Amorphous selenium flat panel detectors for digital mammography: validation of a NPWE model observer with CDMAM observer performance experiments

Model observers have been developed which incorporate a specific imaging task, system performance, and human observer characteristics and can potentially overcome some of the limitations in using detective quantum efficiency for optimization and comparison of detectors. In this paper, a modified nonprewhitening matched filter (NPWE) model observer was developed and validated to predict object detectability for an amorphous selenium (a-Se) direct flat-panel imager (FPI) where aliasing is severe. A preclinical a-Se digital mammography FPI with 85 microm pixel size was used in this investigation. Its physical imaging properties including modulation transfer function (MTF), noise power spectrum, and DQE were fully characterized. An observer performance study was conducted by imaging the CDMAM 3.4 contrast-detail phantom designed specifically for digital mammography and presenting these images to a panel of seven observers. X-ray attenuation and scatter due to the phantom were determined experimentally for use in development of the model observer. The observer study results were analyzed via threshold averaging and signal detection theory (SDT) based techniques to produce contrast-detail curves where threshold contrast is plotted as a function of disk diameter. Validity of the model was established using SDT analysis of the experimental data. The effect of aliasing on the detectability of small diameter disks was determined using the NPWE model observer. The signal spectrum was calculated using the presampling MTF of the detector with and without including the aliased terms. Our results indicate that the NPWE model based on Fourier domain parameters provides reasonable prediction of object detectability for the signal-known-exactly task in uniform image noise for a-Se direct FPI.     

Image quality assessment in digital mammography: part I. Technical characterization of the systems

In many European countries, image quality for digital x-ray systems used in screening mammography is currently specified using a threshold-detail detectability method. This is a two-part study that proposes an alternative method based on calculated detectability for a model observer: the first part of the work presents a characterization of the systems. Eleven digital mammography systems were included in the study; four computed radiography (CR) systems, and a group of seven digital radiography (DR) detectors, composed of three amorphous selenium-based detectors, three caesium iodide scintillator systems and a silicon wafer-based photon counting system. The technical parameters assessed included the system response curve, detector uniformity error, pre-sampling modulation transfer function (MTF), normalized noise power spectrum (NNPS) and detective quantum efficiency (DQE). Approximate quantum noise limited exposure range was examined using a separation of noise sources based upon standard deviation. Noise separation showed that electronic noise was the dominant noise at low detector air kerma for three systems; the remaining systems showed quantum noise limited behaviour between 12.5 and 380 μGy. Greater variation in detector MTF was found for the DR group compared to the CR systems; MTF at 5 mm(-1) varied from 0.08 to 0.23 for the CR detectors against a range of 0.16-0.64 for the DR units. The needle CR detector had a higher MTF, lower NNPS and higher DQE at 5 mm(-1) than the powder CR phosphors. DQE at 5 mm(-1) ranged from 0.02 to 0.20 for the CR systems, while DQE at 5 mm(-1) for the DR group ranged from 0.04 to 0.41, indicating higher DQE for the DR detectors and needle CR system than for the powder CR phosphor systems. The technical evaluation section of the study showed that the digital mammography systems were well set up and exhibiting typical performance for the detector technology employed in the respective systems.     

