Tiny changes in tomographic system matrices can cause large changes in reconstruction quality.

This paper studies the impact of tiny changes in region-of-interest (ROI) tomography system matrices on the variance of the reconstructed ROI. In small-scale and medium-scale examples, the variance in the reconstructed ROI was estimated for different system matrices. The results revealed a striking and counterintuitive phenomenon: a tiny change in the system matrix can dramatically affect the variance of the ROI estimate. In one of our examples, a decrease of 0.1% in one element out of hundreds of thousands of the system matrix resulted in a systematic reduction of the variance inside the ROI, and by a factor of 5 to 10 for some pixels. Our results agree with a recently proven theorem about the ability of additional measurements to reduce the variance in ROI tomography.

Evaluation of the impact of a scanner prototype on proton CT and helium CT image quality and dose efficiency with Monte Carlo simulation.

Objective.The use of ion computed tomography (CT) promises to yield improved relative stopping power (RSP) estimation as input to particle therapy treatment planning. Recently, proton CT (pCT) has been shown to yield RSP accuracy on par with state-of-the-art x-ray dual energy CT. There are however concerns that the lower spatial resolution of pCT compared to x-ray CT may limit its potential, which has spurred interest in the use of helium ion CT (HeCT). The goal of this study was to investigate image quality of pCT and HeCT in terms of noise, spatial resolution, RSP accuracy and imaging dose using a detailed Monte Carlo (MC) model of an existing ion CT prototype.Approach.Three phantoms were used in simulated pCT and HeCT scans allowing estimation of noise, spatial resolution and the scoring of dose. An additional phantom was used to evaluate RSP accuracy. The imaging dose required to achieve the same image noise in a water and a head phantom was estimated at both native spatial resolution, and in a scenario where the HeCT spatial resolution was reduced and matched to that of pCT using Hann windowing of the reconstruction filter. A variance reconstruction formalism was adapted to account for Hann windowing.Main results.We confirmed that the scanner prototype would produce higher spatial resolution for HeCT than pCT by a factor 1.8 (0.86 lp mm-1versus 0.48 lp mm-1at the center of a 20 cm water phantom). At native resolution, HeCT required a factor 2.9 more dose than pCT to achieve the same noise, while at matched resolution, HeCT required only 38% of the pCT dose. Finally, RSP mean absolute percent error (MAPE) was found to be 0.59% for pCT and 0.67% for HeCT.Significance.This work compared the imaging performance of pCT and HeCT when using an existing scanner prototype, with the spatial resolution advantage of HeCT coming at the cost of increased dose. When matching spatial resolution via Hann windowing, HeCT had a substantial dose advantage. Both modalities provided state-of-the-art RSP MAPE. HeCT might therefore help reduce the dose exposure of patients with comparable image noise to pCT, enhanced spatial resolution and acceptable RSP accuracy at the same time.

Scattering proton CT.

Proton computed tomography (CT) is an imaging modality investigated mainly in the context of proton therapy as a complement to x-ray CT. It uses protons with high enough energy to fully traverse the imaged object. Common prototype systems measure each proton's position and direction upstream and downstream of the object as well as the energy loss which can be converted into the water equivalent thickness. A reconstruction algorithm then produces a map of the relative stopping power in the object. As an alternative to energy-loss proton CT, it has been proposed to reconstruct a map of the object's scattering power based on the protons' angular dispersion which can be estimated from the measured directions. As in energy-loss proton CT, reconstruction should best be performed considering the non-linear shape of proton trajectories due to multiple Coulomb scattering (MCS), but no algorithm to achieve this is so far available in the literature. In this work, we propose a filtered backprojection algorithm with distance-driven binning to account for the protons' most likely path. Furthermore, we present a systematic study of scattering proton CT in terms of inherent noise and spatial resolution and study the artefacts which arise from the physics of MCS. Our analysis is partly based on analytical models and partly on Monte Carlo simulations. Our results show that the proposed algorithm performs well in reconstructing relative scattering power maps, i.e. scattering power relative to that of water. Spatial resolution is improved by almost a factor of three compared to straight line projection and is comparable to energy-loss proton CT. Image noise, on the other hand, is inherently much higher. For example, in a water cylinder of 20 cm diameter, representative of a human head, noise in the central image pixel is about 40 times higher in scattering proton CT than in energy-loss proton CT. Relative scattering power in dense regions such as bone inserts is systematically underestimated by a few percent, depending on beam energy and phantom geometry.

