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Proton computed tomography (pCT) can reduce proton therapy uncertainty by measuring Relative Stopping Power (RSP) directly. The spatial resolution of the pCT images decreases due to the multi colomb scattering (MCS) of protons inside the phantom. This reduction of image quality can be compensated by using the most probable proton path in the reconstruction algorithm. In this study, a pCT system was simulated by particle-to-particle tracking of protons using the Geant4 toolkit. This simulation improves the spatial resolution of images obtained from applying different estimators of the proton path, including straight line path (SLP), cubic spline path (CSP), and most likely path (MLP). The Catphan528 phantom was irradiated with 200MeV protons. The energy, position, and direction of the particle were recorded before and after the phantom. The RSP image matrix was modified by weigthing factors obtaind using SLP, CSP, and MLP path esitimators and image was reconstructed using FBP. Spatial resolution and root mean square errors (RMSE) were compared to phantom image data. According to the results, the MLP method is less error-prone and more accurate than other methods in resolving spatial resolutions. For 100,000 protons, with image resolution ranging from 1 to 0.1 mm, the spatial resolution increased from 3 to 9 line pairs/cm, while the RMSE increased from 8.11% to 14.97%.

Proton irradiation is a well-established method to treat deep-seated tumors in radio oncology. Usually, an X-ray computed tomography (CT) scan is used for treatment planning. Since proton therapy is based on the precise knowledge of the stopping power describing the energy loss of protons in the patient tissues, the Hounsfield units of the planning CT have to be converted. This conversion introduces range errors in the treatment plan, which could be reduced, if the stopping power values were extracted directly from an image obtained using protons instead of X-rays. Since protons are affected by multiple Coulomb scattering, reconstruction of the 3D stopping power map results in limited image quality if the curved proton path is not considered. This work presents a substantial code extension of the open-source toolbox TIGRE for proton CT (pCT) image reconstruction based on proton radiographs including a curved proton path estimate. The code extension and the reconstruction algorithms are GPU-based, allowing to achieve reconstruction results within minutes. The performance of the pCT code extension was tested with Monte Carlo simulated data using three phantoms (Catphan® high resolution and sensitometry modules and a CIRS patient phantom). In the simulations, ideal and non-ideal conditions for a pCT setup were assumed. The obtained mean absolute percentage error was found to be below 1% and up to 8 lp/cm could be resolved using an idealized setup. These findings demonstrate that the presented code extension to the TIGRE toolbox offers the possibility for other research groups to use a fast and accurate open-source pCT reconstruction.

Proton irradiation is a well-established method to treat deep-seated tumors in radio oncology. Usually, an X-ray computed tomography (CT) scan is used for treatment planning. Since proton therapy is based on the precise knowledge of the stopping power describing the energy loss of protons in the patient tissues, the Hounsfield units of the planning CT have to be converted. This conversion introduces range errors in the treatment plan, which could be reduced, if the stopping power values were extracted directly from an image obtained using protons instead of X-rays. Since protons are affected by multiple Coulomb scattering, reconstruction of the 3D stopping power map results in limited image quality if the curved proton path is not considered. This work presents a substantial code extension of the open-source toolbox TIGRE for proton CT (pCT) image reconstruction based on proton radiographs including a curved proton path estimate. The code extension and the reconstruction algorithms are GPU-based, allowing to achieve reconstruction results within minutes. The performance of the pCT code extension was tested with Monte Carlo simulated data using three phantoms (Catphan® high resolution and sensitometry modules and a CIRS patient phantom). In the simulations, ideal and non-ideal conditions for a pCT setup were assumed. The obtained mean absolute percentage error was found to be below 1% and up to 8 lp/cm could be resolved using an idealized setup. These findings demonstrate that the presented code extension to the TIGRE toolbox offers the possibility for other research groups to use a fast and accurate open-source pCT reconstruction. [ABSTRACT FROM AUTHOR]

Proton CT (pCT) is a promising new imaging technique that can reconstruct relative stopping power (RSP) more accurately than x-ray CT in each cubic millimeter voxel of the patient. This, in turn, will result in better proton range accuracy and, therefore, smaller planned tumor volumes (PTV). The hardware description and some reconstructed images have previously been reported. In a series of two contributions, we focus on presenting the software algorithms that convert pCT detector data to the final reconstructed pCT images for application in proton treatment planning. There were several options on how to accomplish this, and we will describe our solutions at each stage of the data processing chain. In the first paper of this series, we present the data acquisition with the pCT tracking and energy-range detectors and how the data are preprocessed, including the conversion to the well-formatted track information from tracking data and water-equivalent path length from the data of a calibrated multi-stage energy-range detector. These preprocessed data are then used for the initial image formation with an FDK cone-beam CT algorithm. The output of data acquisition, preprocessing, and FDK reconstruction is presented along with illustrative imaging results for two phantoms, including a pediatric head phantom. The second paper in this series will demonstrate the use of iterative solvers in conjunction with the superiorization methodology to further improve the images resulting from the upfront FDK image reconstruction and the implementation of these algorithms on a hybrid CPU/GPU computer cluster.

