Search

Nanodroplets have demonstrated potential for the range detection of hadron radiotherapies. Our formulation uses superheated perfluorobutane (C4F10) stabilized by a poly(vinyl-alcohol) shell. High-LET (linear energy transfer) particles vaporize the nanodroplets into echogenic microbubbles. Tailored ultrasound imaging translates the generated echo-contrast into a dose distribution map, enabling beam range retrieval. This work evaluates the response of size-sorted nanodroplets to carbon-ion radiation. We studied how thesize of nanodroplets affects their sensitivity at various beam-doses and energies, as a function of concentration and shell cross-linking. First, we show the physicochemical characterization of size-isolated nanodroplets by differential centrifugation. Then, we report on the irradiations of the nanodroplet samples in tissue-mimicking phantoms. We compared the response of large (≈900 nm) and small (≈400 nm) nanodroplets to different carbon-ions energies and evaluated their dose linearity and concentration detection thresholds by ultrasound imaging. Additionally, we verified the beam range detection accuracy for the nanodroplets samples. All nanodroplets exhibited sensitivity to carbon-ions with high range verification precision. However, smaller nanodroplets required a higher concentration sensitivity threshold. The vaporization yield depends on the carbon-ions energy and dose, which are both related to particle count/spot. These findings confirm the potential of nanodroplets for range detection, with performance depending on nanodroplets' properties and beam parameters. [ABSTRACT FROM AUTHOR]

Background: Ionoacoustics is a promising approach to reduce the range uncertainty in proton therapy. A miniature‐sized optical hydrophone (OH) was used as a measuring device to detect weak ionoacoustic signals with a high signal‐to‐noise ratio in water. However, further development is necessary to prevent wave distortion because of nearby acoustic impedance discontinuities while detection is conducted on the patient's skin. Purpose: A prototype of the probe head attached to an OH was fabricated and the required dimensions were experimentally investigated using a 100‐MeV proton beam from a fixed‐field alternating gradient accelerator and k‐Wave simulations. The beam range of the proton in a tissue‐mimicking phantom was estimated by measuring γ‐waves and spherical ionoacoustic waves with resonant frequency (SPIRE). Methods: Four sizes of probe heads were fabricated from agar blocks for the OH. Using the prototype, the γ‐wave was detected at distal and lateral positions to the Bragg peak on the phantom surface for proton beams delivered at seven positions. For SPIRE, independent measurements were performed at distal on‐ and off‐axis positions. The range positions were estimated by solving the linear equation using the sensitive matrix for the γ‐wave and linear fitting of the correlation curve for SPIRE; they were compared with those measured using a film. Results: The first peak of the γ‐wave was undistorted with the 3 × 3 × 3‐cm3 probe head used at the on‐axis and 3‐cm off‐axis positions. The range positions estimated by the γ‐wave agreed with the film‐based range in the depth direction (the maximum deviation was 0.7 mm), although a 0.6–2.1 mm deviation was observed in the lateral direction. For SPIRE, the deviation was <1 mm for the two measurement positions. Conclusions: The attachment of a relatively small‐sized probe head allowed the OH to measure the beam range on the phantom surface. [ABSTRACT FROM AUTHOR]

Introduction: We propose a method for prompt-gamma verification of proton range during particle therapy, called Prompt-Gamma Energy Integration (PGEI). Method: This method is based on the measurement of the total energy deposited in a set of detectors located around a patient. It is particularly suited in the case of high-instantaneous beam intensities, like for pulsed beams extracted from a synchro-cyclotron. GATE simuations were used to evaluate the sensitivity, and dedicated scintillators were tested as a function of beam intensity. Results and discussion: Simulations show that millimetric range shifts can be measured at a beam-spot scale. The sensitivity is slightly degraded as compared to the Prompt-Gamma Peak Integration Method, for which Time-of-Flight can be employed to reduce the background in single-photon detection conditions at cyclotron accelerators. Experimentally, lead tungstate scintillators have shown to cope with the high instantaneous gamma count rates for PGEI at synchrocyclotrons. [ABSTRACT FROM AUTHOR]

Objective.Proton therapy as the next generation radiation-based cancer therapy offers dominant advantages over conventional radiation therapy due to the utilization of the Bragg peak; however, range uncertainty in beam delivery substantially mitigates the advantages of proton therapy. This work reports using protoacoustic measurements to determine the location of proton Bragg peak deposition within a water phantom in real time during beam delivery.Approach.In protoacoustics, proton beams have a definitive range, depositing a majority of the dose at the Bragg peak; this dose is then converted to heat. The resulting thermoelastic expansion generates a 3D acoustic wave, which can be detected by acoustic detectors to localize the Bragg peak.Main results.Protoacoustic measurements were performed with a synchrocyclotron proton machine over the exhaustive energy range from 45.5 to 227.15 MeV in clinic. It was found that the amplitude of the acoustic waves is proportional to proton dose deposition, and therefore encodes dosimetric information. With the guidance of protoacoustics, each individual proton beam (7 pC/pulse) can be directly visualized with sub-millimeter (

Introduction: We propose a method for prompt-gamma verification of proton range during particle therapy, called Prompt-Gamma Energy Integration (PGEI).Method: This method is based on the measurement of the total energy deposited in a set of detectors located around a patient. It is particularly suited in the case of high-instantaneous beam intensities, like for pulsed beams extracted from a synchro-cyclotron. GATE simuations were used to evaluate the sensitivity, and dedicated scintillators were tested as a function of beam intensity.Results and discussion: Simulations show that millimetric range shifts can be measured at a beam-spot scale. The sensitivity is slightly degraded as compared to the Prompt-Gamma Peak Integration Method, for which Time-of-Flight can be employed to reduce the background in single-photon detection conditions at cyclotron accelerators. Experimentally, lead tungstate scintillators have shown to cope with the high instantaneous gamma count rates for PGEI at synchro-cyclotrons.

Nanodroplets have demonstrated potential for the range detection of hadron radiotherapies. Our formulation uses superheated perfluorobutane (C4F10) stabilized by a poly(vinyl-alcohol) shell. High-LET (linear energy transfer) particles vaporize the nanodroplets into echogenic microbubbles. Tailored ultrasound imaging translates the generated echo-contrast into a dose distribution map, enabling beam range retrieval. This work evaluates the response of size-sorted nanodroplets to carbon-ion radiation. We studied how thesize of nanodroplets affects their sensitivity at various beam-doses and energies, as a function of concentration and shell cross-linking. First, we show the physicochemical characterization of size-isolated nanodroplets by differential centrifugation. Then, we report on the irradiations of the nanodroplet samples in tissue-mimicking phantoms. We compared the response of large (≈900 nm) and small (≈400 nm) nanodroplets to different carbon-ions energies and evaluated their dose linearity and concentration detection thresholds by ultrasound imaging. Additionally, we verified the beam range detection accuracy for the nanodroplets samples. All nanodroplets exhibited sensitivity to carbon-ions with high range verification precision. However, smaller nanodroplets required a higher concentration sensitivity threshold. The vaporization yield depends on the carbon-ions energy and dose, which are both related to particle count/spot. These findings confirm the potential of nanodroplets for range detection, with performance depending on nanodroplets’ properties and beam parameters.

