Purpose: Existing methods for checking the light field–radiation field congruence on x-ray equipment either do not fully meet the conditions of various quality control standards regarding inherent uncertainty requirements or contain subjective steps, further increasing the uncertainty of the end result. The aim of this work was to develop a method to check the light field–radiation field congruence on all x-ray equipment. The result should have a low uncertainty which is accomplished by eliminating most subjective user steps in the method. A secondary aim was to maintain the same level of usability as of comparable methods but still able to store the result.
Approach: A new device has been developed where the light field and corresponding radiation field are monitored through measurements of the field edge locations (in total: 2 × 4 edges). The maximum field size location deviation between light field and radiation field in the new method is constrained by the physical limitations of the sensors used in various versions of the prototype: linear image sensors (LISs) of 25 to 29 mm active sensor length. The LISs were sensitized to x-rays by applying a phosphor strip of Gd2O2S : Tb covering the light sensor input area. Later prototypes of the completed LIS device also have the option of a Bluetooth (100-m range standard) connection, thus increasing the mobility.
Results: The developed device has a special feature of localization a field edge without any prior, subjective, alignment procedure of the user, i.e., the signals produced were processed by software storing the associated field edge profiles, localizing the edges in them, and finally displaying the calculated deviation. The uncertainty in field edge location difference was estimated to be <0.1 mm (k = 2). The calculated uncertainty is lower than for other, commercially available, methods for light field–radiation field congruence also presented in this work.
Conclusions: A method to check the light field–radiation field congruence of x-ray systems was developed to improve the limitations found in existing methods, such as device detector resolution, subjective operator steps, or the lack of storing results for later analysis. The development work overcame several challenges including mathematically describing real-life edges of light and radiation fields, noise reduction of radiation edges, and mapping/quantification of the rarely observed phenomenon of focal spot wandering. The assessment of the method showed that the listed limitations were overcome, and the aims were accomplished. It is therefore believed that the device can improve the work in quality controls of x-ray systems.
Better knowledge of elemental composition of patient tissues may improve the accuracy of absorbed dose delivery
in brachytherapy. Deficiencies of water-based protocols have been recognized and work is ongoing to implement
patient-specific radiation treatment protocols. A model based iterative image reconstruction algorithm DIRA
has been developed by the authors to automatically decompose patient tissues to two or three base components
via dual-energy computed tomography. Performance of an updated version of DIRA was evaluated for the
determination of prostate calcification. A computer simulation using an anthropomorphic phantom showed that
the mass fraction of calcium in the prostate tissue was determined with accuracy better than 9%. The calculated
mass fraction was little affected by the choice of the material triplet for the surrounding soft tissue. Relative
differences between true and approximated values of linear attenuation coefficient and mass energy absorption
coefficient for the prostate tissue were less than 6% for photon energies from 1 keV to 2 MeV. The results indicate
that DIRA has the potential to improve the accuracy of dose delivery in brachytherapy despite the fact that
base material triplets only approximate surrounding soft tissues.
The extrinsic (absolute) efficiency of a phosphor is expressed as the ratio of light energy emitted per unit area at the
phosphor surface to incident x-ray energy fluence. A model described in earlier work has shown that by knowing the
intrinsic efficiency, the particle size, the thickness and the light extinction factor ξ, it is possible to deduce the extrinsic
efficiency for an extended range of particle sizes and layer thicknesses for a given design. The model has been tested on
Gd2O2S:Tb and ZnS:Cu fluorescent layers utilized in two quality assurance devices, respectively, aimed for the
assessment of light field and radiation field congruence in diagnostic radiology. The first unit is an established device
based on both fluorescence and phosphorescence containing an x-ray sensitive phosphor (ZnS:Cu) screen comprising a
long afterglow. Uncertainty in field edge position is estimated to 0.8 mm (k=2). The second unit is under development
and based on a linear CCD sensor which is sensitized to x-rays by applying a Gd2O2S:Tb scintillator. The field profiles
and the corresponding edge location are then obtained and compared. Uncertainty in field edge location is estimated to
0.1 mm (k=2).
The properties of the radioluminescent layers are essential for the functionality of the devices and have been optimized
utilizing the previously developed and verified model. A theoretical description of the maximization of phosphorescence
is also briefly discussed as well as an interesting finding encountered during the development processes: focal spot
wandering. The oversimplistic physical assumptions made in the radioluminescence model have not been found to lead
the optimizing process astray. The obtained functionality is believed to be adequate within their respective limitations for
both devices.
