Mammographic Phantom Research Articles

Automated quality control analysis for American College of Radiology (ACR) digital mammography (DM) phantom images.

To develop and validate an automated software analysis method for mammography image quality assessment of the American College of Radiology (ACR) digital mammography (DM) phantom images. Twenty-seven DICOM images were acquired using Fuji mammography systems. All images were evaluated by three expert medical physicists using the Royal Australian and New Zealand College of Radiologists (RANZCR) mammography quality control guideline. To enhance the robustness and sensitivity assessment of our algorithm, an additional set of 12 images from a Hologic mammography system was included to test various phantom positional adjustments. The software automatically chose multiple regions of interest (ROIs) for analysis. A template matching method was primarily used for image analysis, followed by an additional method that locates and scores each target object (speck groups, fibers, and masses). The software performance shows a good to excellent agreement with the average scoring of observers (intraclass correlation coefficient [ICC] of 0.75, 0.79, 0.82 for speck groups, fibers, and masses, respectively). No significant differences were found in the scoring of target objects between human observers and the software. Both methods achieved scores meeting the pass criteria for speck groups and masses. Expert observers allocated lower scores to fiber objects, with diameters less than 0.61mm, when compared to the software. The software was able to accurately score objects when the phantom position changed by up to 25mm laterally, up to 5 degrees rotation, and overhanging the chest wall edge by up to 15mm. Automated software analysis is a feasible method that may help improve the consistency and reproducibility of mammography image quality assessment with reduced reliance on human interaction and processing time.

239 - Improving Radiography Students' Comprehension of Mammographic Positioning with an In-House Developed Mammography Phantom

239 - Improving Radiography Students' Comprehension of Mammographic Positioning with an In-House Developed Mammography Phantom

CNR performance of semiconductor materials for X-ray imaging of breast calcifications

We present the results of a GAMOS/GEANT4 computer simulation of a standard X-ray mammography system, which consists of a Tungsten 28 kVp polychromatic X-ray source with a 50 μm Rh filter, a mammography phantom with Al2O3 spherical specks of different diameters, and a generic pixel detector (55 μm × 55 μm pixel size) with different types of semiconductor sensors. The number of photons simulated is calibrated to produce similar entrance surface dose (ESD) as the one used by a standard clinical mammography screening. Estimates of Contrast to Noise Ratio (CNR) as a function of ESD, sensor thickness and microcalcification diameter are presented for four different sensor materials: Silicon (Si), Cadmium Telluride (CdTe), Gallium Arsenide (GaAs) and Perovskite (MAPbI3). For the X-ray energy spectrum and pixel size considered, and an ESD dose of 4 mGy, our study shows that, with the exception of Si, these sensors, as thin as 200 μm, are able to resolve (with at least 3 standard deviations above background) Al2O3 spherical specks up to a minimum diameter of 180 μm, having statistically compatible CNR performance. The increase in substrate thickness has a substantial improvement in the CNR values provided by the Si sensor, while for the other cases the enhancement of CNR is marginal and consistent with statistical uncertainties with the thinnest case considered.

3D phantom for image quality assessment of mammography systems

Objective. To present an innovative approach for the design of a 3D mammographic phantom for medical equipment quality assessment, estimation of the glandular tissue percentage in the patient’s breast, and emulation of microcalcification (μC) breast lesions. Approach. Contrast-to noise ratio (CNR) measurements, as well as spatial resolution and intensity-to-glandularity calibrations under mammography conditions were performed to assess the effectiveness of the phantom. CNR measurements were applied to different groups of calcium hydroxyapatite (HA) and aluminum oxide (AO) μCs ranging from 200 to 600 μm. Spatial resolution was characterized using an aluminum plate contained in the phantom and standard linear figures of merit, such as the line spread function and modulation transfer function (MTF). The intensity-to-glandularity calibration was developed using an x-ray attenuation matrix within the phantom to estimate the glandular tissue percentage in a breast with a compressed thickness of 4 cm. Main results. For the prototype studied, the minimum confidence level for detecting HA μCs is 95.4%, while for AO μCs is above 68.3%. It was also possible to determine that the MTF of the commercial mammography machine used for this study at the Nyquist frequency is 41%. Additionally, a one-to-one intensity-to-glandularity calibration was obtained and verified with Monte-Carlo simulation results. Significance. The phantom provides traditional arrangements presented in accreditation phantoms, which makes it competitive with available devices, but excelling in regarding affordability, modularity, and inlays distribution. Moreover, its design allows to be positioned in close proximity to the patient's breast during a medical screening for a simultaneous x-ray imaging, such that the features of the phantom can be used as reference values to specify characteristics of the real breast tissue, such as proportion of glandular/adipose composition and/or μC type and size lesions.

