Digital Radiography Imaging Systems Research Articles

Visual Evaluation of Image Quality of a Low Dose 2D/3D Slot Scanner Imaging System Compared to Two Conventional Digital Radiography X-ray Imaging Systems.

The purpose of this study was to assess the image quality of the low dose 2D/3D slot scanner (LDSS) imaging system compared to conventional digital radiography (DR) imaging systems. Visual image quality was assessed using the visual grading analysis (VGA) method. This method is a subjective approach that uses a human observer to evaluate and optimise radiographic images for different imaging technologies. Methods and materials: ten posterior-anterior (PA) and ten lateral (LAT) images of a chest anthropomorphic phantoms and a knee phantom were acquired by an LDSS imaging system and two conventional DR imaging systems. The images were shown in random order to three (chest) radiologists and three experienced (knee) radiographers, who scored the images against a number of criteria. Inter- and intraobserver agreement was assessed using Fleiss’ kappa and weighted kappa. Results: the statistical comparison of the agreement between the observers showed good interobserver agreement, with Fleiss’ kappa coefficients of 0.27–0.63 and 0.23–0.45 for the chest and knee protocols, respectively. Comparison of intraobserver agreement also showed good agreement with weighted kappa coefficients of 0.27–0.63 and 0.23–0.45 for the chest and knee protocols, respectively. The LDSS imaging system achieved significantly higher VGA image quality compared to the DR imaging systems in the AP and LAT chest protocols (p < 0.001). However, the LDSS imaging system achieved lower image quality than one DR system (p ≤ 0.016) and equivalent image quality to the other DR systems (p ≤ 0.27) in the knee protocol. The LDSS imaging system achieved effective dose savings of 33–52% for the chest protocol and 30–35% for the knee protocol compared with DR systems. Conclusions: this work has shown that the LDSS imaging system has the potential to acquire chest and knee images at diagnostic quality and at a lower effective dose than DR systems.

Quantitative Image Quality Metrics of the Low-Dose 2D/3D Slot Scanner Compared to Two Conventional Digital Radiography X-ray Imaging Systems.

The aim of this study was to determine the quantitative image quality metrics of the low-dose 2D/3D EOS slot scanner X-ray imaging system (LDSS) compared with conventional digital radiography (DR) X-ray imaging systems. The effective detective quantum efficiency (eDQE) and effective noise quantum equivalent (eNEQ) were measured using chest and knee protocols. Methods: A Nationwide Evaluation of X-ray Trends (NEXT) of a chest adult phantom and a PolyMethylmethacrylate (PMMA) phantom were used for the chest and knee protocols, respectively. Quantitative image quality metrics, including effective normalised noise power spectrum (eNNPS), effective modulation transfer function (eMTF), eDQE and eNEQ of the LDSS and DR imaging systems were assessed and compared. Results: In the chest acquisition, the LDSS imaging system achieved significantly higher eNEQ and eDQE than the DR imaging systems at lower and higher spatial frequencies (0.001 ≤ p ≤ 0.044). For the knee acquisition, the LDSS imaging system also achieved significantly higher eNEQ and eDQE than the DR imaging systems at lower and higher spatial frequencies (0.001 ≤ p ≤ 0.002). However, there was no significant difference in eNEQ and eDQE between DR systems 1 and 2 at lower and higher spatial frequencies (0.10 < p < 1.00) for either chest or knee protocols. Conclusion: The LDSS imaging system performed well compared to the DR systems. Thus, we have demonstrated that the LDSS imaging system has the potential to be used for clinical diagnostic purposes.

