Detective quantum efficiency measured as a function of energy for two full-field digital mammography systems

New Software for DQE Calculation in Digital Mammography Compliant with IEC 62220–1-2

Significant improvements in mammography systems have been achieved with the introduction of active matrix flat-panel digital detectors. The advent of this technology also makes it possible to implement computational methods for quantitative image analysis. This study describes new software created to perform detective quantum efficiency (DQE) calculations fully compliant with the IEC 62220–1-2 standard. Python-based software was developed that contains modules to calculate inverse conversion function, modulation transfer function (MTF), noise power spectrum (NPS), and DQE itself. A graphical user interface (GUI) and further add-ons make this software more user-friendly. Results are immediately displayed diagrammatically, and complete output data are exported to a .csv file. The code is available freely, as a compiled, executable file (.exe). The program was successfully tested using DICOM images obtained from mammography units from different manufacturers. This study also includes validation of the new software, based on comparisons of results obtained for the same set of data with two other, freely available programs.

Determination of DQE as a quantitative assessment of detectors in digital mammography: Measurements and calculation in practice

Introduction: Advances in digital detector technology and methods of image presentation in digital mammography now offer the possibility of implementing mathematical assessment methods to quantitative image analysis. The aim of this work was to develop new software to simplify the application of the existing international standard for DQE in digital mammography and show in detail how it can be applied, using a Siemens Mammomat Inspiration as a model.

Material and methods: Consistent with the IEC standard a 2 mm Al filter at the tube exit and images in DICOM format as raw data, without applying any additional post-processing were used. Measurements were performed for W/Rh anode/filter combination and different tube voltage values (26 ÷ 34 kV) without any anti-scatter grid. To verify new software doses ranging from 20-600 µGy were used in measurements. Exposure (air kerma) was measured using a calibrated radiation meter (Piranha Black 457, RTI Electronics AB, Sweden). MTF was determined, using an edge test device constructed specifically for this work.

Results: It has been demonstrated that with the new software the DQE can be measured with the accuracy required by the international standard IEC 62220-1-2. DQE has been presented as a function of spatial frequency for W/Rh anode/filter combination and different tube voltage.

Conclusions: New software was used successfully to analyze image quality parameters for the Siemens Mammomat Inspiration detector. This was done on the basis of an internationally accepted methodology. In the next step, mammographs with different detector types can be compared.

On the Response of a Micro Non-Destructive Testing X-ray Detector

Certain imaging performance metrics are examined for a state-of-the-art 20 μm pixel pitch CMOS sensor (RadEye HR), coupled to a Gd₂O₂S:Tb scintillator screen. The signal transfer property (STP), the modulation transfer function (MTF), the normalized noise power spectrum (NNPS) and the detective quantum efficiency (DQE) were estimated according to the IEC 62220-1-1:2015 standard. The detector exhibits excellent linearity (coefficient of determination of the STP linear regression fit, R² was 0.9978), while its DQE peaks at 33% and reaches 10% at a spatial frequency of 3 cycles/mm, for the measured with a Piranha RTI dosimeter (coefficient of variation CV = 0.03%) exposure value of 28.1 μGy DAK (detector Air Kerma). The resolution capabilities of the X-ray detector under investigation were compared to other commercial CMOS sensors, and were found in every case higher, except from the previous RadEye HR model (CMOS-Gd₂O₂S:Tb screen pair with 22.5 μm pixel pitch) version which had slightly better MTF. The present digital imager is designed for industrial inspection applications, nonetheless its applicability to medical imaging, as well as dual-energy is considered and certain approaches are discussed in this respect.