To validate range shifts in proton therapy, we investigated the potential of using the temporal information of prompt gamma rays as an indicator. We simulated the proton transport process using Monte Carlo simulations and used a geometric scorer to obtain the location and timing of prompt gamma ray production. By using a homogeneous target material in the simulation model, we established a fitted relationship between the range of 90-210 MeV protons and the corresponding temporal spectral width. Additionally, by introducing air cavities of 2-20 mm in simulations of inhomogeneous target materials, we observed significant correlations between the range offsets and the temporal spectral widths. These correlations were fitted to derive a functional relationship between the two variables. [ABSTRACT FROM AUTHOR]

In theory, the sharp dose falloff at the distal end of a proton beam allows for high conformal dose to the target. However, conformity has not been fully achieved in practice, primarily due to beam range uncertainty, which is approximately 4% and varies slightly across institutions. To address this issue, we developed a new range verification system prototype: a multi-slit prompt-gamma camera (MSPGC). This system features high prompt-gamma detection sensitivity, an advanced range estimation algorithm, and a precise camera positioning system. We evaluated the range measurement precision of the prototype for single spot beams with varying energies, proton quantities, and positions, as well as for spot-scanning proton beams in a simulated SSPT treatment using a phantom. Our results demonstrated high accuracy (

To validate range shifts in proton therapy, we investigated the potential of using the temporal information of prompt gamma rays as an indicator. We simulated the proton transport process using Monte Carlo simulations and used a geometric scorer to obtain the location and timing of prompt gamma ray production. By using a homogeneous target material in the simulation model, we established a fitted relationship between the range of 90–210 MeV protons and the corresponding temporal spectral width. Additionally, by introducing air cavities of 2–20 mm in simulations of inhomogeneous target materials, we observed significant correlations between the range offsets and the temporal spectral widths. These correlations were fitted to derive a functional relationship between the two variables.

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 × 107 protons. 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. [ABSTRACT FROM AUTHOR]

Objective. The results of a follow-up experiment investigating a novel method for sub-milimetre range verification (RV) in proton therapy (PT) are presented. Approach. The method consists of implanting a hadron tumour marker (HTM) near the planned treatment volume, and measuring the γ -ray signals emitted as a result of activation by the proton beam. These signals are highly correlated with the energy of the beam impinging on the HTM and can provide an absolute measurement of the range of the beam relative to the position of the HTM, which is independent of any uncertainties in beam delivery. Main results. Three candidate HTM materials were identified and combined into a single composite HTM, which makes use of the strongest reaction in each material. The setup of the previous experiment was improved on by using high-purity germanium detectors to measure the γ -ray signal with a higher resolution than was previously achieved. A PMMA phantom was also used to simulate the γ -ray background from tissue activation. HTM RV using the data collected in this study yielded range measurements whose average deviation from the expected value was 0.13(22)mm. Significance. Range uncertainty in PT limits the prescribed treatment plan for cancer patients with large safety margins and constrains the direction of the proton beam in relation to any organ at risk. The sub-milimetre range uncertainty achieved in this study using HTM RV, if implemented clinically, would allow for a reduction in the size of safety margins, increasing the therapeutic window for PT. [ABSTRACT FROM AUTHOR]

Compton-based prompt gamma (PG) imaging is being investigated by several groups as a potential solution for in vivo range monitoring in proton therapy. The performance of this technique depends on the detector system as well as the ability of the reconstruction method to obtain good spatial resolution to establish a quantitative correlation between the PG emission and the proton beam range in the patient. To evaluate the feasibility of PG imaging for range monitoring, we quantitatively evaluated the emission distributions reconstructed by a Maximum Likelihood Expectation Maximization (MLEM) and a Stochastic Origin Ensemble (SOE) algorithm. To this end, we exploit experimental and Monte Carlo (MC) simulation data acquired with the Polaris-J Compton Camera (CC) prototype. The differences between the proton beam range (RD) defined as the 80% distal dose fall-off and the PG range (RPG), obtained by fitting the distal end of the reconstructed profile with a sigmoid function, were quantified. A comparable performance of both reconstruction algorithms was found. For both experimental and simulated irradiation scenarios, the correlation between RD and RPG was within 5 mm. These values were consistent with the ground truth distance (RD-RPGg≈ 3 mm) calculated by using the expected PG emission available from MC simulation. Furthermore, shifts of 3 mm in the proton beam range were resolved with the MLEM algorithm by calculating the relative difference between the RPG for each reconstructed profile. In non-homogeneous targets, the spatial changes in the PG emission due to the different materials could not be fully resolved from the reconstructed profiles; however, the fall-off region still resembled the ground truth emission. For this scenario, the PG correlation (RD-RPG) varied from 0.1 mm to 4 mm, which is close to the ground truth correlation (3 mm). This work provides a framework for the evaluation of the range monitoring capabilities of a CC device for PG imaging. The two investigated image reconstruction algorithms showed a comparable and consistent performance for homogeneous and heterogeneous targets.

The editorial in Frontiers in Physics discusses the use of prompt gamma imaging (PGI) in particle therapy to address range uncertainties. Various PGI systems are being developed, such as the knife-edge slit camera and Compton camera, to improve beam range verification. Studies on prompt gamma timing, modified Compton cameras for boron neutron capture therapy, and hybrid treatment verification using prompt gammas and neutrons show promising advancements in PGI technology. Collaboration between young investigators and experts is crucial to further develop PGI techniques for more accurate particle therapy treatments. [Extracted from the article]

Purpose: Gamma cameras are one of the most promising technologies for in-vivo range monitoring in proton therapy. Monte Carlo (MC) simulation is a common calculation-based technique to design and optimize gamma cameras. However, it is prohibitively time-consuming. Analytical modeling speeds up the process of finding the optimal design. Materials and Methods: We proposed an analytical method using the efficiency-resolution trade-off for optimizing a knife-edge collimator based on the range retrieval precision of protons. Monte Carlo simulation was used for validation of obtained collimator efficiencies. Results: The model predicts that for the optimal range retrieval precision, the ratio of the source-to-detector distance to the source-to-collimator distance should be ranging from . For a special case, it was found that assuming an ideal detector , the falloff retrieval precision is optimal at independent of the collimator resolution. Moreover, using the optimized camera, the difference between the MC calculated range and the absolute range was 0.5 cm (the relative error is about 3%). Conclusion: It was found that the collimator parameters are in good agreement in comparison with that of the MC results reported in the literature. The analytical method studied in this work can be used to design and optimize imaging systems based on KE collimators in combination with new detectors in a fast and reliable way.

Background: The safety and efficacy of proton therapy is currently hampered by range uncertainties. The combination of ultrasound imaging with injectable radiation‐sensitive superheated nanodroplets was recently proposed for in vivo range verification. The proton range can be estimated from the distribution of nanodroplet vaporization events, which is stochastically related to the stopping distribution of protons, as nanodroplets are vaporized by protons reaching their maximal LET at the end of their range. Purpose: Here, we aim to estimate the range estimation precision of this technique. As for any stochastic measurement, the precision will increase with the sample size, that is, the number of detected vaporizations. Thus, we first develop and validate a model to predict the number of vaporizations, which is then applied to estimate the range verification precision for a set of conditions (droplet size, droplet concentration, and proton beam parameters). Methods: Starting from the thermal spike theory, we derived a model that predicts the expected number of droplet vaporizations in an irradiated sample as a function of the droplet size, concentration, and number of protons. The model was validated by irradiating phantoms consisting of size‐sorted perfluorobutane droplets dispersed in an aqueous matrix. The number of protons was counted with an ionization chamber, and the droplet vaporizations were recorded and counted individually using high frame rate ultrasound imaging. After validation, the range estimate precision was determined for different conditions using a Monte Carlo algorithm. Results: A good agreement between theory and experiments was observed for the number of vaporizations, especially for large (5.8 ± 2.2 µm) and medium (3.5 ± 1.1 µm) sized droplets. The number of events was lower than expected in phantoms with small droplets (2.0 ± 0.7 µm), but still within the same order of magnitude. The inter‐phantom variability was considerably larger (up to 30x) than predicted by the model. The validated model was then combined with Monte Carlo simulations, which predicted a theoretical range retrieval precision improving with the square‐root of the number of vaporizations, and degrading at high beam energies due to range straggling. For single pencil beams with energies between 70 and 240 MeV, a range verification precision below 1% of the range required perfluorocarbon concentrations in the order of 0.3‐2.4 µM. Conclusion: We proposed and experimentally validated a model to provide a quick estimate of the number of vaporizations for a given set of conditions (droplet size, droplet concentration, and proton beam parameters). From this model, promising range verification performances were predicted for realistic perfluorocarbon concentrations. These findings are an incentive to move towards preclinical studies, which are critical to assess the achievable droplet distribution in and around the tumor, and hence the in vivo range verification precision. [ABSTRACT FROM AUTHOR]