Experimental realization of dynamic fluence field optimization for proton computed tomography.

Proton computed tomography (pCT) has high accuracy and dose efficiency in producing spatial maps of the relative stopping power (RSP) required for treatment planning in proton therapy. With fluence-modulated pCT (FMpCT), prescribed noise distributions can be achieved, which allows to decrease imaging dose by employing object-specific dynamically modulated fluence during the acquisition. For FMpCT acquisitions we divide the image into region-of-interest (ROI) and non-ROI volumes. In proton therapy, the ROI volume would encompass all treatment beams. An optimization algorithm then calculates dynamically modulated fluence that achieves low prescribed noise inside the ROI and high prescribed noise elsewhere. It also produces a planned noise distribution, which is the expected noise map for that fluence, as calculated with a Monte Carlo simulation. The optimized fluence can be achieved by acquiring pCT images with grids of intensity modulated pencil beams. In this work, we interfaced the control system of a clinical proton beam line to deliver the optimized fluence. Using three phantoms we acquired images with uniform fluence, with a constant noise prescription, and with an FMpCT task. Image noise distributions as well as fluence maps were compared to the corresponding planned distributions as well as to the prescription. Furthermore, we propose a correction method that removes image artifacts stemming from the acquisition with pencil beams having a spatially varying energy distribution that is not seen in clinical operation. RSP accuracy of FMpCT scans was compared to uniform scans and was found to be comparable to standard pCT scans. While we identified technical improvements for future experimental acquisitions, in particular related to an unexpected pencil beam size reduction and a misalignment of the fluence pattern, agreement with the planned noise was satisfactory and we conclude that FMpCT optimized for specific image noise prescriptions is experimentally feasible.

Mid-position treatment strategy for locally advanced lung cancer: a dosimetric study.

OBJECTIVE: The internal target volume (ITV) strategy generates larger planning target volumes (PTVs) in locally advanced non-small cell lung cancer (LA-NSCLC) than the Mid-position (Mid-p) strategy. We investigated the benefit of the Mid-p strategy regarding PTV reduction and dose to the organs at risk (OARs). METHODS: 44 patients with LA-NSCLC were included in a randomized clinical study to compare ITV and Mid-p strategies. GTV were delineated by a physician on maximum intensity projection images and on Mid-p images from four-dimensional CTs. CTVs were obtained by adding 6 mm uniform margin for microscopic extension. CTV to PTV margins were calculated using the van Herk's recipe for setup and delineation errors. For the Mid-p strategy, the mean target motion amplitude was added as a random error. For both strategies, three-dimensional conformal plans delivering 60-66 Gy to PTV were performed. PTVs, dose-volume parameters for OARs (lung, esophagus, heart, spinal cord) were reported and compared. RESULTS: With the Mid-p strategy, the median of volume reduction was 23.5 cm3 (p = 0.012) and 8.8 cm3 (p = 0.0083) for PTVT and PTVN respectively; the median mean lung dose reduction was 0.51 Gy (p = 0.0057). For 37.1% of the patients, delineation errors led to smaller PTV with the ITV strategy than with the Mid-p strategy. CONCLUSION: PTV and mean lung dose were significantly reduced using the Mid-p strategy. Delineation uncertainty can unfavorably impact the advantage. ADVANCES IN KNOWLEDGE: To the best of our knowledge, this is the first dosimetric comparison study between ITV and Mid-p strategies for LA-NSCLC.

2D directional ramp filter.