Dosimetry using a radiochromic film and a mammography phantom.

Mammography is one of the most effective diagnostic methods for the early detection of breast cancer; however, it poses the risk of radiation exposure. To date, mammography dosimetry has been performed according to the mean glandular dose; however, the actual exposure in the breast has not been assessed. Here, we have measured dose distributions and depth doses using both radiochromic films and mammographic phantoms, and a three-dimensional intra-mammary dose assessment was conducted. The absorbed dose distribution at the surface was markedly higher on the chest wall side but lower on the nipple side. The absorbed doses in the depth direction exponentially decreased. The glandular tissue near the surface may be irradiated with an absorbed dose of 7.0mGy or higher. Since LD-V1 could be placed inside the phantom, the absorbed dose inside the breast could also be evaluated in three dimensions.

Utilization of three-layers heterogeneous mammographic phantom through MCNPX code for breast and chest radiation dose levels at different diagnostic X-ray energies: A Monte Carlo simulation study.

We report the breast and chest radiation dose assessment for mammographic examinations using a three-layer heterogeneous breast phantom through the MCNPX Monte Carlo code. A three-layer heterogeneous phantom along with compression plates and X-ray source are modeled. The validation of the simulation code is obtained using the data of AAPM TG-195 report. Deposited energy amount as a function of increasing source energy is calculated over a wide energy range. The behavioral changes in X-ray absorption as well as transmission are examined using the F6 Tally Mesh extension of MCNPX code. Moreover, deposited energy amount is calculated for modeled body phantom in the same energy range. The diverse distribution of glands has a significant impact on the quantity of energy received by the various breast layers. In layers with a low glandular ratio, low-energy primary X-ray penetrability is highest. In response to an increase in energy, the absorption in layers with a low glandular ratio decreased. This results in the X-rays releasing their energy in the bottom layers. Additionally, the increase in energy increases the quantity of energy absorbed by the tissues around the breast.

Devising a deep neural network based mammography phantom image filtering algorithm using images obtained under mAs and kVp control

We study whether deep neural network based algorithm can filter out mammography phantom images that will pass or fail. With 543 phantom images generated from a mammography unit, we created VGG16 based phantom shape scoring models (multi-and binary-class classifiers). Using these models we designed filtering algorithms that can filter failed or passed phantom images. 61 phantom images obtained from two different medical institutions were used for external validation. The performances of the scoring models show an F1-score of 0.69 (95% confidence interval (CI) 0.65, 0.72) for multi-class classifiers and an F1-score of 0.93 (95% CI 0.92, 0.95) and area under the receiver operating characteristic curve of 0.97 (95% CI 0.96, 0.98) for binary-class classifiers. A total of 42 of the 61 phantom images (69%) were filtered by the filtering algorithms without further need for assessment from a human observer. This study demonstrated the potential to reduce the human workload from mammographic phantom interpretation using the deep neural network based algorithm.