Objective. The range uncertainty in proton radiotherapy is a limiting factor to achieve optimum dose conformity to the tumour volume. Ionoacoustics is a promising approach for in situ range verification, which would allow to reduce the size of the irradiated volume relative to the tumour volume. The energy deposition of a pulsed proton beam leads to an acoustic pressure wave (ionoacoustics), the detection of which allows conclusion about the distance between the Bragg peak and the acoustic detector. This information can be transferred into a co-registered ultrasound image, marking the Bragg peak position relative to the surrounding anatomy. Approach. A CIRS 3D abdominal phantom was irradiated with 126 MeV protons at a clinical proton therapy centre. Acoustic signals were recorded on the beam axis distal to the Bragg peak with a Cetacean C305X hydrophone. The ionoacoustic measurements were processed with a correlation filter using simulated filter templates. The hydrophone was rigidly attached to an ultrasound device (Interson GP-C01) recording ultrasound images of the irradiated region. Main results. The time of flight obtained from ionoacoustic measurements were transferred to an ultrasound image by means of an optoacoustic calibration measurement. The Bragg peak position was marked in the ultrasound image with a statistical uncertainty of σ = 0.5 mm of 24 individual measurements depositing 1.2 Gy at the Bragg peak. The difference between the evaluated Bragg peak position and the one obtained from irradiation planning (1.0 mm) is smaller than the typical range uncertainty (≈4 mm) at the given penetration depth (10 cm). Significance. The measurements show that it is possible to determine the Bragg peak position of a clinical proton beam with submillimetre precision and transfer the information to an ultrasound image of the irradiated region. The dose required for this is smaller than that used for a typical irradiation fraction. [ABSTRACT FROM AUTHOR]

The purpose of this article is to share the excitement of the science of proton therapy, told by two physicists, who started their career in this area at different times. The authors' journey spans the evolution of proton therapy over the past 30 years, taking the reader from the time when it was an extremely exotic treatment modality until its more common use today. Over this time period, the authors' research and development aimed at an improved understanding of the physical benefits of intensity‐modulated proton therapy and arc therapy, treatment planning and optimization to take proton‐specific uncertainties into account, and imaging to measure the proton range in the patient. The final section focuses on emerging themes to democratize proton therapy by substantially reducing its size and price, for much greater affordability and global availability of this treatment modality. [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]

Pioneering investigations on the usage of positron-emission-tomography (PET) for the monitoring of ion beam therapy with light (protons, helium) and heavier (stable and radioactive neon, carbon and oxygen) ions started shortly after the first realization of planar and tomographic imaging systems, which were able to visualize the annihilation of positrons resulting from irradiation induced or implanted positron emitting nuclei. And while the first clinical experience was challenged by the utilization of instrumentation directly adapted from nuclear medicine applications, new detectors optimized for this unconventional application of PET imaging are currently entering the phase of (pre)clinical testing for more reliable monitoring of treatment delivery during irradiation. Moreover, recent advances in detector technologies and beam production open several new exciting opportunities which will not only improve the performance of PET imaging under the challenging conditions of in-beam applications in ion beam therapy, but will also likely expand its field of application. In particular, the combination of PET and Compton imaging can enable the most efficient utilization of all possible radiative emissions for both stable and radioactive ion beams, while positronium lifetime imaging may enable probing new features of the underlying tumour and normal tissue environment. Thereby, PET imaging will not only provide means for volumetric reconstruction of the delivered treatment and in-vivo verification of the beam range, but can also shed new insights for biological optimization of the treatment or treatment response assessment.

Compton-based prompt gamma (PG) imaging is being investigated by several groups as a potential solution for in vivo range monitoring in proton therapy. The performance of this technique depends on the detector system as well as the ability of the reconstruction method to obtain good spatial resolution to establish a quantitative correlation between the PG emission and the proton beam range in the patient. To evaluate the feasibility of PG imaging for range monitoring, we quantitatively evaluated the emission distributions reconstructed by a Maximum Likelihood Expectation Maximization (MLEM) and a Stochastic Origin Ensemble (SOE) algorithm. To this end, we exploit experimental and Monte Carlo (MC) simulation data acquired with the Polaris-J Compton Camera (CC) prototype. The differences between the proton beam range ( R D ) defined as the 80% distal dose fall-off and the PG range ( R PG ), obtained by fitting the distal end of the reconstructed profile with a sigmoid function, were quantified. A comparable performance of both reconstruction algorithms was found. For both experimental and simulated irradiation scenarios, the correlation between R D and R PG was within 5 mm. These values were consistent with the ground truth distance ( R D - R PGg ≈ 3 mm) calculated by using the expected PG emission available from MC simulation. Furthermore, shifts of 3 mm in the proton beam range were resolved with the MLEM algorithm by calculating the relative difference between the R PG for each reconstructed profile. In non-homogeneous targets, the spatial changes in the PG emission due to the different materials could not be fully resolved from the reconstructed profiles; however, the fall-off region still resembled the ground truth emission. For this scenario, the PG correlation ( R D - R PG ) varied from 0.1 mm to 4 mm, which is close to the ground truth correlation (3 mm). This work provides a framework for the evaluation of the range monitoring capabilities of a CC device for PG imaging. The two investigated image reconstruction algorithms showed a comparable and consistent performance for homogeneous and heterogeneous targets. [ABSTRACT FROM AUTHOR]

