Impact of glioma peritumoral edema, tumor size, and tumor location on alternating electric fields (AEF) therapy in realistic 3D rat glioma models: a computational study.

Objective.Alternating electric fields (AEF) therapy is a treatment modality for patients with glioblastoma. Tumor characteristics such as size, location, and extent of peritumoral edema may affect the AEF strength and distribution. We evaluated the sensitivity of the AEFs in a realistic 3D rat glioma model with respect to these properties.Approach.The electric properties of the peritumoral edema were varied based on calculated and literature-reported values. Models with different tumor composition, size, and location were created. The resulting AEFs were evaluated in 3D rat glioma models.Main results.In all cases, a pair of 5 mm diameter electrodes induced an average field strength >1 V cm-1. The simulation results showed that a negative relationship between edema conductivity and field strength was found. As the tumor core size was increased, the average field strength increased while the fraction of the shell achieving >1.5 V cm-1decreased. Increasing peritumoral edema thickness decreased the shell's mean field strength. Compared to rostrally/caudally, shifting the tumor location laterally/medially and ventrally (with respect to the electrodes) caused higher deviation in field strength.Significance.This study identifies tumor properties that are key drivers influencing AEF strength and distribution. The findings might be potential preclinical implications.

Electric field distributions in realistic 3D rat head models during alternating electric field (AEF) therapy: a computational study.

Objective.Application of alternating electrical fields (AEFs) in the kHz range is an established treatment modality for primary and recurrent glioblastoma. Preclinical studies would enable innovations in treatment monitoring and efficacy, which could then be translated to benefit patients. We present a practical translational process converting image-based data into 3D rat head models for AEF simulations and study its sensitivity to parameter choices.Approach.Five rat head models composed of up to 7 different tissue types were created, and relative permittivity and conductivity of individual tissues obtained from the literature were assigned. Finite element analysis was used to model the AEF strength and distribution in the models with different combinations of head tissues, a virtual tumor, and an electrode pair.Main results.The simulations allowed for a sensitivity analysis of the AEF distribution with respect to different tissue combinations and tissue parameter values.Significance.For a single pair of 5 mm diameter electrodes, an average AEF strength inside the tumor exceeded 1.5 V cm-1, expected to be sufficient for a relevant therapeutic outcome. This study illustrates a robust and flexible approach for simulating AEF in different tissue types, suitable for preclinical studies in rodents and translatable to clinical use.

A stopping criterion for iterative proton CT image reconstruction based on correlated noise properties.

BACKGROUND: Whereas filtered back projection algorithms for voxel-based CT image reconstruction have noise properties defined by the filter, iterative algorithms must stop at some point in their convergence and do not necessarily produce consistent noise properties for images with different degrees of heterogeneity. PURPOSE: A least-squares iterative algorithm for proton CT (pCT) image reconstruction converges toward a unique solution for relative stopping power (RSP) that optimally fits the protons. We present a stopping criterion that delivers solutions with the property that correlations of RSP noise between voxels are relatively low. This provides a method to produce pCT images with consistent noise properties useful for proton therapy treatment planning, which relies on summing RSP along lines of voxels. Consistent noise properties will also be useful for future studies of image quality using metrics such as contrast to noise ratio, and to compare RSP noise and dose of pCT with other modalities such as dual-energy CT. METHODS: With simulated and real images with varying heterogeneity from a prototype clinical proton imaging system, we calculate average RSP correlations between voxel pairs in uniform regions-of-interest versus distance between voxels. We define a parameter r, the remaining distance to the unique solution relative to estimated RSP noise, and our stopping criterion is based on r falling below a chosen value. RESULTS: We find large correlations between voxels for larger values of r, and anticorrelations for smaller values. For r in the range of 0.5-1, voxels are relatively uncorrelated, and compared to smaller values of r have lower noise with only slight loss of spatial resolution. CONCLUSIONS: Iterative algorithms not using a specific metric or rationale for stopping iterations may produce images with an unknown and arbitrary level of convergence or smoothing. We resolve this issue by stopping iterations of a least-squares iterative algorithm when r reaches the range of 0.5-1. This defines a pCT image reconstruction method with consistent statistical properties optimal for clinical use, including for treatment planning with pCT images.

Current status of the preclinical evaluation of alternating electric fields as a form of cancer therapy.