• Proton micro-tomography experiments have been simulated using Geant4. • Geant4 gives access to information that is not possible to get from experiments. • A phantom of inertial confinement fusion target was constructed. • Accuracy of mass density images reconstructed by different methods was assessed. • Accuracy of the corrections implemented for X-ray attenuation was evaluated. The Geant4 toolkit was used to perform benchmark Monte Carlo simulations of proton micro-tomography imaging. A phantom of an inertial confinement fusion (ICF) target was designed, based on experimental data. Simulations of STIM (Scanning Transmission Ion Microscopy) and PIXE (Particle Induced X-ray Emission) tomography were performed. Quantitative images were obtained from the TomoRebuild and JPIXET software packages, chosen for their ability to handle large solid angles of X-ray detection. The tomographic images were compared with the original phantom, used as a reference. For STIM-T, the accuracy of the calculated mass density was ≤ 2 % for TomoRebuild and ≤ 14 % for JPIXET. Corrections of X-ray production cross section and X-ray absorption were tested for the quantification of Ge, used as a dopant in the ICF target. The accuracy on the obtained Ge density was ≤ 2.9 % for TomoRebuild and ≤ 6.4 % for JPIXET, whereas the error was about 40 % without correction. [ABSTRACT FROM AUTHOR]

Data filtering is crucial for accurate relative stopping power (RSP) reconstruction in proton CT (pCT). In this work, we assess different filters and their performance for the US pCT collaboration prototype pCT system in Monte Carlo (MC) simulations. The potential of using the recently proposed [Formula: see text]-E filter for removing nuclear interactions that occurred in the energy/range detector of the pCT system is investigated. Full pCT scans were acquired with the TOPAS MC simulated version of the prototype scanner that comprises two tracking detectors and a five stage energy/range detector. An ideal water cylinder and a water cylinder with five tissue inserts were investigated. Before image reconstruction, a [Formula: see text] WEPL filter was applied as the only filter, or in addition to filters acting on the energy deposit in each of the energy detector stages, as done currently with the prototype. The potential of the [Formula: see text]-E filter that was recently proposed for helium imaging was assessed. The results were compared to simulations for which nuclear interactions were disabled representing ground truth. The [Formula: see text] WEPL filter alone was not sufficient to filter out all nuclear interaction events and systematic fluctuations in the form of ring artifacts were present in the pCT reconstructed images. Applying energy filters currently used with the device prior to the [Formula: see text] WEPL filter only slightly improved the image quality. A [Formula: see text] WEPL filter improved the mean RSP accuracy, but could not fully remove the systematic fluctuations. The [Formula: see text]-E filter in addition to the current reconstruction procedure efficiently removed the systematic fluctuations and the achieved RSP accuracy closely matched the simulation without nuclear interactions. This study demonstrates the dependence of the accuracy of the usual [Formula: see text] WEPL filter on uncertainties arising within the energy detector. By enabling to remove such uncertainties, the [Formula: see text]-E method proved to yield some potential for improving the accuracy of pCT.

Purpose: Proton computed (transmission) tomography (pCT) refers to the process of imaging an object by letting protons pass through it, while measuring their energy after, and their position and (optionally) direction both before and after their traversal through that object. The so far experimental technique has potential to improve treatment planning of proton therapy by enabling the direct acquisition of a proton stopping power map of tissue, thus removing the need to obtain it by converting X-ray CT attenuation data and thereby eliminating uncertainties which arise in the mentioned conversion process. The image reconstruction in pCT requires accurate estimates of the proton trajectories. In experimental pCT detector setups where the direction of the protons is not measured, the air gap between the detector planes and the imaged object worsens the spatial resolution of the image obtained. In this work we determined the mean proton paths and the corresponding spatial uncertainty, taking into account the presence of the air gap. Methods: We used Monte Carlo simulations of radiation transport to systematically investigate the effect of the air gap size between detector and patient on the spatial resolution of proton (ion) computed tomography for protons with an energy of 200 MeV and 250 MeV as well as for helium ions (He-4) with an energy of 798 MeV. For the simulations we used TOPAS which itself is based on Geant4. Results: For all particles, which are detected at the same entrance and exit coordinate, the average ion path and the corresponding standard deviation was computed. From this information, the dependence of the spatial resolution on the air gap size and the angular confusion of the particle beam was inferred. Conclusion: The presence of the airgap does not pose a problem for perfect fan beams. In realistic scenarios, where the initial angular confusion is around 5 mrad and for typical air gap sizes up to 10 cm, using an energy of 200 MeV a spatial resolution of about 1.6 mm can be achieved. Using protons with E = 250 MeV a spatial resolution of about 1.1 mm and using helium ions (He-4) with E = 798 MeV even a spatial resolution below 0.7 mm respectively is attainable.

