Abstract:The purpose of the work was to test if effective detective quantum efficiency (eDQE) could be useful for optimisation of radiographic factors for computed radiography (CR) for adult chest examinations. The eDQE was therefore measured across a range of kilovoltage, with and without an anti-scatter grid. The modulation transfer function, noise power spectra, transmission factor and scatter fraction were measured with a phantom made of sheets of Aluminum and Acrylic. The entrance air kerma was selected to give an… Show more
“…For approximately matched detector entrance air kerma (Table 1), the eDE is highest at 50 kVp and decreases as the tube voltage increases. This result is similar to that reported by Ertan et al [45], who found that eDE was superior at low tube voltages on a CR system from the same vendor (Agfa) as that employed here, as did Samei et al [23], albeit with an integrated digital imaging system. of 0.77 (p,0.008) was found; both the mean eDE kV_X and VGAS increase as the tube voltage decreases.…”
Objective: The purpose of this study was to examine the correlation between the quality of visually graded patient (clinical) chest images and a quantitative assessment of chest phantom (physical) images acquired with a computed radiography (CR) imaging system.
Methods:The results of a previously published study, in which four experienced image evaluators graded computer-simulated posteroanterior chest images using a visual grading analysis scoring (VGAS) scheme, were used for the clinical image quality measurement. Contrast-to-noise ratio (CNR) and effective dose efficiency (eDE) were used as physical image quality metrics measured in a uniform chest phantom. Although optimal values of these physical metrics for chest radiography were not derived in this work, their correlation with VGAS in images acquired without an antiscatter grid across the diagnostic range of X-ray tube voltages was determined using Pearson's correlation coefficient.Results: Clinical and physical image quality metrics increased with decreasing tube voltage. Statistically significant correlations between VGAS and CNR (R50.87, p,0.033) and eDE (R50.77, p,0.008) were observed.
Conclusion:Medical physics experts may use the physical image quality metrics described here in quality assurance programmes and
“…For approximately matched detector entrance air kerma (Table 1), the eDE is highest at 50 kVp and decreases as the tube voltage increases. This result is similar to that reported by Ertan et al [45], who found that eDE was superior at low tube voltages on a CR system from the same vendor (Agfa) as that employed here, as did Samei et al [23], albeit with an integrated digital imaging system. of 0.77 (p,0.008) was found; both the mean eDE kV_X and VGAS increase as the tube voltage decreases.…”
Objective: The purpose of this study was to examine the correlation between the quality of visually graded patient (clinical) chest images and a quantitative assessment of chest phantom (physical) images acquired with a computed radiography (CR) imaging system.
Methods:The results of a previously published study, in which four experienced image evaluators graded computer-simulated posteroanterior chest images using a visual grading analysis scoring (VGAS) scheme, were used for the clinical image quality measurement. Contrast-to-noise ratio (CNR) and effective dose efficiency (eDE) were used as physical image quality metrics measured in a uniform chest phantom. Although optimal values of these physical metrics for chest radiography were not derived in this work, their correlation with VGAS in images acquired without an antiscatter grid across the diagnostic range of X-ray tube voltages was determined using Pearson's correlation coefficient.Results: Clinical and physical image quality metrics increased with decreasing tube voltage. Statistically significant correlations between VGAS and CNR (R50.87, p,0.033) and eDE (R50.77, p,0.008) were observed.
