Contrast-detail analysis of three flat panel detectors for digital radiography

Image quality and radiation dose in planar imaging - Image quality figure of merits from the CDRAD phantom

Purpose

A contrast‐detail phantom such as CDRAD is frequently used for quality assurance, optimization of image quality, and several other purposes. However, it is often used without considering the uncertainty of the results. The aim of this study was to assess two figure of merits (FOM) originating from CDRAD regarding the variations of the FOMs by dose utilized to create the x‐ray image. The probability of overlapping (assessing an image acquired at a lower dose as better than an image acquired at a higher dose) was determined.

Methods

The CDRAD phantom located underneath 12, 20, and 26 cm PMMA was imaged 16 times at five dose levels using an x‐ray system with a flat‐panel detector. All images were analyzed by CDRAD Analyser, version 1.1, which calculated the FOM inverse image quality figure (IQF_inv) and gave contrast detail curves for each image. Inherent properties of the CDRAD phantom were used to derive a new FOM h, which describes the size of the hole with the same diameter and depth that is just visible. Data were analyzed using heteroscedastic regression of mean and variance by dose. To ease interpretation, probabilities for overlaps were calculated assuming normal distribution, with associated bootstrap confidence intervals.

Results

The proportion of total variability in IQF_inv, explained by the dose (R²), was 91%, 85%, and 93% for 12, 20, and 26 cm PMMA. Corresponding results for h were 91%, 89%, and 95%. The overlap probability for different mAs levels was 1% for 0.8 vs 1.2 mAs, 5% for 1.2 vs 1.6 mAs, 10% for 1.6 vs 2.0 mAs, and 10% for 2.0 mAs vs 2.5 mAs for 12 cm PMMA. For 20 cm PMMA, it was 0.5% for 10 vs 16 mAs, 13% for 16 vs 20 mAs, 14% for 20 vs 25 mAs, and 14% for 25 vs 32 mAs. For 26 cm PMMA, the probability varied from 0% to 6% for various mAs levels. Even though the estimated probability for overlap was small, the 95% confidence interval (CI) showed relatively large uncertainties. For 12 cm PMMA, the associated CI for 0.8 vs 1.2 mAs was 0.1–3.2%, and the CI for 1.2 vs 1.6 mAs was 2.1–7.8%.

Conclusions

Inverse image quality figure and h are about equally related to dose level. The FOM h, which describes the size of a hole that should be seen in the image, may be a more intuitive FOM than IQF_inv. However, considering the probabilities for overlap and their confidence intervals, the FOMs deduced from the CDRAD phantom are not sensitive to dose. Hence, CDRAD may not be an optimal phantom to differentiate between images acquired at different dose levels.

Can the non-pre-whitening model observer, including aspects of the human visual system, predict human observer performance in mammography?

PURPOSE

In mammography, images are processed prior to display. Current methodologies based on physical image quality measurements are however not designed for the evaluation of processed images. Model observers (MO) might be suitable for this evaluation. The aim of this study was to investigate whether the non-pre-whitening (NPW) MO can be used to predict human observer performance in mammography-like images by including different aspects of the human visual system (HVS).

METHODS

The correlation between human and NPW MO performance has been investigated for the detection of disk shaped objects in simulated white noise (WN) and clustered lumpy backgrounds (CLB), representing quantum noise limited and mammography-like images respectively. The images were scored by the MO and five human observers in a 2-alternative forced choice experiment.

RESULTS

For WN images it was found that the log likelihood ratio (RLR2), which expresses the goodness of fit, was highest (0.44) for the NPW MO without addition of HVS aspects. For CLB the RLR2 improved from 0.46 to 0.65 with addition of HVS aspects. The correlation was affected by object size and background.

CONCLUSIONS

This study shows that by including aspects of the HVS, the performance of the NPW MO can be improved to better predict human observer performance. This demonstrates that the NPW MO has potential for image quality assessment. However, due to the dependencies found in the correlation, the NPW MO can only be used for image quality assessment for a limited range of object sizes and background variability.