An experimental method to directly measure DQE[Formula: see text] at k = 0 for 2D x-ray imaging systems

The zero-frequency detective quantum efficiency (DQE), viz., DQE0, is defined as the ratio between output and input squared signal-to-noise ratio of an imaging system. In 1963, R. Shaw applied Fourier analysis to generalize DQE0 to the frequency-dependent DQE, i.e. DQE[Formula: see text]. Under conditions specified by Shaw, DQE[Formula: see text] is the same as DQE0 at k  =  0. The experimental measurement of DQE[Formula: see text] involves the measurement of system modulation transfer function (MTF) and noise power spectrum (NPS). Although the measurement of MTF is straightforward, the experimental measurements of NPS[Formula: see text] encountered several challenges. As a result, some experimental methods may yield a nonphysical NPS value at k  =  0, which makes the measured DQE(k)| k=0 deviate from the true zero-frequency DQE. This work presents new results from three aspects: 1) system drift is a significant error source when a large number of independent image acquisitions are involved in measuring NPS and DQE; 2) a cascaded systems analysis shows that the drift induces a global positive offset to the measured autocovariance function, and the offset is quantitatively related to the NPS error at k  =  0; 3) based on the measured autocovariance data, drift-induced offset can be estimated, so that errors in the measured NPS(k)| k=0 and DQE(k)| k=0 can be corrected. Both numerical simulations with known ground truth for DQE0 and experimental studies were performed to validate the proposed measurement method. The results demonstrated that the method mitigates the undesirable influence of system drift in DQE(k)| k=0 and DQE0, allowing the measured values consistent with the classical definition of zero-frequency DQE.

Measurement of effective detective quantum efficiency for a photon counting scanning mammography system and comparison with two flat panel full-field digital mammography systems

Effective detective quantum efficiency (eDQE) describes the resolution and noise properties of an imaging system along with scatter and primary transmission, all measured under clinically appropriate conditions. Effective dose efficiency (eDE) is the eDQE normalised to mean glandular dose and has been proposed as a useful metric for the optimisation of clinical imaging systems. The aim of this study was to develop a methodology for measuring eDQE and eDE on a Philips microdose mammography (MDM) L30 photon counting scanning system, and to compare performance with two conventional flat panel systems. A custom made lead-blocker was manufactured to enable the accurate determination of dose measurements, and modulation transfer functions were determined free-in-air at heights of 2, 4 and 6 cm above the breast support platform. eDQE were calculated for a Philips MDM L30, Hologic Dimensions and Siemens Inspiration digital mammography system for 2, 4 and 6 cm thick poly(methyl methacrylate) (PMMA). The beam qualities (target/filter and kilovoltage) assessed were those selected by the automatic exposure control, and anti-scatter grids were used where available. Measurements of eDQE demonstrate significant differences in performance between the slit- and scan-directions for the photon counting imaging system. MTF has been shown to be the limiting factor in the scan-direction, which results in a rapid fall in eDQE at mid-to-high spatial frequencies. A comparison with two flat panel mammography systems demonstrates that this may limit image quality for small details, such as micro-calcifications, which correlates with a more conventional image quality assessment with the CDMAM phantom. eDE has shown the scanning photon counting system offers superior performance for low spatial frequencies, which will be important for the detection of large low contrast masses. Both eDQE and eDE are proposed as useful metrics that should enable optimisation of the Philips MDM L30.

ALTERNATIVE FIGURES-OF-MERIT IN DIGITAL MAMMOGRAPHY

The aim of this study is to explore the use of a quality (Q) factor in digital mammography as a figure-of-merit. Q factors take a reference value into account and can be compared to a theoretical value. They are also intended to summarise the performance of any unit based on a number. The mean glandular dose (MGD)-normalised Q factors were also introduced based on the relationship of the Q factors with MGD. Interestingly, the automatic exposure control exposures did not render the maximum normalised Q factor values as expected, which could indicate the need for further optimisation. It was also noted that the Q factors and the CDMAM-related quality parameters can be confidently predicted for a given MGD which in turn may be compared to the measured values. This might be another way to consider or perform optimisation in digital mammography.

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%.

Impact of compressed breast thickness and dose on lesion detectability in digital mammography: FROC study with simulated lesions in real mammograms

PURPOSE

The aim of this work was twofold: (1) to examine whether, with standard automatic exposure control (AEC) settings that maintain pixel values in the detector constant, lesion detectability in clinical images decreases as a function of breast thickness and (2) to verify whether a new AEC setup can increase lesion detectability at larger breast thicknesses.