Conclusion:Medical physics experts may use the physical image quality metrics described here in quality assurance programmes and
“…In particular, the results for the W/Rh combination were greater for the grid-in case. Furthermore, these results showed close agreement with a non-prewhitened match filter with eye response model observer (d') normalized for MGD.The quantities effective detective quantum efficiency (eDQE) and effective noise equivalent quanta (eNEQ) can be seen as a development of the work of Wagner et al [1] , by Samei et al [2] and Ertan et al [3] with application to digital radiographic systems. The eDQE is an attempt to broaden the notion of the detector centric metric of detective quantum efficiency (DQE) to include system parameters such as focus blurring and system scatter rejection methods.…”
supporting
confidence: 67%
“…In the works of Samei et al [2] and Ertan et al [3] the MTF was calculated from an edge placed on the top of the phantom. This configuration introduces a low frequency drop (LFD) in the MTF curve, even if a small region of interest (ROI) is used to calculate the MTF.…”
Section: Resultsmentioning
confidence: 99%
“…The quantities effective detective quantum efficiency (eDQE) and effective noise equivalent quanta (eNEQ) can be seen as a development of the work of Wagner et al [1] , by Samei et al [2] and Ertan et al [3] with application to digital radiographic systems. The eDQE is an attempt to broaden the notion of the detector centric metric of detective quantum efficiency (DQE) to include system parameters such as focus blurring and system scatter rejection methods.…”
Effective detective quantum efficiency (eDQE) and effective noise equivalent quanta (eNEQ) were recently introduced to broaden the notion of DQE and NEQ by including system parameters such as focus blurring and system scatter rejection methods. This work investigates eDQE and eNEQ normalized for mean glandular dose (eNEQ MGD ) as a means to characterize and select optimal exposure parameters for a digital mammographic system. The eDQE was measured for three anode/filter combinations, with and without anti-scatter grid and for four thicknesses of poly(methylmethacrylate) (PMMA). The modulation transfer function used to calculate eDQE and eNEQ was measured from an edge positioned at 20,40,60,70 mm above the table top without scattering material in the beam. The grid-in eDQE results for all A/F settings were generally larger than those for grid-out. Contrarily, the eNEQ MGD results were higher for grid-out than gridin, with a maximum difference of 61% among all A/F combinations and PMMA thicknesses. The W/Rh combination gave the highest eNEQ MGD for all PMMA thicknesses compared to the other A/F combinations (for grid-in and grid-out), supporting the results of alternative methods (e.g. the signal difference to noise ratio method). The eNEQ MGD was then multiplied with the contrast obtained from a 0.2mm Al square, resulting in a normalized quantity that was higher for the W/Rh combination than for the other A/F combinations. In particular, the results for the W/Rh combination were greater for the grid-in case. Furthermore, these results showed close agreement with a non-prewhitened match filter with eye response model observer (d') normalized for MGD.The quantities effective detective quantum efficiency (eDQE) and effective noise equivalent quanta (eNEQ) can be seen as a development of the work of Wagner et al [1] , by Samei et al [2] and Ertan et al [3] with application to digital radiographic systems. The eDQE is an attempt to broaden the notion of the detector centric metric of detective quantum efficiency (DQE) to include system parameters such as focus blurring and system scatter rejection methods. This study applies the eDQE and eNEQ methodology to a digital mammographic system. The formulation of eDQE attempts to compare a system against an ideal imaging system with perfect x-ray detection and scatter rejection, however a patient dose marker is not included. For this reason, eNEQ normalized for the mean glandular dose (MGD) was included in this study (eNEQ MGD ), as system configurations that produce high eDQE may not be the best clinical choice. It is possible that the patient dose associated with parameters that give a high value eDQE could be higher than the patient dose of configuration that is 'suboptimal' in terms of eDQE. The eNEQ MGD describes the impact of the patient dose on the chosen configuration but this term does not give any indication on object detectability. As an example, lower patient dose configurations (eg grid-in), can lead to higher eNEQ MGD without leading to higher object detectabili...
“…Detective quantum efficiency (DQE) determines the ability of a detector to transfer the signal-to-noise ratio (SNR) within the detector as a function of spatial frequency [ 10 ]. The DQE helps characterise digital image detectors and has been used to compare detectors [ 11 , 12 ]. However, DQE is not optimal for assessing overall image quality and performance of the entire imaging system because it does not include impact from the magnification, focal spot blurring, the appearance of scatter radiation generated by the patient, or the presence of anti-scatter grids [ 13 ].…”
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.
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