Background: Proton range uncertainty has been the main factor limiting the ability of proton therapy to concentrate doses to tumors to their full potential. Ionoacoustic (IA) range verification is an approach to reducing this uncertainty by detecting thermoacoustic waves emitted from an irradiated volume immediately following a pulsed proton beam delivery; however, the signal weakness has been an obstacle to its clinical application. To increase the signal-to-noise ratio (SNR) with the conventional piezoelectric hydrophone (PH), the detectorsensitive volume needs to be large, but it could narrow the range of available beam angles and disturb real-time images obtained during beam delivery. Purpose: To prevent this issue, we investigated a millimeter-sized optical hydrophone (OH) that exploits the laser interferometric principle. For two types of IA waves [γ-wave emitted from the Bragg peak (BP) and a spherical IA wave with resonant frequency (SPIRE) emitted from the gold fiducial marker (GM)], comparisons were made with PH in terms of waveforms, SNR, range detection accuracy, and signal intensity robustness against the small detector misalignment, particularly for SPIRE. Methods: A 100-MeV proton beam with a 27 ns pulse width and 4 mm beam size was produced using a fixed-field alternating gradient accelerator and was irradiated to the water phantom. The GM was set on the beam’s central axis. Acrylic plates of various thicknesses, up to 12 mm, were set in front of the phantoms to shift the proton range.OH was set distal and lateral to the beam, and the range was estimated using the time-of -flight method for γ-wave and by comparing with the calibration data (SPIRE intensity versus the distance between the GM and BP) derived from an IA wave transport simulation for SPIRE. The BP dose per pulse was 0.5–0.6 Gy. To measure the variation in SPIRE amplitude against the hydrophone misalignment, the hydrophone was shifted by ± 2 mm at a maximum in lateral directions. Results: Despite its small size, OH could detect γ-wave with a higher SNR than the conventional PH (diameter, 29 mm), and a single measurement was sufficient to detect the beam range with a submillimeter accuracy in water. In the SPIRE measurement, OH was far more robust against the detector misalignment than the focused PH (FPH) used in our previous study [5%/mm (OH) versus 80%/mm (FPH)], and the correlation between the measured SPIRE intensity and the distance between the GM and BP agreed well with the simulation results. However, the OH sensitivity was lower than the FPH sensitivity, and about 5.6-Gy dose was required to decrease the intensity variation among measurements to less than 10%. Conclusion: The miniature OH was found to detect weak IA signals produced by proton beams with a BP dose used in hypofractionated regimens. The OH sensitivity improvement at the MHz regime is worth exploring as the next step. [ABSTRACT FROM AUTHOR]

Background: Proton radiography (PR) uses highly energetic proton beams to create images where energy loss is the main contrast mechanism. Waterequivalent path length (WEPL) measurements using flat panel PR (FP-PR) have potential for in vivo range verification. However, an accurate WEPL measurement via FP-PR requires irradiation with multiple energy layers, imposing high imaging doses. Purpose: A FP-PR method is proposed for accurate WEPL determination based on a patient-specific imaging field with a reduced number of energies (n) to minimize imaging dose. Methods: Patient-specific FP-PRs were simulated and measured for a head and neck (HN) phantom.An energy selection algorithm estimated spot-wise the lowest energy required to cross the anatomy (Emin) using a water-equivalent thickness map.Starting from Emin, n was restricted to certain values (n = 26, 24, 22, …, 2 for simulations, n = 10 for measurements), resulting in patient-specific FP-PRs. A reference FP-PR with a complete set of energies was compared against patient-specific FP-PRs covering the whole anatomy via mean absolute WEPL differences (MAD), to evaluate the impact of the developed algorithm. WEPL accuracy of patient-specific FP-PRs was assessed using mean relative WEPL errors (MRE) with respect to measured multi-layer ionization chamber PRs (MLIC-PR) in the base of skull, brain, and neck regions. Results: MADs ranged from 2.1 mm (n = 26) to 21.0 mm (n = 2) for simulated FP-PRs, and 7.2 mm for measured FP-PRs (n = 10). WEPL differences below 1 mm were observed across the whole anatomy,except at the phantom surfaces. Measured patient-specific FP-PRs showed good agreement against MLIC-PRs, with MREs of 1.3 ± 2.0%, −0.1 ± 1.0%, and −0.1 ± 0.4% in the three regions of the phantom. Conclusion: A method to obtain accurate WEPL measurements using FP-PR with a reduced number of energies selected for the individual patient anatomy was established in silico and validated experimentally. Patient-specific FP-PRs could provide means of in vivo range verification. [ABSTRACT FROM AUTHOR]

The potential of proton therapy is currently limited due to large safety margins. We estimated the potential reduction of clinical margins when using prompt gamma imaging (PGI) for online treatment verification of prostate cancer. For two adaptive scenarios a potential reduction relative to clinical practice was evaluated. The use of a trolley-mounted PGI system for online treatment verification to trigger an adaptation reduced the current range margins from 7 mm to 3 mm. In a case example, the dose reduction due to reduced range margins was substantially larger compared to reduced setup margins when using pre-treatment volumetric imaging.

Purpose: To investigate the static magnetic field generated by a proton pencil beam as a candidate for range verification bymeans of Monte Carlo simulations, thereby improving upon existing analytical calculations. We focus on the impact of statistical current fluctuations and secondary protons and electrons. Methods:We considered a pulsed beam (10 µs pulse duration) during the duty cycle with a peak beam current of 0.2 µA and an initial energy of 100 MeV. We ran Geant4-DNA Monte Carlo simulations of a proton pencil beam in water and extracted independent particle phase spaces. We calculated longitudinal and radial current density of protons and electrons, serving as an input for a magnetic field estimation based on a finite element analysis in a cylindrical geometry. We made sure to allow for non-solenoidal current densities as is the case of a stopping proton beam. Results: The rising proton charge density toward the range is not perturbed by energy straggling and only lowered through nuclear reactions by up to 15%, leading to an approximately constant longitudinal current. Their relative low density however (at most 0.37 protons/mm3 for the 0.2 µA current and a beam cross-section of 2.5 mm), gives rise to considerable current density fluctuations. The radial proton current resulting from lateral scattering and being two orders of magnitude weaker than the longitudinal current is subject to even stronger fluctuations. Secondary electrons with energies above 10 eV, that far outnumber the primary protons, reduce the primary proton current by only 10% due to their largely isotropic flow. A small fraction of electrons (< 1%), undergoing head-on collisions, constitutes the relevant electron current. In the far-field, both contributions to the magnetic field strength (longitudinal and lateral) are independent of the beam spot size. We also find that the nuclear reaction-related losses cause a shift of 1.3mmto the magnetic field profile relative to the actual range, which is further enlarged to 2.4 mm by the electron current (at a distance of = 50 mm away from the central beam axis). For 1 > 45 mm, the shift increases linearly. While the current density variations cause significant magnetic field uncertainty close to the central beam axis with a relative standard deviation (RSD) close to 100%, they average out at a distance of 10 cm, where the RSD of the total magnetic field drops below 2%. Conclusions: With the small influence of the secondary electrons together with the low RSD, our analysis encourages an experimental detection of the magnetic field through sensitive instrumentation, such as optical magnetometry or SQUIDs. Conclusions: With the small influence of the secondary electrons together with the low RSD, our analysis encourages an experimental detection of the magnetic field through sensitive instrumentation, such as optical magnetometry or SQUIDs. [ABSTRACT FROM AUTHOR]

Pioneering investigations on the usage of positron-emission-tomography (PET) for the monitoring of ion beam therapy with light (protons, helium) and heavier (stable and radioactive neon, carbon and oxygen) ions started shortly after the first realization of planar and tomographic imaging systems, which were able to visualize the annihilation of positrons resulting from irradiation induced or implanted positron emitting nuclei. And while the first clinical experience was challenged by the utilization of instrumentation directly adapted from nuclear medicine applications, new detectors optimized for this unconventional application of PET imaging are currently entering the phase of (pre)clinical testing for more reliable monitoring of treatment delivery during irradiation. Moreover, recent advances in detector technologies and beam production open several new exciting opportunities which will not only improve the performance of PET imaging under the challenging conditions of in-beam applications in ion beam therapy, but will also likely expand its field of application. In particular, the combination of PET and Compton imaging can enable the most efficient utilization of all possible radiative emissions for both stable and radioactive ion beams, while positronium lifetime imaging may enable probing new features of the underlying tumour and normal tissue environment. Thereby, PET imaging will not only provide means for volumetric reconstruction of the delivered treatment and in-vivo verification of the beam range, but can also shed new insights for biological optimization of the treatment or treatment response assessment. [ABSTRACT FROM AUTHOR]