METHODS

Screening patient images, acquired on two identical digital mammography systems, were collected over a period of 2 yr. Mammograms were acquired under standard AEC conditions (part 1) and subsequently with a new AEC setup (part 2), programmed to use the standard AEC settings for compressed breast thicknesses ≤49 mm, while a relative dose increase was applied above this thickness. The images were divided into four thickness groups: T1 ≤ 29 mm, T2 = 30-49 mm, T3 = 50-69 mm, and T4 ≥ 70 mm, with each thickness group containing 130 randomly selected craniocaudal lesion-free images. Two measures of density were obtained for every image: a BI-RADS score and a map of volumetric breast density created with a software application (VolparaDensity, Matakina, NZ). This information was used to select subsets of four images, containing one image from each thickness group, matched to a (global) BI-RADS score and containing a region with the same (local) volpara volumetric density value. One selected lesion (a microcalcification cluster or a mass) was simulated into each of the four images. This process was repeated so that, for a given thickness group, half the images contained a single lesion and half were lesion-free. The lesion templates created and inserted in groups T3 and T4 for the first part of the study were then inserted into the images of thickness groups T3 and T4 acquired with higher dose settings. Finally, all images were visualized using the ViewDEX software and scored by four radiologists performing a free search study. A statistical jackknife-alternative free-response receiver operating characteristic analysis was applied.

RESULTS

For part 1, the alternative free-response receiver operating characteristic curves for the four readers were 0.80, 0.65, 0.55 and 0.56 in going from T1 to T4, indicating a decrease in detectability with increasing breast thickness. P-values and the 95% confidence interval showed no significant difference for the T3-T4 comparison (p = 0.78) while all the other differences were significant (p < 0.05). Separate analysis of microcalcification clusters presented the same results while for mass detection, the only significant difference came when comparing T1 to the other thickness groups. Comparing the scores of part 1 and part 2, results for the T3 group acquired with the new AEC setup and T3 group at standard AEC doses were significantly different (p = 0.0004), indicating improved detection. For this group a subanalysis for microcalcification detection gave the same results while no significant difference was found for mass detection.

CONCLUSIONS

These data using clinical images confirm results found in simple QA tests for many mammography systems that detectability falls as breast thickness increases. Results obtained with the AEC setup for constant detectability above 49 mm showed an increase in lesion detection with compressed breast thickness, bringing detectability of lesions to the same level.

Tailoring automatic exposure control toward constant detectability in digital mammography

PURPOSE

The automatic exposure control (AEC) modes of most full field digital mammography (FFDM) systems are set up to hold pixel value (PV) constant as breast thickness changes. This paper proposes an alternative AEC mode, set up to maintain some minimum detectability level, with the ultimate goal of improving object detectability at larger breast thicknesses.

METHODS

The default "opdose" AEC mode of a Siemens MAMMOMAT Inspiration FFDM system was assessed using poly(methyl methacrylate) (PMMA) of thickness 20, 30, 40, 50, 60, and 70 mm to find the tube voltage and anode/filter combination programmed for each thickness; these beam quality settings were used for the modified AEC mode. Detectability index (d'), in terms of a non-prewhitened model observer with eye filter, was then calculated as a function of tube current-time product (mAs) for each thickness. A modified AEC could then be designed in which detectability never fell below some minimum setting for any thickness in the operating range. In this study, the value was chosen such that the system met the achievable threshold gold thickness (Tt) in the European guidelines for the 0.1 mm diameter disc (i.e., Tt ≤ 1.10 μm gold). The default and modified AEC modes were compared in terms of contrast-detail performance (Tt), calculated detectability (d'), signal-difference-to-noise ratio (SDNR), and mean glandular dose (MGD). The influence of a structured background on object detectability for both AEC modes was examined using a CIRS BR3D phantom. Computer-based CDMAM reading was used for the homogeneous case, while the images with the BR3D background were scored by human observers.