Experimental demonstration of ultrahigh sensitivity Talbot-Lau interferometer for low dose mammography

Objective. Even though the techniques used for breast cancer identification have advanced over the years, current mammography based on x-rays absorption, the ‘gold standard’ screening test at present, still has some shortcomings as concerns sensitivity and specificity to early-stage cancers, due to poor differentiation between tumor and normal tissues, especially in the case of the dense breasts. We investigate a possible additional technique for breast cancer detection with higher sensitivity and low dose, x-ray phase-contrast or refraction-based imaging with ultrahigh angular sensitivity grating interferometers, having several meters length. Approach. Towards this goal, we built and tested on a mammography phantom, a table-top laboratory setup based on a 5.7 m long Talbot-Lau interferometer with angular sensitivity better than 1 μrad. We used a high-power x-ray tungsten anode tube with a 400 μm focal spot, operated at 40 kVp and 15 mA with a 2 mm aluminum filter. Main results. The results reported in our paper confirm the ultrahigh sensitivity and dose economy possible with our setup. The visibility of objects simulating cancerous formations is strongly increased in the refraction images over the attenuation ones, even at a low dose of 0.32 mGy. Notably, the smallest fiber of 400 μm diameter and calcifications specs of 160 μm in diameter are detected, even though the spatial resolution at the object of our magnification M ∼ 2 setup with a 400 μm source spot is only ∼250 μm. Significance. Our experiments on a mammography phantom illustrate the capabilities of the proposed technique and can open the way toward low-dose interferometric mammography.

Detectability of category 3 or higher microcalcifications on digital mammograms: a comparative study between 5-MP color and monochrome liquid crystal display monitors.

This study explored the detectability of category 3 or higher microcalcifications using 5-MP color and monochrome monitors. Contrast detail mammography phantom with polymethyl methacrylate (PMMA) images were observed in color and monochrome by five radiographers, and the image quality figures (IQF) were calculated based on the gold disc locations identified. Five radiographers and two radiologists observed 200 mammograms from 100 patients (including 36 with microcalcifications) and rated the microcalcifications. The results were analyzed using area under the curve (AUC) and jackknife resampling. A paired t test was used for statistical analysis (p < 0.05). The mean IQF of color and monochrome monitors were 10.73 and 10.49 (30mm PMMA, p = 0.653) and 8.47 and 8.74 (50mm PMMA, p = 0.774), respectively. The mean AUC of color and monochrome monitors were 0.917 and 0.936 (p = 0.335), respectively, with windowing and magnification. The detectability of microcalcifications was not significantly different between the monitors.

Optimization of the exposure parameters in digital mammography for diverse glandularities using the contrast-detail metric

PurposeThis investigation aims to study the optimization in digital mammography, considering a diverse percentage of breast glandularity using the contrast-detail metric. MethodsThe Figure of Merit (FOM), defined as the ratio of the square of the Inverted Image Quality Figure (IQFINV) by the Mean Glandular Dose (MGD), was used. A Monte Carlo simulation study was carried out to calculate the Normalized Glandular Dose (DgN). A contrast detail analysis employing the test object Contrast-Detail Mammography Phantom (CDMAM, type 3.4) was performed in the Hologic digital mammography system-model Selenia located in the Research Center in Radiation Sciences and Technologies (CPqCTR) facilities (Brazil). It employed the CIRS phantom with 20 %, 30 %, 50 % of glandularity, and 6.0 cm in thickness. ResultsIt was obtained new acquisition parameters for all glandularities that achieved a decrease in the MGD up to ∼ 50 %, maintaining the same image quality. The study was validated using the CIRS, TORMAM, and ACR phantoms through the contrast-to-noise ratio (CNR), the signal-to-noise ratio (SNR), and the MGD values obtained with the optimized parameters and the four AEC modes, which are the optimization proposed by the manufacturer. ConclusionsIn this work, a new procedure was proposed that estimated the IQFINV value using the equivalence criterion between the CIRS phantom and the CDMAM test object with their respective PMMA plates. Based on the optimization carried out in this investigation, the AEC parameters, considering diverse glandularities, could be improved. This achievement permits the implementation of new protocols that optimize the ratio between the image's quality and the breast dose with 6.0 cm in thickness and 20 %, 30 %, and 50 % glandularity using contrast-detail metric.

Automated image quality assessment of mammography phantoms: a systematic review.