A method to incorporate the effect of beam quality on image noise in a digitally reconstructed radiograph (DRR) based computer simulation for optimisation of digital radiography

The use of computer simulated digital x-radiographs for optimisation purposes has become widespread in recent years. To make these optimisation investigations effective, it is vital simulated radiographs contain accurate anatomical and system noise. Computer algorithms that simulate radiographs based solely on the incident detector x-ray intensity (‘dose’) have been reported extensively in the literature. However, while it has been established for digital mammography that x-ray beam quality is an important factor when modelling noise in simulated images there are no such studies for diagnostic imaging of the chest, abdomen and pelvis. This study investigates the influence of beam quality on image noise in a digital radiography (DR) imaging system, and incorporates these effects into a digitally reconstructed radiograph (DRR) computer simulator. Image noise was measured on a real DR imaging system as a function of dose (absorbed energy) over a range of clinically relevant beam qualities. Simulated ‘absorbed energy’ and ‘beam quality’ DRRs were then created for each patient and tube voltage under investigation. Simulated noise images, corrected for dose and beam quality, were subsequently produced from the absorbed energy and beam quality DRRs, using the measured noise, absorbed energy and beam quality relationships. The noise images were superimposed onto the noiseless absorbed energy DRRs to create the final images. Signal-to-noise measurements in simulated chest, abdomen and spine images were within 10% of the corresponding measurements in real images. This compares favourably to our previous algorithm where images corrected for dose only were all within 20%.

A Study of Scattered Radiation Effect on Digital Radiography Imaging System

A Study of Scattered Radiation Effect on Digital Radiography Imaging System

A comparison of digital radiography systems in terms of effective detective quantum efficiency

The purpose of this study is to compare digital radiography systems using the metric effective detective quantum efficiency (eDQE), which better reflects digital radiography imaging system performance under clinical operating conditions, in comparison with conventional metrics such as modulation transfer function (MTF), normalized noise power spectra (NNPS), and detective quantum efficiency (DQE). The eDQE was computed by the calculation of the MTF, the NNPS, the phantom attenuation and scatter, and estimation of x-ray flux. The physical characterization of the systems was obtained with the standard beam conditions RQA5 and RQA9, using the PA Chest phantom proposed by AAPM Report # 31 simulating the attenuation and scatter characteristics of the adult human thorax. The MTF (eMTF) was measured by using an edge test placed at the frontal surface of the phantom, the NNPS (eNNPS) was calculated from images of the phantom acquired at three different exposure levels covering the operating range of the system (E(0), which is the exposure at which a system is normally operated, 1/3 E(0), and 3 E0), and scatter measurements were assessed by using a beam-stop technique. The integral of DQE (IDQE) and eDQE (IeDQE) was calculated over the whole spatial frequency range. The eMTF results demonstrate degradation due to magnification and the presence of scattered radiation. The eNNPS was influenced by the grid presence, and in some systems, it contained structured noise. At typical clinical exposure levels, the magnitude of eDQE(0) with respect to DQE(0) at RQA9 beam conditions was 13%, 17%, 16%, 36%, and 24%, respectively, for Carestream DRX-1, Carestream DRX-1C, Carestream Direct View CR975, Philips Digital Diagnost VM, and GE Revolution XR/d. These results were confirmed by the ratio of IeDQE and IDQE in the same conditions. The authors confirm the robustness and reproducibility of the eDQE method. As expected, the DR systems performed better than the CR systems due to their superior signal-to-noise transfer characteristics. The results of this study suggest the eDQE method may provide an opportunity to more accurately assess the clinical performance of digital radiographic imaging systems by accounting for factors such as the presence of scatter, use of an antiscatter grid, and magnification and focal spot blurring effects, which are not reflected in conventional DQE measures.

Distal radius fracture arthroscopic intraarticular displacement measurement after open reduction and internal fixation from a volar approach

