Impact of flat panel-imager veiling glare on scatter-estimation accuracy and image quality of a commercial on-board cone-beam CT imaging system.

PURPOSE: The purposes of this study is to measure the low frequency drop (LFD) of the modulation transfer function (MTF), associated with the long tails of the detector point spread function (PSF) of an on-board flat panel imager and study its impact on cone-beam CT (CBCT) image quality and scatter measurement accuracy. METHODS: Two different experimental methods were used to characterize LFD and its associated PSF of a Varian OBI flat-panel detector system: the edge response function (ERF) method and the disk transfer function (DTF) method. PSF was estimated by fitting parametric models to these measurements for four values of the applied voltage (kVp). The resultant PSF was used to demonstrate the effect of LFD on image contrast and CT number accuracy in CBCT images reconstructed from synthetic datasets, as well as, accuracy of scatter measurements with the beam-stop method. RESULTS: The MTFs derived from the measured ERF data revealed LFDs varying from 8% (at 60 kVp) to 10.5% (at 120 kVp), while the intensity of the long PSF tails was found to increase with increasing kVp. The veiling glare line spread functions derived from the ERF and DTF methods were in excellent agreement. Uncorrected veiling glare reduced contrast and the image intensity in CBCT reconstruction, near the phantom periphery (by 67 Hounsfield units in a 20 cm-in-diameter water phantom) and (to a smaller degree) near inhomogeneities. Use of the bow-tie filter mitigated these effects. Veiling glare also resulted in about 10%-15% overestimation of the scatter-to-primary ratio when measured with the beam-stop or beam-stop array method. CONCLUSIONS: The long tails of the detector PSF were found to have a modest dependence of beam spectrum, which is reflected on the MTF curve LFD. Our findings show that uncorrected veiling glare can affect quantitative accuracy and contrast in CBCT imaging, based on flat panel imager. In addition, it results in overestimation of the scatter-to-primary ratio, measured with the beam-stop methods.

Bow-tie wobble artifact: effect of source assembly motion on cone-beam CT.

PURPOSE: To investigate the cause of a bow-tie wobble artifact (BWA) discovered on Varian OBI CBCT images and to develop practical correction strategies. METHOD AND MATERIALS: The dependence of the BWA on phantom geometry, phantom position, specific system, and reconstruction algorithm was investigated. Simulations were conducted to study the dependence of the BWA on scatter and beam hardening corrections. Geometric calibration was performed to rule out other gantry-angle dependent mechanical non-idealities as BWA causes. Air scans were acquired with ball-bearing markers to study the motions of the x-ray head assembly as functions of gantry angle. Based on measurements, we developed hypothesis regarding the BWA cause. Simulations were performed to validate our hypothesis. Two correction strategies were implemented: a measurement-based method, which acquires gantry-dependent normalization projections (NPs); and a model-based method that involves numerically shifting the single-angle NP to compensate for the previously-measured bow-tie-filter (BTF) motion. RESULTS: The BWA has a diameter of approximately 15 cm, is centered at the isocenter, and is reproducible independent of phantom, position, system, reconstruction, and standard corrections, but only when the BTF is used. Measurements identified a 2D sinusoidal gantry-angle-dependent motion of the x-ray head assembly, and it was the BTF motion (>3 mm amplitude projected onto the detector) resulting an intensity mismatch between the all-angle CBCT projections and a single-angle NP that caused the BWA. Both correction strategies were demonstrated effective. CONCLUSIONS: A geometric mismatch between the BTF modulation patterns on CBCT projections and on the NP causes the BWA. The BTF wobble requires additional degrees of freedom in CBCT geometric calibration to characterize.

Machine learning for proton path tracking in proton computed tomography.

A Machine Learning approach to the problem of calculating the proton paths inside a scanned object in proton Computed Tomography is presented. The method is developed in order to mitigate the loss in both spatial resolution and quantitative integrity of the reconstructed images caused by multiple Coulomb scattering of protons traversing the matter. Two Machine Learning models were used: a forward neural network (NN) and the XGBoost method. A heuristic approach, based on track averaging was also implemented in order to evaluate the accuracy limits on track calculation, imposed by the statistical nature of the scattering. Synthetic data from anthropomorphic voxelized phantoms, generated by the Monte Carlo (MC) Geant4 code, were utilized to train the models and evaluate their accuracy, in comparison to a widely used analytical method that is based on likelihood maximization and Fermi-Eyges scattering model. Both NN and XGBoost model were found to perform very close or at the accuracy limit, further improving the accuracy of the analytical method (by 12% in the typical case of 200 MeV protons on 20 cm of water object), especially for protons scattered at large angles. Inclusion of the material information along the path in terms of radiation length did not show improvement in accuracy for the phantoms simulated in the study. A NN was also constructed to predict the error in path calculation, thus enabling a criterion to filter out proton events that may have a negative effect on the quality of the reconstructed image. By parametrizing a large set of synthetic data, the Machine Learning models were proved capable to bring-in an indirect and time efficient way-the accuracy of the MC method into the problem of proton tracking.

Monte Carlo evaluation of scatter mitigation strategies in cone-beam CT.