Proton computed tomography (pCT) is a promising tomographic imaging modality allowing direct reconstruction of proton relative stopping power (RSP) required for proton therapy dose calculation. In this review article, we aim at highlighting the role of Monte Carlo (MC) simulation in pCT studies. After describing the requirements for performing proton computed tomography and the various pCT scanners actively used in recent research projects, we present an overview of available MC simulation platforms. The use of MC simulations in the scope of investigations of image reconstruction, and for the evaluation of optimal RSP accuracy, precision and spatial resolution omitting detector effects is then described. In the final sections of the review article, we present specific applications of realistic MC simulations of an existing pCT scanner prototype, which we describe in detail.

PurposeProton computed tomography (pCT) is a promising imaging technique to substitute or at least complement x-ray CT for more accurate proton therapy treatment planning as it allows calculating directly proton relative stopping power from proton energy loss measurements. A proton CT scanner with a silicon-based particle tracking system and a five-stage scintillating energy detector has been completed. In parallel a modular software platform was developed to characterize the performance of the proposed pCT.MethodThe modular pCT software platform consists of (1) a Geant4-based simulation modeling the Loma Linda proton therapy beam line and the prototype proton CT scanner, (2) water equivalent path length (WEPL) calibration of the scintillating energy detector, and (3) image reconstruction algorithm for the reconstruction of the relative stopping power (RSP) of the scanned object. In this work, each component of the modular pCT software platform is described and validated with respect to experimental data and benchmarked against theoretical predictions. In particular, the RSP reconstruction was validated with both experimental scans, water column measurements, and theoretical calculations.ResultsThe results show that the pCT software platform accurately reproduces the performance of the existing prototype pCT scanner with a RSP agreement between experimental and simulated values to better than 1.5%.ConclusionsThe validated platform is a versatile tool for clinical proton CT performance and application studies in a virtual setting. The platform is flexible and can be modified to simulate not yet existing versions of pCT scanners and higher proton energies than those currently clinically available.

Purpose: To present a proton computed tomography (pCT) reconstruction approach that models the integral depth dose (IDD) of the clinical scanning proton beam into beamlets. Using a multilayer ionization chamber (MLIC) as the imager, the proposed pCT system and the reconstruction approach can minimize extra ambient neutron dose and simplify the beamline design by eliminating an additional collimator to confine the proton beam. Methods: Monte Carlo simulation was applied to digitally simulate the IDDs of the exiting proton beams detected by the MLIC. A forward model was developed to model each IDD into a weighted sum of percentage depth doses of the constituent beamlets separated laterally by 1 mm. The water equivalent path lengths (WEPLs) of the beamlets were determined by iteratively minimizing the squared L2‐norm between the forward projected and simulated IDDs. The final WEPL values were reconstructed to pCT images, that is, proton stopping power ratio (SPR) maps, through simultaneous algebraic reconstruction technique with total variation regularization. The reconstruction process was tested with a digital cylindrical water‐based phantom and an ICRP adult reference computational phantom. The mean of SPR within regions of interest (ROIs) and the WEPL along a 4 mm‐wide beam (WEPL4mm${\rm{WEP}}{{\rm{L}}_{4{\rm{mm}}}}$) were compared with the reference values. The spatial resolution was analyzed at the edge of a cortical insert of the cylindrical phantom. Results: The percentage deviations from reference SPR were within ±1% in all selected ROIs. The mean absolute error of the reconstructed SPR was 0.33%, 0.19%, and 0.27% for the cylindrical phantom, the adult phantom at the head and lung region, respectively. The corresponding percentage deviations from reference WEPL4mm${\rm{WEP}}{{\rm{L}}_{4{\rm{mm}}}}$ were 0.48 ± 0.64%, 0.28 ± 0.48%, and 0.22 ± 0.49%. The full width at half maximum of the line spread function (LSF) derived from the radial edge spread function (ESF) of a cortical insert was 0.13 cm. The frequency at 10% of the modulation transfer function (MTF) was 6.38 cm–1. The mean signal‐to‐noise ratio (SNR) of all the inserts was 2.45. The mean imaging dose was 0.29 and 0.25 cGy at the head and lung region of the adult phantom, respectively. Conclusion: A new pCT reconstruction approach was developed by modeling the IDDs of the uncollimated scanning proton beams in the pencil beam geometry. SPR accuracy within ±1%, spatial resolution of better than 2 mm at 10% MTF, and imaging dose at the magnitude of mGy were achieved. Potential side effects caused by neutron dose were eliminated by removing the extra beam collimator. [ABSTRACT FROM AUTHOR]