Usual tomographic reconstruction methods start by filtering projections before backprojecting the data. In some cases, inverting the filtering and the backprojection steps can be useful to preserve spatial information. In this paper, an intermediate between a filter-backproject and a backproject-filter approach is proposed, based on the extension of the usual ramp filter to two dimensions. To this end, an expression for a band-limited 2D version of the ramp filter is derived. We have tested this filter on simulated x-ray CT projections of a Shepp-Logan phantom and on proton CT list-mode data. We accurately reconstructed the x-ray CT and the proton CT data, although the reconstruction can be slightly noisier than a standard filtered backprojection in some cases. A slight improvement of the spatial resolution of proton CT images reconstructed with this 2D filter has been observed.

An optimization algorithm for dose reduction with fluence-modulated proton CT.

PURPOSE: Fluence-modulated proton computed tomography (FMpCT) using pencil beam scanning aims at achieving task-specific image noise distributions by modulating the imaging proton fluence spot-by-spot based on an object-specific noise model. In this work, we present a method for fluence field optimization and investigate its performance in dose reduction for various phantoms and image variance targets. METHODS: The proposed method uses Monte Carlo simulations of a proton CT (pCT) prototype scanner to estimate expected variance levels at uniform fluence. Using an iterative approach, we calculate a stack of target variance projections that are required to achieve the prescribed image variance, assuming a reconstruction using filtered backprojection. By fitting a pencil beam model to the ratio of uniform fluence variance and target variance, relative weights for each pencil beam can be calculated. The quality of the resulting fluence modulations is evaluated by scoring imaging doses and comparing them to those at uniform fluence, as well as evaluating conformity of the achieved variance with the prescription. For three different phantoms, we prescribed constant image variance as well as two regions-of-interest (ROI) imaging tasks with inhomogeneous image variance. The shape of the ROIs followed typical beam profiles for proton therapy. RESULTS: Prescription of constant image variance resulted in a dose reduction of 8.9% for a homogeneous water phantom compared to a uniform fluence scan at equal peak variance level. For a more heterogeneous head phantom, dose reduction increased to 16.0% for the same task. Prescribing two different ROIs resulted in dose reductions between 25.7% and 40.5% outside of the ROI at equal peak variance levels inside the ROI. Imaging doses inside the ROI were increased by 9.2% to 19.2% compared to the uniform fluence scan, but can be neglected assuming that the ROI agrees with the therapeutic dose region. Agreement of resulting variance maps with the prescriptions was satisfactory. CONCLUSIONS: We developed a method for fluence field optimization based on a noise model for a real scanner used in pCT. We demonstrated that it can achieve prescribed image variance targets. A uniform fluence field was shown not to be dose optimal and dose reductions achievable with the proposed method for FMpCT were considerable, opening an interesting perspective for image guidance and adaptive therapy.

SciFi detector and associated method for real-time determination of profile and output factor for small fields in stereotactic radiotherapy.

PURPOSE: For determining small-field profile and output factor during stereotactic radiotherapy quality assurance (QA) procedures, we propose a novel system based on the scintillating fiber (SciFi) detector with output image acquisition and processing to allow real-time monitoring of profile and output factor. MATERIALS AND METHODS: The employed detector is a SciFi detector made of tissue-equivalent scintillating plastic fibers arranged in 6-layer fiber ribbons with a fiber pitch of 275 µm in each layer. The scintillating signal at the detector output is acquired by a sCMOS (scientific complementary metal-oxide-semiconductor) camera and represents the projected field profile along the fibers axis. An iterative reconstruction method of the field from its projected profile based on a priori knowledge of some features of the radiation field defined by the stereotactic cones is suggested. The detector with implemented data processing has been tested in clinical conditions, for determining beam profiles and output factors, using cone collimators of different sizes from 4 to 15 mm diameter. The detector under test was placed at 1.4 cm depth and 98.6 cm source to surface distance (SSD) in a water-equivalent phantom and irradiated by a 6 MV photon beam. RESULTS: The reconstructed field profiles obtained from the detector are coherent with data from EBT3 radiochromic films, with differences within ±0.32 mm for both the FWHM and the penumbra region. For real-time determination of the field output factor, the measured data are also in good agreement with data independently determined by the French Institute for Radiological Protection and Nuclear Safety (IRSN) based on radiochromic films and thermoluminescent 1 × 1 mm2 micro-cubes dosimeters (TLD). The differences are within ±1.6% for all the tested cone sizes. CONCLUSIONS: We propose and have tested a SciFi plastic scintillating detector with an optimized signal processing method to characterize small fields defined by cone collimators. It allows the determination of key field parameters such as full width at half maximum (FWHM) and field output factors. The results are consistent with those independently measured using TLD and radiochromic films. As the SciFi detector does not require a correction factor, it is in line with the International Atomic Energy Agency (IAEA) and the American Association of Physicists in Medicine (AAPM) TRS-483 recommendations, and can be suitable for online QA of small radiation fields used in photon beam radiotherapy, and is compatible with MRI-LINAC.

