Proton Range Research Articles

PO-1610 Proton and carbon range verification for anatomy-like objects with the use of animal tissue samples

PO-1610 Proton and carbon range verification for anatomy-like objects with the use of animal tissue samples

SP-0582 Online CBCT-based proton range and dose calculation

SP-0582 Online CBCT-based proton range and dose calculation

Proton range uncertainty reduction benefits for skull base tumors in terms of normal tissue complication probability (NTCP) and healthy tissue doses.

Proton therapy allows for more conformal dose distributions and lower organ at risk and healthy tissue doses than conventional photon-based radiotherapy, but uncertainties in the proton range currently prevent proton therapy from making full use of these advantages. Numerous developments therefore aim to reduce such range uncertainties. In this work, we quantify the benefits of reductions in range uncertainty for treatments of skull base tumors. The study encompassed 10skull base patients with clival tumors. For every patient, six treatment plans robust to setup errors of 2mm and range errors from 0% to 5% were created. The determined metrics included the brainstem and optic chiasm normal tissue complication probability (NTCP) with the endpoints of necrosis and blindness, respectively, as well as the healthy tissue volume receiving at least 70% of the prescription dose. A range uncertainty reduction from the current level of 4% to a potentially achievable level of 1% reduced the probability of brainstem necrosis by up to 1.3 percentage points in the nominal scenario in which neither setup nor range errors occur and by up to 2.9 percentage points in the worst-case scenario. Such a range uncertainty reduction also reduced the optic chiasm NTCP with the endpoint of blindness by up to 0.9 percentage points in the nominal scenario and by up to 2.2 percentage points in the worst-case scenario. The decrease in the healthy tissue volume receiving at least 70% of the prescription dose ranged from -7.8 to 24.1cc in the nominal scenario and from -3.4 to 38.4cc in the worst-case scenario. The benefits quantified as part of this study serve as a guideline of the OAR and healthy tissue dose benefits that range monitoring techniques may be able to achieve. Benefits were observed between all levels of range uncertainty. Even smaller range uncertainty reductions may therefore be beneficial.

In-vivo proton range verification for reducing the risk of permanent alopecia in medulloblastoma treatment

ObjectiveThe purpose of this work is the clinical commissioning of a recently developed in-vivo range verification system for the head treatment of pediatric medulloblastoma patients. Inaccurate beam range for such treatment could lead to either inadequate dose coverage of the target volume or excessive dose to the head skin resulting permanent alopecia. MethodsThe in-vivo range verification system is designed to perform pre-treatment range verification and adjustment. An array of Si-diode detectors is to be placed on the patient immobilization mask in the exit direction of a whole-brain field; signal is analyzed, and the extracted water equivalent path length (WEPL) is compared to the expected one, revealing if a range correction is needed. The method was tested in solid water and anthropomorphic head phantom, with validation based on independent WEPL measurements. The measured WEPL were compared to those computed by the treatment planning system (TPS). ResultsThe accuracy for the WEPL measurements by the diode system in both solid water and anthropomorphic head phantom were on average within a millimeter from more accurate measurement by the dose-extinction technique, with the error range for the two phantoms as (0–1 ​mm) and (0–1.3 ​mm), respectively. When compared to the WEPL calculated by the treatment planning system, the measured values were on average within 1 ​% (range 0–3%) of the beam range. The accuracy of dose measurements by the diodes in the fall-off part of the depth dose profile was validated against the reference Markus chamber. No need for further correction (due to different beam parameters and detector dose ageing effects) was found. ConclusionsThe range verification workflow was successfully tested in the anthropomorphic head phantom. The performance of the in-vivo range verification system and related workflow meet the clinical requirements in terms of the needed WEPL accuracy for pretreatment range verification.

Accuracy of proton stopping power estimation of silicone breast implants with single and dual-energy CT calibration techniques.

