KEYWORDS: Breast, 3D modeling, Polymethylmethacrylate, Digital breast tomosynthesis, Signal attenuation, Tissues, Target detection, Liquids, Photography, Quality measurement
Purpose: In this work we present equivalent breast thickness and dose sensitivity of a next iteration 3D structured breast phantom with lesion models to demonstrate its potential use for quality assurance measurements in breast imaging. Methods: PMMA equivalent thickness was determined employing the automatic exposure control (AEC) of Siemens Mammomat Inspiration and Siemens Mammomat Revelation. A 2D projection image of the phantom was acquired and the corresponding AEC settings recorded as reference. Equivalent PMMA thickness was found by interpolating between three PMMA thicknesses with mAs values close to the reference settings selected by AEC. Dose sensitivity of the reconstructed digital breast tomosynthesis (DBT) images was assessed by two experienced readers using a four alternative forced choice (4-AFC) study. Three different dose levels for lesion models and microcalcifications were evaluated. Results: PMMA equivalent thickness of the phantom was 46.8 mm and 47.0 mm for measurements on Siemens Mammomat Inspiration and Siemens Mammomat Revelation which equals to a breast equivalent thickness of 55.5 mm and 55.8 mm, respectively, compared to a physical phantom thickness of 53.5 mm. For lesion models dose sensitiviy of the detectability was not obvious. For microcalcification the diameter threshold was found to increase for decreasing dose from high dose to AEC to low dose. Conclusions: We found the measured equivalent breast thickness of our phantom to be close to its physical thickness. It can be concluded that changes in dose can be detected by the presented phantom for the tested dose levels.
In this work we tested different materials for 3D printing of spiculated mass models for their incorporation into an existing 3D structured phantom for performance testing of FFDM and DBT. Counting the number of spicules as a function of dose was then evaluated as a possible extra test feature expressing conspicuity next to detectability. Seven printable materials were exposed together with a PMMA step wedge and material samples with known linear attenuation coefficient to determine PMMA equivalent thickness and linear attenuation coefficient, respectively. Next, two models of spiculated masses were created each with a different complexity in terms of number of spicules. The visibility of the number of spicules of a 3D printed spiculated mass model loosely placed in the phantom or embedded into two different printing materials was assessed for FFDM and DBT. Vero White pure was chosen as the most appropriate material for the printing of masses whereas Vero Clear and Tango+ were chosen as background materials. The visibility of spicules was best in the loose mass models and better in the background material Tango+ compared to Vero Clear. While the discrimination of the different spicules could be assessed in FFDM and DBT, as expected only a limited dose sensitivity was found for the visibility of spicules evaluated for the different background materials and at different beam energies.
KEYWORDS: Mammography, Image quality, Control systems, Radiography, Computing systems, Breast cancer, Medical imaging, Point spread functions, Image analysis
Mammography screenings demand for profound image quality (IQ) assessment to guarantee their screening success. The European protocol for the quality control of the physical and technical aspects of mammography screening (EPQCM) suggests a contrast detail phantom such as the CDMAM phantom to evaluate IQ. For automatic evaluation a software is provided by the EUREF. As human and automatic readouts differ systematically conversion factors were published by the official reference organisation (EUREF). As we experienced a significant difference for these factors for Computed Radiography (CR) systems we developed an objectifying analysis software which presents the cells including the gold disks randomly in thickness and rotation. This allows to overcome the problem of an inevitable learning effect where observers know the position of the disks in advance. Applying this software, 45 computed radiography (CR) systems were evaluated and the conversion factors between human and automatic readout determined. The resulting conversion factors were compared with the ones resulting from the two methods published by EUREF. We found our conversion factors to be substantially lower than those suggested by EUREF, in particular 1.21 compared to 1.42 (EUREF EU method) and 1.62 (EUREF UK method) for 0.1 mm, and 1.40 compared to 1.73 (EUREF EU) and 1.83 (EUREF UK) for 0.25 mm disc diameter, respectively. This can result in a dose increase of up to 90% using either of these factors to adjust patient dose in order to fulfill image quality requirements. This suggests the need of an agreement on their proper application and limits the validity of the assessment methods. Therefore, we want to stress the need for clear criteria for CR systems based on appropriate studies.
Technical quality assurance (TQA) procedures for mammography systems usually include tests with a contrast-detail phantom. These phantoms contain multiple objects of varying dimensions arranged on a flat body. Exposures of the phantom are then evaluated by an observer, either human or software.
