Performance evaluation of a retrofit digital detector-based mammography system

ARTICLE IN PRESS Physica Medica ■■ (2016) ■■–■■

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Physica Medica j o u r n a l h o m e p a g e : h t t p : / / w w w. p h y s i c a m e d i c a . c o m

Original Paper

Performance evaluation of a retrofit digital detector-based mammography system Nicholas W. Marshall *, Chantal van Ongeval, Hilde Bosmans Department of Radiology, UZ Gasthuisberg, Herestraat 49, B-3000 Leuven, Belgium

A R T I C L E

I N F O

Article history: Received 7 September 2015 Received in revised form 7 December 2015 Accepted 4 January 2016 Available online Keywords: Mammography Image quality Detector characterization

A B S T R A C T

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. © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Introduction Mammography x-ray imaging currently forms the backbone of breast screening programs and the associated treatment and evaluation services in many countries [1]. For many years, mammography was performed using screen/film (S/F) (i.e. analog) imaging using dedicated x-ray equipment. Within the last ten years or so, there has been a transition from analog imaging to systems based around full field digital mammography detectors, a result linked, to some extent, to the results of the ACRIN/DMIST trial [2].There has been some geographical variation in FFDM uptake, being particularly strong in the USA [2], Canada [3] and in many European Countries [4–6]. One option when converting from analog to FFDM is to keep the x-ray modality (i.e. the acquisition system) and use computed radiography (CR) x-ray detectors. This is a practical and cost effective solution that can be employed without any reorganization of the service, by swapping from S/F to CR cassettes and installing a CR reader. Although needle based CR systems have become available recently, offering improved imaging performance over powder based systems [7,8], many sites that have converted to CR imaging still employ their original powder-based CR system. A disadvantage of this technology is that if not managed carefully in terms of technical

* Corresponding author. Department of Radiology, UZ Gasthuisberg, Herestraat 49, B-3000 Leuven, Belgium. Tel.: +32 16 34 89 83; fax number: +32 16 34 37 69. E-mail address: [email protected] (N.W. Marshall).

and clinical imaging performance of the system, problems may arise in terms of screening program performance [3]. This is largely due to technical limitations of powder-based CR detectors, namely reduced sharpness, increased noise and reduced detective quantum efficiency (DQE) compared to CsI or a-Se based detectors [8–10]. If powder-based CR systems are to be used with any degree of success in breast imaging then dose levels must be increased such that imaging performance meets the required level [5]. This is can be achieved by setting the Acceptable dose level given in the EUREF protocol [5,11]. An alternative to switching to powder-based CR is to keep the S/F x-ray modality but to fit a CsI or an a-Se flat panel type detector. Advantages of this approach include potentially superior image quality from the flat panel detector over powder-based CR, direct transmission of the images to the PACS (no CR reader) and no manual handling of the CR cassettes. There are, however, some difficulties with this method that must be overcome. CR cassettes can use the ionization chamber that forms part of the original S/F automatic exposure control (AEC) system – provided the AEC is recalibrated to match the characteristics of the CR cassette and the appropriate dose level is set to obtain at least the minimum image quality level. When retrofitting a digital detector, the entire bucky including the ionization chamber is removed and instead, the signal from the digital detector is used to control the AEC acquisition. Some kind of interface must be designed so that the detector signal can correctly control the AEC. This is the approach adopted for the SmartBucky device, where the S/F bucky is replaced by an entirely new flat-panel/grid/bucky combination. This device uses a CsI based flat panel detector in

http://dx.doi.org/10.1016/j.ejmp.2016.01.002 1120-1797/© 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

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combination with a pendulum style antiscatter grid. The aim of this study was to assess the SmartBucky device installed on a GE DMR+ x-ray acquisition modality, situated at our hospital facility. This assessment consisted of several parts: 1. Quantification of detector performance following the International Electrotechnical Commission [12] protocol for modulation transfer function (MTF), normalized noise power spectrum (NNPS) and DQE. 2. Technical evaluation of the SmartBucky device/GE DMR+ system against the EUREF protocol [13]. 3. Establish optimal anode/filter (A/F) settings for the use of the GE DMR+ in combination with the SmartBucky device. 4. Perform a limited scale clinical study by evaluating clinical image quality of a number of cases. The results of these evaluations are then discussed within the context of the technical and clinical image quality performance standards in the EUREF protocol and against system DQE characterization data published for other FFDM systems.

Figure 1. Photograph of the SmartBucky installed on the GE DMR+ x-ray acquisition modality.

Detector corrections Materials and methods X-ray acquisition system The SmartBucky has been designed to integrate with the GE DMR+ screen/film mammography system. One of the reasons for choosing the DMR+ was the availability of multiple anode/filter (A/F) combinations. The unit has molybdenum (Mo) and rhodium (Rh) anodes with 0.8 mm beryllium (Be) intrinsic filtration. Two switchable filters are available that can be used with the Mo anode: 0.030 mm thick Mo and 0.025 mm thick Rh. There is also an aluminum (Al) filter of thickness 1 mm that can be used with both anodes, giving a total of five available A/F combinations: Mo/Mo, Mo/Rh, Mo/Al, Rh/Al and Rh/Rh. However, the Al filter was precluded from use by the manufacturer for a number of reasons. First, an indirect conversion x-ray detector is used in the SmartBucky, incorporating a columnar cesium iodide (CsI) x-ray scintillator and the Mo/Al and Rh/Al are not commonly used combinations for AEC set up with this detector type [14]. Furthermore, the inclusion of these additional A/F combinations requires separate flat field corrections, complicating the routine use of the system. This left the commonly used settings of Mo/Mo, Mo/Rh and Rh/Rh for evaluation which allow considerable flexibility in the selection and tuning of A/F to give low breast dose while maintaining high level image quality for different breast thicknesses.

SmartBucky mammography device The SmartBucky device contains a 23 cm × 29 cm detector. It consists of a CsI x-ray scintillator coupled via a fiber optic plate to an array of light sensitive complementary metal-oxide semiconductor (CMOS) sensors with a 0.075 mm pixel spacing. In addition to the image receptor, the SmartBucky device contains a linear grid with a line spacing of 31 lines cm−1, ratio of 5:1, focused for use between 600 mm and 700 mm from the source. Installation of the SmartBucky requires the complete removal of the original S/F bucky containing the original linear grid and the sensor used by the automatic exposure control (AEC) device. Proprietary electronic interfacing circuits are supplied which connect and coordinate communication between the SmartBucky (detector and grid motion), the DMR+ x-ray system and the controlling acquisition computer. Fig. 1 shows a photograph of the SmartBucky device for which the performance evaluation and clinical study were performed.