Polynomial modelling of proton trajectories in homogeneous media for fast most likely path estimation and trajectory simulation.

Protons undergo many small angle deflections when traversing a medium, such as a patient. This effect, known as multiple Coulomb scattering (MCS), leads to degraded image resolution in proton radiography and computed tomography (CT) and to lateral spreading of the dose distribution in proton therapy. To optimally account for MCS in proton imaging, the most likely path (MLP) of a proton is estimated based on its position and propagation angle measured in front of and behind the object. In this work, we propose a functional which quantifies the likelihood of a proton trajectory and study how it can be used to model proton trajectories in a homogeneous medium. We focus on two aspects: first, we present an analytical method to quickly generate proton trajectories in a homogeneous medium based on the likelihood functional and validate it through Monte Carlo simulations. It could be used for fast generation of proton CT images without a full Monte Carlo simulation, or potentially to complement the components in a treatment planning Monte Carlo which simulate MCS. Second, by maximising the likelihood functional, we derive an expression for the MLP which is equivalent to the conventional ones reported in the literature yet computationally more convenient. Moreover, we show that the MLP is strictly a polynomial function if the protons' energy loss in the medium is approximated as a polynomial and that the orders of both are linked. We validate our MLP through Monte Carlo simulations and compare proton CT images reconstructed with our expression and with the conventional one. We find that an MLP polynomial of orders larger than five do not lead to increased spatial resolution compared to lower order expressions.

Prediction of image noise contributions in proton computed tomography and comparison to measurements.

We present a method to accurately predict image noise in proton computed tomography (pCT) using data generated from a Monte Carlo simulation and a patient or object model that may be generated from a prior x-ray CT image. This enables noise prediction for arbitrary beam fluence settings and, therefore, the application of fluence-modulated pCT (FMpCT), which can achieve prescribed noise targets and may significantly reduce the integral patient dose. We extended an existing Monte Carlo simulation of a prototype pCT scanner to include effects of quenching in the energy detector scintillators and constructed a beam model from experimental tracking data. Simulated noise predictions were compared to experimental data both in the projection domain and in the reconstructed image. Noise prediction agreement between simulated and experimental data in terms of the root-mean-square (RMS) error was better than 7% for a homogeneous water phantom and a sensitometry phantom with tubular inserts. For an anthropomorphic head phantom, modeling the anatomy of a five-year-old child, the RMS error was better than 9% in three evaluated slices. We were able to reproduce subtle noise features near heterogeneities. To demonstrate the feasibility of Monte Carlo simulated noise maps for fluence modulation, we calculated a fluence profile that yields a homogeneous noise level in the image. Unlike for bow-tie filters in x-ray CT this does not require constant fluence at the detector and the shape of the fluence profile is fundamentally different. Using an improved Monte Carlo simulation, we demonstrated the feasibility of using simulated data for accurate image noise prediction for pCT. We believe that the agreement with experimental data is sufficient to enable the future optimization of FMpCT fluence plans to achieve prescribed noise targets in a fluence-modulated acquisition.

Regularised patient-specific stopping power calibration for proton therapy planning based on proton radiographic images.