A major contributing factor to proton range uncertainty is the conversion of computed tomography (CT) Hounsfield Units (HU) to proton relative stopping power (RSP). This uncertainty is elevated with implanted devices, such as silicone breast implants when computed with single energy CT (SECT). In recent years, manufacturers have introduced implants with variations in gel cohesivity. Deriving the RSP for these implants from dual‐energy CT (DECT) can result in a marked reduction of the error associated with SECT. In this study, we investigate the validity of DECT calibration of HU to RSP on silicone breast implants of varying cohesivity levels. A DECT capable scanner was calibrated using the stoichiometric method of Bourque et al for SECT and DECT using a tissue substitute phantom. Three silicone breast implants of increasing gel cohesivity were measured in a proton beam of clinical energy to determine ground‐truth RSP and water equivalent thickness (WET). These were compared to SECT‐derived RSP at three CT spectrum energies and DECT with two energy pairs (80/140 kVp and 100/140 kVp) as obtained from scans with and without an anthropomorphic phantom. The RSP derived from parameters estimates from CT vendor‐specific software (syngo.via) was compared. The WET estimates from SECT deviated from MLIC ground truth approximately +11%–19%, which would result in overpenetration if used clinically. Both the Bourque calibration and syngo.via WET estimates from DECT yielded error ≤0.5% from ground truth; no significant difference was found between models of varying gel cohesivity levels. WET estimates without the anthropomorphic phantom were significantly different than ground truth for the Bourque calibration. From these results, gel cohesivity had no effect on proton RSP. User‐generated DECT calibration can yield comparably accurate RSP estimates for silicone breast implants to vendor software methods. However, care must be taken to account for beam hardening effects.

First-In-Human Validation of CT-Based Proton Range Prediction Using Prompt Gamma Imaging in Prostate Cancer Treatments

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). 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), andDirectSPR. The spot-wise weighted mean range shift from all spots served as a measure for the accuracy of the respective range prediction approach. 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 1mm (2σ) for all approaches, which is smaller than the range prediction uncertainty for deep-seated tumors. 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.

Measurement-based range evaluation for quality assurance of CBCT-based dose calculations in adaptive proton therapy.

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. 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. The simulation approach showed high agreement with the standard recalculation approach. The median values of the range differences of these two methods agreed within 0.1mm and the interquartile ranges (IQRs) within 0.3mm 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 0.1mm and the IQRs less than 0.4mm. 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 0.5mm, respectively. scCBCT- and planCT-based dose distributions were found to have a range agreement better than 3mm (median and IQR) for all considered scenarios (recalculation, simulation, and measurement). 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.

A time-of-flight-based reconstruction for real-time prompt-gamma imaging in proton therapy

We propose a novel prompt-gamma (PG) imaging modality for real-time monitoring in proton therapy: PG time imaging (PGTI). By measuring the time-of-flight (TOF) between a beam monitor and a PG detector, our goal is to reconstruct the PG vertex distribution in 3D. In this paper, a dedicated, non-iterative reconstruction strategy is proposed (PGTI reconstruction). Here, it was resolved under a 1D approximation to measure a proton range shift along the beam direction. In order to show the potential of PGTI in the transverse plane, a second method, based on the calculation of the centre of gravity (COG) of the TIARA pixel detectors’ counts was also explored. The feasibility of PGTI was evaluated in two different scenarios. Under the assumption of a 100 ps (rms) time resolution (achievable in single proton regime), MC simulations showed that a millimetric proton range shift is detectable at 2σ with 108 incident protons in simplified simulation settings. With the same proton statistics, a potential 2 mm sensitivity (at 2σ with 108 incident protons) to beam displacements in the transverse plane was found using the COG method. This level of precision would allow to act in real-time if the treatment does not conform to the treatment plan. A worst case scenario of a 1 ns (rms) TOF resolution was also considered to demonstrate that a degraded timing information can be compensated by increasing the acquisition statistics: in this case, a 2 mm range shift would be detectable at 2σ with 109 incident protons. By showing the feasibility of a time-based algorithm for the reconstruction of the PG vertex distribution for a simplified anatomy, this work poses a theoretical basis for the future development of a PG imaging detector based on the measurement of particle TOF.