PURPOSE: To investigate the efficacy of two widely used scatter mitigation methods: antiscatter grids (ASGs) and beam modulating with bowtie filters (BTFs), in combination with subtractive scatter correction or zeroth order normalization phantom calibration, for improving image noise, contrast, contrast-to-noise ratio (CNR), and image uniformity for on-board cone-beam CT (CBCT) imaging systems used for image-guided radiation therapy. METHODS: PTRAN Monte Carlo CBCT x-ray projections of head and pelvic phantoms were calculated for combinations of beam-modulation and scatter rejection methods and images were reconstructed by in-house developed software. In addition, a simple one-dimensional analytic model was developed to predict scatter-to-primary ratio (SPR) and CNR as a function of cylindrical phantom thickness, ASG transmission, and beam modulation with bow-tie filters. RESULTS: ASGs were found to have slightly negative or no effect on head phantom image CNR and to modestly improve CNR (10%-20%) in pelvic phantom images. However, scatter subtraction and norm-phantom calibration perform better when applied on data acquired with ASGs. Scatter subtraction improves CT number accuracy, but increases noise, and in high SPR/low primary-photon transmission scenarios can dramatically reduce CNR and introduce streaking artifacts. The BTF is found to reduce SPR and image noise, resulting in a better trade-off between CNR and imaging dose, but introduces a circular band artifact. CONCLUSIONS: Our study shows that ASGs have a modest positive impact in pelvic scans and negative in head scans, scatter subtraction improves the HU accuracy but reduces CNR, while BTF has a clearly positive effect.

Molière maximum likelihood proton path estimation approximated by cubic Bézier curve for scatter corrected proton CT reconstruction.

A maximum likelihood approach to the problem of calculating the proton paths inside the scanned object in proton computed tomography is presented. Molière theory is used for the first time to derive a physical model that describes proton multiple Coulomb scattering, avoiding the need for the Gaussian approximation currently used. To enable this, the proposed method approximates proton paths with cubic Bézier curves and subsequently maximizes the path likelihood through parametric optimization, based on the Molière model. Results from the Highland formula-based Gaussian approximation are also presented for comparison. The simplex method is utilized for optimisation. The scattering properties of the material(s) of the scanned object are taken into account by appropriately calculating the scattering parameters from the stopping power map that is calculated/updated at every iteration of the algebraic reconstruction process. Proton track length constraint imposed by the proton energy loss is accounted for. The method is also applied in the case that no exit angle data are measured. Geant4 Monte Carlo simulations were performed for model validation. Our results show that use of Molière probability density function for modelling the multiple Coulomb scattering presents a modest 2% accuracy improvement over the Gaussian approximation and most-likely-path method. Simulations of voxelized phantom showed no essential benefit from the inclusion of the material information into the optimization, while path optimization with energy constraint slightly increased path resolution in a bone/water interface phantom. Method error was found to depend on energy, proton track-length within the medium, and proportion of data filtering.

Size-selective protein adsorption to polystyrene surfaces by self-assembled grafted poly(ethylene glycols) with varied chain lengths.

We report about the surface modification of polystyrene (PSt) with photoreactive alpha-4-azidobenzoyl-omega-methoxy poly(ethylene glycol)s (ABMPEG) of three different molecular weights (MWs of approximately 2, approximately 5, and approximately 10 kg/mol) and with two poly(ethylene glycol)/poly(propylene glycol) triblock copolymers (PEG-PPG-PEG) of about identical PEG/PPG ratio (80/20, w/w) and MW(PEG) of approximately 3 and approximately 6 kg/mol, all via adsorption from aqueous solutions. For ABMPEGs, an additional UV irradiation was used for photografting to the PSt. Contact angle (CA) and atomic force microscopy data revealed pronounced differences of the hydrophilicity/hydrophobicity and topography of the surfaces as a function of PEG type and concentration used for the modification. In all cases, an incomplete coverage of the PSt was observed even after modification at the highest solution concentrations (10 g/L). However, clear differences were seen between PEG-PPG-PEGs and ABMPEGs; only for the latter was a nanoscale-ordered interphase structure with an influence of MW(PEG) on the PEG density observed; after modification at the same solution concentrations, the density was significantly higher for lower MW(PEG). The adsorption of three proteins, myoglobin (Mgb), bovine serum albumin (BSA), and fibrinogen to the various surfaces was analyzed by surface plasmon resonance. Pronounced differences between the two PEG types with respect to the reduction of protein adsorption were found. At high, but still incomplete, surface coverage and similar CA, the shielding of ABMPEG layers toward the adsorption of Mgb and BSA was much more efficient; e.g., the adsorbed Mgb mass relative to that of unmodified PSt was reduced to 10% for ABMPEG 2 kg/mol while for both PEG-PPG-PEGs the Mgb mass was still around 100%. In addition, for the ABMPEG layers an effect of MW(PEG) on adsorbed protein mass-decrease with decreasing MW-could be confirmed; and the highest Mgb/BSA selectivities were also observed. A "two-dimensional molecular sieving", based on PEG molecules having a nanoscale order at the hydrophobic substrate polymer surface has been proposed, and the main prerequisites were the use of PEG conjugates which are suitable for an "end-on" grafting (e.g., ABMPEGs), the use of suitable (not too high) concentrations for the surface modification via adsorption/self-assembly, optionally the photografting on the substrate (possible only for ABMPEG), and presumably, a washing step to remove the excess of unbound PEGs. The results of this study also strongly support the hypothesis that the biocompatibility of hydrophobic materials can be very much improved by PEG modifications at surface coverages that are incomplete but have an ordered layer structure controlled by the size and steric interactions of surface-bound PEGs.