The CsI detector requires the typical set of detector corrections used for flat panel-type [15] x-ray detectors, namely offset, gain and detector defect corrections. There is an offset (background) subtraction that removes accumulated signal level due to electronic noise within the detector; this offset level is re-measured systematically after every patient, and is repeated regularly if no patient is examined. The default value for measurement is every five minutes although this value is configurable to match patient workflow. The gain correction is measured periodically by the service engineer using a homogeneous block of PMMA for the individual A/F settings that are used by the system (Mo/Mo, Mo/Rh and Rh/Rh). This correction is performed with a minimum six monthly frequency, although experience has shown that for this CMOS detector there are only small changes in gain over time and with temperature. Of importance is the total number of images used to form the gain correction as residual noise in the correction image (due to an insufficient number in the gain mask) is directly multiplied into the clinical images [15], leading to a reduction in DQE. Finally there is a defect correction applied, in which aspects such as non-responsive detector elements are interpolated using a correction file, again acquired by the service engineer. Automatic exposure control The automatic exposure control (AEC) device is an essential component of an FFDM system, determining the balance between patient dose and image quality for the range of breast thicknesses and breast types examined. While there are differences in architecture, all current flat-panel type FFDM systems sample some region(s) of the image within the breast area and use the signal from the detector signal to control the exposure to the breast. Given that the detector is applied as a retrofit to an existing acquisition modality, the sampled detector signal has to be conditioned using proprietary electronics such that the levels expected from the original AEC sensor (a scintillating screen in conjunction with a photomultiplier tube) are emulated by the digital detector. The basis of the AEC is a set of configurable sensing regions of dimension 50 × 50 mm defined in a 6 × 3 grid over the detector panel, thereby covering 30 cm × 15 cm. During an image acquisition, ‘imaging pixels’ within these sensing regions are read at high speed without changing their value (‘non-destructively’) by the flat panel electronics. The non-destructive read out enables the pixels to contribute to the image; this type of readout is applied to both the test

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exposure and the main image exposure. The values of the selected imaging pixels in the region(s) are averaged to obtain a reference level. When an x-ray exposure is initiated, the subsequent level within the sensing region is subtracted from the reference level and the result used as reference for the charge rate of the panel. This process, which takes ~4.5 ms, is repeated until some pre-set target value of charge is reached; this value is set via the AEC sensitivity settings in the generator in combination with a calibration procedure. The AEC circuit in the generator measures the charge rate and the x-ray exposure is terminated when the total charge (associated with a pixel value (PV)) is reached for the given breast compression thickness. In the original AEC control circuit of the GE DMR+, a combination of mechanical breast thickness, a test shot (‘pre-exposure’) and measured compression force are used to determine the A/F setting, tube voltage and tube current-time product (mAs) from AEC look up tables (LUTs). These LUTs are still used in the SmartBucky system with the exception that the mAs is controlled by monitoring the PV in the main exposure, as described above. The practical implementation of the AEC in the SmartBucky works as follows. The DMR+ console is left in normal (auto-timed) mode (i.e. the tube voltage and A/F are set manually and the system sets the mAs). The operator positions the patient, compresses the breast and enters the compressed breast thickness into the user interface. This thickness is used to set by software control the initial tube voltage and A/F setting on the console from a LUT. The operator then initiates the exposure (i.e. ‘prep’ followed by ‘expose’) and the system performs the pre-exposure followed by the main exposure. The DMR+ uses a fixed 1 mAs pre-exposure and the image generated by the pre-exposure is stored and used as part of the main image (see section ‘High Dynamic Range (HDR) mode’). The gap between the pre-exposure and main exposure is 180 ms. Hence, the AEC is not fully automatic, as mechanical breast thickness cannot be sent from the DMR+ system to the controlling electronics at the time of the x-ray turn-on/off and must therefore be entered by the operator prior to the exposure. As described above, this thickness value is used to program the tube voltage and A/F from a LUT – but not the mAs, which is set dynamically by monitoring the PV in the image. There are three AEC modes (LUTs) available on the DMR+ (‘STANDARD’, ‘DOSE’ and ‘CONTRAST’); the measurements used to establish the optimal mode for use with the SmartBucky flat panel detector are described later. High Dynamic Range (HDR) mode The CMOS flat panel detector has a relatively limited dynamic range compared to current a-Si TFT based imaging arrays used for mammography applications. High Dynamic Range (HDR) imaging is becoming a standard technique in photography to increase dynamic range of an image through a weighted combination of images of the same scene, acquired at different light exposure levels [16]. As described earlier, a standard AEC acquisition is divided into a pre-exposure followed by the main-exposure. Given the low mAs used for the pre-exposure, the skin edge region will be imaged at typical detector exposure levels, while the bulk of the breast (the central/dense regions) will be underexposed (i.e. PV will be below the target PV). Conversely, in the main-exposure, the edge regions of the breast will be outside the dynamic range of the detector and thus saturated, while the main part of the breast will be at the target PV and hence correctly exposed. The pre-exposure image therefore contains the full profile of the breast edge/skin edge and the nipple region. The mAs used to acquire the pre-exposure image should be chosen to remain within the detector dynamic range, thereby avoiding saturation in the air or at the skin edge. The HDR software implemented with the SmartBucky system analyzes both images and assigns a per-pixel weighing factor based on the intensity