One well-known issue of this method is that dose distribution is not uniform across the image area of any mammography system, mainly due to the heel effect. The purpose of this work is to investigate to what extent image quality differs across the detector plane.
We analyze a total of 320 homogeneous mammography exposures from 32 radiology institutes. Systems of different models and manufacturers, both computed radiography (CR) and direct radiography (DR) are included. All images were taken from field installations operated within the nationwide Austrian mammography screening program, which includes mandatory continuous TQA.
We calculate signal-to-noise ratios (SNR) for 15 regions of interest arranged to cover the area of the phantom. We define the 'signal range' of an image and compare this value categorized by technologies.
We found the deviations of SNR greater in anterior-posterior than in lateral direction. SNR ranges are significantly higher for CR systems than for DR systems.
KEYWORDS: Image quality, Gold, Mammography, Image analysis, Medical imaging, Control systems, Digital mammography, Medical physics, Biomedical engineering, Physics
A contrast-detail phantom like the CDMAM phantom (Artinis Medical Systems, Zetten, NL) is suggested by the ’European protocol for the quality control of the physical and technical aspects of mammography screening’ to evaluate image quality of digital mammography systems. In a recent paper the commonly used CDMAM 3.4 was evaluated according to its dose sensitivity in comparison to other phantoms. The successor phantom (CDMAM 4.0) features other disc diameters and thicknesses that were adapted to be more closely to the image quality which can be found in modern mammography systems. It seems to be obvious to compare this two generations of phantoms with respect to a potential improvement. The time-current product was varied within a range of clinically used values (40-160 mAs). Image evaluation was performed using the automatic evaluation software provided by Artinis. The relative dose sensitivity was compared in dependence of different diameters. Additionally, the IQFinv parameter, which averages over the diameters was computed to get a more global conclusion. We found that the dose is of a considerable smoother dependence with the CMDAM 4.0 phantom. Also the IQFinv parameter shows a more linear behaviour than with the CDMAM 3.4. As the automatic evaluation shows different results on the two phantoms, conversion factors from automatic to human readouts have to be adapted consequently.
For the use in routine technical quality assurance (TQA) we developed a tissue-mimicking phantom and an evaluation algorithm. Key properties of US phantom materials are sound velocity and acoustic attenuation. For daily clinical use the material also has to be nontoxic, durable and easy in handling and maintenance. The base material of our phantom is Poly(vinyl alcohol) (PVA), a synthetic polymer. By freezing the phantom body during the production process, it changes its sound velocity to closely match the one of the human body. The phantom's base form is a cuboid containing a large anechoic cylindric target. In routine QA it is required to gain comparable and reproducible results from a single image. To determine spatial resolution of phantom images, we calculate a modulation transfer function (MTF). We developed an algorithm, that calculates a radial MTF from a circular structure representing spatial resolution averaged across all directions. For evaluation of the algorithm, we created a set of synthetic images. A comparison of the results from a traditional slanted edge algorithm and our solution showed a close correlation. The US phantom was imaged with a commercial US-scanner at different sound frequencies. The computed MTFs of higher frequency images show higher transfer percentages in all spatial frequencies than the MTFs of lower frequency images. The results suggest that the proposed method produces clear statements about the spatial resolution of evaluated imaging devices. We therefore consider the method as suitable for application in technical quality assurance of diagnostic ultrasound scanners.
Technical quality assurance (TQA) is one of the key issues in breast screening protocols where the
two crucial aspects are image quality and dose. While digital radiography (DR) systems can produce
excellent image quality at low dose, it appears often to be difficult with computed radiography (CR)
systems to fulfill the requirements for image quality and to keep the dose below the limits. Here, the
choice of the optimal spectrum can be necessary to comply with the limiting values given by the
standards.
To determine the optimal spectrum, we calculated the contrast-noise ratio (CNR) for different
anode/filter (a/f) combinations in dependence of tube voltage. This was done for breast thicknesses
of 50, 60 and 70 mm. The figure-of-merit to be optimized was the quotient of squared CNR and
average glandular dose. The investigated imaging plates were made of BaFBrI:Eu from a Fuji CR
system. For comparison we repeated the measurements on a Carestream system.
With respect to the Fuji system we found that the two k-edges of Iodine at 33 kV and Barium
at 37 kV influence the results significantly. A peak as found in DR systems is followed by two
additional peaks resulting from the higher absorption at the k-edges. This can be experienced with
all a/f combinations. The same effect also occurred on the Carestream system.
