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Background: Positron emission tomography (PET) has been investigated for its ability to reconstruct proton-induced positron activity distributions in proton therapy. This technique holds potential for range verification in clinical practice. Recently, deep learning-based dose estimation from positron activity distributions shows promise for in vivo proton dose monitoring and guided proton therapy., Purpose: This study evaluates the effectiveness of three classical neural network models, recurrent neural network (RNN), U-Net, and Transformer, for proton dose estimating. It also investigates the characteristics of these models, providing valuable insights for selecting the appropriate model in clinical practice., Methods: Proton dose calculations for spot beams were simulated using Geant4. Computed tomography (CT) images from four head cases were utilized, with three for training neural networks and the remaining one for testing. The neural networks were trained with one-dimensional (1D) positron activity distributions as inputs and generated 1D dose distributions as outputs. The impact of the number of training samples on the networks was examined, and their dose prediction performance in both homogeneous brain and heterogeneous nasopharynx sites was evaluated. Additionally, the effect of positron activity distribution uncertainty on dose prediction performance was investigated. To quantitatively evaluate the models, mean relative error (MRE) and absolute range error (ARE) were used as evaluation metrics., Results: The U-Net exhibited a notable advantage in range verification with a smaller number of training samples, achieving approximately 75% of AREs below 0.5 mm using only 500 training samples. The networks performed better in the homogeneous brain site compared to the heterogeneous nasopharyngeal site. In the homogeneous brain site, all networks exhibited small AREs, with approximately 90% of the AREs below 0.5 mm. The Transformer exhibited the best overall dose distribution prediction, with approximately 92% of MREs below 3%. In the heterogeneous nasopharyngeal site, all networks demonstrated acceptable AREs, with approximately 88% of AREs below 3 mm. The Transformer maintained the best overall dose distribution prediction, with approximately 85% of MREs below 5%. The performance of all three networks in dose prediction declined as the uncertainty of positron activity distribution increased, and the Transformer consistently outperformed the other networks in all cases., Conclusions: Both the U-Net and the Transformer have certain advantages in the proton dose estimation task. The U-Net proves well suited for range verification with a small training sample size, while the Transformer outperforms others at dose-guided proton therapy., (© 2024 American Association of Physicists in Medicine.)

Purpose: Ionoacoustics is one of the promising approaches to verify the beam range in proton therapy. However, the weakness of the wave signal remains a main hindrance to its application in clinics. Here we studied the potential use of a fixed-field alternating gradient accelerator (FFA), one of the accelerator candidates for future proton therapy. For such end, magnitude of the pressure wave and range accuracy achieved by the short-pulsed beam of FFA were assessed, using both simulation and experimental procedure., Methods: A 100 MeV proton beam from the FFA was applied on a water phantom, through the acrylic wall. The beam range measured by the Bragg peak (BP)-ionization chamber (BPC) was 77.6 mm, while the maximum dose at BP was estimated to be 0.35 Gy/pulse. A hydrophone was placed 20 mm downstream of the BP, and signals were amplified and stored by a digital oscilloscope, averaged, and low-pass filtered. Time-of-flight (TOF) and two relative TOF values were analyzed in order to determine the beam range. Furthermore, an acoustic wave transport simulation was conducted to estimate the amplitude of the pressure waves., Results: The range calculated when using two relative TOF was 78.16 ± 0.01 and 78.14 ± 0.01 mm, respectively, both values being coherent with the range measured by the BPC (the difference was 0.5-0.6 mm). In contrast, utilizing the direct TOF resulted in a range error of 1.8 mm. Fivefold and 50-fold averaging were required to suppress the range variation to below 1 mm for TOF and relative TOF measures, respectively. The simulation suggested the magnitude of pressure wave at the detector exceeded 7 Pascal., Conclusion: A submillimeter range accuracy was attained with a pulsed beam of about 21 ns from an FFA, at a clinical energy using relative TOF. To precisely quantify the range with a single TOF measurement, subsequent improvement in the measuring system is required., (© 2021 American Association of Physicists in Medicine.)