Exposing cancer cells to alternating electric fields of 100-300 kHz frequency and 1-4 V/cm strength has been shown to significantly reduce cancer growth in cell culture and in human patients. This form of anti-cancer therapy is more commonly referred to as tumor treating fields (TTFields), a novel treatment modality that has been approved by the U.S. Food and Drug Administration for use in patients with glioblastoma and malignant pleural mesothelioma. Pivotal trials in other solid organ cancer trials are underway. In regards to overall survival, TTFields alone is comparable to chemotherapy alone in recurrent glioblastoma. However, when combined with adjuvant chemotherapy, TTFields prolong median survival by 4.9 months in newly-diagnosed glioblastoma. TTFields hold promise as a therapeutic approach to numerous solid organ cancers. This review summarizes the current status of TTFields research at the preclinical level, highlighting recent aspects of a relatively complex working hypothesis. In addition, we point out the gaps between limited preclinical in vivo studies and the available clinical data. To date, no customized system for TTFields delivery in rodent models of glioblastoma has been presented. We aim to motivate the expansion of TTFields preclinical research and facilitate the availability of suitable hardware, to ultimately improve outcomes in patients with cancer.

Comparative accuracy and resolution assessment of two prototype proton computed tomography scanners.

BACKGROUND: Improving the accuracy of relative stopping power (RSP) in proton therapy may allow reducing range margins. Proton computed tomography (pCT) has been shown to provide state-of-the-art RSP accuracy estimation, and various scanner prototypes have recently been built. The different approaches used in scanner design are expected to impact spatial resolution and RSP accuracy. PURPOSE: The goal of this study was to perform the first direct comparison, in terms of spatial resolution and RSP accuracy, of two pCT prototype scanners installed at the same facility and by using the same image reconstruction algorithm. METHODS: A phantom containing cylindrical inserts of known RSP was scanned at the phase-II pCT prototype of the U.S. pCT collaboration and at the commercially oriented ProtonVDA scanner. Following distance-driven binning filtered backprojection reconstruction, the radial edge spread function of high-density inserts was used to estimate the spatial resolution. RSP accuracy was evaluated by the mean absolute percent error (MAPE) over the inserts. No direct imaging dose estimation was possible, which prevented a comparison of the two scanners in terms of RSP noise. RESULTS: In terms of RSP accuracy, both scanners achieved the same MAPE of 0.72% when excluding the porous sinus insert from the evaluation. The ProtonVDA scanner reached a better overall MAPE when all inserts and the body of the phantom were accounted for (0.81%), compared to the phase-II scanner (1.14%). The spatial resolution with the phase-II scanner was found to be 0.61 lp/mm, while for the ProtonVDA scanner somewhat lower at 0.46 lp/mm. CONCLUSIONS: The comparison between two prototype pCT scanners operated in the same clinical facility showed that they both fulfill the requirement of an RSP accuracy of about 1%. Their spatial resolution performance reflects the different design choices of either a scanner with full tracking capabilities (phase-II) or of a more compact tracker system, which only provides the positions of protons but not their directions (ProtonVDA).

A dose-volume constraint (DVC) projection-based algorithm for IMPT inverse planning optimization.

PURPOSE: Provide a projection-based algorithm to solve the class of optimization problems encountered in intensity modulated proton therapy (IMPT). The algorithm can handle percentage dose-volume constraints (DVCs) that are usually found in such problems. METHODS: To seek a feasible solution, the automatic relaxation method was used to project the spot weight vector onto the interval defined by lower and upper bound target dose constraints. The obtained solution was optimized separately based on the objective of each organ at risk (OAR) in addition to maximizing the minimum target dose using the bisection search method using a stopping criterion of 10 cGy. The combined weight was used in the CQ algorithm to solve the split feasibility problem but with a special projection technique due to the nonconvexity of DVCs. The algorithm was applied to four clinical IMPT cases (meningioma, prostate, tongue, and oropharynx) and compared to the corresponding treatment plans optimized in Eclipse. RESULTS: The treatment plans obtained, for the four cases, using the BCQ-ARM algorithm have dosimetric endpoints that are similar to their counterparts generated from Eclipse. The algorithm worked equally well with all cases, including the complex head and neck ones. The stopping criterion of 10 cGy results in making the generated plans slightly less optimal ( ε $\epsilon$ -optimal) rather than optimal, but with the advantage of the possibility of generating a database of plans. CONCLUSIONS: The application of the BCQ-ARM algorithm to different cases of IMPT plans with DVCs was demonstrated. The algorithm is successful in generating plans that are dosimetrically equivalent to their corresponding Eclipse plans. Thus, it is suitable to generate optimized treatment plans in a clinically reasonable time frame.