Computerized image analysis is a viable technique for evaluating image quality as a complement to human observers. To systematically review the image analysis software used in the assessment of 2D image quality using mammography phantoms. A systematic search of multiple databases was performed from inception to July 2020 for articles that incorporated computerized analysis of 2D images of physical mammography phantoms to determine image quality. A total of 26 studies were included, 12 were carried out using direct digital imaging and 14 using screen film mammography. The ACR phantom (model-156) was the most frequently evaluated phantom, possibly due to the lack of accepted standard software. In comparison to the inter-observer variations, the computerized image analysis was more consistent in scoring test objects. The template matching method was found to be one of the most reliable algorithms, especially for high-contrast test objects, while several algorithms found low-contrast test objects to be harder to distinguish due to the smaller contrast variations between test objects and their backgrounds. This was particularly true for small object sizes. Image analysis software was in agreement with human observers but demonstrated higher consistency and reproducibility of quality evaluation. Additionally, using computerized analysis, several quantitative metrics such as contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) could be used to complement the conventional scoring method. Implementing a computerized approach for monitoring image quality over time would be crucial to detect any deteriorating mammography system before clinical images are impacted.

Investigation of polyvinyl alcohol (PVAL) composite gels and the outcome of variation in breast phantom densities on image quality and dose in full-field digital mammography

This study evaluates the possibility of using a blend of polyvinyl alcohol (PVAL) and graphite powder as phantom materials to stimulate an extremely dense breast tissue for mammography based on the Breast Imaging-Reporting and Data System (BIRADS). The linear (μ) and mass attenuation coefficients (μ/ρ), computed tomography (CT) number, and physical and relative electron densities of the fabricated PVAL materials were determined. Mammography images of the fabricated PVAL materials and standard RMI 156 mammography phantoms were acquired using full-field digital mammography (FFDM) system at 28 kVp. The effect of breast density on contrast (Cn), contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and mean glandular dose (MGD) were evaluated. The fabricated phantoms made from PVAL + 4% graphite powder (G4) showed good resemblance to extremely dense breast tissues (BIRADS D). Higher Cn, CNR, and SNR values were achieved with lower density breast equivalent phantoms. Density correlated positively with mean glandular dose (MGD) and the values of the MGD for the different categories of phantoms were within the acceptable limit of 3.0 mGy consistent with the ACR protocol.

Utilization of an energy-resolving detection system for mammography applications: A preliminary study

Abstract Breast cancer remains one of the major causes of mortality among female cancer patients. This fact caused a spark in the medical field, which in turn helped to improve the diagnostic and treatment of breast cancer patients over the years making this field always active with new ideas and innovative methods. In our study, a new method was explored using an energy-resolving detection system made from a NaI (Tl) scintillation detector to detect the gamma photons from an Am-241 radiation source to try and construct an image by scanning the American College of Radiology (ACR) mammography phantom. In addition to the experimental work, a Geant4 Application for Tomographic Emission (GATE) toolkit was used to investigate more complex options to improve the image quality of mammographic systems, which is limited by the experimental setup. From the experimental setup, the researchers were able to construct an image using the 26.3 keV and the 59.5 keV energy photons, to show the largest size tumour (12 mm) in the ACR phantom. With an improved setup in the simulation environment, the majority of the ACR phantom tumours was visible using both energy windows from the 26.3 keV and the 59.5 keV, where the 26.3 keV yielded better quality images showing four tumours compared to three when using 59.5 keV. The simulation results were promising; however, several improvements need to be incorporated into the experimental work so that the system can generate high-resolution mammographic images similar to the ones obtained by the GATE simulation setup.