Proton CT (pCT) is a promising new imaging technique that can reconstruct relative stopping power (RSP) more accurately than x-ray CT in each cubic millimeter voxel of the patient. This, in turn, will result in better proton range accuracy and, therefore, smaller planned tumor volumes (PTV). The hardware description and some reconstructed images have previously been reported. In a series of two contributions, we focus on presenting the software algorithms that convert pCT detector data to the final reconstructed pCT images for application in proton treatment planning. There were several options on how to accomplish this, and we will describe our solutions at each stage of the data processing chain. In the first paper of this series, we present the data acquisition with the pCT tracking and energy-range detectors and how the data are preprocessed, including the conversion to the well-formatted track information from tracking data and water-equivalent path length from the data of a calibrated multi-stage energy-range detector. These preprocessed data are then used for the initial image formation with an FDK cone-beam CT algorithm. The output of data acquisition, preprocessing, and FDK reconstruction is presented along with illustrative imaging results for two phantoms, including a pediatric head phantom. The second paper in this series will demonstrate the use of iterative solvers in conjunction with the superiorization methodology to further improve the images resulting from the upfront FDK image reconstruction and the implementation of these algorithms on a hybrid CPU/GPU computer cluster.

Radiation therapy with protons and heavier ions is an attractive form of cancer treatment that could enhance local control and survival of cancers that are currently difficult to cure and lead to less side effects due to sparing of normal tissues. However, particle therapy faces a significant technical challenge because one cannot accurately predict the particle range in the patient using data provided by existing imaging technologies. Proton computed tomography (pCT) is an emerging imaging modality capable of improving the accuracy of range prediction. In this paper, we describe the successive pCT scanners designed and built by our group with the goal to support particle therapy treatment planning and image guidance by reconstructing an accurate 3D map of the stopping power relative to water in patient tissues. The pCT scanners we have built to date consist of silicon telescopes, which track the proton before and after the object to be reconstructed, and an energy or range detector, which measures the residual energy and/or range of the protons used to evaluate the water equivalent path length (WEPL) of each proton in the object. An overview of a decade-long evolution of the conceptual design of pCT scanners and their calibration is given. Results of scanner performance tests are presented, which demonstrate that the latest pCT scanner approaches readiness for clinical applications in hadron therapy.

PurposeProton computed tomography (pCT) will enable accurate prediction of proton and ion range in a patient while providing the benefit of lower radiation exposure than in x-ray CT. The accuracy of the range prediction is essential for treatment planning in proton or ion therapy and depends upon the detector used to evaluate the water-equivalent path length (WEPL) of a proton passing through the object. A novel approach is presented for an inexpensive WEPL detector for pCT and proton radiography.MethodsA novel multistage detector with an aperture of 10 × 37.5 cm was designed to optimize the accuracy of the WEPL measurements while simplifying detector construction and the performance requirements of its components. The design of the five-stage detector was optimized through simulations based on the geant4 detector simulation toolkit, and the fabricated prototype was calibrated in water-equivalent millimeters with 200 MeV protons in the research beam line of the clinical proton synchrotron at Loma Linda University Medical Center. A special polystyrene step phantom was designed and built to speed up and simplify the calibration procedure. The calibrated five-stage detector was tested in the 200 MeV proton beam as part of the pCT head scanner, using a water phantom and polystyrene slabs to verify the WEPL reconstruction accuracy.ResultsThe beam-test results demonstrated excellent performance of the new detector, in good agreement with the simulation results. The WEPL measurement accuracy is about 3.0 mm per proton in the 0-260 mm WEPL range required for a pCT head scan with a 200 MeV proton beam.ConclusionsThe new multistage design approach to WEPL measurements for proton CT and radiography has been prototyped and tested. The test results show that the design is competitive with much more expensive calorimeter and range-counter designs.