Proton transmission imaging has been proposed and investigated as imaging modality complementary to x-ray based techniques in proton beam therapy. In particular, it addresses the issue of range uncertainties due to the conversion of an x-ray patient computed tomography (CT) image expressed in Hounsfield Units (HU) to relative stopping power (RSP) needed as input to the treatment planning system. One approach to exploit a single proton radiographic projection is to perform a patient-specific calibration of the CT to RSP conversion curve by optimising the match between a measured and a numerically integrated proton radiography. In this work, we develop the mathematical tools needed to perform such an optimisation in an efficient and robust way. Our main focus lies on set-ups which combine pencil beam scanning with a range telescope detector, although most of our methods can be employed in combination with other set-ups as well. Proton radiographies are simulated in Monte Carlo using an idealised detector and applying the same data processing chain used with experimental data. This approach allows us to have a ground truth CT-RSP curve to compare the optimisation results with. Our results show that the parameters of the CT-RSP curve are strongly correlated when using a pencil beam based set-up, which leads to unrealistic variation in the optimised CT-RSP curves. To address this issue, we introduce a regularisation procedure which guarantees a plausible degree of smoothness in the optimised CT-RSP curves. We investigate three different methods to perform the numerical projection operation needed to generate a proton digitally reconstructed radiography. We find that the approximate and computationally faster method performs as well as the more accurate but more demanding method. We perform a Monte Carlo experiment based on a head and neck patient to evaluate the range accuracy achievable with the optimised CT-RSP curves and find an agreement with the ground truth expectation of better than [Formula: see text]. Our results further indicate that the region in the patient in which the proton radiography is acquired does not necessarily have to correspond to the treatment volume to achieve this accuracy. This is important as the imaged region could be freely chosen, e.g. in order to spare organs at risk.

A comprehensive theoretical comparison of proton imaging set-ups in terms of spatial resolution.

We present a comprehensive analytical comparison of four types of proton imaging set-ups and, to this end, develop a mathematical framework to calculate the width of the uncertainty envelope around the most likely proton path depending on set-up geometry, detector properties, and proton beam parameters. As a figure of merit for the spatial resolution achievable with each set-up, we use the frequency [Formula: see text] at which the modular transfer function of a density step decreases below 10%. We verify the analytical results with Monte Carlo simulations. We find that set-ups which track the angle and position of individual protons in front of and behind the phantom would yield an average spatial resolution of 0.3-0.35 lp mm-1 assuming realistic geometric parameters (i.e. 30-40 cm distance between detector and phantom, 15-20 cm phantom thickness). For set-ups combining pencil beam scanning with either a position sensitive detector, e.g. an x-ray flat panel, or with a position insensitive detector, e.g. a range telescope, we find an average spatial resolution of about 0.1 lp mm-1 for an 8 mm FWHM beam spot size. The pixel information improves the spatial resolution by less than 10%. In both set-up types, performance can be significantly improved by reducing the pencil beam size down to 2 mm FWHM. In this case, the achievable spatial resolution reaches about 0.25 lp mm-1. Our results show that imaging set-ups combining double scattering with a pixel detector can provide sufficient spatial resolution only under very stringent conditions and are not ideally suited for computed tomography applications. We further propose a region-of-interest method for set-ups with a pixel detector to filter out protons which have undergone nuclear reactions and discuss the impact of tracker detector uncertainties on the most likely path.

Registration of phase-contrast images in propagation-based X-ray phase tomography.

X-ray phase tomography aims at reconstructing the 3D electron density distribution of an object. It offers enhanced sensitivity compared to attenuation-based X-ray absorption tomography. In propagation-based methods, phase contrast is achieved by letting the beam propagate after interaction with the object. The phase shift is then retrieved at each projection angle, and subsequently used in tomographic reconstruction to obtain the refractive index decrement distribution, which is proportional to the electron density. Accurate phase retrieval is achieved by combining images at different propagation distances. For reconstructions of good quality, the phase-contrast images recorded at different distances need to be accurately aligned. In this work, we characterise the artefacts related to misalignment of the phase-contrast images, and investigate the use of different registration algorithms for aligning in-line phase-contrast images. The characterisation of artefacts is done by a simulation study and comparison with experimental data. Loss in resolution due to vibrations is found to be comparable to attenuation-based computed tomography. Further, it is shown that registration of phase-contrast images is nontrivial due to the difference in contrast between the different images, and the often periodical artefacts present in the phase-contrast images if multilayer X-ray optics are used. To address this, we compared two registration algorithms for aligning phase-contrast images acquired by magnified X-ray nanotomography: one based on cross-correlation and one based on mutual information. We found that the mutual information-based registration algorithm was more robust than a correlation-based method.