Contrast-detail phantom scoring methodology

Published results of medical imaging studies which make use of contrast detail mammography (CDMAM) phantom images for analysis are difficult to compare since data are often not analyzed in the same way. In order to address this situation, the concept of ideal contrast detail curves is suggested. The ideal contrast detail curves are constructed based on the requirement of having the same product of the diameter and contrast (disk thickness) of the minimal correctly determined object for every row of the CDMAM phantom image. A correlation and comparison of five different quality parameters of the CDMAM phantom image determined for obtained ideal contrast detail curves is performed. The image quality parameters compared include: (1) contrast detail curve--a graph correlation between "minimal correct reading" diameter and disk thickness; (2) correct observation ratio--the ratio of the number of correctly identified objects to the actual total number of objects multiplied by 100; (3) image quality figure--the sum of the product of the diameter of the smallest scored object and its relative contrast; (4) figure-of-merit--the zero disk diameter value obtained from extrapolation of the contrast detail curve to the origin (e.g., zero disk diameter); and (5) k-factor--the product of the thickness and the diameter of the smallest correctly identified disks. The analysis carried out showed the existence of a nonlinear relationship between the above parameters, which means that use of different parameters of CDMAM image quality potentially can cause different conclusions about changes in image quality. Construction of the ideal contrast detail curves for CDMAM phantom is an attempt to determine the quantitative limits of the CDMAM phantom as employed for image quality evaluation. These limits are determined by the relationship between certain parameters of a digital mammography system and the set of the gold disks sizes in the CDMAM phantom. Recommendations are made on selections of CDMAM phantom regions which should be used for scoring at different image quality and which scoring methodology may be most appropriate. Special attention is also paid to the use of the CDMAM phantom for image quality assessment of digital mammography systems particularly in the vicinity of the Nyquist frequency.     

Are phantoms useful for predicting the potential of dose reduction in full-field digital mammography?

A phantom study was performed in full-field digital mammography to investigate the opportunity and the magnitude of a possible dose reduction that would leave the image quality above the accepted thresholds associated with some classical phantoms. This preliminary work is intended to lay the groundwork for a future clinical study on the impact of dose reduction on clinical results. Three different mammography phantoms (ACR RMI 156, CIRS 11A and CDMAM 3.4) were imaged by a full-field digital mammography unit (GE Senographe 2000D) at different dose levels. Images were rated by three observers with softcopy reading and scoring methods specific to each phantom. Different types of data analysis were applied to the ACR (American College of Radiology) and the other two phantoms, respectively. With reference to the minimum acceptance score in screen/film accreditation programmes, the ACR phantom showed that about 45% dose reduction could be applied, while keeping the phantom scores above that threshold. A relative comparison was done for CIRS and CDMAM, for which no threshold is defined. CIRS scoring remained close to the reference level down to 40% dose reduction, the inter- and intra-observer variability being the main source of uncertainty. Contrast-detail curves provided by CDMAM overlapped down to 50% dose reduction, at least for object contrast values ranging between 30% and 3%. This multi-phantom study shows the potential of further reducing the dose in full-field digital mammography beyond the current values. A common dose reduction factor around 50% seems acceptable for all phantoms. However, caution is required before extrapolating the results for clinical use, given the limitations of these widely used phantoms, mainly related to their limited dynamic range and uniform background.     

Validation of a digital mammographic unit model for an objective and highly automated clinical image quality assessment

In mammography, image quality assessment has to be directly related to breast cancer indicator (e.g. microcalcifications) detectability. Recently, we proposed an X-ray source/digital detector (XRS/DD) model leading to such an assessment. This model simulates very realistic contrast-detail phantom (CDMAM) images leading to gold disc (representing microcalcifications) detectability thresholds that are very close to those of real images taken under the simulated acquisition conditions. The detection step was performed with a mathematical observer. The aim of this contribution is to include human observers into the disc detection process in real and virtual images to validate the simulation framework based on the XRS/DD model. Mathematical criteria (contrast-detail curves, image quality factor, etc.) are used to assess and to compare, from the statistical point of view, the cancer indicator detectability in real and virtual images. The quantitative results given in this paper show that the images simulated by the XRS/DD model are useful for image quality assessment in the case of all studied exposure conditions using either human or automated scoring. Also, this paper confirms that with the XRS/DD model the image quality assessment can be automated and the whole time of the procedure can be drastically reduced. Compared to standard quality assessment methods, the number of images to be acquired is divided by a factor of eight.     

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.     