Contrast detail phantom comparison on a commercially available unit. Digital breast tomosynthesis (DBT) versus full-field digital mammography (FFDM)

The performance of a commercial digital mammographic system working in 2D planar versus tomosynthesis mode was evaluated in terms of the image signal difference to noise ratio (SDNR). A contrast detail phantom was obtained embedding 1 cm Plexiglas, including 49 holes of different diameter and depth, between two layers containing a breast-simulating material. The phantom was exposed with the details plane perpendicular to the X-ray beam using the manufacturer's standard clinical breast acquisition parameters. SDNR in the digital breast tomosynthesis (DBT) images was higher than that of the full-field digital mammography (FFDM) for 38 out of 49 details in complex background conditions. These differences (p < 0.05) are statistically significant for 19 details out of 38. The relative SDNR results for DBT and FFDM images showed a dependence on the diameter of the details considered. This paper proposes an initial framework for a global image quality evaluation for commercial systems that can operate with different image acquisition modality using the same detector.

Quality control measurements for digital x-ray detectors

This paper describes a digital radiography (DR) quality control protocol for DR detectors from the forthcoming report from the Institute of Physics and Engineering in Medicine (IPEM). The protocol was applied to a group of six identical caesium iodide (CsI) digital x-ray detectors to assess reproducibility of methods, while four further detectors were assessed to examine the wider applicability. Twelve images with minimal spatial frequency processing are required, from which the detector response, lag, modulation transfer function (MTF), normalized noise power spectrum (NNPS) and threshold contrast-detail (c-d) detectability are calculated. The x-ray spectrum used was 70 kV and 1 mm added copper filtration, with a target detector air kerma of 2.5 µGy for the NNPS and c-d results. In order to compare detector performance with previous imaging technology, c-d data from four screen/film systems were also acquired, at a target optical density of 1.5 and an average detector air kerma of 2.56 µGy. The DR detector images were typically acquired in 20 min, with a further 45 min required for image transfer and analysis. The average spatial frequency for the 50% point of the MTF for six identical detectors was 1.29 mm(-1) ± 0.05 (3.9% coefficient of variation (cov)). The air kerma set for the six systems was 2.57 µGy ± 0.13 (5.0% cov) and the NNPS at this air kerma was 1.42 × 10(-5) mm(2) (6.5% cov). The detective quantum efficiency (DQE) measured for the six identical detectors was 0.60 at 0.5 mm(-1), with a maximum cov of 10% at 2.9 mm(-1), while the average DQE was 0.56 at 0.5 mm(-1) for three CsI detectors from three different manufacturers. Comparable c-d performance was found for these detectors (5.9% cov) with an average threshold contrast of 0.46% for 11 mm circular discs. The average threshold contrast for the S/F systems was 0.70% at 11 mm, indicating superior imaging performance for the digital systems. The protocol was found to be quick, reproducible and gave an in-depth assessment of performance for a range of digital x-ray detectors.

[Correlation between basic imaging properties and subjective evaluations of two digital radiographic X-ray systems based on direct-conversion flat panel detector]

The purpose of this study was to examine the correlation between the basic imaging properties of two digital radiographic X-ray systems with a direct conversion flat-panel detector and their image qualities, which were evaluated by the observer in hard copy and soft copy studies. The subjective image quality was evaluated and compared in terms of the low-contrast detectability and image sharpness in the two digital radiographic X-ray systems. We applied the radiographs of a contrast detail phantom to the evaluation of low-contrast detectability and analyzed the contrast detail diagrams. Finally, low-contrast detectability was evaluated by the image quality figure (IQF) calculated from the contrast detail diagrams. Also, the subjective image sharpness of human dry bones of two systems was examined and evaluated by the normalized-rank method. The results indicated that System A tended to provide superior subjective image quality compared to System B in both observer studies. We also found high correlations between IQFs and basic imaging properties, such as the noise power spectrum (NPS) and the noise equivalent quantum (NEQ). In conclusion, the low-contrast detectability of the two digital radiographic X-ray systems with a direct conversion flat-panel detector corresponded to the NPS and the NEQ in both outputs (soft copy and hard copy). On the other hand, the subjective image sharpness of human dry bones was affected by their noise properties.

Application of QC_DR software for acceptance testing and routine quality control of direct digital radiography systems: initial experiences using the Italian Association of Physicist in Medicine quality control protocol

Ideally, medical x-ray imaging systems should be designed to deliver maximum image quality at an acceptable radiation risk to the patient. Quality assurance procedures are employed to ensure that these standards are maintained. A quality control protocol for direct digital radiography (DDR) systems is described and discussed. Software to automatically process and analyze the required images was developed. In this paper, the initial results obtained on equipment of different DDR manufacturers were reported. The protocol was developed to highlight even small discrepancies in standard operating performance.