A comparison of proton stopping power measured with proton CT and x-ray CT in fresh postmortem porcine structures.

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.

An empirical artifact correction for proton computed tomography.

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.

Particle-Tracking Proton Computed Tomography-Data Acquisition, Preprocessing, and Preconditioning.

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.

Proof of concept image artifact reduction by energy-modulated proton computed tomography (EMpCT).

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: EMpCT allows to effectively avoid regions of the energy detector that cause image artifacts. Thereby, image quality is improved.

An Improved Method of Total Variation Superiorization Applied to Reconstruction in Proton Computed Tomography.

Previous work has shown that total variation superiorization (TVS) improves reconstructed image quality in proton computed tomography (pCT). The structure of the TVS algorithm has evolved since then and this paper investigated if this new algorithmic structure provides additional benefits to pCT image quality. Structural and parametric changes introduced to the original TVS algorithm included: (1) inclusion or exclusion of TV reduction requirement, (2) a variable number, N , of TV perturbation steps per feasibility-seeking iteration, and (3) introduction of a perturbation kernel . The structural change of excluding the TV reduction requirement check tended to have a beneficial effect for 3 ≤ N ≤ 6 and allows full parallelization of the TVS algorithm. Repeated perturbations per feasibility-seeking iterations reduced total variation (TV) and material dependent standard deviations for 3 ≤ N ≤ 6 . The perturbation kernel α , effectively equal to α = 0.5 in the original TVS algorithm, reduced TV and standard deviations as α was increased beyond α = 0.5 , but negatively impacted reconstructed relative stopping power (RSP) values for . The reductions in TV and standard deviations allowed feasibility-seeking with a larger relaxation parameter λ than previously used, without the corresponding increases in standard deviations experienced with the original TVS algorithm. This paper demonstrates that the modifications related to the evolution of the original TVS algorithm provide benefits in terms of both pCT image quality and computational efficiency for appropriately chosen parameter values.

Experimental comparison of proton CT and dual energy x-ray CT for relative stopping power estimation in proton therapy.

Proton computed tomography (pCT) has been proposed as an alternative to x-ray computed tomography (CT) for acquiring relative to water stopping power (RSP) maps used for proton treatment planning dose calculations. In parallel, it has been shown that dual energy x-ray CT (DECT) improves RSP accuracy when compared to conventional single energy x-ray CT. This study aimed at directly comparing the RSP accuracy of both modalities using phantoms scanned at an advanced prototype pCT scanner and a state-of-the-art DECT scanner. Two phantoms containing 13 tissue-mimicking inserts of known RSP were scanned at the pCT phase II prototype and a latest generation dual-source DECT scanner (Siemens SOMATOM Definition FORCE). RSP accuracy was compared by mean absolute percent error (MAPE) over all inserts. A highly realistic Monte Carlo (MC) simulation was used to gain insight on pCT image artifacts which degraded MAPE. MAPE was 0.55% for pCT and 0.67% for DECT. The realistic MC simulation agreed well with pCT measurements ([Formula: see text]). Both simulation and experimental results showed ring artifacts in pCT images which degraded the MAPE compared to an ideal pCT simulation ([Formula: see text]). Using the realistic simulation, we could identify sources of artifacts, which are attributed to the interfaces in the five-stage plastic scintillator energy detector and calibration curve interpolation regions. Secondary artifacts stemming from the proton tracker geometry were also identified. The pCT prototype scanner outperformed a state-of-the-art DECT scanner in terms of RSP accuracy (MAPE) for plastic tissue mimicking inserts. Since artifacts tended to concentrate in the inserts, their mitigation may lead to further improvements in the reported pCT accuracy.

Improving single-event proton CT by removing nuclear interaction events within the energy/range detector.

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.

Simultaneous optimization of RBE-weighted dose and nanometric ionization distributions in treatment planning with carbon ions.

Inverse treatment planning in intensity modulated particle therapy (IMPT) with scanned carbon-ion beams is currently based on the optimization of RBE-weighted dose to satisfy requirements of target coverage and limited toxicity to organs-at-risk (OARs) and healthy tissues. There are many feasible IMPT plans that meet these requirements, which allows the introduction of further criteria to narrow the selection of a biologically optimal treatment plan. We propose a novel treatment planning strategy based on the simultaneous optimization of RBE-weighted dose and nanometric ionization details (ID) as a new physical characteristic of the delivered plan beyond LET. In particular, we focus on the distribution of large ionization clusters (more than 3 ionizations) to enhance the biological effect across the target volume while minimizing biological effect in normal tissues. Carbon-ion treatment plans for different patient geometries and beam configurations generated with the simultaneous optimization strategy were compared against reference plans obtained with RBE-weighted dose optimization alone. Quality indicators, inhomogeneity index and planning volume histograms of RBE-weighted dose and large ionization clusters were used to evaluate the treatment plans. We show that with simultaneous optimization, ID distributions can be optimized in carbon-ion radiotherapy without compromising the RBE-weighted dose distributions. This strategy can potentially be used to account for optimization of endpoints closely related to radiation quality to achieve better tumor control and reduce risks of complications.