Characterization of the effects of the FineView algorithm for full field digital mammography

The aim of this study was to characterize the effect of an image processing algorithm (FineView) on both quantitative image quality parameters and the threshold contrast detail response of the GE Senographe DS full-field digital mammography system. The system was characterized using signal transfer property, pre-sampling modulation transfer function (MTF), normalized noise power spectrum (NNPS) and detective quantum efficiency (DQE) of the system. An algorithmic modulation transfer function (MTF(a)) was calculated from images acquired at a reduced detector air kerma (DAK) and with the FineView algorithm enabled. Two sets of beam conditions were used: Mo/Mo/28 kV and Rh/Rh/29 kV, both with 2 mm added Al filtration at the x-ray tube. Images were acquired with and without FineView at four DAK levels from 14 to 378 μGy. The threshold contrast detail response was assessed using the CDMAM contrast-detail test object which was imaged under standard clinical conditions with and without FineView at three DAK levels from 24 to 243 μGy. The images were scored by both human observers and by automated scoring software. Results indicated an improvement of up to 125% at 5 mm?1 in MTF(a) when FineView was activated, particularly at high DAK levels. A corresponding increase of up to 425% at 5 mm?1 was also seen in the NNPS, again with the same DAK dependence. FineView did not influence DQE, an indication that the signal to noise ratio transfer of the system remained unchanged. FineView did not affect the threshold contrast detectability of the system, a result that is consistent with the DQE results.     

Threshold contrast detail detectability measurement of the fluoroscopic image quality of a dynamic solid-state digital x-ray image detector

Solid-state digital x-ray imaging detectors of flat-panel construction will play an increasingly important role in future medical imaging facilities. Solid-state detectors that will support both dynamic (including fluoroscopic) and radiographic image recording are under active development. The image quality of an experimental solid-state digital x-ray image detector operating in a continuous fluoroscopy mode has been investigated. The threshold contrast detail detectability (TCDD) technique was used to compare the fluoroscopic imaging performance of an experimental dynamic solid-state digital x-ray image detector with that of a reference image intensifier television (IITV) fluoroscopy system. The reference system incorporated Plumbicon TV. Results were presented as a threshold detection index, or H(T)(A), curves. Measurements were made over a range of mean entrance air kerma (EAK) rates typically used in conventional IITV fluoroscopy. At the upper and mid EAK rate range (440 and 220 nGy/s) the solid-state detector outperformed the reference IITV fluoroscopy system as measured by TCDD performance. At the lowest measured EAK rate (104 nGy/s), the solid-state detector produces slightly inferior TCDD performance compared with the reference system. Although not statistically significant at this EAK rate, the difference will increase as EAK is lowered further. Overall the TCDD results and early clinical experiences support the proposition that a current design of dynamic solid-state detector produces image quality competitive with that of modern IITV fluoroscopy systems. These findings encourage the development of compact and versatile universal x-ray imaging systems based upon solid-state detector technology to support R & F and vascular/interventional applications.     

Automated assessment of low contrast sensitivity for CT systems using a model observer

Purpose: Low contrast sensitivity of CT scanners is regularly assessed by subjective scoring of low contrast detectability within phantom CT images. Since in these phantoms low contrast objects are arranged in known fixed patterns, subjective rating of low contrast visibility might be biased. The purpose of this study was to develop and validate a software for automated objective low contrast detectability based on a model observer.Methods: Images of the low contrast module of the Catphan 600 phantom were used for the evaluation of the software. This module contains two subregions: the supraslice region with three groups of low contrast objects (each consisting of nine circular objects with diameter 2-15 mm and contrast 0.3, 0.5, and 1.0%, respectively) and the subslice region with three groups of four circular objects each (diameter 3-9 mm; contrast 1.0%). The software method offered automated determination of low contrast detectability using a NPWE (nonprewhitening matched filter with an eye filter) model observer for the supraslice region. The model observer correlated templates of the low contrast objects with the acquired images of the Catphan phantom and a discrimination index d' was calculated. This index was transformed into a proportion correct (PC) value. In the two-alternative forced choice (2-AFC) experiments used in this study, a PC ≥ 75% was proposed as a threshold to decide whether objects were visible. As a proof of concept, influence of kVp (between 80 and 135 kV), mAs (25-200 mAs range) and reconstruction filter (four filters, two soft and two sharp) on low contrast detectability was investigated. To validate the outcome of the software in a qualitative way, a human observer study was performed.Results: The expected influence of kV, mAs and reconstruction filter on image quality are consistent with the results of the proposed automated model. Higher values for d' (or PC) are found with increasing mAs or kV values and for the soft reconstruction filters. For the highest contrast group (1%), PC values were fairly above 75% for all object diameters >2 mm, for all conditions. For the 0.5% contrast group, the same behavior was observed for object diameters >3 mm for all conditions. For the 0.3% contrast group, PC values were higher than 75% for object diameters >6 mm except for the series acquired at the lowest dose (25 mAs), which gave lower PC values. In the human observer study similar trends were found.Conclusions: We have developed an automated method to objectively investigate image quality using the NPWE model in combination with images of the Catphan phantom low contrast module. As a first step, low contrast detectability as a function of both acquisition and reconstruction parameter settings was successfully investigated with the software. In future work, this method could play a role in image reconstruction algorithms evaluation, dose reduction strategies or novel CT technologies, and other model observers may be implemented as well.     