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of each pixel. The weighted images are summed to give a single output image with an increased dynamic range compared to just using information from the main image. The HDR image enables visualization of both the breast edge and nipple areas along with the main image area, even though the images were acquired using a detector with a limited dynamic range. The limitation associated with this technique is that there should be no motion of the breast between acquisition of the pre-exposure and the mainexposure. However, this is unlikely to be a problem for the current implementation of the SmartBucky given the 180 ms gap between pre-exposure and main-exposure. Detector characterization Physical evaluation of the x-ray detector imaging performance was performed using standard methods [12,13]: detector sharpness was characterized using the presampling modulation transfer function (MTF), the noise was quantified using the normalized noise power spectrum (NNPS) and detector signal-to-noise ratio (SNR) transfer efficiency was quantified with the detective quantum efficiency (DQE). The first step was the measurement of the detector response function for the Mo/Mo, Mo/Rh and Rh/Rh A/F combinations, using a tube voltage of 28 kV with a 2 mm Al plate at the x-ray tube exit. The air kerma required for these measurements was measured with a calibrated RTI Barracuda (Molndal, Sweden) meter and a solid-state multipurpose detector (MPD) and corrected to give detector air kerma (DAK) at the x-ray detector input plane using the inverse-square law. Homogeneously exposed (flood) images were then acquired for a range of DAK values, with the antiscatter grid removed. The processing steps applied to the flood images were offset, gain and detector defect corrections, yielding DICOM ‘for processing’ images. This image type was used for all the detector characterization measurements. For the response function, a 5 × 5 mm region of interest (ROI) was located at ‘the standard position’ in the images, 60 mm from the chest wall edge and centered left-right. PV and variance were measured for each A/F setting; PV was then plotted as a function of DAK and a linear fit applied to give the gradient and offset for the response. The variance was then plotted versus DAK and a 2nd order polynomial fitted (with data weighting) in order to estimate the approximate electronic (e), quantum (q) and structure (s) noise coefficients for the detector [17–19]. These noise (variance) components were then expressed as a fraction of total variance and plotted versus DAK and the quantum limited range was estimated [19]. The MTF was measured using a version of the edge method described by Samei et al. [20]; details of the implementation are given elsewhere [9,21].The edge used was 60 × 120 mm, composed of steel and of thickness 0.8 mm. MTF was measured for beam qualities of 28 kV, 2 mm Al added and for the Mo/Mo, Mo/Rh and Rh/Rh combinations. The grid was removed when acquiring these images. A 50 × 50 mm region was used to form the oversampled edge spread function (ESF). The NNPS was calculated using the method described in the IEC standard protocol [12]. In this implementation, a region of 1024 × 1024 pixels was extracted from the center of the flood image and the PV data linearized to DAK using the response function. A second order polynomial was fitted to this region and then subtracted from the PV data in order to reduce the influence of low frequency trends on the NNPS. The 2D NNPS was calculated from 256 × 256 ROIs extracted from this de-trended region and reduced to a 1D spectrum using a radial average. NNPS data were calculated from flood images acquired at target DAK levels of 50 μGy and at a factor of 2 higher and lower than this value (25 μGy and 100 μGy). Finally, the DQE was calculated from the presampling MTF, the NNPS and the estimated number of photons at the detector using the equation:

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DQE (u) =

MTF 2 (u) q 0 ⋅ K ⋅ NNPS (u)

(1)

where K is the estimated air kerma at the detector input plane and q0 is the number of photons per unit air kerma taken from IEC 622201-2 [12] for the respective A/F setting. Optimization of exposure parameters Given that this is a retrofit imaging device, the detector has to be integrated with the AEC modes that are available in the software of the GE DMR+ acquisition station. Practically, this means first finding which tube voltage and A/F combinations give the optimal balance between breast dose and image quality for a given breast thickness and second, finding which LUTs pre-programmed for the AEC modes (the ‘STANDARD’, ‘CONTRAST’ and ‘DOSE’ modes) most closely match the theoretical optimal target A/F settings. This was achieved using a figure of merit (FOM) based on the signaldifference-to-noise ratio (SDNR) [22] and applied earlier to mammography imaging [23–25]. The geometry employed for the SDNR optimization was that given for AEC testing in the EUREF protocol [15], in which a 5 × 5 mm square of 0.2 mm thick Al is located at the standard position. The PMMA thickness was varied from 20 mm to 70 mm, thus covering an approximate breast equivalent range of 21 mm–90 mm [26,27]. The Al square was always positioned on the 20 mm PMMA block, and any additional PMMA was added on top of this. For a given tube voltage, A/F and PMMA thickness combination, SDNR was measured as a function of mAs settings (three mAs values). SDNR was not measured for the Rh/Rh A/F at 20 mm and 30 mm PMMA, as the AEC system excludes this A/F combination for these thicknesses. The FOM was then calculated using:

FOM =

SDNR 2 MGD

(2)

where MGD is the mean glandular dose, calculated according to the method of Dance et al. [26,27]. For quantum noise limited images, the FOM will be independent of mAs and hence can be averaged from the three mAs values [22]. This was checked by applying a power curve fit to SDNR plotted against mAs; the fitted power coefficient should be close to 0.5 if quantum noise is the dominant image noise source [28]. Just three tube voltage settings were considered for each A/F setting and PMMA thickness combination, as a strong tube voltage dependency for the FOM in mammography (FOM) is not expected [25].

equivalence of the CDMAM plate with 40 mm PMMA). Four additional image sets were acquired around the mAs setting delivered by the AEC, with approximate steps of 40% between each mAs step. CDMAM scoring was performed automatically using the CDCOM module available from the EUREF website; CDCOM was controlled via ERICA2 (version 2.2.3). The additional processing steps described by Karssemeijer and Thijssen [29] and Young et al. [30] were applied in order to generate curves of threshold gold thickness against disc diameter. Image quality of the clinical images Clinical breast images were acquired in a two stage clinical study, controlled under a protocol approved by the ethical committee of our hospital. In stage one, images for a given woman were acquired on an established FFDM system in routine clinical use and then one additional (oblique) view was acquired on the SmartBucky system. These images were evaluated by an experienced radiologist according to the image quality guidelines given in the European Guidelines [11,13]; Table 1 lists the questions. Evaluation was made in a standard clinical reading environment, with DICOM ‘FOR PRESENTATION’ images drawn from the PACS system and read on 5 megapixel monitors whose calibration followed the DICOM grayscale function. The information from the radiologist in this stage one was used to adjust the image processing and the image blending used to form the HDR image. Following a positive evaluation for all the patient cases in stage one, twenty two further cases (two view) were acquired just on the SmartBucky system (stage two). The final twenty of these cases were submitted to a visual grading analysis controlled using the ViewDEX software tool [31]. Three radiologists evaluated the images using the image quality criteria in Table 1. Responses were given on a 6 point scale: 1 = Criterion definitely not

Table 1 Questions used for the clinical image quality evaluation, following the protocol given the European Protocol (EC 2006). Responses for the first 9 questions were given on a 6 point scale: 1 = Criterion definitely not fulfilled, 2 = Criterion probably not fulfilled, 3 = Indecisive whether criterion fulfilled or not, 4 = Criterion probably fulfilled, 5 = Criterion definitely fulfilled and 6 = not applicable. Number

Criterion

1 2

Is the skin line visualized well? Are the vascular structures visible through the dense parenchyma? Is the pectoral muscle visualized sharply? Are the Cooper’s ligaments and vascular structures in the subcutaneous and pre-pectoral area visualized well? Are the microcalcifications well visualized and well outlined? Is the contrast in the dark areas sufficient (e.g. no saturation of intensity of signals, no fully dark regions)? Is the contrast in the white areas sufficient (e.g. no fully white regions)? Is the glandular tissue sufficiently white? Is the background sufficiently dark?