A comparative contrast-detail study of five medical displays

The objective of this study was to compare the contrast-detail performance of five different commercial liquid crystal displays (LCDs) to other LCD and cathode-ray tube (CRT) displays for medical applications. A contrast-detail phantom, supplemented with 5 in. of acrylic, was imaged on a commercial digital radiographic system using techniques comparable to chest radiography. The phantom design enabled observer evaluation by a four-alternative forced choice paradigm. The acquired images were independently scored by five observers on five medical display devices: a 5 megapixel monochrome LCD, a 3 megapixel monochrome LCD, a 9 megapixel color LCD, a 5 megapixel monochrome CRT, and a mammographic-grade monochrome CRT. The data were analyzed using the method suggested by the manufacturer based on a nearest neighbor correction technique. They were further analyzed using a logistic regression response model with a natural threshold using an overall chi-square test for display type followed by pairwise comparisons for individual display performance. The differences between the display devices were small. The standard analysis of the results based on the manufacturer-recommended method did not yield any statistically discernible trend among displays. The logistic regression analysis, however, indicated that the 5 megapixel monochrome LCD was statistically significantly (p <0.0001) superior to the others, followed by the 3 megapixel monochrome LCD (p<0.0001). The three other displays exhibited lower but generally similar performance characteristics. The findings suggest that 5 and 3 megapixel monochrome LCDs provide comparable but subtly superior contrast detectability than other tested displays, with the former performing slightly better in the detection of subtle and fine details.

Physical characteristics of GE Senographe Essential and DS digital mammography detectors

The purpose of this study was to investigate physical characteristics of two full field digital mammography (FFDM) systems (GE Senographe Essential and DS). Both are indirect conversion (x ray to light) alpha-Si flat panels coupled with a CsI(Tl) scintillator. The examined systems have the same pixel size (100 microm) but a different field of view: a conventional size 23 x 19.2 cm2 and a large field 24 X 30.7 cm2, specifically designed to image large breasts. In the GE Senographe Essential model relevant improvements in flat panel design were implemented and new deposition tools for metal, alpha-Si, and CsI(Tl) were introduced by GE. These changes in detector design are expected to be beneficial for advanced applications such as breast tomosynthesis. The presampling modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE) were measured for a wide range of exposure (25-240 microGy) with a RQA-M2 technique (28 kVp with a Mo/Mo target/filter combination and 2 mm of additional aluminum filtration). At 1, 2, and at 4 lp/mm MTF is equal to 0.9, 0.76, and 0.46 for the conventional field detector and to 0.85, 0.59, and 0.24 for the large field detector. The latter detector exhibits an improved NNPS due to a lower electronic noise and a better DQE that reaches 60%. In addition a contrast-detail analysis was performed with CDMAM 3.4 phantom and CDCOM software: GE Senographe DS showed statistically significant poorer detection ability in comparison with the GE Senographe Essential. These results could have been expected, at least qualitatively, considering the relative DQE of the two systems.

Early experience in the use of quantitative image quality measurements for the quality assurance of full field digital mammography x-ray systems