Purpose: The implementation of volumetric in-room imaging for online adaptive radiotherapy makes extensive testing of this image data for treatment planning necessary. Especially for proton beams the higher sensitivity to stopping power properties of the tissue results in more stringent requirements. Current approaches mainly focus on recalculation of the plans on the new image data, lacking experimental verification, and ignoring the impact on the plan re-optimization process. The aim of this study was to use gel and film dosimetry coupled with a three-dimensional (3D) printed head phantom (based on the planning CT of the patient) for 3D range verification of intensity-corrected cone beam computed tomography (CBCT) image data for adaptive proton therapy., Methods: Single field uniform dose pencil beam scanning proton plans were optimized for three different patients on the patients' planning CT (planCT) and the patients' intensity-corrected CBCT (scCBCT) for the same target volume using the same optimization constraints. The CBCTs were corrected on projection level using the planCT as a prior. The dose optimized on planCT and recalculated on scCBCT was compared in terms of proton range differences (80% distal fall-off, recalculation). Moreover, the dose distribution resulting from recalculation of the scCBCT-optimized plan on the planCT and the original planCT dose distribution were compared (simulation). Finally, the two plans of each patient were irradiated on the corresponding patient-specific 3D printed head phantom using gel dosimetry inserts for one patient and film dosimetry for all three patients. Range differences were extracted from the measured dose distributions. The measured and the simulated range differences were corrected for range differences originating from the initial plans and evaluated., Results: The simulation approach showed high agreement with the standard recalculation approach. The median values of the range differences of these two methods agreed within 0.1 mm and the interquartile ranges (IQRs) within 0.3 mm for all three patients. The range differences of the film measurement were accurately matching with the simulation approach in the film plane. The median values of these range differences deviated less than 0.1 mm and the IQRs less than 0.4 mm. For the full 3D evaluation of the gel range differences, the median value and IQR matched those of the simulation approach within 0.7 and 0.5 mm, respectively. scCBCT- and planCT-based dose distributions were found to have a range agreement better than 3 mm (median and IQR) for all considered scenarios (recalculation, simulation, and measurement)., Conclusions: The results of this initial study indicate that an online adaptive proton workflow based on scatter-corrected CBCT image data for head irradiations is feasible. The novel presented measurement- and simulation-based method was shown to be equivalent to the standard literature recalculation approach. Additionally, it has the capability to catch effects of image differences on the treatment plan optimization. This makes the measurement-based approach particularly interesting for quality assurance of CBCT-based online adaptive proton therapy. The observed uncertainties could be kept within those of the registration and positioning. The proposed validation could also be applied for other alternative in-room images, e.g. for MR-based pseudoCTs., (© 2021 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Abstract Proton therapy is a fast growing treatment modality for cancer and is in selected cases preferred over conventional radiotherapy with photons because of the highly conformal dose distribution that can be achieved with protons due to their steep dose gradients. However, these steep gradients also make proton therapy sensitive to range uncertainties. Proton ranges are calculated from proton stopping powers relative to that in water (Relative Stopping Power, RSP). The RSPs needed for a treatment plan can be estimated from CT (Computed Tomography) data of a patient. High accuracy reference values of RSPs are required to assess the accuracy of these CT based estimates. In this paper we present a water phantom that enables accurate measurement of depth dose profiles in water. Experimental RSPs with a relative standard uncertainty smaller than 0.4% (1 σ) for samples with a water equivalent thickness of about 2 cm can be derived from the measured depth dose distributions. Most CT based RSP estimates use an approximate RSP model based on the Bethe-Bloch formula without the shell, density, Barkas and Bloch correction. In the Geant4 Monte Carlo code these corrections are included and RSP calculations with this code are expected to be more accurate. In this work, a set of 32 well defined (composition and density), mostly clinically relevant materials is used to assess the correspondence between RSPs that were measured, that were estimated from the approximate RSP model and that were calculated from Monte Carlo simulations. With the measured RSPs we provide a ground-truth bench mark to test the validity of RSPs derived from CT imaging and Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