Objective. Beams of stable ions have been a well-established tool for radiotherapy for many decades. In the case of ion beam therapy with stable 12C ions, the positron emitters 10,11C are produced via projectile and target fragmentation, and their decays enable visualization of the beam via positron emission tomography (PET). However, the PET activity peak matches the Bragg peak only roughly and PET counting statistics is low. These issues can be mitigated by using a short-lived positron emitter as a therapeutic beam. Approach. An experiment studying the precision of the measurement of ranges of positron-emitting carbon isotopes by means of PET has been performed at the FRS fragment-separator facility of GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany. The PET scanner used in the experiment is a dual-panel version of a Siemens Biograph mCT PET scanner. Main results. High-quality in-beam PET images and activity distributions have been measured from the in-flight produced positron emitting isotopes 11C and 10C implanted into homogeneous PMMA phantoms. Taking advantage of the high statistics obtained in this experiment, we investigated the time evolution of the uncertainty of the range determined by means of PET during the course of irradiation, and show that the uncertainty improves with the inverse square root of the number of PET counts. The uncertainty is thus fully determined by the PET counting statistics. During the delivery of 1.6 × 107 ions in 4 spills for a total duration of 19.2 s, the PET activity range uncertainty for 10C, 11C and 12C is 0.04 mm, 0.7 mm and 1.3 mm, respectively. The gain in precision related to the PET counting statistics is thus much larger when going from 11C to 10C than when going from 12C to 11C. The much better precision for 10C is due to its much shorter half-life, which, contrary to the case of 11C, also enables to include the in-spill data in the image formation. Significance. Our results can be used to estimate the contribution from PET counting statistics to the precision of range determination in a particular carbon therapy situation, taking into account the irradiation scenario, the required dose and the PET scanner characteristics. [ABSTRACT FROM AUTHOR]

Background: A clinical study regarding the potential of range verification in proton therapy (PT) by prompt gamma imaging (PGI) is carried out at our institution. Manual interpretation of the detected spot‐wise range shift information is time‐consuming, highly complex, and therefore not feasible in a broad routine application. Purpose: Here, we present an approach to automatically detect and classify treatment deviations in realistically simulated PGI data for head‐and‐neck cancer (HNC) treatments using convolutional neural networks (CNNs) and conventional machine learning (ML) approaches. Methods: For 12 HNC patients and 1 anthropomorphic head phantom (n = 13), pencil beam scanning (PBS) treatment plans were generated, and 1 field per plan was assumed to be monitored with a PGI slit camera system. In total, 386 scenarios resembling different relevant or non‐relevant treatment deviations were simulated on planning and control CTs and manually classified into 7 classes: non‐relevant changes (NR) and relevant changes (RE) triggering treatment intervention due to range prediction errors (±RP), setup errors in beam direction (±SE), anatomical changes (AC), or a combination of such errors (CB). PBS spots with reliable PGI information were considered with their nominal Bragg peak position for the generation of two 3D spatial maps of 16 × 16 × 16 voxels containing PGI‐determined range shift and proton number information. Three complexity levels of simulated PGI data were investigated: (I) optimal PGI data, (II) realistic PGI data with simulated Poisson noise based on the locally delivered proton number, and (III) realistic PGI data with an additional positioning uncertainty of the slit camera following an experimentally determined distribution. For each complexity level, 3D‐CNNs were trained on a data subset (n = 9) using patient‐wise leave‐one‐out cross‐validation and tested on an independent test cohort (n = 4). Both the binary task of detecting RE and the multi‐class task of classifying the underlying error source were investigated. Similarly, four different conventional ML classifiers (logistic regression, multilayer perceptron, random forest, and support vector machine) were trained using five previously established handcrafted features extracted from the PGI data and used for performance comparison. Results: On the test data, the CNN ensemble achieved a binary accuracy of 0.95, 0.96, and 0.93 and a multi‐class accuracy of 0.83, 0.81, and 0.76 for the complexity levels (I), (II), and (III), respectively. In the case of binary classification, the CNN ensemble detected treatment deviations in the most realistic scenario with a sensitivity of 0.95 and a specificity of 0.88. The best performing ML classifiers showed a similar test performance. Conclusions: This study demonstrates that CNNs can reliably detect relevant changes in realistically simulated PGI data and classify most of the underlying sources of treatment deviations. The CNNs extracted meaningful features from the PGI data with a performance comparable to ML classifiers trained on previously established handcrafted features. These results highlight the potential of a reliable, automatic interpretation of PGI data for treatment verification, which is highly desired for a broad clinical application and a prerequisite for the inclusion of PGI in an automated feedback loop for online adaptive PT. [ABSTRACT FROM AUTHOR]

Range uncertainty that reduces the dosimetric advantage of carbon ion therapy is a major problem limiting its treatment precision. To address this issue, high-precision monitoring of the in-beam range is essential. This paper proposes a method for range verification using a secondary particle intensity (SPI) system consisting of a cerium bromide (CeBr 3) scintillation detector and an integrated ionization chamber (IC). This method uses the secondary particle intensity produced by the primary particles per monitor unit (MU) observed by the SPI system to convert the carbon ion range. Secondary particles, including gamma rays, neutrons, and charged particles, can be detected in the CeBr 3 detector as long as their signal exceeds the threshold, and no discrimination by particle type is required. The Heavy Ion Medical Machine (HIMM) terminal, situated in Lanzhou, China, provided the 12C6+ beam with energies ranging from 160.86 to 211.44 MeV/u. The experiment demonstrated that the carbon ion range accuracy of the 12C6+ beam in a polymethyl methacrylate (PMMA) target can reach 0.92 ± 0.67 mm under a 10 ms measurement period. The secondary particle energy spectrum was recorded during both the in-beam and off-beam phases, clearly recognizing the 511 keV annihilation photopeak with a full width at half maximum (FWHM) of 31.37 keV. The photopeak of annihilation confirmed the accumulation of activated products. During the 15 min continuous irradiation process, the effect of activated product accumulation on the range verification is about 1.15 mm. This paper illustrates the feasibility of SPI method for fast measurement of carbon ion range, which could potentially reduce the effects of range uncertainty in carbon ion therapy. [ABSTRACT FROM AUTHOR]

Objective. Image guidance and precise irradiation are fundamental to ensure the reliability of small animal oncology studies. Accurate positioning of the animal and the in-beam monitoring of the delivered radio-therapeutic treatment necessitate several imaging modalities. In the particular context of proton therapy with a pulsed beam, information on the delivered dose can be retrieved by monitoring the thermoacoustic waves resulting from the brief and local energy deposition induced by a proton beam (ionoacoustics). The objective of this work was to fabricate a multimodal phantom (x-ray, proton, ultrasound, and ionoacoustics) allowing for sufficient imaging contrast for all the modalities. Approach. The phantom anatomical parts were extracted from mouse computed tomography scans and printed using polylactic acid (organs) and a granite/polylactic acid composite (skeleton). The anatomical pieces were encapsulated in silicone rubber to ensure long term stability. The phantom was imaged using x-ray cone-beam computed tomography, proton radiography, ultrasound imaging, and monitoring of a 20 MeV pulsed proton beam using ionoacoustics. Main results. The anatomical parts could be visualized in all the imaging modalities validating the phantom capability to be used for multimodal imaging. Ultrasound images were simulated from the x-ray cone-beam computed tomography and co-registered with ultrasound images obtained before the phantom irradiation and low-resolution ultrasound images of the mouse phantom in the irradiation position, co-registered with ionoacoustic measurements. The latter confirmed the irradiation of a tumor surrogate for which the reconstructed range was found to be in reasonable agreement with the expectation. Significance. This study reports on a realistic small animal phantom which can be used to investigate ionoacoustic range (or dose) verification together with ultrasound, x-ray, and proton imaging. The co-registration between ionoacoustic reconstructions of the impinging proton beam and x-ray imaging is assessed for the first time in a pre-clinical scenario. [ABSTRACT FROM AUTHOR]