Proton computed tomography (pCT) is a promising tomographic imaging modality allowing direct reconstruction of proton relative stopping power (RSP) required for proton therapy dose calculation. In this review article, we aim at highlighting the role of Monte Carlo (MC) simulation in pCT studies. After describing the requirements for performing proton computed tomography and the various pCT scanners actively used in recent research projects, we present an overview of available MC simulation platforms. The use of MC simulations in the scope of investigations of image reconstruction, and for the evaluation of optimal RSP accuracy, precision and spatial resolution omitting detector effects is then described. In the final sections of the review article, we present specific applications of realistic MC simulations of an existing pCT scanner prototype, which we describe in detail. [ABSTRACT FROM AUTHOR]

Proton computed (transmission) tomography (pCT) refers to the process of imaging an object by letting protons pass through it, while measuring their energy after, and their position and (optionally) direction both before and after their traversal through that object. The so far experimental technique has potential to improve treatment planning of proton therapy by enabling the direct acquisition of a proton stopping power map of tissue, thus removing the need to obtain it by converting X-ray CT attenuation data and thereby eliminating uncertainties which arise in the mentioned conversion process. The image reconstruction in pCT requires accurate estimates of the proton trajectories. In experimental pCT detector setups where the direction of the protons is not measured, the air gap between the detector planes and the imaged object worsens the spatial resolution of the image obtained. In this work we determined the mean proton paths and the corresponding spatial uncertainty, taking into account the presence of the air gap. We used Monte Carlo simulations of radiation transport to systematically investigate the effect of the air gap size between detector and patient on the spatial resolution of proton (ion) computed tomography for protons with an energy of 200 MeV and 250 MeV as well as for helium ions (He-4) with an energy of 798 MeV. For the simulations we used TOPAS which itself is based on Geant4. For all particles, which are detected at the same entrance and exit coordinate, the average ion path and the corresponding standard deviation was computed. From this information, the dependence of the spatial resolution on the air gap size and the angular confusion of the particle beam was inferred. The presence of the airgap does not pose a problem for perfect fan beams. In realistic scenarios, where the initial angular confusion is around 5 mrad and for typical air gap sizes up to 10 cm, using an energy of 200 MeV a spatial resolution of about 1.6 mm can be achieved. Using protons with E = 250 MeV a spatial resolution of about 1.1 mm and using helium ions (He-4) with E = 798 MeV even a spatial resolution below 0.7 mm respectively is attainable. [ABSTRACT FROM AUTHOR]

• PIXE tomography distributions of element content are obtained for thick samples. • Corrections for X-ray attenuation are modeled in the reconstruction code. • The accuracy of the reconstructed tomographic images is evaluated using Geant4. • A good agreement is obtained (accuracy ≤4% for phosphorus). • Geant4 provides data that cannot be obtained experimentally. Proton computed microtomography is a technique that reveals the inner content of microscopic samples. The density distribution of the material (in g·cm−3) is obtained from proton transmission tomography (STIM: Scanning Transmission Ion Microscopy) and the element content from X-ray emission tomography (PIXE: Particle Induced X-ray Emission). A precise quantification of chemical elements is difficult for thick samples, because of the variations of X-ray production cross-sections and of X-ray absorption. Both phenomena are at the origin of an attenuation of the measured X-ray spectra, which leads to an underestimation of the element content. Our aim is to quantify the accuracy of a specific correction method that we designed for thick samples. In this study, we describe how the 3D variations in the mass density were taken into account in the reconstruction code, in order to quantify the correction according to the position of the proton beam and the position and aperture angle of the X-ray detector. Moreover, we assess the accuracy of the reconstructed densities using Geant4 simulations on numerical phantoms, used as references. The correction process was successfully applied and led, for the largest regions of interest (little affected by partial volume effects), to an accuracy ≤ 4% for phosphorus (compared to about 40% discrepancy without correction). This study demonstrates the accuracy of the correction method implemented in the tomographic reconstruction code for thick samples. It also points out some advantages offered by Geant4 simulations: i) they produce projection data that are totally independent of the inversion method used for the image reconstruction; ii) one or more physical processes (X-ray absorption, proton energy loss) can be artificially turned off, in order to precisely quantify the effect of the different phenomena involved in the attenuation of X-ray spectra. [ABSTRACT FROM AUTHOR]

Purpose: Currently, calculations of proton range in proton therapy patients are based on a conversion of CT Hounsfield units of patient tissues into proton relative stopping power. Uncertainties in this conversion necessitate larger proximal and distal planned target volume margins. Proton CT can potentially reduce these uncertainties by directly measuring proton stopping power. We aim to demonstrate proton CT imaging with complex porcine samples, to analyze in detail three‐dimensional regions of interest, and to compare proton stopping powers directly measured by proton CT to those determined from x‐ray CT scans. Methods: We have used a prototype proton imaging system with single proton tracking to acquire proton radiography and proton CT images of a sample of porcine pectoral girdle and ribs, and a pig's head. We also acquired close in time x‐ray CT scans of the same samples and compared proton stopping power measurements from the two modalities. In the case of the pig's head, we obtained x‐ray CT scans from two different scanners and compared results from high‐dose and low‐dose settings. Results: Comparing our reconstructed proton CT images with images derived from x‐ray CT scans, we find agreement within 1% to 2% for soft tissues and discrepancies of up to 6% for compact bone. We also observed large discrepancies, up to 40%, for cavitated regions with mixed content of air, soft tissue, and bone, such as sinus cavities or tympanic bullae. Conclusions: Our images and findings from a clinically realistic proton CT scanner demonstrate the potential for proton CT to be used for low‐dose treatment planning with reduced margins. [ABSTRACT FROM AUTHOR]