Fixed forced detection for fast SPECT Monte-Carlo simulation.

Monte-Carlo simulations of SPECT images are notoriously slow to converge due to the large ratio between the number of photons emitted and detected in the collimator. This work proposes a method to accelerate the simulations based on fixed forced detection (FFD) combined with an analytical response of the detector. FFD is based on a Monte-Carlo simulation but forces the detection of a photon in each detector pixel weighted by the probability of emission (or scattering) and transmission to this pixel. The method was evaluated with numerical phantoms and on patient images. We obtained differences with analog Monte Carlo lower than the statistical uncertainty. The overall computing time gain can reach up to five orders of magnitude. Source code and examples are available in the Gate V8.0 release.

Application of fluence field modulation to proton computed tomography for proton therapy imaging.

This simulation study presents the application of fluence field modulated computed tomography, initially developed for x-ray CT, to proton computed tomography (pCT). By using pencil beam (PB) scanning, fluence modulated pCT (FMpCT) may achieve variable image quality in a pCT image and imaging dose reduction. Three virtual phantoms, a uniform cylinder and two patients, were studied using Monte Carlo simulations of an ideal list-mode pCT scanner. Regions of interest (ROI) were selected for high image quality and only PBs intercepting them preserved full fluence (FF). Image quality was investigated in terms of accuracy (mean) and noise (standard deviation) of the reconstructed proton relative stopping power compared to reference values. Dose calculation accuracy on FMpCT images was evaluated in terms of dose volume histograms (DVH), range difference (RD) for beam-eye-view (BEV) dose profiles and gamma evaluation. Pseudo FMpCT scans were created from broad beam experimental data acquired with a list-mode pCT prototype. FMpCT noise in ROIs was equivalent to FF images and accuracy better than -1.3%(-0.7%) by using 1% of FF for the cylinder (patients). Integral imaging dose reduction of 37% and 56% was achieved for the two patients for that level of modulation. Corresponding DVHs from proton dose calculation on FMpCT images agreed to those from reference images and 96% of BEV profiles had RD below 2 mm, compared to only 1% for uniform 1% of FF. Gamma pass rates (2%, 2 mm) were 98% for FMpCT while for uniform 1% of FF they were as low as 59%. Applying FMpCT to preliminary experimental data showed that low noise levels and accuracy could be preserved in a ROI, down to 30% modulation. We have shown, using both virtual and experimental pCT scans, that FMpCT is potentially feasible and may allow a means of imaging dose reduction for a pCT scanner operating in PB scanning mode. This may be of particular importance to proton therapy given the low integral dose found outside the target.

Filtered back-projection reconstruction for attenuation proton CT along most likely paths.

This work investigates the attenuation of a proton beam to reconstruct the map of the linear attenuation coefficient of a material which is mainly caused by the inelastic interactions of protons with matter. Attenuation proton computed tomography (pCT) suffers from a poor spatial resolution due to multiple Coulomb scattering (MCS) of protons in matter, similarly to the conventional energy-loss pCT. We therefore adapted a recent filtered back-projection algorithm along the most likely path (MLP) of protons for energy-loss pCT (Rit et al 2013) to attenuation pCT assuming a pCT scanner that can track the position and the direction of protons before and after the scanned object. Monte Carlo simulations of pCT acquisitions of density and spatial resolution phantoms were performed to characterize the new algorithm using Geant4 (via Gate). Attenuation pCT assumes an energy-independent inelastic cross-section, and the impact of the energy dependence of the inelastic cross-section below 100 MeV showed a capping artifact when the residual energy was below 100 MeV behind the object. The statistical limitation has been determined analytically and it was found that the noise in attenuation pCT images is 411 times and 278 times higher than the noise in energy-loss pCT images for the same imaging dose at 200 MeV and 300 MeV, respectively. Comparison of the spatial resolution of attenuation pCT images with a conventional straight-line path binning showed that incorporating the MLP estimates during reconstruction improves the spatial resolution of attenuation pCT. Moreover, regardless of the significant noise in attenuation pCT images, the spatial resolution of attenuation pCT was better than that of conventional energy-loss pCT in some studied situations thanks to the interplay of MCS and attenuation known as the West-Sherwood effect.