To improve the quality of cancer treatment with protons, a translation of X-ray Computed Tomography (CT) images into a map of the proton stopping powers needs to be more accurate. Proton stopping powers determined from CT images have systematic uncertainties in the calculated proton range in a patient of typically 3-4% and even up to 10% in a region containing bone. As a consequence, part of a tumor may receive no dose, or a very high dose can be delivered in healthy tissues and organs at risks (e.g. brain stem). A transmission radiograph of high-energy protons measuring proton stopping powers directly will allow to reduce these uncertainties, and thus improve the quality of treatment. The best way to obtain a sufficiently accurate radiograph is by tracking individual protons traversing the phantom (patient). In our simulations, we have used an ideal position sensitive detectors measuring a single proton before and after a phantom, while the residual energy of a proton was detected by a BaF2 crystal. To obtain transmission radiographs, different phantom materials have been irradiated with a 3 × 3 cm2 scattered proton beam, with various beam energies. The simulations were done using the Geant4 simulation package. In this study, we focus on the simulations of the energy loss radiographs for various proton beam energies that are clinically available in proton radiotherapy. [ABSTRACT FROM AUTHOR]

Boron-enhanced proton therapy has recently appeared as a promising approach to increase the efficiency of proton therapy on tumor cells, and this modality can further be improved by the use of boron nanoparticles (B NPs) as local sensitizers to achieve enhanced and targeted therapeutic outcomes. However, the mechanisms of tumor cell elimination under boron-enhanced proton therapy still require clarification. Here, we explore possible molecular mechanisms responsible for the enhancement of therapeutic outcomes under boron NP-enhanced proton therapy. Spherical B NPs with a mode size of 25 nm were prepared by methods of pulsed laser ablation in water, followed by their coating by polyethylene glycol to improve their colloidal stability in buffers. Then, we assessed the efficiency of B NPs as sensitizers of cancer cell killing under irradiation with a 160.5 MeV proton beam. Our experiments showed that the combined effect of B NPs and proton irradiation induces an increased level of superoxide anion radical generation, which leads to the depolarization of mitochondria, a drop in their membrane mitochondrial potential, and the development of apoptosis. A comprehensive gene expression analysis (via RT-PCR) confirmed increased overexpression of 52 genes (out of 87 studied) involved in the cell redox status and oxidative stress, compared to 12 genes in the cells irradiated without B NPs. Other possible mechanisms responsible for the B NPs-induced radiosensitizing effect, including one related to the generation of alpha particles, are discussed. The obtained results give a better insight into the processes involved in the boron-induced enhancement of proton therapy and enable one to optimize parameters of proton therapy in order to maximize therapeutic outcomes. [ABSTRACT FROM AUTHOR]

Purpose: We investigated the design of a prompt gamma camera for real‐time dose delivery verification and the partial mitigation of range uncertainties. Methods: A slit slat (SS) camera was optimized using the trade‐off between the signal‐to‐noise ratio and spatial resolution. Then, using the GATE Monte Carlo package, the camera performances were estimated by means of target shifts, beam position quantification, changing the camera distance from the beam, and air cavity inserting. A homogeneous PMMA phantom and the air gaps induced PMMA phantom were used. The air gaps ranged from 5 mm to 30 mm by 5 mm increments were positioned in the middle of the beam range. To reduce the simulation time, phase space scoring was used. The batch method with five realizations was used for stochastic error calculations. Results: The system's detection efficiency was 1.1×10−4PGsEmittedPGs(1.8×10−5$1.1 \times {10}^{-4}\frac{{\rm PGs}}{{\rm Emitted}\ {\rm PGs}}\ (1.8 \times {10}^{-5}$ PGs/proton) for a 10 × 20 cm2 detector (source‐to‐collimator distance = 15.0 cm). Axial and transaxial resolutions were 23 mm and 18 mm, respectively. The SS camera estimated the range as 69.0 ± 3.4 (relative stochastic error 1‐sigma is 5%) and 67.6 ± 1.8 mm (2.6%) for the real range of 67.0 mm for 107 and 108 protons of 100 MeV, respectively. Considering 160 MeV, these values are 155.5 ± 3.1 (2%) and 152.2 ± 2.0 mm (1.3%) for the real range of 152.0 mm for 107 and 108 protons, respectively. Considering phantom shift, for a 100 MeV beam, the precision of the quantification (1‐sigma) in the axial and lateral phantom shift estimation is 2.6 mm and 1 mm, respectively. Accordingly, the axial and lateral quantification precisions were 1.3 mm and 1 mm for a 160 MeV beam, respectively. Furthermore, the quantification of an air gap formulated as gapdet=0.98×gapreal${{\rm gap}}_{det}=0.98 \times {{\rm gap}}_{{\rm real}}$, where gapdet${{\rm gap}}_{det}$ and gapreal are the estimated and real air gap, respectively. The precision of the air gap quantification is 1.6 mm (1 sigma). Moreover, 2D PG images show the trajectory of the proton beam through the phantom. Conclusion: The proposed slit‐slat imaging systems can potentially provide a real‐time, in‐vivo, and non‐invasive treatment monitoring method for proton therapy. [ABSTRACT FROM AUTHOR]