3 4

System performance according to the EUREF protocol In order to establish the SmartBucky system performance as a whole (x-ray tube and generator, x-ray detector, antiscatter grid and AEC) and compare against other FFDM systems, the EUREF protocol for technical performance testing was applied [11,13]. Parameters assessed were x-ray tube and generator performance, AEC short term repeatability, AEC performance as a function of PMMA thickness, detector ghosting, x-ray field alignments and missing tissue at the chest wall, detector uniformity error, detector element failure, grid factor and exposure time. The test of AEC tracking of local dense area was not performed as this had not been implemented by our service at the time of system installation. Image quality was assessed via threshold contrast-detail (c-d) detectability, measured with the CDMAM test object type 3.4 (serial number 1033) (Artinis BV, Netherlands). The CDMAM test object was centered between 40 mm PMMA and eight images acquired with the antiscatter grid in place for each dataset. Sets of images were acquired at the AEC setting of 30 kV Rh/Rh for 50 mm PMMA (the approximate PMMA

5

6

7

8 9

11 12 13

Is there disturbing noise in the dark areas? Is there disturbing noise in the white areas? Are there any artifacts?

Minimum

Maximum

Mean

3.3 3.4

3.6 3.8

3.4 3.6

2.9

3.8

3.4

2.8

3.4

3.1

3.9

4.9

4.5

3.1

3.7

3.3

3.2

3.5

3.4

3.2

3.7

3.5

3.3

4.3

3.9

Yes (%) 90 75 75

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fulfilled, 2 = Criterion probably not fulfilled, 3 = Indecisive whether criterion fulfilled or not, 4 = Criterion probably fulfilled, 5 = Criterion definitely fulfilled and 6 = not applicable. Given that there was access to previous images for the different cases, we aimed for a wide range of breast types for imaging on the SmartBucky system, within the constraints of the necessary patient consent. Results Detector characterization Fig. 2a shows the response curves for the three A/F settings, measured at 28 kV and 2 mm Al added filter; the associated linear fit coefficients are listed in Table 2. The R2 coefficient for these three fits were ≥0.999, suggesting that the linear model closely fits the measured response curves. These coefficients show an increase in the gradient of the response function consistent with the increase in mean energy and the photons per unit air kerma seen for the A/F combinations [32]. Variance for the three noise sources expressed as a fraction of total variance is plotted in Fig. 2b for the Mo/Rh A/F setting. The estimated quantum noise limited range for the three combinations is given in Table 2. The presampling MTF, plotted in Fig. 3a shows only small differences in MTF for the different A/F settings. At 5 mm−1, the MTF is 0.31, 0.33 and 0.34 for the Mo/Mo, Mo/Rh and Rh/Rh combinations, respectively. This finding is consistent with previous results [32] and implies that x-ray energy had little or no influence on MTF for the energy and energy range relevant to current FFDM systems and detectors. Fig. 3b shows NNPS measured in the left-right and front-back directions for the Mo/Rh at 28 kV with 2 mm Al added. The NNPS is seen to be isotropic with the exception of the spikes at 3 mm−1 and 6 mm−1 in the left-right direction, due probably to the presence of line structures (grid related) in the homogeneous

images from which NNPS was calculated [33,34]. The influence of DAK on the NNPS is clear, with NNPS falling as DAK increases. The ratio between NNPS at the different DAK levels is equal to 1/DAK, indicating quantum noise is dominating the total NNPS. This is consistent with the noise (variance) separation results in Fig. 2b. Fig. 4a plots DQE for the three A/F combinations at a target DAK of 50 μGy, showing that there is no significant difference in DQE between the three A/F settings, given the approximate 6% uncertainty (coefficient of variation). Peak DQE is approximately 0.53 for the three A/F modes. The graph in Fig. 4b shows a small reduction of ~12% for the Mo/Rh setting (DQE averaged up to 4 mm−1) as target DAK is increased from 25 μGy to 100 μGy. DQE above 4.5 mm−1 is unaffected. This is consistent with the presence of some structured noise in the detector that starts to limit DQE lower spatial frequency as DAK increases. Optimization of exposure parameters The calculated figure of merit results are plotted in Fig. 5 and show, for a given A/F setting, a reduction in FOM as PMMA thickness increases. Consistent with the results of Williams et al. [25], only a small dependence on tube voltage can be noted. For a given setting (A/F and PMMA thickness), the ratio of FOM to the mean FOM for the three tube voltage values was 1.00, when averaged for all settings measured (maximum ratio was 1.07, minimum was 0.91). It can also be seen that A/F setting has only a small influence on the FOM up to 40 mm but from 50 mm PMMA onwards the A/F has a large influence the FOM. The optimal factors (or range of factors, where no clear optimal setting was found), are given in Table 3. At 20 and 30 mm PMMA, there is no particular preference for the Mo/Mo or Mo/Rh setting. For PMMA thicknesses of 40 mm and above, Rh/Rh emerges as the A/F setting that clearly gives the highest FOM. The DMR+ ‘DOSE’ AEC program is the mode that most closely

1.0

12000 Mo/Mo; 28 kV; 2 mm Al Mo/Rh Rh/Rh

quantum noise structure noise electronic noise

0.9 0.8 fraction of total variance

10000 8000 Pixel Value

5

6000 4000 2000

0.7 0.6 0.5 0.4 0.3 0.2 0.1

a) 0

b)

0.0 0

100

200 DAK (μGy)

300

0

25

50

75

100 125 150 175 200 DAK (μGy)

Figure 2. (a) Detector response measured at 28 kV with 2 mm Al at the x-ray tube for the Mo/Mo, Mo/Rh and Rh/Rh A/F combinations; (b) approximate electronic, quantum and structure noise (variance) expressed as a fraction of total variance for the Mo/Rh A/F setting.