Robust Iterative Methods: Convergence and Applications to Proton Computed Tomography.

Robust methods, such as Tikhonov regularization and Bounded data uncertainty, have been used extensively in relatively small problems involving dense matrices for many decades, but have not been used in large-scale iterative methods for image reconstruction in particle imaging until recently. In this case, robust methods may allow more accurate reconstruction of images in the presence of errors of both the energy measurement of the protons and ions but also in the estimated path taken by the proton or ion through the object. Robust systems may also be used when entire blocks of data are missing, or in low-dose reconstructions using a very small number of particles without substantial loss of image quality. In this contribution, we demonstrate that robust methods show great promise in proton/ion (particle) computed tomography (pCT), and, for the first time, that they can be proven to converge. Thus, the convergence of robust methods as well as benefits for reconstruction in uncertain systems is shown to constitute the main advantage for pCT reconstruction.

Two-dimensional noise reconstruction in proton computed tomography using distance-driven filtered back-projection of simulated projections.

We present a formalism for two-dimensional (2D) noise reconstruction in proton computed tomography (pCT). This is necessary for the application of fluence modulated pCT (FMpCT) since it permits image noise prescription and the corresponding proton fuence optimization. We aimed at extending previously published formalisms to account for the impact of multiple Coulomb scattering (MCS) on projection noise, and the use of filtered back projection (FBP) reconstruction along curved paths with distance driven binning (DDB). 2D noise reconstruction for a beam of protons with parallel initial momentum vectors, and for projections binned both at the rear tracker and with DDB, was established. Monte Carlo (MC) simulations of pCT scans of a water cylinder were employed to generate pCT projections and to calculate their noise for use in 2D noise reconstruction. These were compared to results from an analytical model accounting for MCS for rear tracker binning as well as against the previously published central pixel model which ignores MCS. Image noise reconstructed with the formalism for rear tracker binning and DDB were compared to MC results using annular regions of interest (ROIs). Agreement better than 8% was obtained between the noise of projections calculated with MC simulation and our model. Noise from annular ROIs agreed with our noise reconstructions for rear tracker binning and DDB. The central pixel model ignoring MCS underestimated projection and thus image noise by up to 40% towards the object's edge. The use of DDB decreased the image noise towards the object's edge when compared to rear tracker binning and yielded more uniform noise throughout the image. MCS should not be neglected when predicting image noise for pixels away from the center of an object in a pCT scan due to the increasing influence of the gradient of the object's hull closer to the edges.

The impact of secondary fragments on the image quality of helium ion imaging.

Single-event ion imaging enables the direct reconstruction of the relative stopping power (RSP) information required for ion-beam therapy. Helium ions were recently hypothesized to be the optimal species for such technique. The purpose of this work is to investigate the effect of secondary fragments on the image quality of helium CT (HeCT) and to assess the performance of a prototype proton CT (pCT) scanner when operated with helium beams in Monte Carlo simulations and experiment. Experiments were conducted installing the U.S. pCT consortium prototype scanner at the Heidelberg Ion-Beam Therapy Center (HIT). Simulations were performed with the scanner using the TOPAS toolkit. HeCT images were reconstructed for a cylindrical water phantom, the CTP404 (sensitometry), and the CTP528 (line-pair) [Formula: see text] ® modules. To identify and remove individual events caused by fragmentation, the multistage energy detector of the scanner was adapted to function as a [Formula: see text] telescope. The use of the developed filter eliminated the otherwise arising ring artifacts in the HeCT reconstructed images. For the HeCT reconstructed images of a water phantom, the maximum RSP error was improved by almost a factor 8 with respect to unfiltered images in the simulation and a factor 10 in the experiment. Similarly, for the CTP404 module, the mean RSP accuracy improved by a factor 6 in both the simulation and the experiment when the filter was applied (mean relative error 0.40% in simulation, 0.45% in experiment). In the evaluation of the spatial resolution through the CTP528 module, the main effect of the filter was noise reduction. For both simulated and experimental images the spatial resolution was ∼4 lp cm-1. In conclusion, the novel filter developed for secondary fragments proved to be effective in improving the visual quality and RSP accuracy of the reconstructed images. With the filter, the pCT scanner is capable of accurate HeCT imaging.