Purpose: Eye‐dedicated proton therapy (PT) facilities are used to treat malignant intraocular lesions, especially uveal melanoma (UM). The first commercial ocular PT beamline from Varian was installed in the Netherlands. In this work, the conceptual design of the new eyeline is presented. In addition, a comprehensive comparison against five PT centers with dedicated ocular beamlines is performed, and the clinical impact of the identified differences is analyzed. Material/Methods: The HollandPTC eyeline was characterized. Four centers in Europe and one in the United States joined the study. All centers use a cyclotron for proton beam generation and an eye‐dedicated nozzle. Differences among the chosen ocular beamlines were in the design of the nozzle, nominal energy, and energy spectrum. The following parameters were collected for all centers: technical characteristics and a set of distal, proximal, and lateral region measurements. The measurements were performed with detectors available in‐house at each institution. The institutions followed the International Atomic Energy Agency (IAEA) Technical Report Series (TRS)‐398 Code of Practice for absolute dose measurement, and the IAEA TRS‐398 Code of Practice, its modified version or International Commission on Radiation Units and Measurements Report No. 78 for spread‐out Bragg peak normalization. Energy spreads of the pristine Bragg peaks were obtained with Monte Carlo simulations using Geant4. Seven tumor‐specific case scenarios were simulated to evaluate the clinical impact among centers: small, medium, and large UM, located either anteriorly, at the equator, or posteriorly within the eye. Differences in the depth dose distributions were calculated. Results: A pristine Bragg peak of HollandPTC eyeline corresponded to the constant energy of 75 MeV (maximal range 3.97 g/cm2 in water) with an energy spread of 1.10 MeV. The pristine Bragg peaks for the five participating centers varied from 62.50 to 104.50 MeV with an energy spread variation between 0.10 and 0.70 MeV. Differences in the average distal fall‐offs and lateral penumbrae (LPs) (over the complete set of clinically available beam modulations) among all centers were up to 0.25 g/cm2, and 0.80 mm, respectively. Average distal fall‐offs of the HollandPTC eyeline were 0.20 g/cm2, and LPs were between 1.50 and 2.15 mm from proximal to distal regions, respectively. Treatment time, around 60 s, was comparable among all centers. The virtual source‐to‐axis distance of 120 cm at HollandPTC was shorter than for the five participating centers (range: 165–350 cm). Simulated depth dose distributions demonstrated the impact of the different beamline characteristics among institutions. The largest difference was observed for a small UM located at the posterior pole, where a proximal dose between two extreme centers was up to 20%. Conclusions: HollandPTC eyeline specifications are in accordance with five other ocular PT beamlines. Similar clinical concepts can be applied to expect the same high local tumor control. Dosimetrical properties among the six institutions induce most likely differences in ocular radiation‐related toxicities. This interinstitutional comparison could support further research on ocular post‐PT complications. Finally, the findings reported in this study could be used to define dosimetrical guidelines for ocular PT to unify the concepts among institutions. [ABSTRACT FROM AUTHOR]