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

• Single particle tracking proton CT accuracy can be degraded by image artifacts. • An empirical method was used to reduced artifacts in scans with a preclinical scanner. • The mean average percentage error was reduced by 47% and was below 0.48%. Purpose: To reduce image artifacts of proton computed tomography (pCT) from a preclinical scanner, for imaging of the relative stopping power (RSP) needed for particle therapy treatment planning using a simple empirical artifact correction method. Methods: We adapted and employed a correction method previously used for beam-hardening correction in x-ray CT which makes use of a single scan of a custom-built homogeneous phantom with known RSP. Exploiting the linearity of the filtered backprojection operation, a function was found which corrects water-equivalent path lengths (RSP line integrals) in experimental scans using a prototype pCT scanner. The correction function was applied to projection values of subsequent scans of a homogeneous water phantom, a sensitometric phantom with various inserts and an anthropomorphic head phantom. Data were acquired at two different incident proton energies to test the robustness of the method. Results: Inaccuracies in the detection process caused an offset and known ring artifacts in the water phantom which were considerably reduced using the proposed method. The mean absolute percentage error (MAPE) of mean RSP values of all inserts of the sensitometric phantom and the water phantom was reduced from 0.87% to 0.44% and from 0.86% to 0.48% for the two incident energies respectively. In the head phantom a clear reduction of artifacts was observed. Conclusions: Image artifacts of experimental pCT scans with a prototype scanner could substantially be reduced both in homogeneous, heterogeneous and anthropomorphic phantoms. RSP accuracy was also improved. [ABSTRACT FROM AUTHOR]

• First application of the GPU-based framework TIGRE to proton CT image reconstruction. • Geant4 simulations were used to generate reconstruction input data. • A straight-line approximation allowed reconstruction within seconds. • Tomographic images of two Catphan modules were analyzed. • An image resolution of three line pairs per cm was achieved. In proton therapy, the knowledge of the proton stopping power, i.e. the energy deposition per unit length within human tissue, is essential for accurate treatment planning. One suitable method to directly measure the stopping power is proton computed tomography (pCT). Due to the proton interaction mechanisms in matter, pCT image reconstruction faces some challenges: the unique path of each proton has to be considered separately in the reconstruction process adding complexity to the reconstruction problem. This study shows that the GPU-based open-source software toolkit TIGRE, which was initially intended for X-ray CT reconstruction, can be applied to the pCT image reconstruction problem using a straight line approach for the proton path. This simplified approach allows for reconstructions within seconds. To validate the applicability of TIGRE to pCT, several Monte Carlo simulations modeling a pCT setup with two Catphan® modules as phantoms were performed. Ordered-Subset Simultaneous Algebraic Reconstruction Technique (OS-SART) and Adaptive-Steepest-Descent Projection Onto Convex Sets (ASD-POCS) were used for image reconstruction. Since the accuracy of the approach is limited by the straight line approximation of the proton path, requirements for further improvement of TIGRE for pCT are addressed. [ABSTRACT FROM AUTHOR]

• Image artifacts limit the performance of a prototype pCT scanner. • Using energy-modulated proton CT (EMpCT) avoids critical regions of the energy detector. • Image quality is improved by EMpCT. To reduce imaging artifacts and improve image quality of a specific proton computed tomography (pCT) prototype scanner by combining pCT data acquired at two different incident proton energies to avoid protons stopping in sub-optimal detector sections. Image artifacts of a prototype pCT scanner are linked to protons stopping close to internal structures of the scanner's multi-stage energy detector. We aimed at avoiding such protons by acquiring pCT data at two different incident energies and combining the data in post-processing from which artifact-reduced images of the relative stopping power (RSP) were calculated. Energy-modulated pCT (EMpCT) images were assessed visually and quantitatively and compared to the original mono-energetic images in terms of RSP accuracy and noise. Data were acquired for a homogeneous water phantom. RSP images reconstructed from the mono-energetic datasets displayed local image artifacts which were ring-shaped due to the homogeneity of the phantom. The merged EMpCT dataset achieved a superior visual image quality with reduced artifacts and only minor remaining rings. The inter-quartile range (25/75) of RSP values was reduced from 0.7 % with the current standard acquisition to 0.2 % with EMpCT due to the reduction of ring artifacts. In this study, dose was doubled compared to a standard scan, but we discuss strategies to reduce excess dose. EMpCT allows to effectively avoid regions of the energy detector that cause image artifacts. Thereby, image quality is improved. [ABSTRACT FROM AUTHOR]