Table 2 Fit coefficients for the detector response curve for the three A/F settings measured at 28 kV and 2 mm Al added, along with mean energy for the spectrum. Also shown is the estimated detector air kerma levels where non x-ray quantum noise starts to be the dominant noise source and the quantum noise limited range. Anode/filter (A/F)

Mean energy (keV)

Photons (μGy−1 mm−2)

A

B

Electronic noise dominant below (μGy)

Structure noise dominant above (μGy)

Quantum noise limited range (μGy)

Mo/Mo Mo/Rh Rh/Rh

19.5 20.2 21.1

5153 5622 6196

229.6 220.5 322.0

38.3 43.1 51.0

5.2 1.8 6.5

258 352 254

253 350 247

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1.0

1.0E-04

Mo/Mo

0.9

26.2 μGy 52.5 μGy 105 μGy front-back direction

Mo/Rh 0.8

Rh/Rh

NNPS (mm2)

0.7 MTF (u)

0.6 0.5 0.4

1.0E-05

1.0E-06

0.3 0.2 0.1

b)

a) 0.0

1.0E-07 0

1

2

3

4

5

6

7

8

9 10 11 12

0

1

spatial frequency (mm-1)

2

3

4

5

6

7

spatial frequency (mm-1)

Figure 3. (a) Detector presampling Modulation Transfer Function (MTF) measured at 28 kV with 2 mm Al at the x-ray tube for the Mo/Mo, Mo/Rh and Rh/Rh A/F combinations. The MTF curve for each A/F is averaged for the left-right and front-back directions. (b) Radially averaged Normalized Noise Power Spectrum (NNPS) for the Mo/Rh A/F setting at three DAK levels. The solid line shows the NNPS in the left-right direction while the dotted line gives NNPS in the front-back direction.

thicknesses. This SDNR performance is achieved at mean glandular dose values that are on or lower than the Achievable curve from the EUREF protocol. Fig. 6b shows that MGD for the AEC setup remains below the EUREF Achievable level for all PMMA thicknesses. The threshold contrast-detail curves used to characterize system image quality (at 30 kV Rh/Rh) are plotted in Fig. 7a along with the associated MGD for the acquisitions. The acquisitions at the two lowest doses (0.28 mGy and 0.45 mGy) are outside the Acceptable level in the EUREF protocol; threshold gold thickness for the remaining acquisitions are on or within the Acceptable level (0.73 mGy and above). Fig. 7b plots threshold gold thickness for the 0.1 mm diameter disc in Fig. 7a as a function of MGD, along with a curve showing threshold gold thickness predicted from the measured value at 0.73 mGy assuming quantum noise limited operation of the detector. At the set AEC operating level of 1.02 mGy for 50 mm PMMA,

matches these optimal settings and the AEC results for this mode measured as a function of PMMA are also shown in Table 3. System performance according to the EUREF protocol Tube and generator performance was within the performance limits listed in the EUREF protocol [11,13], as was AEC short term repeatability for both mAs and SNR variation. AEC performance in terms of SDNR versus PMMA thickness for the ‘DOSE’ mode, along with the selected tube voltage and A/F setting, as listed in Table 3. Fig. 6a shows a drop in SDNR as PMMA thickness increases, in common with the typical SDNR performance of the majority of the FFDM systems. The SDNR results for the SmartBucky system remain above the limiting value curve given in the EUREF protocol, meaning that the system maintains SDNR at larger breast (PMMA equivalent)

1.0

1.0 Mo/Mo Mo/Rh Rh/Rh

0.9

0.8

0.7

0.7

0.6

0.6

DQE (u)

DQE (u)

0.8

Mo/Rh at 26.2 μGy 52.5 μGy 105 μGy

0.9

0.5 0.4

0.5 0.4

0.3

0.3

0.2

0.2

0.1

0.1

b)

a) 0.0

0.0 0

1

2 3 4 5 6 spatial frequency (mm-1)

7

0

1

2 3 4 5 spatial frequency (mm-1)

6

7

Figure 4. (a) Detective quantum efficiency (DQE) measured at 28 kV with 2 mm Al at the x-ray tube for the Mo/Mo, Mo/Rh and Rh/Rh A/F combinations at DAK of 49.4 μGy, 52.5 μGy and 49.5 μGy, respectively. (b) DQE for the Mo/Rh A/F setting at three DAK levels. Error bars show coefficient of variation of 6%.

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1000.0

20 mm Mo/Mo 20 mm Mo/Rh

figure of merit (FOM) (mGy-1)

30 mm Mo/Mo 30 mm Mo/Rh 40 mm Mo/Mo 40 mm Mo/Rh 40 mm Rh/Rh 50 mm Mo/Mo

100.0

50 mm Mo/Rh 50 mm Rh/Rh 60 mm Mo/Mo 60 mm Mo/Rh 60 mm Rh/Rh 70 mm Mo/Mo 70 mm Mo/Rh 70 mm Rh/Rh

10.0 22

24

26

28

30

32

34

tube voltage (kV) Figure 5. Figure of merit (FOM) versus tube voltage with PMMA and A/F combination as parameters. The FOM with the maximum value for a given for a given A/F and thickness combination is indicated/connected by a line. Error bars show average cov of 7%.

level at an MGD of less than 0.54 mGy and the Achievable level at 1.27 mGy. The remaining EUREF test results were as follows. Regarding alignment, there was no missing at the chest wall edge and the x-ray field alignments (to light and to the image receptor) were within tolerance. System grid factor measured with 40 mm on the breast support table was found to be 1.84 while grid factor for primary

the measured threshold gold thickness passed the Acceptable value of 1.68 μm gold and approached the Achievable level (1.1 μm), with a measured value of 1.19 μm for the 0.1 mm diameter discs. It can be seen that the measured values lie close to those predicted, indicating that quantum noise is the dominant source of image noise, and therefore consistent with noise separation data shown in Fig. 2a. The data in Fig. 7b show that the system can meet the Acceptable

Table 3 Optimal anode/filter settings from the SDNR data and X-ray acquisition factors, SDNR and contrast for the AEC acquisitions. PMMA (cm)

2 3 4 4.5 5 6 7

Optimal settings

AEC ‘DOSE’ mode setting

kV

Anode/filter setting

kV

Anode/filter setting

mAs

Contrast (%)

SDNR

SDNR vs limit at 50 mm (%)

SDNR limit (%)

MGD (mGy)

24–26 24–28 26–30 – 28–30 28–32 28–32

Mo/Mo or Mo/Rh Mo/Mo or Mo/Rh Mo/Rh or Rh/Rh – Rh/Rh Rh/Rh Rh/Rh

26 26 28 29 30 31 32

Mo/Mo Mo/Rh Rh/Rh Rh/Rh Rh/Rh Rh/Rh Rh/Rh

23 40 36 35 80 55 72

20.3 17.1 13.8 13.1 12.4 11.4 10.5

16.7 13.7 10.1 9.1 9.7 7.9 6.9

242 198 147 133 141 114 101

115 110 105 103 100 95 90

0.58 0.75 0.75 0.76 1.02 1.23 1.58

8 relative SDNR limiting value

250

mean glandular dose (mGy)

SDNR relative to SDNR at 50 mm (%)

300

200 150 100

a) 50

measured ACCEPTABLE ACHIEVABLE

7 6 5 4 3 2 1

b)

0 1

2

3

4 5 6 PMMA (cm)

7

8

1

2

3

4 5 PMMA (cm)

6

7

8

Figure 6. (a) SDNR relative to SDNR at 50 mm versus PMMA thickness for the ‘DOSE’ mode. The dotted line shows the minimum expected value from the EUREF protocol. (b) Measured MGD versus PMMA thickness. The solid and dotted lines show the EUREF Acceptable and Achievable MGD values.