For optimization and evaluation of image quality, one can use visual grading experiments, where observers rate some
aspect of image quality on an ordinal scale. To take into account the ordinal character of the data, ordinal logistic
regression is used in the statistical analysis, an approach known as visual grading regression (VGR). In the VGR model
one may include factors such as imaging parameters and post-processing procedures, in addition to patient and observer
identity. In a single-image study, 9 radiologists graded 24 cardiac CTA images acquired with ECG-modulated tube
current using standard settings (310 mAs), reduced dose (62 mAs) and reduced dose after post-processing. Image quality
was assessed using visual grading with five criteria, each with a five-level ordinal scale from 1 (best) to 5 (worst). The
VGR model included one term estimating the dose effect (log of mAs setting) and one term estimating the effect of postprocessing.
The model predicted that 115 mAs would be required to reach an 80% probability of a score of 1 or 2 for
visually sharp reproduction of the heart without the post-processing filter. With the post-processing filter, the
corresponding figure would be 86 mAs. Thus, applying the post-processing corresponded to a dose reduction of 25%.
For other criteria, the dose-reduction was estimated to 16-26%. Using VGR, it is thus possible to quantify the potential
for dose-reduction of post-processing filters.
To analyze visual grading experiments, ordinal logistic regression (here called visual grading regression, VGR) may be
used in the statistical analysis. In addition to types of imaging or post-processing, the VGR model may include factors
such as patient and observer identity, which should be treated as random effects. Standard software does not allow
random factors in ordinal logistic regression, but using Generalized Linear Latent And Mixed Models (GLLAMM) this
is possible. In a single-image study, 9 radiologists graded 24 cardiac Computed Tomography Angiography (CTA)
images with reduced dose without and after post-processing with a 2D adaptive filter, using five image quality criteria.
First, standard ordinal logistic regression was carried out, treating filtering, patient and observer identity as fixed effects.
The same analysis was then repeated with GLLAMM, treating filtering as a fixed effect and patient and observer identity
as random effects. With both approaches, a significant effect (p<0.01) of the filtering was found for all five criteria. No
dramatic differences in parameter estimates or significance levels were found between the two approaches. It is
concluded that random effects can be appropriately handled in VGR using GLLAMM, but no major differences in the
results were found in a preliminary evaluation.
The primary aim of the present work was to analyze the effects of varying scatter-to-primary ratios on the appearance of
simulated nodules in chest tomosynthesis section images. Monte Carlo simulations of the chest tomosynthesis system
GE Definium 8000 VolumeRAD (GE Healthcare, Chalfont St. Giles, UK) were used to investigate the variation of
scatter-to-primary ratios between different angular projections. The simulations were based on a voxel phantom created
from CT images of an anthropomorphic chest phantom. An artificial nodule was inserted at 80 different positions in the
simulated phantom images, using five different approaches for the scatter-to-primary ratios in the insertion process. One
approach included individual determination of the scatter-to primary-ratio for each projection image and nodule location,
while the other four approaches were using mean value, median value and zero degree projection value of the scatter-toprimary
ratios at each nodule position as well as using a constant scatter-to-primary ratio of 0.5 for all nodule positions.
The results indicate that the scatter-to-primary ratios vary up to a factor of 10 between the different angular
tomosynthesis projections (±15°). However, the error in the resulting nodule contrast introduced by not taking all
variations into account is in general smaller than 10 %.
Monte Carlo (MC) computer simulation of chest x-ray imaging systems has hitherto been performed using anthropomorphic phantoms with too large (3 mm) voxel sizes. The aim for this work was to develop and use a Monte Carlo computer program to compute projection x-ray images of a high-resolution anthropomorphic voxel phantom for visual clinical image quality evaluation and dose-optimization. An Alderson anthropomorphic chest phantom was imaged in a CT-scanner and reconstructed with isotropic voxels of 0.7 mm. The phantom was segmented and included in a Monte Carlo computer program using the collision density estimator to derive the energies imparted to the detector per unit area of each pixel by scattered photons. The image due to primary photons was calculated analytically including a pre-calculated detector response function. Attenuation and scatter of x-rays in the phantom, grid and image detector was considered. Imaging conditions (tube voltage, anti-scatter device) were varied and the images compared to a real computed radiography (Fuji FCR 9501) image. Four imaging systems were simulated (two tube voltages 81 kV and 141 kV using either a grid with ratio 10 or a 30 cm air gap). The effect of scattered radiation on the visibility of thoracic vertebrae against the heart and lungs is demonstrated. The simplicity in changing the imaging conditions will allow us not only to produce images of existing imaging systems, but also of hypothetical, future imaging systems. We conclude that the calculated images of the high-resolution voxel phantom are suitable for human detection experiments of low-contrast lesions.
To evaluate the image quality of clinical radiographs with two different methods, and to find correlations between the two methods.