Objective : To present a long short-term memory (LSTM)-based prompt gamma (PG) emission prediction method for proton therapy. Approach : Computed tomography (CT) scans of 33 patients with a prostate tumor were included in the dataset. A set of 10 7 histories proton pencil beam (PB)s was generated for Monte Carlo (MC) dose and PG simulation. For training (20 patients) and validation (3 patients), over 6000 PBs at 150, 175 and 200 MeV were simulated. 3D relative stopping power (RSP), PG and dose cuboids that included the PB were extracted. Three models were trained, validated and tested based on an LSTM-based network: (1) input RSP and output PG, (2) input RSP with dose and output PG (single-energy), and (3) input RSP/dose and output PG (multi-energy). 540 PBs at each of the four energy levels (150, 175, 200, and 125-210 MeV) were simulated across 10 patients to test the three models. The gamma passing rate (2%/2 mm) and PG range shift were evaluated and compared among the three models. Results : The model with input RSP/dose and output PG (multi-energy) showed the best performance in terms of gamma passing rate and range shift metrics. Its mean gamma passing rate of testing PBs of 125-210 MeV was 98.5% and the worst case was 92.8%. Its mean absolute range shift between predicted and MC PGs was 0.15 mm, where the maximum shift was 1.1 mm. The prediction time of our models was within 130 ms per PB. Significance : We developed a sub-second LSTM-based PG emission prediction method. Its accuracy in prostate patients has been confirmed across an extensive range of proton energies., (Creative Commons Attribution license.)

Objective . To compare in reproducible and equalized conditions the performance of two independent proton range verification systems based on prompt gamma-ray detectors from two different proton therapy centers. Approach . An anthropomorphic head phantom with calibrated stopping power, serving as ground truth, was irradiated with comparable treatment plans, spot positions and energies in both facilities. Clinical beam current, tumor contour and dose were used. The absolute range measurement was compared to the expected value according to the ground truth. The statistical precision was assessed by repeating each measurement ten times. Sensitivity to relative range shifts was evaluated by introducing 2 mm and 5 mm plastic slabs on half of the field. Main results . The resulting absolute range accuracy was within 2.4 mm in all cases. Relative range shifts were detected with deviations lower than 14%. Significance . The performance of both systems was deemed worthy of clinical application for the detection of range deviations. This study represents the first comparison of independent prompt gamma-ray-based proton range verification systems under equalized conditions with realistic treatment fields and beam currents., (Creative Commons Attribution license.)

Objective. In carbon ion therapy, the visualization of the range of incident particles in a patient body is important for treatment verification. In-beam positron emission tomography (PET) imaging is one of the methods to verify the treatment in ion therapy due to the high quality of PET images. We have shown the feasibility of in-beam PET imaging of radioactive 15O and 11C ion beams for range verification using our OpenPET system. Recently, we developed a whole gamma imager (WGI) that can simultaneously work as PET, single gamma ray and triple gamma ray imaging. The WGI has high potential to detect the location of 10C, which emits positrons with a simultaneous gamma ray of 718 keV, within the patient’s body during ion therapy. Approach. In this work, we focus on investigating the performance of WGI for 10C imaging and its feasibility for range verification in carbon ion therapy. First, the performance of the WGI was studied to image a 10C point source using the Geant4 toolkit. Then, the feasibility of WGI was investigated for an irradiated polymethyl methacrylate (PMMA) phantom with a 10C ion beam at the carbon therapy facility of the Heavy Ion Medical Accelerator in Chiba. Main results. The average spatial resolution and sensitivity for the simulated 10C point source at the centre of the field of view were 5.5 mm FWHM and 0.010%, respectively. The depth dose of the 10C ion beam was measured, and the triple gamma image of 10C nuclides for an irradiated PMMA phantom was obtained by applying a simple back projection to the detected triple gammas. Significance. The shift between Bragg peak position and position of the peak of the triple gamma image in an irradiated PMMA phantom was 2.8 ± 0.8 mm, which demonstrates the capability of triple gamma imaging using WGI for range verification of 10C ion beams. [ABSTRACT FROM AUTHOR]

Compton camera (CC)-based prompt gamma imaging (PGI) is promising to realize real-time in-vivo range verification during proton therapy. Lutetium–yttrium orthosilicate (LYSO)-based CC has advantages in high detection efficiency and position resolution. However, few LYSO C C-based PGI experimental evaluations have been investigated. We built a 46 × 46 two-layer dense-pixel LYSO CC prototype for PGI. We attempt the first-ever effort to conduct the proton range shift verification experiments with the LYSO CC prototype. A 13 MeV proton beam with a cross-section of 1 mm2 produced by the Compact Pulsed Hadron Source (CPHS) and a lead collimator irradiates a block of graphite, a block of polymethacrylates (PMMA) and a block of fresh pork, respectively. A range shift varied from 1 mm to 5 mm of the proton beam is used to evaluate the performance of the prototype in PGI. The peak current intensity was about 640 nA. The pulse width and frequency were 100 μs and 1 Hz, respectively. The rate of incident protons in each measurement is about 3.6 × 108/s, and the corresponding delivered dose is about 5.8 Gy. The built LYSO CC prototype can distinguish the displacement of the Bragg peak in 2 mm (reaching 1 mm) at a distance of about 13 cm, and can accurately reconstruct the positions of the Bragg peak with a mean deviation of 0.2 mm in the eighteen groups of experiments. The experiments demonstrate the feasibility of the developed two-layer dense-pixel LYSO CC in realizing accurate range shift monitoring and show its potential in range verification during clinical proton therapy and high particle rate proton therapy (e.g., FLASH proton therapy). • The performance of a developed Compton camera was verified on a 13 MeV proton beam. • Bragg peak shifts are achieved through the relative displacements of targets. • The Compton camera can locate the Bragg peak with a mean deviation of 0.2 mm. • The developed Compton camera achieves 2 mm precision proton range shift monitoring. [ABSTRACT FROM AUTHOR]

We studied the application of a deep, fully connected Neural Network (NN) to process prompt gamma (PG) data measured by a Compton camera (CC) during the delivery of clinical proton radiotherapy beams. The network identifies 1) recorded “bad” PG events arising from background noise during the measurement, and 2) the correct ordering of PG interactions in the CC to help improve the fidelity of “good” data used for image reconstruction. PG emission from a tissue-equivalent target during irradiation with a 150 MeV proton beam delivered at clinical dose rates was measured with a prototype CC. Images were reconstructed from both the raw measured data and the measured data that was further processed with a neural network (NN) trained to identify “good” and “bad” PG events and predict the ordering of individual interactions within the good PG events. We determine if NN processing of the CC data could improve the reconstructed PG images to a level in which they could provide clinically useful information about the in vivo range and range shifts of the proton beams delivered at full clinical dose rates. Results showed that a deep, fully connected NN improved the achievable contrast to noise ratio (CNR) in our images by more than a factor of 8x. This allowed the path, range, and lateral width of the clinical proton beam within a tissue equivalent target to easily be identified from the PG images, even at the highest dose rates of a 150 MeV proton beam used for clinical treatments. On average, shifts in the beam range as small as 3 mm could be identified. However, when limited by the amount of PG data measured with our prototype CC during the delivery of a single proton pencil beam (∼1 × 109 protons), the uncertainty in the reconstructed PG images limited the identification of range shift to ∼5 mm. Substantial improvements in CC images were obtained during clinical beam delivery through NN pre-processing of the measured PG data. We believe this shows the potential of NNs to help improve and push CC-based PG imaging toward eventual clinical application for proton RT treatment delivery verification.