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0.28 0.45 0.73 1.02 1.82 Acceptable Achievable

threshold gold thickness (μm)

1.00

0.10

measured at 30 kV Rh/Rh predicted from 0.73 mGy result Acceptable gold thickness Achievable gold thickness Acceptable MGD Achievable MGD

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threshold gold thickness (μm)

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1.5

1.0

a)

b) 0.5

0.01 0.10

1.00 detail diameter (mm)

0.0

1.0 2.0 MGD (mGy)

3.0

Figure 7. (a) Measured threshold gold thickness plotted as a function of disc diameter, with MGD as a parameter. Circles and squares show the EUREF Acceptable and Achievable c-d values, respectively. (b) Threshold gold thickness for the 0.1 mm disc versus MGD (square points, from measurements). The curve shows threshold gold thickness predicted from the 0.73 mGy measurement, assuming quantum noise limited operation. The solid and dotted lines show the EUREF Acceptable and Achievable values for the threshold gold thickness and MGD.

radiation was 1.39. Exposure time for the standard test block passed the achievable level of <1.5 s. The pixel correction map was available and the detector element failure was within the specified tolerances. Detector (brightness) uniformity error, calculated as the maximum deviation on the mean, was 5.5%, 2.7% and 2.6% for the Mo/Mo, Mo/Rh and Rh/Rh A/F combinations, respectively. Detector ghost factor was within the 30% limit, at 1.3%. Image quality of the clinical images For the first 15 cases, a gray rim was consistently present, extending 1 cm–2 cm from the skin line to the interior of the breast. Furthermore there was a difference of the overall contrast between the cases, sometimes within one examination (e.g. between MLO and CC view). Given the acceptable presentation of microcalcifications and masses, more efforts were made to improve the image processing. After multiple attempts, the processing of the last 10 images resulted in a homogeneous subcutaneous and glandular breast tissue presentation and a more constant contrast of the images for a given patient and of the images between patients. A total of 20 patients were included in the visual grading analysis Compressed breast thickness ranged from 28 mm to 71 mm while breast density scored using the BI-RADS scale ranged from 1 to 4 (BI-RADS 1 density = 4 cases, BI-RADS 2 density = 10 cases, BI-RADS 3 density = 4 cases and BI-RADS 4 density = 1 case). BIRADS score of malignancy ranged from 1 to 5 (BI-RADS 1 malignancy = 3 cases, BI-RADS 2 malignancy = 16 cases, BI-RADS 5 malignancy = 1 case). Results of the visual grading responses are given in Table 1. The ‘Average’ column gives the average of the three reader scores for a given question while ‘Minimum’ and ‘Maximum’ columns are the minimum and maximum of the average reader scores (averaged over twenty cases) for a given question. A note on the use of the scoring scale at this center: a score of the three or more is considered Acceptable and suitable for clinical use. Readers at this center are experienced in terms visual grading and regularly participate in these types of studies. Although individual readers gave two ratings just below 3 (question 3 (sharp visualization of pectoral muscle) and question 4 (relating to Cooper’s ligaments/vascular structures)), the average of the three readers for questions 1–9 was greater than 3. Highest average score was given to microcalcification

visualization, with an average score of 4.5. For question 10, the percentage of images containing disturbing noise in the dark areas (averaged for three readers) was 90%. On further investigation, it was found that this was only at the extreme skin edge; the noise extended several millimeters (~2–5 mm) towards the interior of the breasts in approximately 60% of the cases. Fig. 8 shows two example breast images with Fig. 8b showing some noise in the black area towards the skin edge. Image quality in at the skin edge was initially of concern, given the limited dynamic range of the detector. These results suggest that the HDR method used to visualize the skin edge region has largely overcome the problem of the limited dynamic range. In an additional evaluation, all cases were also compared with previous examinations (performed on different systems), especially in terms of imaging of the glandular tissues, and the results considered acceptable. As an overall assessment, the readers considered the system to produce satisfactory image quality but thought that additional work on the image processing could possibly yield further improvements in final image quality.

Discussion The detector characterization results are consistent with good overall detector performance for the CsI/CMOS-type detector utilized in the SmartBucky device. Detector presampling MTF is typically used to characterize detector sharpness [20]. Taking the spatial frequency for the 50% point of the MTF gives a result of 3.30 mm−1, while MTF at 5 mm−1 is approximately 0.32. These figures can be compared against data for other FFDM systems [9]. The SmartBucky system results compare favorably to data for the CsI based GE Essential detector of 2.38 mm−1 for the MTF 50% point and 0.16 for the MTF at 5 mm−1. For two common systems using a-Se detectors, the MTF 50% and MTF at 5 mm−1 values are somewhat higher than the SmartBucky detector at ~4.5 mm−1 and ~0.46, respectively for the Siemens Inspiration and Hologic systems. The SmartBucky system is clearly sharper than typical powder CR detectors, where MTF % is ~2.00 mm−1 and MTF at 5 mm−1 is ~0.14 mm−1. The ratio MTF in the front-back to left-right directions was within 1%, indicating good sharpness isotropy. This finding is supported by the isotropy seen in the NNPS curves of Fig. 3b.

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Figure 8. (a) Mediolateral view of the left breast. Postoperative changes with clips in the cranial part of the breast. BIRADS 2; (b) Craniocaudal view of the left breast. Fibrocystic disease with adenosis calcifications. Image quality: noise in the black area of the subcutaneous space. BIRADS 2.