Applications of a novel detector for pencil beam scanning proton therapy beam quality assurance

This study utilized a new type of detector, the CROSS II (Liverage Biomedical Inc., Taiwan), to perform a beam quality assurance (QA) procedure on a Sumitomo (Sumitomo Heavy Industries, Inc., Japan) pencil beam linear scanning proton therapy machine. The Cross II can monitor proton Pristine Bragg peak range, beam width, beam size, beam position, and scanning speed. All the data presented here were collected during a time span of over one year. The accuracy of the QA program could be verified if all the QA items were tested stably and within the programmed tolerances. Our results showed that the proton range remained within the [Formula: see text] mm tolerance, with the majority of measurements within [Formula: see text] mm, [Formula: see text] mm for spot size, 1.5 mm for spot position, and [Formula: see text]% for scanning speed. We found that the CROSS II detector is in high precise and steady state with highly efficient. Our proton therapy system was also proven to be in an accurate and reliable condition according to our QA results.

Optical method for measuring proton projected range in GaAs

The knowledge of the consequences of charged particles interaction with semiconductor materials is of paramount interest to study the performance of devices for space applications. Particularly, GaAs is one of the most used for device development. Here, we present a novel method to measure the projected range of energetic protons impinging crystalline GaAs based on µRaman spectroscopy. To validate the method, different proton energies were obtained using appropriate Al foils, an approach which has been properly justified. Finally, the spatial variation of different parameters obtained from Raman spectra is compared with SRIM (Stopping and Range of Ions in Matter) simulations, showing a remarkable agreement of the theoretical and experimental ranges.

NRG Oncology Survey of Monte Carlo Dose Calculation Use in US Proton Therapy Centers.

Purpose/Objective(s)Monte Carlo (MC) dose calculation has appeared in primary commercial treatment-planning systems and various in-house platforms. Dual-energy computed tomography (DECT) and metal artifact reduction (MAR) techniques complement MC capabilities. However, no publications have yet reported how proton therapy centers implement these new technologies, and a national survey is required to determine the feasibility of including MC and companion techniques in cooperative group clinical trials.Materials/MethodsA 9-question survey was designed to query key clinical parameters: scope of MC utilization, validation methods for heterogeneities, clinical site-specific imaging guidance, proton range uncertainties, and how implants are handled. A national survey was distributed to all 29 operational US proton therapy centers on 13 May 2019.ResultsWe received responses from 25 centers (86% participation). Commercial MC was most commonly used for primary plan optimization (16 centers) or primary dose evaluation (18 centers), while in-house MC was used more frequently for secondary dose evaluation (7 centers). Based on the survey, MC was used infrequently for gastrointestinal, genitourinary, gynecology and extremity compared with other more heterogeneous disease sites (P < .007). Although many centers had published DECT research, only 3/25 centers had implemented DECT clinically, either in the treatment-planning system or to override implant materials. Most centers (64%) treated patients with metal implants on a case-by-case basis, with a variety of methods reported. Twenty-four centers (96%) used MAR images and overrode the surrounding tissue artifacts; however, there was no consensus on how to determine metal dimension, materials density, or stopping powers.ConclusionThe use of MC for primary dose calculation and optimization was prevalent and, therefore, likely feasible for clinical trials. There was consensus to use MAR and override tissues surrounding metals but no consensus about how to use DECT and MAR for human tissues and implants. Development and standardization of these advanced technologies are strongly encouraged for vendors and clinical physicists.