A comparison between objective and subjective image quality measurements for a full field digital mammography system

This paper presents pre-sampling modulation transfer function (MTF), normalized noise power spectrum (NNPS) and detective quantum efficiency (DQE) results for an amorphous selenium (a-Se) full field digital mammography system. MTF was calculated from the image of an angled 0.5 mm thick Cu edge, acquired without additional beam filtration. NNPS data were acquired at detector air-kerma levels ranging from 9.1 microGy to 331 microGy, using a standard mammography x-ray spectrum of 28 kV, Mo/Mo target/filter combination and 4 cm of PMMA additional filtration. Prior to NNPS estimation, the image statistics were assessed using a variance image. This method was able to easily identify a detector artefact and should prove useful in routine quality assurance (QA) measurements. Detector DQE, calculated from the NNPS and MTF data, dropped to 0.3 for low detector air-kerma settings but reached an approximately constant value of 0.6 above 50 microGy at the detector. Subjective image quality data were also obtained at these detector air-kerma settings using the CDMAM contrast-detail (c-d) test object. The c-d data reflected the trend seen in DQE, with threshold contrast increasing at low detector air-kerma values. The c-d data were then compared against predictions made using two established models, the Rose model and a standard signal detection theory model. Using DQE(0), the Rose model gave results within approximately 15% on average for all the detector air-kerma values studied and for detail diameters down to 0.2 mm. Similar agreement was also found between the measured c-d data and the signal detection theory results, which were calculated using an ideal human visual response function and a system magnification of unity. The use of full spatial frequency DQE improved the agreement between the calculated and observer results for detail sizes below 0.13 mm.     

The value of scatter removal by a grid in full field digital mammography

Our objective in this study was to investigate the usefulness of an anti-scatter grid in digital mammography using a contrast detail phantom. The mammography system we investigated was a GE Senographe 2000D. We carried out phantom measurements under various conditions with and without using the anti-scatter grid. A new version of the CDMAM phantom (version 3.4) was used. This phantom consists of a matrix of square cells with disks of varying size and contrast. For given exposure conditions detectability of these disks can be determined and used for construction of contrast detail curves. Previously, a computer program was developed at our institute that performs a fully automatic analysis of the phantom recordings using the ideal observer model. Breast thickness was simulated by a homogeneous layer of PMMA in the range of 1 to 7 cm. Series of images were recorded for different KeV and target-filter combinations depending on the simulated thickness. The dose was kept constant for each thickness with and without using a grid. It appeared that image quality improved for simulated breast thickness below 5 cm when the grid was removed. In the range from 5 to 7 cm contrast detail curves obtained with or without a grid were similar. Results suggest that for compressed breast thickness in the range of 1 to 7 cm a grid might not be needed in the digital mammography system we investigated. Below 5 cm, omitting the grid may allow lower dose to the patient without losing image quality.     