Reliable quality assurance of X-ray mammography scanner by evaluation the standard mammography phantom image using an interpretable deep learning model

ObjectiveMammography is the initial examination to detect breast cancer symptoms, and quality control of mammography devices is crucial to maintain accurate diagnosis and to safeguard against degradation of performance. The objective of this study was to assist radiologists in mammography phantom image evaluation by developing and validating an interpretable deep learning model capable of objectively evaluating the quality of standard phantom images for mammography. Materials and MethodsA total of 2,208 mammography phantom images were collected for periodic accreditation of the scanner from 1,755 institutions. The dataset was randomly split into training (1,808 images) and testing (400 images) datasets with subgroups (76 images) for the multi-reader study. To develop an interpretable model that contains two deep learning networks in series, five processing steps were performed: mammography phantom detection, phantom object detection, post-processing, score evaluation, and a report with a comment about ambiguous results. ResultsFor phantom detection, the accuracy and mean intersection over union (mIOU) were 1.00 and 0.938 in the test dataset, respectively. During phantom object detection, a total of 6,369 out of 6,400 objects were detected as the correct object class, and the accuracy and mIOU were 0.995 and 0.813, respectively. The predicted score for each object showed a consensus of 97.40% excluding ambiguous points and 59.10% for ambiguous points of the groups. ConclusionsThe interpretable deep learning model using large-scale data from multiple centers shows high performance and reasonable object scoring, successfully validating the reliability and feasibility of mammography phantom image quality management.

Evaluation and comparison of a CdTe based photon counting detector with an energy integrating detector for X-ray phase sensitive imaging of breast cancer.

To compare imaging performance of a cadmium telluride (CdTe) based photon counting detector (PCD) with a CMOS based energy integrating detector (EID) for potential phase sensitive imaging of breast cancer. A high energy inline phase sensitive imaging prototype consisting of a microfocus X-ray source with geometric magnification of 2 was employed. The pixel pitch of the PCD was 55μm, while 50μm for EID. The spatial resolution was quantitatively and qualitatively assessed through modulation transfer function (MTF) and bar pattern images. The edge enhancement visibility was assessed by measuring edge enhancement index (EEI) using the acrylic edge acquired images. A contrast detail (CD) phantom was utilized to compare detectability of simulated tumors, while an American College of Radiology (ACR) accredited phantom for mammography was used to compare detection of simulated calcification clusters. A custom-built phantom was employed to compare detection of fibrous structures. The PCD images were acquired at equal, and 30% less mean glandular dose (MGD) levels as of EID images. Observer studies along with contrast to noise ratio (CNR) and signal to noise ratio (SNR) analyses were performed for comparison of two detection systems. MTF curves and bar pattern images revealed an improvement of about 40% in the cutoff resolution with the PCD. The excellent spatial resolution offered by PCD system complemented superior detection of the diffraction fringes at boundaries of the acrylic edge and resulted in an EEI value of 3.64 as compared to 1.44 produced with EID image. At equal MGD levels (standard dose), observer studies along with CNR and SNR analyses revealed a substantial improvement of PCD acquired images in detection of simulated tumors, calcification clusters, and fibrous structures. At 30% less MGD, PCD images preserved image quality to yield equivalent (slightly better) detection as compared to the standard dose EID images. CdTe-based PCDs are technically feasible to image breast abnormalities (low/high contrast structures) at low radiation dose levels using the high energy inline phase sensitive imaging technique.

Attenuation properties of common 3D printed FFF plastics for mammographic applications

The aim of this study was to evaluate the feasibility of using acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) 3D printing filaments as materials for mammography phantom construction, comparing their attenuation properties at two different set-ups: at a Calibration Laboratory and directly to a mammography unit. The attenuation of 3D printed test phantoms of two types of common 3D printing Fused Filament Fabrication (FFF) filaments (ABS and PLA) were characterized in comparison with polymethylmethacrylate (PMMA). The measurements were carried out with standard IEC 61267 X-rays, using RQR 2-M and RQR 4-M beam qualities at the Instruments Calibration Laboratory, and then applied to a mammography unit, with measurements with 28 kVp and 35 kVp. Attenuation characteristics evaluated indicates the suitable equivalence of PLA to PMMA for 3D printing breast tissue equivalent complex phantoms. The plastic materials used in this study suggest that the FFF technique may be suitable for mammography phantom development.