The potential of proton therapy to improve the conformity of the delivered dose to the tumor volume is currently limited by range uncertainties. Injectable superheated nanodroplets have recently been proposed for ultrasound-based in vivo range verification, as these vaporize into echogenic microbubbles on proton irradiation. In previous studies, offline ultrasound images of phantoms with dispersed nanodroplets were acquired after irradiation, relating the induced vaporization profiles to the proton range. However, the aforementioned method did not enable the counting of individual vaporization events, and offline imaging cannot provide real-time feedback. In this study, we overcame these limitations using high-frame-rate ultrasound imaging with a linear array during proton irradiation of phantoms with dispersed perfluorobutane nanodroplets at 37°C and 50°C. Differential image analysis of subsequent frames allowed us to count individual vaporization events and to localize them with a resolution beyond the ultrasound diffraction limit, enabling spatial and temporal quantification of the interaction between ionizing radiation and nanodroplets. Vaporization maps were found to accurately correlate with the stopping distribution of protons (at 50°C) or secondary particles (at both temperatures). Furthermore, a linear relationship between the vaporization count and the number of incoming protons was observed. These results indicate the potential of real-time high-frame-rate contrast-enhanced ultrasound imaging for proton range verification and dosimetry. [ABSTRACT FROM AUTHOR]

• New phantom for range verification and audit of clinical proton beams. • Radiochromic film accurately measures range shift within heterogeneous phantom. • Validation of film ranges via Monte Carlo and scaled depth methods. • Phantom tested through treatment workflow to assess audit application. In particle therapy, determination of range by measurement or calculation can be a significant source of uncertainty. This work investigates the development of a bespoke Range Length Phantom (RaLPh) to allow independent determination of proton range in tissue. This phantom is intended to be used as an audit device. RaLPh was designed to be compact and allows different configurations of tissue substitute slabs, to facilitate measurement of range using radiochromic film. Fourteen RaLPh configurations were tested, using two types of proton fluence optimised water substitutes, two types of bone substitute, and one lung substitute slabs. These were designed to mimic different complex tissue interfaces. Experiments were performed using a 115 MeV mono-energetic scanning proton beam to investigate the proton range for each configuration. Validation of the measured film ranges was performed via Monte Carlo simulations and ionisation chamber measurements. The phantom was then assessed as an audit device, by comparing film measurements with Treatment Planning System (TPS) predicted ranges. Varying the phantom slab configurations allowed for measurable range differences, and the best combinations of heterogeneous material gave agreement between film and Monte Carlo on average within 0.2% and on average within 0.3% of ionisation chamber measurements. Results against the TPS suggest a material density override is currently required to enable the phantom to be an audit device. This study found that a heterogeneous phantom with radiochromic film can provide range verification as part of a dedicated audit for clinical proton therapy beams. [ABSTRACT FROM AUTHOR]

• Filtered back projection (FBP) and DirectDensity (DD) algorithms were compared. • The range variations were often less than the calculation grid in case of DD. • DD was more robust with respect to variations in the CT imaging conditions than FBP. • DD is effective in a robust workflow and reduces uncertainties in range calculations. Accurate calculation of the proton beam range inside a patient is an important topic in proton therapy. In recent times, a computed tomography (CT) image reconstruction algorithm was developed for treatment planning to reduce the impact of the variation of the CT number with changes in imaging conditions. In this study, we investigated the usefulness of this new reconstruction algorithm (DirectDensity™: DD) in proton therapy based on its comparison with filtered back projection (FBP). We evaluated the effects of variations in the X-ray tube potential and target size on the FBP- and DD-image values and investigated the usefulness of the DD algorithm based on the range variations and dosimetric quantity variations. For X-ray tube potential variations, the range variation in the case of FBP was up to 12.5 mm (20.8%), whereas that of DD was up to 3.3 mm (5.6%). Meanwhile, for target size variations, the range variation in the case of FBP was up to 2.2 mm (2.5%), whereas that of DD was up to 0.9 mm (1.4%). Moreover, the variations observed in the case of DD were smaller than those of FBP for all dosimetric quantities. The dose distributions obtained using DD were more robust against variations in the CT imaging conditions (X-ray tube potential and target size) than those obtained using FBP, and the range variations were often less than the dose calculation grid (2 mm). Therefore, the DD algorithm is effective in a robust workflow and reduces uncertainty in range calculations. [ABSTRACT FROM AUTHOR]

Purpose: Uncertainty in computed tomography (CT)-based range prediction substantially impairs the accuracy of proton therapy. Direct determination of the stopping-power ratio (SPR) from dual-energy CT (DECT) has been proposed (DirectSPR), and initial validation studies in phantoms and biological tissues have proven a high accuracy. However, a thorough validation of range prediction in patients has not yet been achieved by any means. Here, we present the first systematic validation of CT-based proton range prediction in patients using prompt gamma imaging (PGI).Methods and Materials: A PGI slit camera system with improved positioning accuracy, using a floor-based docking station, was used. Its overall uncertainty for range prediction validation was determined experimentally with both x-ray and beam measurements. The accuracy of range prediction in patients was determined from clinical PGI measurements during hypofractionated treatment of 5 patients with prostate cancer - in total 30 fractions with in-room control-CTs. For each pencil-beam-scanning spot, the range shift was obtained by comparing the PGI measurement to a control-CT-based PGI simulation. Three different SPR prediction approaches were applied in simulations: a standard CT-number-to-SPR conversion (Hounsfield look-up table [HLUT]), an adapted HLUT (DECT optimized), and DirectSPR. The spot-wise weighted mean range shift from all spots served as a measure for the accuracy of the respective range prediction approach.Results: A mean range prediction accuracy of 0.0% ± 0.5%, 0.3% ± 0.4%, and 1.8% ± 0.4% was obtained for DirectSPR, adapted HLUT, and standard HLUT, respectively. The overall validation uncertainty of the second-generation PGI slit camera is about 1 mm (2σ) for all approaches, which is smaller than the range prediction uncertainty for deep-seated tumors.Conclusions: For the first time, range prediction accuracy was assessed in clinical routine using PGI range verification in prostate cancer treatments. Both DECT-derived range prediction approaches agree well with the measured proton range from PGI verification, whereas the standard HLUT approach differs relevantly. These results endorse the recent reduction of clinical safety margins in DirectSPR-based treatment planning in our institution. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

PurposeRange verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits.MethodsAn analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method. Various beam pulse widths (0.1-10 μs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum.ResultsThe calculated noise in the transducer was 12-28 mPa, depending on the transducer central frequency (70-380 kHz). The minimum number of protons detectable by the technique was on the order of 3-30 × 10(6) per pulse, with 30-800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 μs pulses producing signals with frequency less than 100 kHz.ConclusionsThe proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton-acoustic range verification may be feasible with approximately 5 × 10(6) protons/pulse and beam current.