Image quality assurance is one of the key issues in breast screening protocols. Although image
quality can always be improved by increasing dose this mechanism is restricted by limiting values
given by the standards. Therefore, it is crucial for system adjustment to describe the dependency
of the image quality parameters on small changes in dose. This dose sensitivity was tested for three
image quality evaluation methods. The European protocol requires the use of the CDMAM phantom
which is a conventional contrast-detail phantom, while in North America the American College of
Radiology (ACR) accreditation phantom is proposed. In contrast to these visual test methods the
German PAS 1054 phantom uses digital image processing to derive image quality parameters like
the noise-equivalent number of quanta (NEQ).
We varied the dose within the range of clinical use. For the ACR phantom the examined parameter
was the number of detected objects. With the CDMAM phantom we chose the diameters 0,10,
0.13, 0.20, 0.31 and 0.5 mm and recorded the threshold thicknesses. With respect to the PAS 1054
measurements we evaluated the NEQ at typical spatial frequencies to calculate the relative changes.
NEQ versus dose increment shows a linear relationship and can be described by a linear function
(R = .998). Every current-time product increment can be detected. With the ACR phantom the
number of detected objects increases only in the lower dose range and reaches saturation at about
100mAs. The CDMAM can detect a 50% increase in dose confidently although the parameter
increase is not monotonous.
We conclude that an NEQ based method can be used as a simple and highly sensitive procedure
for weekly quality assurance.
According to the European protocol for the quality control of the physical and technical aspects of mammography
screening (EPQCM) image quality of digital mammography devices has to be evaluated using the CDMAM
(contrast-detail mammography) phantom. The evaluation of image quality is accomplished by the determination
of threshold thicknesses of gold disks of different diameters (0.08 mm to 2 mm). The EPQCM requires this task
to be performed by qualified human observers and revealed to be very time consuming.Therefore a software
solution was provided by the European Reference Organisation for Quality Assured Breast Screening (Euref)
known as 'cdcom'. The problem with this program is that it provides threshold thicknesses different from the
results gained by human readers. Factors for the conversion from automatic to human read outs depend on the
diameter of the gold disk and were estimated using a huge amount of data, both human and automatic read
outs. But these factors provided by various groups differ from each other and are purely phenomenological.
Our approach uses the Rose theory which gives a correlation between threshold contrast, diameter of the object
and number of incident photons. To estimate the five conversion factors between the diameters of 0.2 mm and
0.5 mm we exposed with five different current-time products which resulted in 25 equations with six unknowns
(5 factors and one constant). This optimization problem was then solved using the Excel built-in solver. The
theoretical conversion factors amounted to be 1.62, 1.75, 2.04, 2.20, 2.39 for the diameters of 0.2, 0.25, 0.31, 0.4,
and 0.5 mm. The corresponding phenomenological factors found in literature are 1.74, 1.78, 1.83, 1.88, and 1.93.
The applied method reveals to be very robust and produces factors comparable to the phenomenological ones.
According to the 'European protocol for the quality control of the physical and technical aspects of mammography
screening' (EPQC) image quality digital mammography units has to be evaluated at different breast thicknesses.
At the standard thickness of 50 mm polymethyl methacrylate (PMMA) image quality is determined by the
analysis of CDMAM contrast detail phantom images where threshold contrasts are calculated for different gold
disc diameters. To extend these results to other breast thicknesses contrast-to-noise ratios (CNR) and threshold
contrast (TC) visibilities have to be calculated for all required thicknesses. To calculate the latter the mass
attenuation coefficient (MAC) of gold has to be known for all possible beam qualities in the tube voltage range
between 26 and 32 kV.
In this paper we first determined the threshold contrast visibility using the CDMAM phantom with the same
beam quality at different current-time products (mAs). We can derive from Rose theory that CNR • CT • α =
const, where α is the diameter of the gold cylinder. From this the corresponding attenuation coefficients can be
calculated. This procedure was repeated for four different beam qualities (Mo/Mo 27kV, Rh/Rh 29kV, Rh/Rh
31 kV, and W/Rh 29 kV)).
Next, we measured the aluminium half value layer (HVL) of all x-ray spectra relevant for mammography.
Using a first order Taylor expansion of MAC as a function of HVL, all other desired MAC can be calculated.
The MAC as a function of the HVL was derived to MAChvl = -286.97 * hvl+186.03 with R2 = 0.997, where
MAChvl indicates the MAC for all specific x-ray spectrum defined by its aluminium half value layer. Based on
this function all necessary MACs needed for quality assurance (QA) were calculated. The results were in good
agreement with the data found in the protocol.
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