RESULTS

The default opdose AEC mode maintained PV constant as PMMA thickness increased, leading to a reduction in SDNR for the homogeneous background 39% and d' 37% in going from 20 to 70 mm; introduction of the structured BR3D plate changed these figures to 22% (SDNR) and 6% (d'), respectively. Threshold gold thickness (0.1 mm diameter disc) for the default AEC mode in the homogeneous background increased by 62% in going from 20 to 70 mm PMMA thickness; in the structured background, the increase was 39%. Implementation of the modified mode entailed an increase in mAs at PMMA thicknesses >40 mm; the modified AEC held threshold gold thickness constant above 40 mm PMMA with a maximum deviation of 5% in the homogeneous background and 3% in structured background. SDNR was also held constant with a maximum deviation of 4% and 2% for the homogeneous and the structured background, respectively. These results were obtained with an increase of MGD between 15% and 73% going from 40 to 70 mm PMMA thickness.

CONCLUSIONS

This work has proposed and implemented a modified AEC mode, tailored toward constant detectability at larger breast thickness, i.e., above 40 mm PMMA equivalent. The desired improvement in object detectability could be obtained while maintaining MGD within the European guidelines achievable dose limit. (A study designed to verify the performance of the modified mode using more clinically realistic data is currently underway.).

Performance evaluation of a retrofit digital detector-based mammography system

A retrofit flat panel detector was integrated with a GE DMR+ analog mammography system and characterized using detective quantum efficiency (DQE). Technical system performance was evaluated using the European Guidelines protocol, followed by a limited evaluation of clinical image quality for 20 cases using image quality criteria in the European Guidelines. Optimal anode/filter selections were established using signal difference-to-noise ratio measurements. Only small differences in peak DQE were seen between the three anode/filter settings, with an average value of 0.53. For poly(methyl methacrylate) (PMMA) thicknesses above 60 mm, the Rh/Rh setting was the optimal anode/filter setting. The system required a mean glandular dose of 0.54 mGy at 30 kV Rh/Rh to reach the Acceptable gold thickness limit for 0.1 mm details. Imaging performance of the retrofit unit with the GE DMR+ is notably better than of powder based computed radiography systems and is comparable to current flat panel FFDM systems.

Positive predictive values by mammographic density and screening mode in the Norwegian Breast Cancer Screening Program

OBJECTIVE

To investigate the probability of breast cancer among women recalled due to abnormal findings on the screening mammograms (PPV-1) and among women who underwent an invasive procedure (PPV-2) by mammographic density (MD), screening mode and age.

METHODS

We used information about 28,826 recall examinations from 26,951 subsequently screened women in the Norwegian Breast Cancer Screening Program, 1996-2010. The radiologists who performed the recall examinations subjectively classified MD on the mammograms into three categories: fatty (<30% fibroglandular tissue); medium dense (30-70%) and dense (>70%). Screening mode was defined as screen-film mammography (SFM) and full-field digital mammography (FFDM). We examined trends of PPVs by MD, screening mode and age. We used logistic regression to estimate odds ratio (OR) of screen-detected breast cancer associated with MD among women recalled, adjusting for screening mode and age.

RESULTS

PPV-1 and PPV-2 decreased by increasing MD, regardless of screening mode (p for trend <0.05 for both PPVs). PPV-1 and PPV-2 were statistically significantly higher for FFDM compared with SFM for women with fatty breasts. Among women recalled, the adjusted OR of breast cancer decreased with increasing MD. Compared with women with fatty breasts, the OR was 0.90 (95% CI: 0.84-0.96) for those with medium dense breasts and 0.85 (95% CI: 0.76-0.95) for those with dense breasts.

CONCLUSION

PPVs decreased by increasing MD. Fewer women needed to be recalled or undergo an invasive procedure to detect one breast cancer among those with fatty versus dense breasts in the screening program in Norway, 1996-2010.

Characterization of a high-energy in-line phase contrast tomosynthesis prototype

PURPOSE

In this research, a high-energy in-line phase contrast tomosynthesis prototype was developed and characterized through quantitative investigations and phantom studies.