Binary tomography reconstruction from few projections with Total Variation regularization for bone microstructure studies.

Discrete tomography refers to a class of reconstruction methods adapted to discrete-valued images. Many different approaches have been investigated to address the binary case, when a two-phase object is considered. This reconstruction problem is very important in medical or material applications where it is crucial to reduce the number of projections. In this paper, we address the problem of binary image reconstruction for X-ray CT imaging from a small number of projections. We propose a TV (Total Variation) regularization approach and compare the results obtained with or without an additional box convex constraint. The schemes are applied to a simple disk image and to more complex bone cross-sections for various noise levels. The minimization of the regularization functional is performed with the state-of-the-art ADMM (Alternate Direction Minimization Method) algorithm. The methods perform equally well on a simple disk image. The additional box convex constraints improves the reconstruction results for complex structures with fine details.

Monte Carlo comparison of x-ray and proton CT for range calculations of proton therapy beams.

Proton computed tomography (CT) has been described as a solution for imaging the proton stopping power of patient tissues, therefore reducing the uncertainty of the conversion of x-ray CT images to relative stopping power (RSP) maps and its associated margins. This study aimed to investigate this assertion under the assumption of ideal detection systems. We have developed a Monte Carlo framework to assess proton CT performances for the main steps of a proton therapy treatment planning, i.e. proton or x-ray CT imaging, conversion to RSP maps based on the calibration of a tissue phantom, and proton dose simulations. Irradiations of a computational phantom with pencil beams were simulated on various anatomical sites and the proton range was assessed on the reference, the proton CT-based and the x-ray CT-based material maps. Errors on the tissue's RSP reconstructed from proton CT were found to be significantly smaller and less dependent on the tissue distribution. The imaging dose was also found to be much more uniform and conformal to the primary beam. The mean absolute deviation for range calculations based on x-ray CT varies from 0.18 to 2.01 mm depending on the localization, while it is smaller than 0.1 mm for proton CT. Under the assumption of a perfect detection system, proton range predictions based on proton CT are therefore both more accurate and more uniform than those based on x-ray CT.

Effects of home visiting and maternal mental health on use of the emergency department among late preterm infants.

OBJECTIVE: To describe use of the emergency department (ED) among late preterm versus term infants enrolled in a home visiting program and to determine whether home visiting frequency was associated with outcome differences. DESIGN: Retrospective, cohort study. SETTING: Regional home visiting program in southwest Ohio from 2007­2010. PARTICIPANTS: Late preterm and term infants born to mothers enrolled in home visiting. Program eligibility requires ≥ one of four characteristics: unmarried, low income, < 18 years, or suboptimal prenatal care. METHODS: Data were derived from vital statistics, hospital discharges, and home visiting records. Negative binomial regression was used to determine association of ED visits in the first year with late preterm birth and home visit frequency, adjusting for maternal and infant characteristics. RESULTS: Of 1,804 infants, 9.2% were born during the late preterm period. Thirty-eight percent of all infants had at least one ED visit, 15.6% had three or more. No significant difference was found between the number of ED visits for late preterm and term infants (39.4% vs. 37.8% with at least one ED visit, p = .69). In multivariable analysis, late preterm birth combined with a maternal mental health diagnosis was associated with an ED incident rate ratio (IRR) of 1.26, p = .03; high frequency of home visits was not significant (IRR = .92, p = .42). CONCLUSIONS: Frequency of home visiting service over the first year of life is not significantly associated with reduced ED visits for infants with at-risk attributes and born during the late preterm period. Research on how home visiting can address ED use, particularly for those with prematurity and maternal mental health conditions, may strengthen program impact and cost benefits.