Training a deep neural network coping with diversities in abdominal and pelvic images of children and young adults for CBCT-based adaptive proton therapy

PurposeTo train a deep neural network for correcting abdominal and pelvic cone-beam computed tomography (CBCT) of children and young adults in the presence of diverse patient size, anatomic extent, and scan parameters. Materials and MethodsPretreatment CBCT and planning/repeat CT image pairs from 64 children and young adults treated with proton therapy (aged 1–23 years) were analyzed. To evaluate the impact of anatomic extent in CBCT and data size in the training data, we compared the performance of three cycle-consistent generative adversarial network models that were separately trained by three datasets comprising abdominal (n = 21), pelvic (n = 29), and combined abdominal-pelvic image pairs (n = 50), respectively. The maximum body width of each patient was normalized to a fixed width before training and model application to reduce the impact of variations in body size. The corrected CBCT images by the three models were comparatively evaluated against the repeat CT closest in time to the CBCT (median gap, 0 days; range, 0–6 days) in HU accuracy, estimated dose distribution, and proton range. ResultsThe network model trained by the combined dataset significantly outperformed the abdomen and pelvis models in mean absolute HU error of the corrected CBCT from 14 testing patients (47 ± 7 HU versus 51 ± 8 HU; paired Wilcoxon signed-rank test, P < 0.01). The larger error (60 ± 7 HU) without the body-size normalization confirmed the efficacy of the preprocessing. The model trained with the combined dataset resulted in gamma passing rates of 98.5 ± 1.9% (2%/2 mm criterion) and the range (80% distal fall-off) differences from the reference within ±3 mm for 91.2 ± 11.5% beamlets. ConclusionCombining data from adjacent anatomic sites and normalizing age-dependent body sizes in children and young adults were beneficial in training a neural network to accurately estimate proton dose from CBCT despite limited training data size and anatomic diversities.

Secondary Particle Interactions in a Compton Camera Designed for in vivo Range Verification of Proton Therapy.

The purpose of this study was to determine the types, proportions, and energies of secondary particle interactions in a Compton camera (CC) during the delivery of clinical proton beams. The delivery of clinical proton pencil beams ranging from 70 to 200 MeV incident on a water phantom was simulated using Geant4 software (version 10.4). The simulation included a CC similar to the configuration of a Polaris J3 CC designed to image prompt gammas (PGs) emitted during proton beam irradiation for the purpose of in vivo range verification. The interaction positions and energies of secondary particles in each CC detector module were scored. For a 150-MeV proton beam, a total of 156,688(575) secondary particles per 108 protons, primarily composed of gamma rays (46.31%), neutrons (41.37%), and electrons (8.88%), were found to reach the camera modules, and 79.37% of these particles interacted with the modules. Strategies for using CCs for proton range verification should include methods of reducing the large neutron backgrounds and low-energy non-PG radiation. The proportions of interaction types by module from this study may provide information useful for background suppression.

Proton range verification with MACACO II Compton camera enhanced by a neural network for event selection

The applicability extent of hadron therapy for tumor treatment is currently limited by the lack of reliable online monitoring techniques. An active topic of investigation is the research of monitoring systems based on the detection of secondary radiation produced during treatment. MACACO, a multi-layer Compton camera based on LaBr3 scintillator crystals and SiPMs, is being developed at IFIC-Valencia for this purpose. This work reports the results obtained from measurements of a 150 MeV proton beam impinging on a PMMA target. A neural network trained on Monte Carlo simulations is used for event selection, increasing the signal to background ratio before image reconstruction. Images of the measured prompt gamma distributions are reconstructed by means of a spectral reconstruction code, through which the 4.439 MeV spectral line is resolved. Images of the emission distribution at this energy are reconstructed, allowing calculation of the distal fall-off and identification of target displacements of 3 mm.

The dose magnifying glass quality assurance system for daily proton therapy range verification