Computation of realistic virtual phantom images for an objective lesion detectability assessment in digital mammography

Image quality assessment is required for an optimal use of mammographic units. On the one hand, there are objective image quality assessment methods based on the measurement of technical parameters such as modulation transfer function (MTF), noise power spectrum (NPS) or detection quantum efficiency (DQE) describing performances of digital detectors. These parameters are, however, without direct relationship with lesion detectability in clinical practice. On the other hand, there are image quality assessment methods involving time consuming procedures, but presenting a direct relationship with lesion detectability. This contribution describes an X-ray source/digital detector model leading to the simulation of virtual contrast-detail phantom (CDMAM) images. The virtual image computation method requires the acquisition of only few real images and allows for an objective image quality assessment presenting a direct relationship with lesion detectability. The transfer function of the proposed model takes as input physical parameters (MTF* and noise) measured under clinical conditions on mammographic units. As presented in this contribution, MTF* is a modified MTF taking into account the effects due to X-ray scatter in the breast and magnification. Results obtained with the structural similarity index prove that the simulated images are quite realistic in terms of contrast and noise. Tests using contrast detail curves highlight the fact that the simulated and real images lead to very similar data quality in terms of lesion detectability. Finally, various statistical tests show that quality factors computed for both the simulated images and the real images are very close for the two data sets.     

Digital mammography image simulation using Monte Carlo

Monte Carlo simulations of digital images of the contrast detail phantom and the ACR phantom are presented for two different x-ray digital mammography modalities: a synchrotron mammography system and a next-generation scanning slot clinical system. A combination of variance reduction methods made it possible to simulate accurate images using real pixel dimensions within reasonable computation times. The complete method of image simulation, including a simple detector response model, a simple noise model, and the incorporation of system effects (MTF), is presented. The simulated images of the phantoms show good agreement with images measured on the two systems.     

Quantification of Al-equivalent thickness of just visible microcalcifications in full field digital mammograms

Characterization of digital mammography systems is often performed by means of contrast-detail curves using a homogeneous phantom with inserts of different sizes and thicknesses. In this article, a more direct measure of the threshold contrast-detail characteristics of microcalcifications in clinical mammograms is proposed, which also takes into account routine processing and display. The proposed method scores the detectability of simulated microcalcifications with known size and aluminum-equivalent thickness. Thickness estimates, based on x-ray transmission coefficients, were first validated for Al particles. The same approach was then applied to associate Al-equivalent thickness with simulated microcalcifications. Thirty-five mammograms of patients were acquired using a full field digital mammography (FFDM) system operating under standard exposure conditions. Different microcalcifications were simulated using templates of real microcalcifications as described in Med. Phys. 30, 2234-2240 (2003). These templates were first modified such that they simulated a template of the same microcalcification for an ideally sharp detector. They were then adjusted for the imaging characteristics of the FFDM, beam quality, and breast thickness. Microcalcification sizes in the image plane ranged from 200 to 800 microm. Their peak Al-equivalent thickness varied between 70 and 1000 microm. Software phantoms were created. They consisted of 0-10 simulated microcalcifications randomly distributed in 2 cm by 2 cm frames embedded within digital mammograms. Routine processing and printing followed. Three experienced radiologists recorded the locations of the microcalcifications, and confidence ratings were given. Free response receiver operating characteristics (FROC) analysis was performed. Using a binary score, the fractions of detected microcalcifications were plotted as a function of equivalent diameter for the different Al-equivalent thicknesses. Pair-wise agreement of the detected microcalcifications was calculated for the different Al-equivalent thickness groups. The FROC curves of each radiologist indicated similar true positive fractions for a given number of false positives per image. One radiologist applied a more conservative scoring. Detected fractions for the different sizes of the microcalcifications showed the same trend for all observers. In addition, the observer with the least FP also detected less microcalcifications. The pair-wise agreement of the detected microcalcifications was good. The average detected fractions were >0.5 for microcalcifications with equivalent diameter >400 microm and Al-equivalent thickness >400 microm. An average detected fraction >0.5 was also seen for microcalcifications with equivalent diameter <400 microm and equivalent thickness >800 microm. The detected fractions of smaller microcalcifications were <0.5. The results obtained with this method indicate that it may be possible to quantify the performance of a digital mammography detector including processing and viewing for the detection of microcalcifications. We hypothesize that the FROC curves and detected fractions of simulated microcalcifications of different sizes reflect the clinical reality.     