Peak DQE is approximately 0.53 while DQE at 5 mm−1 is 0.32, for the three A/F settings measured at 28 kV with 2 mm Al added. The approximate mean energies for the Mo/Mo, Mo/Rh and Rh/Rh spectra are 19.5 keV, 20.2 keV and 21.1 keV, respectively; these energies can be compared to the mean energy of 20.3 keV and 20.7 keV for the exit spectrum at 28 kV, Mo/Rh and 50 mm PMMA [35]. These results suggest that there is no distinct advantage in terms of signal-tonoise ratio transfer efficiency in using one particular A/F setting over another for standard breast-equivalent thicknesses. The differences in FOM seen for the three A/F settings in Fig. 5 (from 40 mm and above) possibly arise from differences in the efficiency of the x-ray spectrum [36] at producing a target SDNR for a given MGD, although further measurements would be needed to confirm this. Against single sided powder CR technology, the peak DQE is superior at 0.53 compared to values ranging between 0.26 and 0.36 [9,36,37]. When comparing against CsI or a-Se detector based FFDM systems, the peak DQE value lies within the typical range seen of 0.48–0.63 [9,38,39]. At 5 mm−1, the DQE of the SmartBucky device (0.33) is notably higher than that seen for the CsI or a-Se detector based FFDM systems (DQE at 5 mm−1 ~0.15–0.21). DQE of the SmartBucky system does not quite reach the level found for the Fuji Amulet or Sectra (now Philips) Microdose [9,36]. The beam optimization data in Fig. 5 are consistent with the data of Williams et al. [25] and Dance et al. [36] and show for smaller breasts (e.g. at 20 mm PMMA equivalent) the Mo/Mo or Mo/Rh are optimal. At larger breast equivalent thicknesses (60 mm and 70 mm PMMA), the Rh/Rh spectrum, which produces relatively higher energies compared to Mo/Mo and Mo/Rh, becomes optimal. The system successfully passed the technical part of the EUREF protocol [11,13], used to characterize dose (in terms of MGD measured using PMMA blocks), AEC performance using SDNR and image quality using threshold gold thickness. The MGD and measured threshold gold thickness result for the system can be combined to

give the MGD required to meet the Acceptable or Achievable threshold gold thickness levels (e.g. for the 0.1 mm and 0.25 mm diameter discs) [39]. The SmartBucky system requires 0.54 mGy and 1.27 mGy to reach the Acceptable and Achievable levels for the 0.1 mm diameter disc. To meet the Acceptable level, other CsI and a-Se based FFDM systems require between 0.34 mGy and 0.79 mGy [39], a figure that is influenced by the detector DQE and the A/F settings that are available on a given system. By way of comparison, needle based CR systems take approximately 1.28 mGy to meet the Acceptable level [8,39], while powder CR systems require a notably higher MGD, ranging from 1.47 mGy to 2.34 mGy. Technical evaluation following the EUREF protocol is extremely valuable in guaranteeing a minimum level of technical performance, however a system cannot enter routine clinical service unless the images are evaluated and passed by radiologists [11]. This de-facto includes an evaluation of the clinical image processing set. While there is no explicit limiting value in terms of detector dynamic range in the EUREF technical protocol, a system with a limited detector dynamic range could not produce clinically acceptable breast images, especially at the skin edge. Indeed, initial evaluation of clinical image quality showed a lack of homogeneous presentation of the images, more specifically a gray rim was consistently seen beneath the skin line. Improvement of the image processing finally led to a consistent level of image quality, with homogeneous contrast both within each image and between successive images. With regard to the SmartBucky system, this is an important test of the steps taken to extend the dynamic range using the HDR mode, in which the AEC pre-shot and the main exposure are combined to produce images with a wider dynamic range. The radiologist found the skin line to be visualized with acceptable quality, even though some noise was noted in the dark regions at the skin edge, suggesting that the HDR method is working at the level required. If we examine the ‘For Processing’ AEC pre-shot image of a typical breast,

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the linearized PV at the start of the skin edge falls from approximately 35 μGy–10 μGy in ~2.5 mm. There is then a gradual reduction from 10 μGy to approximately 5 μGy by about 10 mm in going from the skin edge towards the breast center. This is a low DAK value and it could be possible that electronic noise is starting to dominate image noise, however it can be seen that DAK remains above the approximate lower quantum noise limit of 5 μGy. We note that there is also signal in the main image that contributes to the final, blended HDR image. To conclude, some remarks concerning implementation, system use and ergonomics are given. It is clear that there is a limited time frame within which a device such as the SmartBucky can be implemented, as the upgrade requires analog systems that have been installed relatively recently and are in good working order. A further requirement is that a supply of replacement parts for the analog system must be available for the foreseen lifetime of the unit. As it stands, the SmartBucky is only available for the GE DMR+ model; implementation with acquisition modalities from other manufacturers would require modification of the AEC interface electronics but this could be achieved. As can be seen from Fig. 1, the bucky system is not large or cumbersome and bears close resemblance to other FFDM devices in terms of physical depth. Dead space at the chest wall edge is some way within the EUREF requirement of <5 mm. The bucky design was such that the replaced analog components, compression table and Bucky mechanism in the DMR+ design were matched/copied in terms of depth and distances. There is however no shifting compression paddle to aid with the positioning of patients with small breasts; for oblique views the large paddle must be used. A product specific application workstation handles access to the patient work list and history. Controls for the patient acquisition are provided by a graphical user interface, navigated using keyboard, mouse and a touch screen. Finally, MGD is recorded in the DICOM image header along with tube voltage, mAs, anode and filter materials and compressed breast thickness. This enables routine evaluation of patient breast dose via dose monitoring applications. Conclusions This study has shown that the SmartBucky device in combination with a GE DMR+ x-ray acquisition modality passes the technical quality aspects of the EUREF protocol. At the set operating level of 1.02 mGy for 50 mm PMMA, threshold gold thickness for the 0.1 mm disc was 1.19 μm and hence comfortably passed the Acceptance level within the dose limits. The system could meet this Acceptable image quality level at an MGD of 0.54 mGy, performance similar to CsI and a-Se based FFDM systems and superior to powder-based CR detectors. Detector performance in terms of MTF and DQE was on a par with established CsI and a-Se based FFDM detectors and easily surpassed that of powder-based CR detectors. The limited dynamic range of the flat panel detector was extended through the use of a high dynamic range technique that combined the pre-shot AEC image and the main AEC image. This aspect, together with overall image quality performance, was assessed by radiologists in a clinical study; overall clinical performance, including visualization and noise was considered to be acceptable. In sum, the SmartBucky device successfully upgrades an analog mammography system to operate with a flat panel-type x-ray detector, yielding imaging performance similar to that found for other CsI or a-Se based FFDM systems and clearly superior to that of powder-based CR detectors. Acknowledgements We would like to acknowledge the great help and contribution of Anne Similon and the radiography staff in the mammography

