Estimation of dose-area product-to-effective dose conversion factors for neonatal radiography using PCXMC.

Dose-area product-to-effective dose (E) conversion factors for chest, abdomen and abdomen-chest neonatal radiographs were computed. Seven patient models in the Monte Carlo software, PCXMC, were defined, representing neonates ranging in weight from 0.5 to 6.0 kg. Conversion factors for a tube potential range of 50-80 kVp at two beam filtrations (3.0 mm Al and 3.0 mm Al+0.1 mm Cu) were calculated. For 133 neonatal radiographs, effective dose values determined using these conversion factors were compared with those obtained from PCXMC simulations customised for each radiograph. For a 3.0-kg newborn irradiated at 60 kVp/3.0 mm Al beam filtration, the conversion factors were 2.58, 1.90 and 1.91 µSv (mGy cm(2))(-1) for chest, chest-abdomen and abdomen radiographs, respectively. Average dose difference between the conversion factors and customised dose calculations was 16 %. Disagreement in effective dose was most strongly correlated with under-collimation in the lateral direction.

Estimation of organ and effective doses from newborn radiography of the chest and abdomen.

Neonatal intensive care patients undergo frequent chest and abdomen radiographic imaging. In this study, the organ doses and the effective dose resulting from combined chest-abdomen radiography of the newborn child are determined. These values are calculated using the Monte Carlo simulation software PCXCM 2.0 and compared with direct dose measurements obtained from thermoluminescent detectors (TLDs) in a physical phantom. The effective dose obtained from PCXMC is 21.2 ± 0.7 µSv and that obtained from TLD measurements is 22.0 ± 0.5 µSv. While the two methods are in close agreement with regard to the effective dose, there is a wide range of variation in organ doses, ranging from 85 % difference for the testes to 1.4 % for the lungs. Large organ dose variations are attributed to organs at the edge of the field of view, or organs with large experimental error or simulation uncertainty. This study suggests that PCXMC can be used to estimate organ and effective doses for newborn patients.

Antiscatter grid use in pediatric digital tomosynthesis imaging.

The objective of this study was to assess the effect of antiscatter grid use on tomosynthesis image quality. We performed an observer study that rated the image quality of digital tomosynthesis scout radiographs and slice images of a Leeds TO.20 contrast-detail test object embedded in acrylic with and without a grid. We considered 10, 15, 20 and 25 cm of acrylic to represent the wide range of patient thicknesses encountered in pediatric imaging. We also acquired and rated images without a grid at an increased patient dose. The readers counted the total number of visible details in each image as a measure of relative image quality. We observed that the antiscatter grid improves tomosynthesis image quality compared to the grid-out case, which received image quality scores similar to grid-in radiography. Our results suggest that, in order to achieve the best image quality in exchange for the increase in patient dose, it may often be appropriate to include an antiscatter grid for pediatric tomosynthesis imaging, particularly if the patient thickness is greater than 10 cm.

A GPU implementation of EGSnrc's Monte Carlo photon transport for imaging applications.

EGSnrc is a well-known Monte Carlo simulation package for coupled electron-photon transport that is widely used in medical physics application. This paper proposes a parallel implementation of the photon transport mechanism of EGSnrc for graphics processing units (GPUs) using NVIDIA's Compute Unified Device Architecture (CUDA). The implementation is specifically designed for imaging applications in the diagnostic energy range and does not model electrons. No approximations or simplifications of the original EGSnrc code were made other than using single floating-point precision instead of double precision and a different random number generator. To avoid performance penalties due to the random nature of the Monte Carlo method, the simulation was divided into smaller steps that could easily be performed in a parallel fashion suitable for GPUs. Speedups of 20 to 40 times for 64(3) to 256(3) voxels were observed while the accuracy of the simulation was preserved. A detailed analysis of the differences between the CUDA simulation and the original EGSnrc was conducted. The two simulations were found to produce equivalent results for scattered photons and an overall systematic deviation of less than 0.08% was observed for primary photons.

Epp: A C++ EGSnrc user code for x-ray imaging and scattering simulations.

PURPOSE: Easy particle propagation (Epp) is a user code for the EGSnrc code package based on the c+ + class library egspp. A main feature of egspp (and Epp) is the ability to use analytical objects to construct simulation geometries. The authors developed Epp to facilitate the simulation of x-ray imaging geometries, especially in the case of scatter studies. While direct use of egspp requires knowledge of c+ +, Epp requires no programming experience. METHODS: Epp's features include calculation of dose deposited in a voxelized phantom and photon propagation to a user-defined imaging plane. Projection images of primary, single Rayleigh scattered, single Compton scattered, and multiple scattered photons may be generated. Epp input files can be nested, allowing for the construction of complex simulation geometries from more basic components. To demonstrate the imaging features of Epp, the authors simulate 38 keV x rays from a point source propagating through a water cylinder 12 cm in diameter, using both analytical and voxelized representations of the cylinder. The simulation generates projection images of primary and scattered photons at a user-defined imaging plane. The authors also simulate dose scoring in the voxelized version of the phantom in both Epp and DOSXYZnrc and examine the accuracy of Epp using the Kawrakow-Fippel test. RESULTS: The results of the imaging simulations with Epp using voxelized and analytical descriptions of the water cylinder agree within 1%. The results of the Kawrakow-Fippel test suggest good agreement between Epp and DOSXYZnrc. CONCLUSIONS: Epp provides the user with useful features, including the ability to build complex geometries from simpler ones and the ability to generate images of scattered and primary photons. There is no inherent computational time saving arising from Epp, except for those arising from egspp's ability to use analytical representations of simulation geometries. Epp agrees with DOSXYZnrc in dose calculation, since they are both based on the well-validated standard EGSnrc radiation transport physics model.