Based on fifteen lumbar spine radiographs, two new sets of images were created. A hybrid image set was created by adding two distributions of artificial lesions to each original image. The image quality parameters spatial resolution and noise were manipulated and a total of 210 hybrid images were created. A set of 105 disease-free images was created by applying the same combinations of spatial resolution and noise to the original images. The hybrid images were evaluated with the free-response forced error experiment (FFE) and the normal images with visual grading analysis (VGA) by nine experienced radiologists. The VGA study showed that images with low noise are preferred over images with higher noise levels. The alteration of the MTF had a limited influence on the VGA score. For the FFE study the visibility of the lesions was independent of the spatial resolution and the noise level. In this study we found no correlation between the two methods, probably because the detectability of the artificial lesions was not influenced by the manipulations of noise level and resolution. Hence, the detection of lesions in lumbar spine radiography may not be a quantum-noise limited task. The results show the strength of the VGA technique in terms of detecting small changes in the two image quality parameters. The method is more robust and has a higher statistical power than the ROC related method and could therefore, in some cases, be more suitable for use in optimization studies.
Cone-beam computed tomography (CT) projections were calculated by the Monte Carlo method for two cylindrical water phantoms of different sizes and for an antropomorphic voxel phantom with and without the presence of an anti-scatter grid. The scatter-to-primary ratio (SPR) was evaluated for each projection and the dependence of the amount of scattered radiation on the phantom size, cone beam size, photon energy, and antiscatter grid was investigated. It was found that the amount of scattered radiation is a slowly varying function of position in the image plane whose values, depending on configuration parameters, may cover a range of several magnitudes. The SPR reflects changes in the amount of primary photons and may reach values around 5 for large phantoms, wide beams and 120 kV spectrum or even higher values for low energy photons.
A Monte Carlo program has been developed to model X-ray imaging systems. It incorporates an adult voxel phantom and includes anti-scatter grid, radiographic screen and film. The program can calculate contrast and noise for a series of anatomical details. The use of measured H and D curves allows the absolute calculation of the patient entrance air kerma for a given film optical density (or vice versa). Effective dose can also be estimated. In an initial validation, the program was used to predict the optical density for exposures with plastic slabs of various thicknesses. The agreement between measurement and calculation was on average within 5%. In a second validation, a comparison was made between computer simulations and measurements for chest and lumbar spine patient radiographs. The predictions of entrance air kerma mostly fell within the range of measured values (e.g. chest PA calculated 0.15 mGy, measured 0.12 - 0.17 mGy). Good agreement was also obtained for the calculated and measured contrasts for selected anatomical details and acceptable agreement for dynamic range. It is concluded that the program provides a realistic model of the patient and imaging system. It can thus form the basis of a detailed study and optimization of X-ray imaging systems.
A novel approach to patient dose and image quality optimization was developed and implemented for chest and lumbar spine radiography. A Monte Carlo model of the imaging chain, including an anthropomorphic voxel-phantom to simulate the patient, was utilized. Detector noise and system unsharpness were modeled and their influence on image quality considered. Image quality was quantified by the contrast ((Delta) OD) and the ideal observer signal-to-noise (SNR) for a number of relevant image details at various positions in the anatomy and measures of dynamic range (DR). Among systems evaluated in a clinical trial, a reference system, acknowledged to yield acceptable image quality, was selected. A large variety of other imaging conditions were simulated and compared to the reference system. Some of the simulated systems were found to give as good imaging performance but at substantially reduced patient doses: 35% and 50% reduction in the lumbar spine AP and the chest PA view, respectively. The model was also used to define a single-valued 'figure-of- merit,' the physical image quality score, PIQS, with the aim to make possible ranking of the imaging systems. By comparing the ranking according to PIQS with radiologists' ranking it was possible to analyze the features in the images which are clinically important.
KEYWORDS: Receptors, Photons, Modulation transfer functions, Signal to noise ratio, Imaging systems, X-rays, Image quality, Monte Carlo methods, Systems modeling, Spatial frequencies
Inappropriate or poorly designed x-ray imaging systems can lead to inadequate image quality and/or excessive patient absorbed dose. To study this dilemma, we have developed a computer program, based on Monte Carlo methods, to model the imaging chain and to optimize the design of individual imaging system components. The Monte Carlo method is used to simulate the transport of x-ray photons through the patient and anti-scatter device and into the image receptor. Image quality is calculated in terms of contrast and signal-to-noise ratio (SNR) and patient risk in terms of mean absorbed dose. The model of the radiographic screen includes the statistics of x-ray to light conversion and diffusion of light photons and the spatial distribution of absorbed x rays. The optimal system was defined as that which, for a constant measure of image quality, results in the lowest mean absorbed dose in the patient. The results of the model agree with measured data. Examples are given for different measures of reducing the absorbed dose for constant SNR in a simulated lumbar spine examination. At the optimal tube potential, the dose reductions associated with using a thicker screen, a fiber-interspaced grid and an additional Cu-filtration are 53%, 42%, and 31%, respectively.
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