Calibrating automatic exposure control devices for digital radiography

The energy responses of digital radiography detectors differ from those of screen-film systems. To provide a consistent level of image quality at different tube potentials automatic exposure control (AEC) devices must be calibrated to suit the energy response of the image receptor with which they are intended for use. AEC calibration for digital radiography systems requires an alternative parameter to optical density, ideally one related to the quality of a digital image. Energy responses of computed radiography (CR) and indirect digital radiography (IDR) image receptors have been calculated, and compared with those for screen-film systems. Practical assessments of the relative sensitivities of a CR detector made using the detector dose indicator (DDI), pixel value and signal-to-noise ratio showed similar variations with tube potential. The DDI has been used to determine the correct kV compensation curve required to calibrate the AECs for the loss in detector sensitivity with tube potential. AECs are set up relative to a predetermined air kerma incident on the detector at 80 kV for CR and IDR systems using this curve and the method used is described. Factors influencing the calibration of AECs for digital radiography including techniques, types of phantom and contributions from scatter are reviewed, and practical methods recommended for use.     

Dose efficiency and low-contrast detectability of an amorphous silicon x-ray detector for digital radiography

The effect of dose reduction on low-contrast detectability is investigated theoretically and experimentally for a production grade amorphous silicon (a-Si) x-ray detector and compared with a standard thoracic screen-film combination. A non-prewhitening matched filter observer model modified to include a spatial response function and internal noise for the human visual system (HVS) is used to calculate a signal-to-noise ratio (SNR) related to object detectability. Other inputs to the SNR calculation are the detective quantum efficiency (DQE) and the modulation transfer function (MTF) of the imaging system. Besides threshold detectability, the model predicts the equivalent perception dose ratio (EPDR), which is the fraction of the screen film exposure for which the digital detector provides equal detectability. Images of a contrast-detail phantom are obtained with the digital detector at dose levels corresponding to 27%, 41%, 63% and 100% of the dose used for screen-film. The images are used in a four-alternative forced choice (4-AFC) observer perception study in order to measure threshold detectability. A statistically significant improvement in contrast detectability is measured with the digital detector at 100% and 63% of the screen-film dose. There is no statistical difference between screen-film and digital at 41% of the dose. On average, the experimental EPDR is 44%, which agrees well with the model prediction of 40%.     

Comparison of low contrast detectability between a digital amorphous silicon and a screen-film based imaging system for thoracic radiography.

Low contrast threshold detectability is investigated theoretically and experimentally for an amorphous silicon (a-Si) x-ray detector designed for digital radiography and for a standard thoracic screen-film combination. A theoretical signal-to-noise ratio is described with a human observer signal detection model. It is calculated using the detective quantum efficiency (DQE) and the modulation transfer function of the imaging system, as well as a spatial response function for the human visual system. Using a four-alternative forced choice observer perception study, the threshold contrasts of disk shaped objects ranging in size from 0.3 to 4.0 mm are determined. Significantly better contrast detectability is obtained from the digital detector, which is attributed to its higher DQE. On average, the disk shaped objects can be detected at 45% less contrast than required for screen-film. With no free parameters the experimental data agree well with those predicted by the observer model. Based upon the data, the model predicts that x-ray exposure for the a-Si detector only needs to be 30% of the exposure required to perform equally well on the contrast-detail detectability task using screen-film.     