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

The iMPACT project aims at building a novel pCT scanner for protons of medical energies in the range between 200 and 300 MeV, a proton tracking system that provides accurate information to create a map of the tissue density of human organs. Such information is crucial for an accurate aiming of proton-therapy beams and is currently provided by X-rays CT scans, with an accuracy lower than the one which could be achieved by using protons. One of its core elements is a high-granularity scintillator-based range calorimeter, designed to measure the proton residual energy after it travels the patient's body. Here we review the design features of the iMPACT calorimeter, together with an all-around qualification of prototypes of its core components through test-bench measurements and proton beam data. We focus, in particular, on the qualification of the calorimeter elements towards a large-scale prototype, and a calibration study which will eventually allow to operate such a high granularity calorimeter with a fully digital readout at the target proton rate. [ABSTRACT FROM AUTHOR]

• A pixel-based range telescope is a good candidate for proton computed tomography. • The detector design must be optimized for proton track reconstruction. • A design with 3.5 mm Al absorbers between the sensor layers is recommended. • Simulations show that over ten million protons per second can be reconstructed. A pixel-based range telescope for tracking particles during proton imaging is described. The detector applies a 3D matrix of stacked Monolithic Active Pixel Sensors with fast readout speeds. This study evaluates different design alternatives of the range telescope on basis of the protons' range accuracy and the track reconstruction efficiency. Detector designs with different thicknesses of the energy-absorbing plates between each sensor layer are simulated using the GATE/Geant4 Monte Carlo software. Proton tracks traversing the detector layers are individually reconstructed, and a Bragg curve fitting procedure is applied for the calculation of each proton's range. Simulations show that the setups with 4 mm and thinner absorber layers of aluminum have a low range uncertainty compared to the physical range straggling, systematic errors below 0.3 mm water equivalent thickness and a track reconstruction capability exceeding ten million protons per second. In order to restrict the total number of layers and to yield the required tracking and range resolution properties, a design recommendation is reached where the proposed range telescope applies 3.5 mm thick aluminum absorber slabs between each sensor layer. [ABSTRACT FROM AUTHOR]

In recent years the use of hadrons for cancer radiation treatment has grown in importance, and many facilities are currently operational or under construction worldwide. To fully exploit the therapeutic advantages offered by hadron therapy, precise body imaging for accurate beam delivery is decisive. While traditional X-ray Computed Tomography (xCT) fails in providing 3D images with the precision required for hadrons treatment guidance, Proton Computer Tomography (pCT) scanners, currently in their R&D phase, can. A pCT scanner consists of a tracker system, to track protons, and of a calorimeter, to measure their residual energy. In this paper we will present the iMPACT project, which foresees a novel proton tracking detector with higher scanning speed, better spatial resolution and lower material budget with respect to present state-of-the-art detectors, leading to enhanced performances. The tracker will be matched to a fast, highly segmented proton range calorimeter. [ABSTRACT FROM AUTHOR]

Purpose: Radiography and tomography using proton beams promise benefit to image guidance and treatment planning for proton therapy. A novel proton tracking detector is described and experimental demonstrations at a therapy facility are reported. A new type of proton CT reconstructing relative "scattering power" rather than "stopping power" is also demonstrated. Notably, this new type of imaging does not require the measurement of the residual energies of the protons. Methods: A large area, silicon microstrip tracker with high spatial and temporal resolution has been developed by the Proton Radiotherapy Verification and Dosimetry Applications consortium and commissioned using beams of protons at iThemba LABS, Medical Radiation Department, South Africa. The tracker comprises twelve planes of silicon developed using technology from high energy physics with each plane having an active area of ~10×10 cm segmented into 2048 microstrips. The tracker is organized into four separate units each containing three detectors at 60? to one another creating an x-u-v coordinate system. Pairs of tracking units are used to reconstruct vertices for protons Methods: A large area, silicon microstrip tracker with high spatial and temporal resolution has been developed by the Proton Radiotherapy Verification and Dosimetry Applications consortium and commissioned using beams of protons at iThemba LABS, Medical Radiation Department, South Africa. The tracker comprises twelve planes of silicon developed using technology from high energy physics with each plane having an active area of ~10×10 cm segmented into 2048 microstrips. The tracker is organized into four separate units each containing three detectors at 60? to one another creating an x-u-v coordinate system. Pairs of tracking units are used to reconstruct vertices for protons. Results: Experimental results are reported for tracking the path of protons with initial energies of 125 and 191 MeV. A spherical phantom of 75 mm diameter was imaged by positioning it between the entrance and exit detectors of the tracker. Positions and directions of individual protons were used to create angular distributions and 2D fluence maps of the beam. These results were acquired for 36 equally spaced projections spanning 180?, allowing, for the first time, an experimental CT image based upon the relative scattering power of protons to be reconstructed. Conclusions: Successful tracking of protons through a thick target (phantom) has demonstrated that the tracker discussed in this paper can provide the precise directional information needed to perform proton radiography and tomography. When synchronized with a range telescope, this could enable the reconstruction of proton CT images of stopping power. Furthermore, by measuring the deflection of many protons through a phantom, it was demonstrated that it is possible to reconstruct a new kind of CT image (scattering power) based upon this tracking information alone. [ABSTRACT FROM AUTHOR]