The goal of this work was to create a technique that could measure all possible spatial and temporal delivery rates used in pencil-beam scanning (PBS) proton therapy. The proposed system used a fast scintillation screen for full-field imaging to resolve temporal and spatial patterns as it was delivered. A fast intensified CMOS camera used continuous mode with 10 ms temporal frame rate and 1 × 1 mm2 spatial resolution, imaging a scintillation screen during clinical proton PBS delivery. PBS plans with varying dose, dose rate, energy, field size, and spot-spacing were generated, delivered and imaged. The captured images were post processed to provide dose and dose rate values after background subtraction, perspective transformation, uniformity correction for the camera and the scintillation screen, and calibration into dose. The linearity in scintillation response with respect to varying dose rate, dose, and field size was within 2%. The quenching corrected response with varying energy was also within 2%. Large spatio-temporal variations in dose rate were observed, even for plans delivered with similar dose distributions. Dose and dose rate histograms and maximum dose rate maps were generated for quantitative evaluations. With the fastest PBS delivery on a clinical system, dose rates up to 26.0 Gy s−1 were resolved. The scintillation imaging technique was able to quantify proton PBS dose rate profiles with spot weight as low as 2 MU, with spot-spacing of 2.5 mm, having a 1 × 1 mm2 spatial resolution. These dose rate temporal profiles, spatial maps, and cumulative dose rate histograms provide useful metrics for the potential evaluation and optimization of dose rate in treatment plans. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to assess the performance of a novel dual‐energy CT (DECT) approach for proton stopping power ratio (SPR) mapping that integrates image reconstruction and material characterization using a joint statistical image reconstruction (JSIR) method based on a linear basis vector model (BVM). A systematic comparison between the JSIR‐BVM method and previously described DECT image‐ and sinogram‐domain decomposition approaches is also carried out on synthetic data. Methods: The JSIR‐BVM method was implemented to estimate the electron densities and mean excitation energies (I‐values) required by the Bethe equation for SPR mapping. In addition, image‐ and sinogram‐domain DECT methods based on three available SPR models including BVM were implemented for comparison. The intrinsic SPR modeling accuracy of the three models was first validated. Synthetic DECT transmission sinograms of two 330 mm diameter phantoms each containing 17 soft and bony tissues (for a total of 34) of known composition were then generated with spectra of 90 and 140 kVp. The estimation accuracy of the reconstructed SPR images were evaluated for the seven investigated methods. The impact of phantom size and insert location on SPR estimation accuracy was also investigated. Results: All three selected DECT‐SPR models predict the SPR of all tissue types with less than 0.2% RMS errors under idealized conditions with no reconstruction uncertainties. When applied to synthetic sinograms, the JSIR‐BVM method achieves the best performance with mean and RMS‐average errors of less than 0.05% and 0.3%, respectively, for all noise levels, while the image‐ and sinogram‐domain decomposition methods show increasing mean and RMS‐average errors with increasing noise level. The JSIR‐BVM method also reduces statistical SPR variation by sixfold compared to other methods. A 25% phantom diameter change causes up to 4% SPR differences for the image‐domain decomposition approach, while the JSIR‐BVM method and sinogram‐domain decomposition methods are insensitive to size change. Conclusion: Among all the investigated methods, the JSIR‐BVM method achieves the best performance for SPR estimation in our simulation phantom study. This novel method is robust with respect to sinogram noise and residual beam‐hardening effects, yielding SPR estimation errors comparable to intrinsic BVM modeling error. In contrast, the achievable SPR estimation accuracy of the image‐ and sinogram‐domain decomposition methods is dominated by the CT image intensity uncertainties introduced by the reconstruction and decomposition processes. [ABSTRACT FROM AUTHOR]