Effect of area x-ray beam equalization on image quality and dose in digital mammography

In mammography, thick or dense breast regions persistently suffer from reduced contrast-to-noise ratio (CNR) because of degraded contrast from large scatter intensities and relatively high noise. Area x-ray beam equalization can improve image quality by increasing the x-ray exposure to under-penetrated regions without increasing the exposure to other breast regions. Optimal equalization parameters with respect to image quality and patient dose were determined through computer simulations and validated with experimental observations on a step phantom and an anthropomorphic breast phantom. Three parameters important in equalization digital mammography were considered: attenuator material (Z = 13-92), beam energy (22-34 kVp) and equalization level. A Mo/Mo digital mammography system was used for image acquisition. A prototype 16 x 16 piston driven equalization system was used for preparing patient-specific equalization masks. Simulation studies showed that a molybdenum attenuator and an equalization level of 20 were optimal for improving contrast, CNR and figure of merit (FOM = CNR2/dose). Experimental measurements using these parameters showed significant improvements in contrast, CNR and FOM. Moreover, equalized images of a breast phantom showed improved image quality. These results indicate that area beam equalization can improve image quality in digital mammography.     

Evaluation of detector dynamic range in the x-ray exposure domain in mammography: a comparison between film-screen and flat panel detector systems

Digital detectors in mammography have wide dynamic range in addition to the benefit of decoupled acquisition and display. How wide the dynamic range is and how it compares to film-screen systems in the clinical x-ray exposure domain are unclear. In this work, we compare the effective dynamic ranges of film-screen and flat panel mammography systems, along with the dynamic ranges of their component image receptors in the clinical x-ray exposure domain. An ACR mammography phantom was imaged using variable mAs (exposure) values for both systems. The dynamic range of the contrast-limited film-screen system was defined as that ratio of mAs (exposure) values for a 26 kVp Mo/Mo (HVL=0.34 mm Al) beam that yielded passing phantom scores. The same approach was done for the noise-limited digital system. Data from three independent observers delineated a useful phantom background optical density range of 1.27 to 2.63, which corresponded to a dynamic range of 2.3 +/- 0.53. The digital system had a dynamic range of 9.9 +/- 1.8, which was wider than the film-screen system (p<0.02). The dynamic range of the film-screen system was limited by the dynamic range of the film. The digital detector, on the other hand, had an estimated dynamic range of 42, which was wider than the dynamic range of the digital system in its entirety by a factor of 4. The generator/tube combination was the limiting factor in determining the digital system's dynamic range.     

Ambient dose equivalent and effective dose from scattered x-ray spectra in mammography for Mo/Mo, Mo/Rh and W/Rh anode/filter combinations

In this study, scattered x-ray distributions were produced by irradiating a tissue equivalent phantom under clinical mammographic conditions by using Mo/Mo, Mo/Rh and W/Rh anode/filter combinations, for 25 and 30 kV tube voltages. Energy spectra of the scattered x-rays have been measured with a Cd(0.9)Zn(0.1)Te (CZT) detector for scattering angles between 30 degrees and 165 degrees . Measurement and correction processes have been evaluated through the comparison between the values of the half-value layer (HVL) and air kerma calculated from the corrected spectra and measured with an ionization chamber in a nonclinical x-ray system with a W/Mo anode/filter combination. The shape of the corrected x-ray spectra measured in the nonclinical system was also compared with those calculated using semi-empirical models published in the literature. Scattered x-ray spectra measured in the clinical x-ray system have been characterized through the calculation of HVL and mean photon energy. Values of the air kerma, ambient dose equivalent and effective dose have been evaluated through the corrected x-ray spectra. Mean conversion coefficients relating the air kerma to the ambient dose equivalent and to the effective dose from the scattered beams for Mo/Mo, Mo/Rh and W/Rh anode/filter combinations were also evaluated. Results show that for the scattered radiation beams the ambient dose equivalent provides an overestimate of the effective dose by a factor of about 5 in the mammography energy range. These results can be used in the control of the dose limits around a clinical unit and in the calculation of more realistic protective shielding barriers in mammography.