Proton therapy has a distinct dosimetric advantage over conventional photon therapy due to its Bragg peak profile. This allows greater accuracy in dose delivery and dose conformation to the target, however it requires greater precision in setup, delivery and for quality assurance (QA) procedures. The AAPM TG 224 report recommends daily range and spot position checks with tolerance on the order of a millimetre. Daily QA systems must therefore be efficient for daily use and be capable of sub-millimetre precision however few suitable commercial systems are available. In this work, a compact, real-time daily QA system is optimised and characterised for proton range verification using an ad-hoc Geant4 simulation. The system is comprised of a monolithic silicon diode array detector embedded in a perspex phantom. The detector is orientated at an angular offset to the incident proton beam to allow range in perspex to be determined for flat proton fields. The accuracy of the system for proton range in perspex measurements was experimentally evaluated over the full range of clinical proton energies. The mean R 100, R 90 and R 80 ranges measured with the system were accurate within ±0.6 mm of simulated ranges in a perspex phantom for all energies assessed. This system allows real-time read-out of individual detector channels also making it appropriate for temporal beam delivery diagnostics and for spot position monitoring along one axis. The system presented provides a suitable, economical and efficient alternative for daily QA in proton therapy.

A Monte Carlo Determination of Dose and Range Uncertainties for Preclinical Studies with a Proton Beam.

Simple SummaryIf reference studies can be found on the uncertainties linked to the clinical context of proton therapy, they, although equally critical, are very patchy in a preclinical context, and are specific to each beam line. This work provides the community with a complete assessment of the sources of uncertainties for a preclinical proton beam line. This aims to ensure that, in this line, the biological results observed and the dose–response relationships are obtained without any bias. Despite being specific to a preclinical line, the results presented here can be transposed to other types of proton preclinical facilities, and thus allow us to effectively compare them to one another. Proton therapy (PRT) is an irradiation technique that aims at limiting normal tissue damage while maintaining the tumor response. To study its specificities, the ARRONAX cyclotron is currently developing a preclinical structure compatible with biological experiments. A prerequisite is to identify and control uncertainties on the ARRONAX beamline, which can lead to significant biases in the observed biological results and dose–response relationships, as for any facility. This paper summarizes and quantifies the impact of uncertainty on proton range, absorbed dose, and dose homogeneity in a preclinical context of cell or small animal irradiation on the Bragg curve, using Monte Carlo simulations. All possible sources of uncertainty were investigated and discussed independently. Those with a significant impact were identified, and protocols were established to reduce their consequences. Overall, the uncertainties evaluated were similar to those from clinical practice and are considered compatible with the performance of radiobiological experiments, as well as the study of dose–response relationships on this proton beam. Another conclusion of this study is that Monte Carlo simulations can be used to help build preclinical lines in other setups.

Can iodine be used as a contrast agent for protontherapy range verification? Measurement of the 127I(p,n)127mXe (reaction) cross section in the 4.5–10 MeV energy range

Full exploitation of the therapeutic potential of protontherapy is still prevented by uncertainties in the determination of the proton range within the patient's body. Several methods have been proposed to verify the proton range in-vivo by measuring the secondary activity (either PET or prompt-gamma) induced by proton fields. However, none of the presented solutions has yet reached clinical maturity, due to low activity counts and different spatial distributions of dose and proton-induced activity profiles.The quality of verification images can be largely improved by the use of contrast agents that provide an increased induced radioactivity near the Bragg peak region. Iodine is a contrast agent already approved for a number of medical applications. It presents a promising proton reaction channel producing the metastable isomer 127mXe, with a half-life of 69.2(9) s, which could be used for online range verification. However, cross section production for this reaction has not been measured down to small proton energies present near the Bragg peak.To overcome this lack of data, we put in place a specific set-up consisting of two pairs of collinear opposed LaBr3(Ce) detectors and a fully digital acquisition system and performed irradiations in the low energy (4–10 MeV) range in the microbeam line at the Center for Micro Analysis of Materials (Madrid, Spain).We report on a new measurement of the 127I(p,n)127mXe reaction cross section in the 4.5–10 MeV energy region using the activation technique. The accuracy of the measured cross sections is better than 30%, and the observed values are in agreement with theoretical calculations using the default parameters of the TALYS code. Significant activity was observed for proton energies above 4.5 MeV, corresponding to a range in water of less than 0.3 mm. Our results support the viability of 127I as a contrast agent for proton radiotherapy.