Quantitative image quality results in the form of the modulation transfer function (MTF), normalized noise power spectrum (NNPS) and detective quantum efficiency (DQE) are presented for nine full field digital mammography (FFDM) systems. These parameters are routinely measured as part of the quality assurance (QA) programme for the seven FFDM units covered by our centre. Just one additional image is required compared to the standard FFDM protocol; this is the image of an edge, from which the MTF is calculated. A variance image is formed from one of the flood images used to measure the detector response and this provides useful information on the condition of the detector with respect to artefacts. Finally, the NNPS is calculated from the flood image acquired at a target detector air kerma (DAK) of 100 microGy. DQE is then estimated from these data; however, no correction is currently made for effects of detector cover transmission on DQE. The coefficient of variation (cov) of the 50% point of the MTF for five successive MTF results was 1%, while the cov for the 50% MTF point for an a-Se system over a period of 17 months was approximately 3%. For four a-Se based systems, the cov for the NNPS at 1 mm(-1) for a target DAK of 100 microGy was approximately 4%; the same result was found for four CsI based FFDM units. With regard to the stability of NNPS over time, the cov for four NNPS results acquired over a period of 12 months was also approximately 4%. The effect of acquisition geometry on NNPS was also assessed for a CsI based system. NNPS data acquired with the antiscatter grid in place showed increased noise at low spatial frequency; this effect was more severe as DAK increased. DQE results for the three detector types (a-Se, CsI and CR) are presented as a function of DAK. Some reduction in DQE was found for both the a-Se and CsI based systems at a target DAK of 12.5 microGy when compared to DQE data acquired at 100 microGy. For the CsI based systems, DQE at 1 mm(-1) fell from 0.49 at 100 microGy to 0.38 at 12.5 microGy. For the a-Se units, there was a slightly greater reduction in average DQE at 1 mm(-1), from 0.53 at 100 microGy to 0.31 at 12.5 microGy. Somewhat different behaviour was seen for the CR unit; DQE (at 1 mm(-1)) increased from 0.40 at 100 microGy to 0.49 at 12.5 microGy; however, DQE fell to 0.30 at 420 microGy. DQE stability over time was assessed using the cov of DQE at 1 mm(-1) and a target DAK of 100 microGy; the cov for data acquired over a period of 17 months for an a-Se system was approximately 7%. For comparison with conventional testing methods, the cov was calculated for contrast-detail (cd) data acquired over the same period of time for this unit. The cov for the threshold contrast results (averaged for disc diameters between 0.1 mm and 2 mm) was 6%, indicating similar stability.

Information loss in visual assessments of medical images

We applied information theory to quantify information losses in assessing contrast-detail (C-D) analysis. Images of a C-D phantom were acquired with a flat panel detector (FPD) and a computed radiography (CR) by changing surface entrance doses. Six phantom radiographs (FPD: five images; CR: one image) were prepared for visual evaluations. Thirteen radiographers and two radiologists participated in the observation test. Detectability was defined as the shortest length of the cylinders of which border the observers could recognize from the background, and was recorded using row number. Information content was defined as the entropy summation operatorp(i)log(1/p(i)) with detection probabilities p(i), which were calculated from distribution of detection rate of the ith column. Information loss, in unit of bits, was calculated as the difference between information obtained and information content when all the columns were detected. The information losses decreased with the increase in cylinder diameters and with the increase in surface entrance dose. Because the information loss varies depending on distribution of detection rate, this method of using the information theory was expected to be more sensitive in evaluating the C-D image quality than using the averaged values of detectability.

Comparison of different commercial FFDM units by means of physical characterization and contrast-detail analysis

The purpose of this study was to perform a complete evaluation of three pieces of clinical digital mammography equipment. Image quality was assessed by performing physical characterization and contrast-detail (CD) analysis. We considered three different FFDM systems: a computed radiography unit (Fuji "FCR 5000 MA") and two flat-panel units, the indirect conversion a-Si based GE "Senographe 2000D" and the direct conversion a-Si based IMS "Giotto Image MD." The physical characterization was estimated by measuring the MTF, NNPS, and DQE of the detectors with no antiscatter grid and over the clinical range of exposures. The CD analysis was performed using a CDMAM 3.4 phantom and custom software designed for automatic computation of the contrast-detail curves. The physical characterization of the three digital systems confirms the excellent MTF properties of the direct conversion flat-panel detector (FPD). We performed a relative standard deviation (RSD) analysis, for investigating the different components of the noise presented by the three systems. It turned out that the two FPDs show a significant additive component, whereas for the CR system the statistical noise is dominant. The multiplicative factor is a minor constituent for all the systems. The two FPDs demonstrate better DQE, with respect to the CR system, for exposures higher than 70 microGy. The CD analysis indicated that the three systems are not statistically different for detail objects with a diameter greater than 0.3 mm. However, the IMS system showed a statistically significant different response for details smaller than 0.3 mm. In this case, the poor response of the a-Se detector could be attributed to its high-frequency noise characteristics, since its MTF, NEQ, and DQE are not inferior to those of the other systems. The CD results were independent of exposure level, within the investigated clinical range. We observed slight variations in the CD results, due to the changes in the visualization parameters (window/level and magnification factor). This suggests that radiologists would benefit from viewing images using varied window/level and magnification.