Purpose: Proton radiography (PR) and proton computed tomography (PCT) can be used to measure proton stopping power directly. However, practical and cost effective proton imaging detectors are not widely available. In this study, the authors investigated the feasibility of proton imaging using a silicon diode array. Methods: A one-dimensional silicon diode detector array (1DSDA) was aligned with the central axis (CAX) of the proton beam. Polymethyl methacrylate (PMMA) slabs were used to find the correspondence between the water equivalent thickness (WET) and 1DSDA channel number. Two-dimensional proton radiographs were obtained by translation and rotation of a phantom relative to CAX while the proton nozzle and 1DSDA were kept stationary. A PCT image of one slice of the phantom was reconstructed using filtered backprojection. Results: PR and PCT images of the PMMA cube were successfully acquired using the 1DSDA. The WET of the phantom was measured using PR data. The resolution and maximum error in WET measurement are 2.0 and 1.5 mm, respectively. Structures down to 2.0 mm in size could be resolved completely. Reconstruction of a PCT image showed very good agreement with simulation. Limitations in spatial resolution are attributed to limited spatial sampling, beam collimation, and proton scatter. Conclusions: The results demonstrate the feasibility of using silicon diode arrays for proton imaging. Such a device can potentially offer fast image acquisition and high spatial and energy resolution for PR and PCT. [ABSTRACT FROM AUTHOR]

For many years, silicon micro-strip detectors have been successfully used as tracking detectors for particle and nuclear physics experiments. A new application of this technology is to the field of particle therapy where radiotherapy is carried out by use of charged particles such as protons or carbon ions. Such a treatment has been shown to have advantages over standard x-ray radiotherapy and as a result of this, many new centres offering particle therapy are currently under construction around the world today. The Proton Radiotherapy, Verification and Dosimetry Applications (PRaVDA) consortium are developing instrumentation for particle therapy based upon technology from high-energy physics. The characteristics of a new silicon micro-strip tracker for particle therapy will be presented. The array uses specifically designed, large area sensors with technology choices that follow closely those taken for the ATLAS experiment at the HL-LHC. These detectors will be arranged into four units each with three layers in an x – u – v configuration to be suitable for fast proton tracking with minimal ambiguities. The sensors will form a tracker capable of tracing the path of ~200 MeV protons entering and exiting a patient allowing a new mode of imaging known as proton computed tomography ( p CT). This will aid the accurate delivery of treatment doses and in addition, the tracker will also be used to monitor the beam profile and total dose delivered during the high fluences used for treatment. We present here details of the design, construction and assembly of one of the four units that will make up the complete tracker along with its characterisation using radiation tests carried out using a 90 Sr source in the laboratory and a 60 MeV proton beam at the Clatterbridge Cancer Centre. [ABSTRACT FROM AUTHOR]

Radiation therapy with protons and heavier ions is an attractive form of cancer treatment that could enhance local control and survival of cancers that are currently difficult to cure and lead to less side effects due to sparing of normal tissues. However, particle therapy faces a significant technical challenge because one cannot accurately predict the particle range in the patient using data provided by existing imaging technologies. Proton computed tomography (pCT) is an emerging imaging modality capable of improving the accuracy of range prediction. In this paper, we describe the successive pCT scanners designed and built by our group with the goal to support particle therapy treatment planning and image guidance by reconstructing an accurate 3D map of the stopping power relative to water in patient tissues. The pCT scanners we have built to date consist of silicon telescopes, which track the proton before and after the object to be reconstructed, and an energy or range detector, which measures the residual energy and/or range of the protons used to evaluate the water equivalent path length (WEPL) of each proton in the object. An overview of a decade-long evolution of the conceptual design of pCT scanners and their calibration is given. Results of scanner performance tests are presented, which demonstrate that the latest pCT scanner approaches readiness for clinical applications in hadron therapy. [ABSTRACT FROM AUTHOR]