Animal tissue-based quantitative comparison of dual-energy CT to SPR conversion methods using high-resolution gel dosimetry

Dual-energy computed tomography (DECT) has been shown to allow for more accurate ion therapy treatment planning by improving the estimation of tissue stopping power ratio (SPR) relative to water, among other tissue properties. In this study, we measured and compared the accuracy of SPR values derived using both dual- and single-energy CT (SECT) based on different published conversion algorithms. For this purpose, a phantom setup containing either fresh animal soft tissue samples (beef, pork) and a water reference or tissue equivalent plastic materials was designed and irradiated in a clinical proton therapy facility. Dosimetric polymer gel was positioned downstream of the samples to obtain a three-dimensional proton range distribution with high spatial resolution. The mean proton range in gel for each tissue relative to the water sample was converted to a SPR value. Additionally, the homogeneous samples were probed with a variable water column encompassed by two ionization chambers to benchmark the SPR accuracy of the gel dosimetry. The SPR values measured with both methods were consistent with a mean deviation of 0.2%, but the gel dosimetry captured range variations up to 5 mm within individual samples.Across all fresh tissue samples the SECT approach yielded significantly greater mean absolute deviations from the SPR deduced using gel range measurements, with an average difference of 1.2%, compared to just 0.3% for the most accurate DECT-based algorithm. These results show a significant advantage of DECT over SECT for stopping power prediction in a realistic setting, and for the first time allow to compare a large set of methods under the same conditions.

Analysis of characteristics of images acquired with a prototype clinical proton radiography system.

Verification of patient-specific proton stopping powers obtained in the patient's treatment position can be used to reduce the distal and proximal margins needed in particle beam planning. Proton radiography can be used as a pretreatment instrument to verify integrated stopping power consistency with the treatment planning CT. Although a proton radiograph is a pixel by pixel representation of integrated stopping powers, the image may also be of high enough quality and contrast to be used for patient alignment. This investigation quantifies the accuracy and image quality of a prototype proton radiography system on a clinical proton delivery system. We have developed a clinical prototype proton radiography system designed for integration into efficient clinical workflows. We tested the images obtained by this system for water-equivalent thickness (WET) accuracy, image noise, and spatial resolution. We evaluated the WET accuracy by comparing the average WET and rms error in several regions of interest (ROI) on a proton radiograph of a custom peg phantom. We measured the spatial resolution on a CATPHAN Line Pair phantom and a custom edge phantom by measuring the 10% value of the modulation transfer function (MTF). In addition, we tested the ability to detect proton range errors due to anatomical changes in a patient with a customized CIRS pediatric head phantom and inserts of varying WET placed in the posterior fossae of the brain. We took proton radiographs of the phantom with each insert in place and created difference maps between the resulting images. Integrated proton range was measured from an ROI in the difference maps. We measured the WET accuracy of the proton radiographic images to be ±0.2mm (0.33%) from known values. The spatial resolution of the images was 0.6lp/mm on the line pair phantom and 1.13lp/mm on the edge phantom. We were able to detect anatomical changes producing changes in WET as low as 0.6mm. The proton radiography system produces images with image quality sufficient for pretreatment range consistency verification.

Analog Filters Design for Improving Precision in Proton Sound Detectors

This paper analyzes how to improve the precision of ionoacoustic proton range verification by optimizing the analog signal processing stages with particular emphasis on analog filters. The ionoacoustic technique allows one to spatially detect the proton beam penetration depth/range in a water absorber, with interesting possible applications in real-time beam monitoring during hadron therapy treatments. The state of the art uses nonoptimized detectors that have low signal quality and thus require a higher total dose, which is not compatible with clinical applications. For these reasons, a comprehensive analysis of acoustic signal bandwidth, signal-to-noise-ratio and noise power/bandwidth will be presented. The correlation between these signal-quality parameters with maximum achievable proton range measurement precision will be discussed. In particular, the use of an optimized analog filter allows one to decrease the dose required to achieve a given precision by as much as 98.4% compared to a nonoptimized filter approach.