the CSC-like phenotype. These findings suggest that PF-06424439 pre-treatment coupled to X-ray exposure might potentiate breast cancer cell radiosensitivity and potentially improve the radiotherapy effectiveness.

Proton range shift analysis on brain pseudo-CT generated from T1 and T2 MR.

BACKGROUND: In radiotherapy, MR imaging is only used because it has significantly better soft tissue contrast than CT, but it lacks electron density information needed for dose calculation. This work assesses the feasibility of using pseudo-CT (pCT) generated from T1w/T2w MR for proton treatment planning, where proton range comparisons are performed between standard CT and pCT. MATERIAL AND METHODS: MR and CT data from 14 glioblastoma patients were used in this study. The pCT was generated by using conversion libraries obtained from tissue segmentation and anatomical regioning of the T1w/T2w MR. For each patient, a plan consisting of three 18 Gy beams was designed on the pCT, for a total of 42 analyzed beams. The plan was then transferred onto the CT that represented the ground truth. Range shift (RS) between pCT and CT was computed at R80 over 10 slices. The acceptance threshold for RS was according to clinical guidelines of two institutions. A γ-index test was also performed on the total dose for each patient. RESULTS: Mean absolute error and bias for the pCT were 124 ± 10 and -16 ± 26 Hounsfield Units (HU), respectively. The median and interquartile range of RS was 0.5 and 1.4 mm, with highest absolute value being 4.4 mm. Of the 42 beams, 40 showed RS less than the clinical range margin. The two beams with larger RS were both in the cranio-caudal direction and had segmentation errors due to the partial volume effect, leading to misassignment of the HU. CONCLUSIONS: This study showed the feasibility of using T1w and T2w MRI to generate a pCT for proton therapy treatment, thus avoiding the use of a planning CT and allowing better target definition and possibilities for online adaptive therapies. Further improvements of the methodology are still required to improve the conversion from MRI intensities to HUs.

A simulation study on proton computed tomography (CT) stopping power accuracy using dual energy CT scans as benchmark.

BACKGROUND: Accurate stopping power estimation is crucial for treatment planning in proton therapy, and the uncertainties in stopping power are currently the largest contributor to the employed dose margins. Dual energy x-ray computed tomography (CT) (clinically available) and proton CT (in development) have both been proposed as methods for obtaining patient stopping power maps. The purpose of this work was to assess the accuracy of proton CT using dual energy CT scans of phantoms to establish reference accuracy levels. MATERIAL AND METHODS: A CT calibration phantom and an abdomen cross section phantom containing inserts were scanned with dual energy and single energy CT with a state-of-the-art dual energy CT scanner. Proton CT scans were simulated using Monte Carlo methods. The simulations followed the setup used in current prototype proton CT scanners and included realistic modeling of detectors and the corresponding noise characteristics. Stopping power maps were calculated for all three scans, and compared with the ground truth stopping power from the phantoms. RESULTS: Proton CT gave slightly better stopping power estimates than the dual energy CT method, with root mean square errors of 0.2% and 0.5% (for each phantom) compared to 0.5% and 0.9%. Single energy CT root mean square errors were 2.7% and 1.6%. Maximal errors for proton, dual energy and single energy CT were 0.51%, 1.7% and 7.4%, respectively. CONCLUSION: Better stopping power estimates could significantly reduce the range errors in proton therapy, but requires a large improvement in current methods which may be achievable with proton CT.

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.

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.

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.

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.

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.

Dosimetric assessment of a novel metal artifact reduction method in CT images.

The aim of this study was to assess the ability of metal artifact reduction (MAR) algorithm in restoring the CT image quality while correcting the tissue density information for the accurate estimation of the absorbed dose. A phantom filled with titanium (low-Z metal) and Cerrobend (high-Z metal) inserts was used for this purpose. The MAR algorithm was applied to phantom's CT dataset. Static intensity-modulated radiation therapy (IMRT) plans, including five beam angles, were designed and optimized on the uncorrected images to deliver 10 Gy on the simulated target. Monte Carlo dose calculation was computed on uncorrected, corrected, and ground truth image datasets. It was firstly verified that MAR methodology was able to correct HU errors due to the metal presence. In the worst situation (high-Z phantom), the image difference, uncorrected ground truth and corrected ground truth, went from -4.4 ± 118.8 HU to 0.4 ± 10.8 HU, respectively. Secondly, it was observed that the impact of dose errors estimation depends on the atomic number of the metal: low-Z inserts do not produce significant dose inaccuracies, while high-Z implants substantially influence the computation of the absorbed dose. In this latter case, dose errors in the PTV region were up to 23.56% (9.72% mean value) when comparing the uncorrected vs. the ground truth dataset. After MAR correction, errors dropped to 0.11% (0.10% mean value). In conclusion, it was assessed that the new MAR algorithm is able to restore image quality without distorting mass density information, thus producing a more accurate dose estimation.

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 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.

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.

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.

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.

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.

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.