department at UZ Leuven. The help of Lesley Cockmartin in setting up the visual grading study is gladly acknowledged. References [1] Giordano L, von Karsa L, Tomatis M, Majek O, de Wolf C, Lancucki L, et al. Mammographic screening programmes in Europe: organization, coverage and participation. J Med Screen 2012;19(Suppl. 1):72–82. [2] Pisano ED, Gatsonis C, Hendrick E, Yaffe M, Baum JK, Acharyya S, et al. Diagnostic performance of digital versus film mammography for breast-cancer screening. N Engl J Med 2005;353:1773–83. [3] Chiarelli AM, Edwards SA, Prummel MV, Muradali D, Majpruz V, Done SJ, et al. Digital compared with screen-film mammography: performance measures in concurrent cohorts within an organized breast screening program. Radiology 2013;268:684–93. [4] Hambly NM, McNicholas MM, Phelan N, Hargaden GC, O’Doherty A, Flanagan FL. Comparison of digital mammography and screen-film mammography in breast cancer screening: a review in the Irish breast screening program. 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[14] Reinhard E, Ward G, Pattanaik S, Debevec P. High dynamic range imaging: acquisition, display and image based lighting. San Francisco, CA, USA: Morgan Kaufmann Publishers; 2005. [15] van Engen RE, Bosmans H, Dance DR, Heid P, Lazzari B, Marshall N, et al. Digital mammography update. European protocol for the quality control of the physical and technical aspects of mammography screening. S1, part 1: acceptance and constancy testing. In: Perry N, Broeders M, de, Wolf C, Törnberg S, Holland R, et al., editors. European guidelines for quality assurance in breast cancer screening and diagnosis. 4th ed, Supplements. Luxembourg: European Commission, Office for Official Publications of the European Union; 2013a. p. 1–54. [16] NHSBSP (National Health Service Breast Screening Programme). Technical evaluation of the GE Essential Full Field Digital Mammography System NHSBSP equipment report 0803. Sheffield: NHSBSP Publications; 2008. [17] Burgess A. On the noise variance of a digital mammography system. Med Phys 2004;31:1987–95. [18] Bouwman R, Young K, Lazzari B, Ravaglia V, Broeders M, van Engen R. An alternative method for noise analysis using pixel variance as part of quality control procedures on digital mammography systems. Phys Med Biol 2009;54:6809–22. [19] Monnin P, Bosmans H, Verdun FR, Marshall NW. Comparison of the polynomial model against explicit measurements of noise components for different mammography systems. Phys Med Biol 2014;59:5741–61. [20] Samei E, Flynn MJ, Reimann DA. A method for measuring the presampled MTF of digital radiographic systems using an edge test device. Med Phys 1998;25:102–13. [21] Marshall NW. A comparison between objective and subjective image quality measurements for a full field digital mammography system. Phys Med Biol 2006;51:2441–63. [22] Chakraborty DP, Barnes GT. An energy sensitive cassette for dual energy mammography. Med Phys 1989;16(1):7–13. 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[24] Toroi P, Zanca F, Young KC, Van Ongeval C, Marchal G, Bosmans H. Experimental investigation on the choice of the tungsten/rhodium anode/filter combination for an amorphous selenium based digital mammography system. Eur Radiol 2007;17(9):2368–75. [25] Williams MB, Raghunathan P, More MJ, Seibert JA, Kwan A, Lo JY, et al. Optimization of exposure parameters in full field digital mammography. Med Phys 2008;35(6):2414–23. [26] Dance DR, Skinner CL, Young KC, Beckett JR, Kotre CJ. Additional factors for the estimation of mean glandular breast dose using the UK mammography dosimetry protocol. Phys Med Biol 2000;45(11):3225–40. [27] Dance DR, Young KC, van Engen RE. Further factors for the estimation of mean glandular dose using the United Kingdom, European and IAEA breast dosimetry protocols. Phys Med Biol 2009;54(14):4361–72. [28] Monnin P, Marshall NW, Bosmans H, Bochud FO, Verdun FR. Image quality assessment in digital mammography: part II. NPWE as a validated alternative for contrast detail analysis. Phys Med Biol 2011;56:4221–38. [29] Karssemeijer N, Thijssen MAO. Determination of contrast-detail curves of mammography systems by automated image analysis. In: Doi K, Giger ML, Nishikawa RM, Scmidt RA, editors. Digital mammography. Amsterdam: Elsevier; 1996. p. 155–60. [30] Håkansson M, Svensson S, Zachrisson S, Svalkvist A, Båth M, Månsson LG. ViewDEX: an efficient and easy-to-use software for observer performance studies. Rad Prot Dosim 2010;139:42–51. [31] Young KC, Cook JJH, Okudo JM, Bosmans H. Comparison of software and human observers in reading images of the CDMAM test object to assess digital mammography systems. Proc SPIE 2006;6142:614206.

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[32] Marshall NW. Detective quantum efficiency measured as a function of energy for two full-field digital mammography systems. Phys Med Biol 2009;54:2845– 61. [33] Williams MB, Mangiafico PA, Simoni PU. Noise power spectra of images from digital mammography detectors. Med Phys 1999;26(7):1279–93. [34] Marshall NW. Early experience in the use of quantitative image quality measurements for the quality assurance of full field digital mammography x-ray systems. Phys Med Biol 2007;52:5545–68. [35] Boone JM, Fewell TR, Jennings RJ. Molybdenum, rhodium, and tungsten anode spectral models using interpolating polynomials with application to mammography. Med Phys 1997;24(12):1863–74. [36] Dance DR, Thilander AK, Sandborg M, Skinner CL, Castellano IA, Carlsson GA. Influence of anode/filter material and tube potential on contrast, signal-to-noise ratio and average absorbed dose in mammography: a Monte Carlo study. Br J Radiol 2000;73(874):1056–67. [37] Monnin P, Gutierrez D, Bulling S, Guntern D, Verdun FR. A comparison of the performance of digital mammography systems. Med Phys 2007;34: 906–14. [38] Mackenzie A, Dance DR, Diaz O, Young KC. Image simulation and a model of noise power spectra across a range of mammographic beam qualities. Med Phys 2014;41:121901. [39] NHSBSP (National Health Service Breast Screening Programme). Technical evaluation of Philips MicroDose L30 with AEC software version 8.3 NHSBSP equipment report 1305. Sheffield: NHSBSP Publications; 2013.

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