METHODS

The prototype system consists of an x-ray source, a motorized rotation stage, and a CMOS detector with a pixel pitch of 0.05 mm. The x-ray source was operated at 120 kVp for this study, and the objects were mounted on the rotation stage 76.2 cm (R1) from the source and 114.3 cm (R2) from the detector. The large air gap between the object and detector guarantees sufficient phase-shift effects. The quantitative evaluation of this prototype included modulation transfer function and noise power spectrum measurements conducted under both projection mode and tomosynthesis mode. Phantom studies were performed including three custom designed phantoms with complex structures: a five-layer bubble wrap phantom, a fishbone phantom, and a chicken breast phantom with embedded fibrils and mass structures extracted from an ACR phantom. In-plane images of the phantoms were acquired to investigate their image qualities through observation, intensity profile plots, edge enhancement evaluations, and/or contrast-to-noise ratio calculations. In addition, the robust phase-attenuation duality (PAD)-based phase retrieval method was applied to tomosynthesis for the first time in this research. It was utilized as a preprocessing method to fully exhibit phase contrast on the angular projection before reconstruction.

RESULTS

The resolution and noise characteristics of this high-energy in-line phase contrast tomosynthesis prototype were successfully investigated and demonstrated. The phantom studies demonstrated that this imaging prototype can successfully remove the structure overlapping in phantom projections, obtain delineate interfaces, and achieve better contrast-to-noise ratio after applying phase retrieval to the angular projections.

CONCLUSIONS

This research successfully demonstrated a high-energy in-line phase contrast tomosynthesis prototype. In addition, the PAD-based method of phase retrieval was combined with tomosynthesis imaging for the first time, which demonstrated its capability in significantly improving the contrast-to-noise ratios in the images.

Should processed or raw image data be used in mammographic image quality analyses? A comparative study of three full-field digital mammography systems

The purpose of this study is to compare a number of measured image quality parameters using processed and unprocessed or raw images in two full-field direct digital units and one computed radiography mammography system. This study shows that the difference between raw and processed image data is system specific. The results have shown that there are no significant differences between raw and processed data in the mean threshold contrast values using the contrast-detail mammography phantom in all the systems investigated; however, these results cannot be generalised to all available systems. Notable differences were noted in contrast-to-noise ratios and in other tests including: response function, modulation transfer function , noise equivalent quanta, normalised noise power spectra and detective quantum efficiency as specified in IEC 62220-1-2. Consequently, the authors strongly recommend the use of raw data for all image quality analyses in digital mammography.

Effective detective quantum efficiency for two mammography systems: measurement and comparison against established metrics

PURPOSE

The aim of this paper was to illustrate the value of the new metric effective detective quantum efficiency (eDQE) in relation to more established measures in the optimization process of two digital mammography systems. The following metrics were included for comparison against eDQE: detective quantum efficiency (DQE) of the detector, signal difference to noise ratio (SdNR), and detectability index (d') calculated using a standard nonprewhitened observer with eye filter.

METHODS

The two systems investigated were the Siemens MAMMOMAT Inspiration and the Hologic Selenia Dimensions. The presampling modulation transfer function (MTF) required for the eDQE was measured using two geometries: a geometry containing scattered radiation and a low scatter geometry. The eDQE, SdNR, and d' were measured for poly(methyl methacrylate) (PMMA) thicknesses of 20, 40, 60, and 70 mm, with and without the antiscatter grid and for a selection of clinically relevant target/filter (T/F) combinations. Figures of merit (FOMs) were then formed from SdNR and d' using the mean glandular dose as the factor to express detriment. Detector DQE was measured at energies covering the range of typical clinically used spectra.

RESULTS

The MTF measured in the presence of scattered radiation showed a large drop at low spatial frequency compared to the low scatter method and led to a corresponding reduction in eDQE. The eDQE for the Siemens system at 1 mm(-1) ranged between 0.15 and 0.27, depending on T/F and grid setting. For the Hologic system, eDQE at 1 mm(-1) varied from 0.15 to 0.32, again depending on T/F and grid setting. The eDQE results for both systems showed that the grid increased the system efficiency for PMMA thicknesses of 40 mm and above but showed only small sensitivity to T/F setting. While results of the SdNR and d' based FOMs confirmed the eDQE grid position results, they were also more specific in terms of T/F selection. For the Siemens system at 20 mm PMMA, the FOMs indicated Mo/Mo (grid out) as optimal while W/Rh (grid in) was the optimal configuration at 40, 60, and 70 mm PMMA. For the Hologic, the FOMs pointed to W/Rh (grid in) at 20 and 40 mm of PMMA while W/Ag (grid in) gave the highest FOM at 60 and 70 mm PMMA. Finally, DQE at 1 mm(-1) averaged for the four beam qualities studied was 0.44 ± 0.02 and 0.55 ± 0.03 for the Siemens and Hologic detectors, respectively, indicating only a small influence of energy on detector DQE.