Experimental fluence-modulated proton computed tomography by pencil beam scanning.

PURPOSE: This experimental study is aimed at demonstrating, using a simple cylindrical water phantom, the feasibility of fluence-modulated proton computed tomography (FMpCT) by pencil beam scanning (PBS) proton computed tomography (pCT). METHODS: The phase II pCT prototype of the Loma Linda U. and U. C. Santa Cruz was operated using the PBS beam line of the Northwestern Medicine Chicago Proton Center. A 20 × 10 grid of 1.37 cm full width half maximum pencil beams (PB) equally spaced by 1 cm was used to acquire 45 projections in step and shoot mode. The PB pattern's fluence was modified to allow FMpCT scans with fluence modulation factors (FMF) of 50% and 20%. A central FMpCT region of interest (FMpCT-ROI) was used to define a high image quality region. Reconstructed images were evaluated in terms of relative stopping power (RSP) accuracy and noise using annular ROIs. The FMpCT dose savings were estimated by Monte Carlo (MC) simulation of the pCT acquisitions using beam phase space distributions. PBS pCT results with homogeneous fluence were additionally compared to broad beam results in terms of RSP accuracy and noise. RESULTS: PBS pCT scans with acceptable pileup were possible, and images were comparable to previously acquired broad beam pCT images in terms of both noise and accuracy. In the FMpCT-ROI, the noise and accuracy from full fluence (FF) scans were preserved. Dose savings of up to 60% were achieved at the object's edge when using FMF of 20%. CONCLUSION: In this study, we have demonstrated that PBS pCT scans can achieve equivalent accuracy as those obtained from broad beams. The feasibility of FMpCT scans was demonstrated; image accuracy and noise were successfully preserved in the central FMpCT-ROI chosen for this study, and dose reduction of up to 60% at the object's edge was realized.

Helium CT: Monte Carlo simulation results for an ideal source and detector with comparison to proton CT.

PURPOSE: To evaluate the accuracy of relative stopping power and spatial resolution of images reconstructed with simulated helium CT (HeCT) in comparison to proton CT (pCT). METHODS: A Monte Carlo (MC) study with the TOPAS tool was performed to compare the accuracy of relative stopping power (RSP) reconstruction and spatial resolution of low-fluence HeCT to pCT, both using 200 MeV/u particles. An ideal setup consisting of a flat beam source and a totally absorbing energy-range detector was implemented to estimate the theoretically best achievable RSP accuracy for the calibration and reconstruction methods currently used for pCT. The phantoms imaged included a cylindrical water phantom with inserts of different materials, sizes, and positions, a Catphan phantom with a module containing high-contrast line pairs (CTP528) and a module with cylindrical inserts of different RSP (CTP404), as well as a voxelized 10-year-old female phantom. Dose to the cylindrical water phantom was also calculated. The RSP accuracy was studied for all phantoms except the CTP528 module. The latter was used for the estimation of the spatial resolution, evaluated as the modulation transfer function (MTF) at 10%. RESULTS: An overall error under 0.5% was achieved for HeCT for the water phantoms with the different inserts, in all cases better than that for pCT, in some cases by a factor 3. The inserts in the CTP404 module were reconstructed with an average RSP accuracy of 0.3% for HeCT and 0.2% for pCT. Anatomic structures (brain, bones, air cavities, etc.) in the digitized head phantom were well recognizable and no artifacts were visible with both HeCT and pCT. The three main tissue materials (soft tissue, brain, and cranium) were well identifiable in the reconstructed RSP-volume distribution with both imaging modalities. Using 360 projection angles, the spatial resolution was 4 lp/cm for HeCT and 3 lp/cm for pCT. Generally, spatial resolution increased with the number of projection angles and was always higher for HeCT than for pCT for the same number of projections. When HeCT and pCT scan were performed to deliver the same dose in the phantom, the resolution for HeCT was higher than pCT. CONCLUSION: MC simulations were used to compare HeCT and pCT image reconstruction. HeCT images had similar or better RSP accuracy and higher spatial resolution compared to pCT. Further investigation of the potential of helium ion imaging is warranted.

Software platform for simulation of a prototype proton CT scanner.

PURPOSE: Proton 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. METHOD: The 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. RESULTS: The 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%. CONCLUSIONS: The 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.