A novel hybrid reconstruction algorithm for first generation incoherent scatter CT (ISCT) of large objects with potential medical imaging applications.

This work presents a first generation incoherent scatter CT (ISCT) hybrid (analytic-iterative) reconstruction algorithm for accurate ρ{e}imaging of objects with clinically relevant sizes. The algorithm reconstructs quantitative images of ρ{e} within a few iterations, avoiding the challenges of optimization based reconstruction algorithms while addressing the limitations of current analytical algorithms. A 4π detector is conceptualized in order to address the issue of directional dependency and is then replaced with a ring of detectors which detect a constant fraction of the scattered photons. The ISCT algorithm corrects for the attenuation of photons using a limited number of iterations and filtered back projection (FBP) for image reconstruction. This results in a hybrid reconstruction algorithm that was tested with sinograms generated by Monte Carlo (MC) and analytical (AN) simulations. Results show that the ISCT algorithm is weakly dependent on the ρ{e} initial estimate. Simulation results show that the proposed algorithm reconstruct ρ{e} images with a mean error of -1% ± 3% for the AN model and from -6% to -8% for the MC model. Finally, the algorithm is capable of reconstructing qualitatively good images even in the presence of multiple scatter. The proposed algorithm would be suitable for in-vivo medical imaging as long as practical limitations can be addressed.

A 1st generation scatter CT algorithm for electron density breast imaging which accounts for bound incoherent, coherent and multiple scatter: A Monte Carlo study.

Breast CT is an emerging modality that reconstructs 3D linear attenuation coefficient (µ) images of the breast. Its tomographic nature reduces the overlap of structures and may improve tissue visualization. Current prototype systems produce large levels of scatter that could be used to reconstruct electron density (ρ _{e}) images. This could potentially enhance diagnosis. We are developing a first generation bench top CT system to investigate the benefits of simultaneous imaging µ and ρ _{e} of the intact breast. The system uses an algorithm capable of reconstructing ρ _{e} images from single Klein-Nishina scatter. It has been suggested that this algorithm may be impractical since measurements include coherent, bound incoherent and multiple scatter. To investigate this, the EGSnrc Monte Carlo (MC) code was used to simulate scans using a first generation system. These simulations were used to quantify the dose per scan, to provide raw data for the ρ _{e} reconstructions and to investigate corrections for multiple and coherent scatter since these can not be directly related to ρ _{e}. MC simulations show that the dose coefficients are similar to those of cone beam breast CT. Coherent scatter is only ∼9% concentrated in scattering angles < 8°. Electron binding reduces the number of incoherently scattered photons but this reduction can be included in the quantification of scatter measured by the system. Multiple scatter was found to be the major source of errors and, if not corrected for, can result in an overestimation of ρ _{e} by more than a factor of two. Empirical corrections, based on breast thickness or radiological path, can be used to reconstruct images where the variance in ρ _{e} error is half of that found in images derived from primary photons only. Although some practical challenges remain in creating a laboratory system, this work has shown that it is possible to reconstruct scatter images of the breast with a 4 mGy dose and further experimental evaluation of this technique is warranted.

Automatic exposure control for a slot scanning full field digital mammography system.

Automatic exposure control (AEC) is an important feature in mammography. It enables consistently optimal image exposure despite variations in tissue density and thickness, and user skill level. Full field digital mammography systems cannot employ conventional AEC methods because digital receptors fully absorb the x-ray beam. In this paper we describe an AEC procedure for slot scanning mammography. With slot scanning detectors, our approach uses a fast low-resolution and low-exposure prescan to acquire an image of the breast. Tube potential depends on breast thickness, and the prescan histogram provides the necessary information to calculate the required tube current. We validate our approach with simulated prescan images and phantom measurements. We achieve accurate exposure tracking with thickness and density, and expect this method of AEC to reduce retakes and improve workflow.

Statistical image reconstruction for polyenergetic X-ray computed tomography.

This paper describes a statistical image reconstruction method for X-ray computed tomography (CT) that is based on a physical model that accounts for the polyenergetic X-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. We assume that the object consists of a given number of nonoverlapping materials, such as soft tissue and bone. The attenuation coefficient of each voxel is the product of its unknown density and a known energy-dependent mass attenuation coefficient. We formulate a penalized-likelihood function for this polyenergetic model and develop an ordered-subsets iterative algorithm for estimating the unknown densities in each voxel. The algorithm monotonically decreases the cost function at each iteration when one subset is used. Applying this method to simulated X-ray CT measurements of objects containing both bone and soft tissue yields images with significantly reduced beam hardening artifacts.