BackgroundThe purpose of this study was to assess articular surface reduction arthroscopically after volar locked-plate fixation of distal radius fractures (DRFs) via fluoroscopyguided open reduction/internal fixation. We also aimed to develop preoperative radiographic criteria to help assist in determining which DRFs may need arthroscopic evaluation. MethodsA total of 31 consecutive patients with DRF were prospectively enrolled. Posteroanterior (PA) and lateral radiographs as well as axial, coronal, and sagittal CT scans were obtained just after attempted reduction of the DRF. The widest articular displacement at the radiocarpal joint surface of the distal radius (preopD) was then measured using a digital radiography imaging system. The DRF was reduced under fluoroscopy, and a volar locked plate was applied. The degree of residual articular displacement was then measured arthroscopically, and the maximum displacement (postopD) was measured with a calibrated probe. ResultsOf the 31 patients, 7 had an arthroscopically assessed maximum postopD of ≥2mm after internal fixation. The correlation coefficients between each preopD and postopD of all radiographs and CTs were statistically significant. The cutoff values were 0.5mm for PA radiographs, 2.10mm for lateral radiographs, 2.15mm for axial CT scans, 3.15mm for coronal CT scans, and 1.20mm for sagittal CT scans. All cutoff values for PA and lateral radiographs and for axial, coronal, and sagittal CT scans were unsuitable as screening criteria for arthroscopic reduction of DRF because of their low sensitivities and specificities. The cutoff value of the new preopD (the sum of the preopDs determined by lateral radiography and coronal CT scan) was 5.80mm, and its sensitivity and specificity were 100% and 83.3%, respectively. ConclusionsBecause a new preopD cutoff value of 5.80mm is a good indicator for residual articular displacement after internal fixation of >2 mm, it is also a good indicator for the need for arthroscopic evaluation after internal fixation.

Investigation of Luminescence Properties of Lu$_{2}$SiO$_{5}$:Ce (LSO) Powder Scintillator in the X-Ray Radiography Energy Range

This paper investigates the light emission efficiency of Lu <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> SiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sub> :Ce (LSO) powder scintillator under conditions employed in projection X-ray imaging. Although single-crystal LSO has been thoroughly studied in medical imaging energies, the efficiency of powder LSO has not been previously investigated experimentally under X-ray medical radiography conditions. For this purpose, three scintillating screens with a coating thickness of 63.4, 108.4, and 172.5 mg/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> were prepared by sedimentation of LSO powder. Measurements of luminescence efficiency (emitted light energy flux over incident X-ray energy flux) were performed in the radiographic X-ray tube voltages range (40-140 kVp). Parameters related to X-ray detection, i.e., quantum detection efficiency, energy absorption efficiency and probability of K-fluorescence reabsorption were calculated. A theoretical model, describing radiation and light transfer, was employed to fit luminescence experimental data and to estimate values of the intrinsic conversion efficiency and of the light attenuation coefficients of the scintillating screens. The spectral compatibility of the LSO powder scintillator to various optical detectors used in digital radiography was also determined by performing light emission spectrum measurements and by taking into account the spectral sensitivity of electronic optical detectors. Maximum values of LSO luminescence efficiency were observed within the range from 40 to 60 kVp. The 172.5 mg/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> thick screen was found more efficient than the two thinner screens examined in our experiments. The intrinsic conversion efficiency of LSO (0.10) was found close to that of currently employed phosphors. Spectral compatibility data of LSO screens indicates that LSO may be efficiently coupled to optical detectors used in digital radiography imaging systems.

Comparison of adaptive linear interpolation and conventional linear interpolation for digital radiography systems

Some large field digital radiography systems are currently under development using multiple detectors. These small size two dimension detectors are abutted together to cover a large field. Physical gaps existing between adjacent detectors produce seams between the resultant subimages. In this paper, an adaptive linear interpolation algorithm was introduced for estimating missing information at the seams and was compared with conventional linear interpolation and with nonlinear interpolation. The effectiveness of the algorithms was evaluated for relative/absolute errors. Phantom images were acquired using prototype digital radiography systems. Seams with width ranging from two pixel to six pixel were introduced and adaptive linear interpolation algorithms were applied to estimate missing information at the seams. Quantitatively, the adaptive interpolation offers at least equivalent or less error than that of the linear interpolation algorithm. The experimental results prove that there is a significant difference between two algorithms for tested radiographic images. The comparison results also show that the adaptive interpolation offers better performance than nonlinear interpolation. When developing large field digital radiography imaging systems, gaps between adjacent detectors should be minimized. For narrow seams, the adaptive linear interpolation algorithm is a practical solution because of its simplicity and effectiveness.