Purpose Dual-energy CT ( DECT) promises improvements in estimating stopping power ratios ( SPRs) for proton therapy treatment planning. Although several comparable mathematical formalisms have been proposed in literature, the optimal techniques to characterize human tissue SPRs with DECT in a clinical environment are not fully established. The aim of this work is to compare the most robust DECT methods against conventional single-energy CT ( SECT) in conditions reproducing a clinical environment, where CT artifacts and noise play a major role on the accuracy of these techniques. Methods Available DECT tissue characterization methods are investigated and their ability to predict SPRs is compared in three contexts: (a) a theoretical environment using the XCOM cross section database; (b) experimental data using a dual-source CT scanner on a calibration phantom; (c) simulations of a virtual humanoid phantom with the ImaSim software. The latter comparison accounts for uncertainties caused by CT artifacts and noise, but leaves aside other sources of uncertainties such as CT grid size and the I-values. To evaluate the clinical impact, a beam range calculation model is used to predict errors from the probability distribution functions determined with ImaSim simulations. Range errors caused by SPR errors in soft tissues and bones are investigated. Results Range error estimations demonstrate that DECT has the potential of reducing proton beam range uncertainties by 0.4% in soft tissues using low noise levels of 12 and 8 HU in DECT, corresponding to 7 HU in SECT. For range uncertainties caused by the transport of protons through bones, the reduction in range uncertainties for the same levels of noise is found to be up to 0.6 to 1.1 mm for bone thicknesses ranging from 1 to 5 cm, respectively. We also show that for double the amount noise, i.e., 14 HU in SECT and 24 and 16 HU for DECT, the advantages of DECT in soft tissues are lost over SECT. In bones however, the reduction in range uncertainties is found to be between 0.5 and 0.9 mm for bone thicknesses ranging from 1 to 5 cm, respectively. Conclusion DECT has a clear potential to improve proton beam range predictions over SECT in proton therapy. However, in the current state high levels of noise remain problematic for DECT characterization methods and do not allow getting the full benefits of this technology. Future work should focus on adapting DECT methods to noise and investigate methods based on raw-data to reduce CT artifacts. [ABSTRACT FROM AUTHOR]

Noble metal nanoparticles, such as gold (Au NPs), platinum (Pt NPs), or palladium (Pd NPs), due to their highly developed surface, stability, and radiosensitizing properties, can be applied to support proton therapy (PT) of cancer. In this paper, we investigated the potential of bimetallic, c.a. 30 nm PtAu and PdAu nanocomplexes, synthesized by the green chemistry method and not used previously as radiosensitizers, to enhance the effect of colorectal cancer PT in vitro. The obtained nanomaterials were characterized by scanning transmission electron microscopy (STEM), selected area electron diffraction (SAED), energy-dispersive X-ray spectroscopy (EDS), UV-Vis spectroscopy, and zeta potential measurements. The effect of PtAu and PdAu NPs in PT was investigated on colon cancer cell lines (SW480, SW620, and HCT116), as well as normal colon epithelium cell line (FHC). These cells were cultured with both types of NPs and then irradiated by proton beam with a total dose of 15 Gy. The results of the MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) test showed that the NPs-assisted PT resulted in a better anticancer effect than PT used alone; however, there was no significant difference in the radiosensitizing properties between tested nanocomplexes. The MTS results were further verified by defining the cell death as apoptosis (Annexin V binding assay). Furthermore, the data showed that such a treatment was more selective for cancer cells, as normal cell viability was only slightly affected. [ABSTRACT FROM AUTHOR]

Simple Summary: An increasing number of cancer patients are treated with proton therapy. Nevertheless, there are still open questions that require preclinical studies, for example, those regarding long-term side effects or new treatment approaches. In this review, we discuss the main research topics of proton radiobiology and describe the typical challenges related to preclinical experiments in this field. We provide a summary of the different available preclinical models, and how they were applied to conduct proton-specific research in the past. This includes cell culture models of increasing complexity, animal studies, and computer simulations. In addition, we give an overview of possible endpoints and suggest models from other disciplines for adaptation to biomedical proton research. In doing so, we contribute to designing meaningful research studies in the future, which will ultimately help to improve patient treatment. The number of proton therapy centers worldwide are increasing steadily, with more than two million cancer patients treated so far. Despite this development, pending questions on proton radiobiology still call for basic and translational preclinical research. Open issues are the on-going discussion on an energy-dependent varying proton RBE (relative biological effectiveness), a better characterization of normal tissue side effects and combination treatments with drugs originally developed for photon therapy. At the same time, novel possibilities arise, such as radioimmunotherapy, and new proton therapy schemata, such as FLASH irradiation and proton mini-beams. The study of those aspects demands for radiobiological models at different stages along the translational chain, allowing the investigation of mechanisms from the molecular level to whole organisms. Focusing on the challenges and specifics of proton research, this review summarizes the different available models, ranging from in vitro systems to animal studies of increasing complexity as well as complementing in silico approaches. [ABSTRACT FROM AUTHOR]