Purpose: In vivo range and dose verification based on proton‐induced acoustics (protoacoustics) is potentially a useful tool for proton therapy. Built upon our previous study with two‐dimensional reconstruction, the time reversal (TR) method was extended to three‐dimensional (3D) and evaluated at two treatment sites (head and liver) through simulation, with the emphasis on a number of aspects such as increased spatial coverage, computational workload, and signal interference among slices. Methods: Two mono‐energetic pencil beams were modeled in each site. The k‐Wave toolbox was used to investigate the propagation and TR reconstruction of acoustic waves. The performance was quantitatively assessed based on mean square error (MSE) for dose verification and Bragg peak localization error (ΔBP) for range verification, with regard to five parameters: number of sensors, sampling duration, sampling timestep, spill time, and noise level. Results: The respective impacts of five parameters are examined. Under the optimum setting, the achievable ΔBP can be limited within 1 voxel (voxel size: 3 × 3 × 3 mm3) and the achievable MSE can be limited below 0.02, for the head case (56 sensors) and the liver case (204 sensors), respectively. Conclusions: The feasibility of range and dose verification utilizing the 3D TR method is demonstrated, as the very first step. In spite of several challenges unique to the 3D case (spatial coverage, computational workload, and signal interference among slices, etc.), promising performance is found and can be further improved through optimizing the deployment of sensors. The proposed approach may find potential use in several applications: beam diagnostics, in vivo dosimetry, and treatment monitoring. [ABSTRACT FROM AUTHOR]

• Prompt-gamma emission in proton therapy is investigated. • Results of experiments on phantoms are shown along with Geant4 simulations. • Several Geant4 versions and physics lists are tested. • None of the configurations is able to fully reproduce the experimental data. • It is not the most recent Geant4 version which gives the best agreement with data. The field of online monitoring of the beam range is one of the most researched topics in proton therapy over the last decade. The development of detectors that can be used for beam range verification under clinical conditions is a challenging task. One promising possible solution are modalities that record prompt-gamma radiation produced by the interactions of the proton beam with the target tissue. A good understanding of the energy spectra of the prompt gammas and the yields in certain energy regions is crucial for a successful design of a prompt-gamma detector. Monte-Carlo simulations are an important tool in development and testing of detector concepts, thus the proper modelling of the prompt-gamma emission in those simulations are of vital importance. In this paper, we confront a number of GEANT4 simulations of prompt-gamma emission, performed with different versions of the package and different physics lists, with experimental data obtained from a phantom irradiation with proton beams of four different energies in the range 70–230 MeV. The comparison is made on different levels: features of the prompt-gamma energy spectrum, gamma emission depth profiles for discrete transitions and the width of the distal fall-off in those profiles. The best agreement between the measurements and the simulations is found for the GEANT4 version 10.4.2 and the reference physics list QGSP_BIC_HP. Modifications to prompt-gamma emission modelling in higher versions of the software increase the discrepancy between the simulation results and the experimental data. [ABSTRACT FROM AUTHOR]

• Fast (4-6 us) and stress-confined, delivery enables thermoacoustic range verification. • Submillimeter range accuracy was achieved for beamlets that delivered ~0.5 Gy to soft tissue. • Estimates are accurate relative to ultrasound images soundspeed inhomogeneity • Synchrocyclotrons deliver stress-confined proton pulses. • Acoustic ringing indicated beam traversed bone; metallic implants will also cause ringing. The purpose of this phantom study is to demonstrate that thermoacoustic range verification could be performed clinically. Thermoacoustic emissions generated in an anatomical multimodality imaging phantom during delivery of a clinical plan are compared to simulated emissions to estimate range shifts compared to the treatment plan. A single-field 12-layer proton pencil beam scanning (PBS) treatment plan created in Pinnacle prescribing 6 Gy/fraction was delivered by a superconducting synchrocyclotron to a triple modality (CT, MRI, and US) abdominal imaging phantom. Data was acquired by four acoustic receivers rigidly affixed to a linear ultrasound array. Receivers 1–2 were located distal to the treatment volume, whereas 3–4 were lateral. Receivers' room coordinates were computed relative to the ultrasound image plane after co-registration to the planning CT volume. For each prescribed beamlet, a set of thermoacoustic emissions corresponding to varied beam energies were computed. Simulated emissions were compared to measured emissions to estimate shifts of the Bragg peak. Shifts were small for high-dose beamlets that stopped in soft tissue. Signals acquired by channels 1–2 yielded shifts of - 0.2 ± 0.7 m m relative to Monte Carlo simulations for high dose spots (~40 cGy) in the second layer. Additionally, for beam energy ≥ 125 MeV, thermoacoustic emissions qualitatively tracked lateral motion of pristine beams in a layered gelatin phantom, and time shifts induced by changing phantom layers were self-consistent within nanoseconds. Acoustic receivers tuned to spectra of thermoacoustic emissions may enable range verification during proton therapy. [ABSTRACT FROM AUTHOR]

Purpose: Despite the physical benefits of protons over conventional photon radiation in cancer treatment, range uncertainties impede the ability to harness the full potential of proton therapy. While monitoring the proton range in vivo could reduce the currently adopted safety margins, a routinely applicable range verification technique is still lacking. Recently, phase‐change nanodroplets were proposed for proton range verification, demonstrating a reproducible relationship between the proton range and generated ultrasound contrast after radiation‐induced vaporization at 25°C. In this study, previous findings are extended with proton irradiations at different temperatures, including the physiological temperature of 37°C, for a novel nanodroplet formulation. Moreover, the potential to modulate the linear energy transfer (LET) threshold for vaporization by varying the degree of superheat is investigated, where the aim is to demonstrate vaporization of nanodroplets directly by primary protons. Methods: Perfluorobutane nanodroplets with a shell made of polyvinyl alcohol (PVA‐PFB) or 10,12‐pentacosadyinoic acid (PCDA‐PFB) were dispersed in polyacrylamide hydrogels and irradiated with 62 MeV passively scattered protons at temperatures of 37°C and 50°C. Nanodroplet transition into echogenic microbubbles was assessed using ultrasound imaging (gray value and attenuation analysis) and optical images. The proton range was measured independently and compared to the generated contrast. Results: Nanodroplet design proved crucial to ensure thermal stability, as PVA‐shelled nanodroplets dramatically outperformed their PCDA‐shelled counterpart. At body temperature, a uniform radiation response proximal to the Bragg peak is attributed to nuclear reaction products interacting with PVA‐PFB nanodroplets, with the 50% drop in ultrasound contrast being 0.17 mm ± 0.20 mm (mean ± standard deviation) in front of the proton range. Also at 50°C, highly reproducible ultrasound contrast profiles were obtained with shifts of −0.74 mm ± 0.09 mm (gray value analysis), −0.86 mm ± 0.04 mm (attenuation analysis) and −0.64 mm ± 0.29 mm (optical analysis). Moreover, a strong contrast enhancement was observed near the Bragg peak, suggesting that nanodroplets were sensitive to primary protons. Conclusions: By varying the degree of superheat of the nanodroplets' core, one can modulate the intensity of the generated ultrasound contrast. Moreover, a submillimeter reproducible relationship between the ultrasound contrast and the proton range was obtained, either indirectly via the visualization of secondary reaction products or directly through the detection of primary protons, depending on the degree of superheat. The potential of PVA‐PFB nanodroplets for in vivo proton range verification was confirmed by observing a reproducible radiation response at physiological temperature, and further studies aim to assess the nanodroplets' performance in a physiological environment. Ultimately, cost‐effective online or offline ultrasound imaging of radiation‐induced nanodroplet vaporization could facilitate the reduction of safety margins in treatment planning and enable adaptive proton therapy. [ABSTRACT FROM AUTHOR]