CONCLUSIONS

Both the DQE and eDQE data showed only a small sensitivity to T/F setting for these two systems. The eDQE showed clear preferences in terms of scatter reduction, being highest for the grid-in geometry for PMMA thicknesses of 40 mm and above. The SdNR and d' based figures of merit, which contain additional weighting for contrast and dose, pointed to specific T/F settings for both systems.

Study of DQE dependence with beam quality on GE essential mammography flat panel

This paper deals with the analysis of the behavior of objective image quality parameters for the new GE Senographe Essential FFDM system, in particular its dependence with beam quality. The detector consists of an indirect conversion a‐Si flat panel coupled to a CsI:Tl scintillator. The system under study has gone through a series of relevant modifications in flat panel with respect to the previous model (GE Senographe DS 2000). These changes in the detector modify its performance and are intended to favor advanced applications like tomosynthesis, which uses harder beam spectra and lower doses per exposure than conventional FFDM. Although our system does not have tomosynthesis implemented, we noticed that most clinical explorations were performed by automatically selecting a harder spectrum than that of typical use in FFDM (Rh/Rh 28–30 kV instead of Mo/Mo 28 kV). Since flat‐panel optimization for tomosynthesis influences the usual FFDM clinical performance, the new detector behavior needed to be investigated. Therefore, the aim of our study is evaluating the dependence of the detector performance for different beam spectra and exposure levels. In this way, we covered the clinical beam quality range (Rh/Rh 28–30 kV) and we extended the study to even harder spectra (Rh/Rh 34 kV). Detector performance is quantified by means of modulation transfer function (MTF), normalized noise power spectrum (NNPS) and detective quantum efficiency (DQE). We found that flat‐panel optimization results in slightly – but statistically significant – higher DQE values as beam quality increases, which is contrary to the expected behavior. This positive correlation between beam quality and DQE is also diametrically opposite to that of the previous model by the same manufacturer. As a direct consequence, usual FFDM takes advantage of the changes in the detector, as less exposure is needed to achieve the same DQE if harder beams are used.

PACS number: 87.59.ej

Simulation of image detectors in radiology for determination of scatter-to-primary ratios using Monte Carlo radiation transport code MCNP/MCNPX

PURPOSE

The purpose of this study was to compare and validate three methods to simulate radiographic image detectors with the Monte Carlo software MCNP/MCNPX in a time efficient way.

METHODS

The first detector model was the standard semideterministic radiography tally, which has been used in previous image simulation studies. Next to the radiography tally two alternative stochastic detector models were developed: A perfect energy integrating detector and a detector based on the energy absorbed in the detector material. Validation of three image detector models was performed by comparing calculated scatter-to-primary ratios (SPRs) with the published and experimentally acquired SPR values.

RESULTS

For mammographic applications, SPRs computed with the radiography tally were up to 44% larger than the published results, while the SPRs computed with the perfect energy integrating detectors and the blur-free absorbed energy detector model were, on the average, 0.3% (ranging from -3% to 3%) and 0.4% (ranging from -5% to 5%) lower, respectively. For general radiography applications, the radiography tally overestimated the measured SPR by as much as 46%. The SPRs calculated with the perfect energy integrating detectors were, on the average, 4.7% (ranging from -5.3% to -4%) lower than the measured SPRs, whereas for the blur-free absorbed energy detector model, the calculated SPRs were, on the average, 1.3% (ranging from -0.1% to 2.4%) larger than the measured SPRs.

CONCLUSIONS

For mammographic applications, both the perfect energy integrating detector model and the blur-free energy absorbing detector model can be used to simulate image detectors, whereas for conventional x-ray imaging using higher energies, the blur-free energy absorbing detector model is the most appropriate image detector model. The radiography tally overestimates the scattered part and should therefore not be used to simulate radiographic image detectors.