Gold nanoparticles (GNPs) are promising radiosensitizers with the potential to enhance radiotherapy. Experiments have shown GNP enhancement of proton therapy and indicated that chemical damage by reactive species plays a major role. Simulations of the distribution and yield of reactive species from 10 ps to 1 µs produced by a single GNP, two GNPs in proximity and a GNP cluster irradiated with a proton beam were performed using the Geant4 Monte Carlo toolkit. It was found that the reactive species distribution at 1 µs extended a few hundred nm from a GNP and that the largest enhancement occurred over 50 nm from the nanoparticle. Additionally, the yield for two GNPs in proximity and a GNP cluster was reduced by up to 17% and 60% respectively from increased absorption. The extended range of action from the diffusion of the reactive species may enable simulations to model GNP enhanced proton therapy. The high levels of absorption for a large GNP cluster suggest that smaller clusters and diffuse GNP distributions maximize the total radiolysis yield within a cell. However, this must be balanced against the high local yields near a cluster particularly if the cluster is located adjacent to a biological target. [ABSTRACT FROM AUTHOR]

Proton radiography, which images patients with the same type of particles as those with which they are to be treated, is a promising approach to image guidance and water equivalent path length (WEPL) verification in proton radiation therapy. We have shown recently that proton radiographs could be obtained by measuring time-resolved dose rate functions (DRFs) using an x-ray amorphous silicon flat panel. The WEPL values were derived solely from the root-mean-square (RMS) of DRFs, while the intensity information in the DRFs was filtered out. In this work, we explored the use of such intensity information for potential improvement in WEPL accuracy and imaging quality. Three WEPL derivation methods based on, respectively, the RMS only, the intensity only, and the intensity-weighted RMS were tested and compared in terms of the quality of obtained radiograph images and the accuracy of WEPL values. A Gammex CT calibration phantom containing inserts made of various tissue substitute materials with independently measured relative stopping powers (RSP) was used to assess the imaging performances. Improved image quality with enhanced interfaces was achieved while preserving the accuracy by using intensity information in the calibration. Other objects, including an anthropomorphic head phantom, a proton therapy range compensator, a frozen lamb’s head and an ‘image quality phantom’ were also imaged. Both the RMS only and the intensity-weighted RMS methods derived RSPs within  ±  1% for most of the Gammex phantom inserts, with a mean absolute percentage error of 0.66% for all inserts. In the case of the insert with a titanium rod, the method based on RMS completely failed, whereas that based on the intensity-weighted RMS was qualitatively valid. The use of intensity greatly enhanced the interfaces between different materials in the obtained WEPL images, suggesting the potential for image guidance in areas such as patient positioning and tumor tracking by proton radiography. [ABSTRACT FROM AUTHOR]

Treatment quality assessment is a crucial feature for both present and next-generation ion therapy facilities. Several approaches are being explored, based on prompt radiation emission or on PET signals by -decaying isotopes generated by beam interactions with the body. In-beam PET monitoring at synchrotron-based ion therapy facilities has already been performed, either based on inter-spill data only, to avoid the influence of the prompt radiation, or including both in-spill and inter-spill data. However, the PET images either suffer of poor statistics (inter-spill) or are more influenced by the background induced by prompt radiation (in-spill). Both those problems are expected to worsen for accelerators with improved duty cycle where the inter-spill interval is reduced to shorten the treatment time. With the aim of assessing the detector performance and developing techniques for background reduction, a test of an in-beam PET detector prototype was performed at the CNAO synchrotron-based ion therapy facility in full-beam acquisition modality. Data taken with proton beams impinging on PMMA phantoms showed the system acquisition capability and the resulting activity distribution, separately reconstructed for the in-spill and the inter-spill data. The coincidence time resolution for in-spill and inter-spill data shows a good agreement, with a slight deterioration during the spill. The data selection technique allows the identification and rejection of most of the background originated during the beam delivery. The activity range difference between two different proton beam energies (68 and 72 MeV) was measured and found to be in sub-millimeter agreement with the expected result. However, a slightly longer (2 mm) absolute profile length is obtained for in-spill data when compared to inter-spill data. [ABSTRACT FROM AUTHOR]