GATE/GEANT4 simulation of radiation risk induced cancer from mammographic screening

The main objective of the paper is to estimate organ risk of radiation-induced cancer using Monte Carlo simulation Gate/Geant4 applying the Moroccan breast screening guidelines using digital mammography (DM) technique taken into consideration two views (cranio-caudal (CC) and medio-lateral oblique (MLO)), considering the age range of 45–60 years. We apply a new approach consisting of the use of a female voxel phantom EVA and FASH 3 computational phantoms merged with three-layer heterogeneous mammographic phantoms to estimate the incidence risks of cancer on a particular organ and the calculation of the total effective risk of radiation-induced cancer. The effective risk (ER) discrepancy between standing posture phantom FASH 3 and supine posture EVA phantom for organs were: 29.9% (breast examined), 54.83% (thyroid), and 10.97% (total effective risk). These results show a posture sensitivity in terms of organ dose calculation. To investigate the impact of glandular distribution on the ER, each layer of the breast was set to a glandular fraction of 25%, 50%, or 75% to simulate a glandular heterogeneous distribution of uniform, concentrated, superior, and inferior glandular distributions. The heterogeneous distribution shows lower values of the total effective risk of radiation-induced cancer of those of uniform one. This finding shows that the total effective risk for radiation-induced cancer using voxel phantom and heterogeneous breast distribution should be considered in clinical practice to provide DRL in conventional breast dosimetry.

Detectability of Fibrils by Dilation Technique in Digital Mammography

The detectability of fibrils in mammographic phantom images by morphological enhancement was analysed in the present study. Materials that mimic fibrils were imaged by a digital mammography machine at 28 and 29 kVP. The images were processed by a dilation technique to produce second set of images. Receiver operating characteristic analysis was performed to compare the detection performance from the two sets of images. As compared to original images, the 28 kVP’s fibrils images from dilation technique become more prominence to be detected by observers. While at 29 kVP only a few observers can found the fibrils images from dilation technique. This study suggests morphological enhancement of mammography image did not increase the detection of low frequency signals of the images.

Potential use of polyvinyl alcohol (PVAL) gel materials as mammography phantoms for the detection of calcifications

The study focused on the construction of phantoms made of the polyvinyl alcohol (PVAL) gel materials for mammography based on the dimensions of available RMI phantom for quality control in mammography. The PVAL gel phantoms were fabricated at 20% percentages of PVAL to water to provide target density of 1.0 g/cm3 and physical strength similar to that of human soft tissues. The calcifications were simulated by using calcium based powders at three different depths. Mammography images were obtained based on the automatic exposure control (AEC) at different compression forces. The results showed That all samples showed good visualisation of calcifications in the mammography images of all fabricated phantoms. The calcifications were well defined with no significant differences of the visualisation of calcifications in all mammography images of all fabricated PVAL gel phantoms. The results indicated the potential of PVAL gel materials to be developed and used as phantoms for the quality control works in mammography.

Innovative monochromatic x-ray source for high-quality and low-dose medical imaging.

An estimated 377 million diagnostic and interventional radiological exams are performed annually in the United States and approximately 4 to 5 billion globally. All use x-ray tubes that emit x-rays over a broad energy band, a technology that is more than a century old. Only a small fraction of the radiation is useful for imaging while the remaining fraction either increases the radiation dose received by the patient or degrades the image. Monochromatic x-rays can provide lower dose images in many of these radiological applications while maintaining or improving image quality. We report the development of the first monochromatic x-ray source suitable for low-dose, high-quality imaging in the clinic and demonstrate its first application and performance with mammography phantoms. X-ray fluorescence was used to generate monochromatic x-rays with selectable energies from 18 to 60keV. This patented technology was incorporated into a laboratory prototype of a monochromatic x-ray mammography system. Image quality was evaluated as a function of radiation dose in standard breast phantoms using the signal-to-noise ratio (SNR) measured for high and low contrast masses and microcalcifications. Spatial imaging properties were assessed from these images as well as from modulation transfer function (MTF) analysis. Measurements using an iodine contrast agent were also performed. The results were compared to those obtained using a commercially available, conventional x-ray mammography system. Our prototype system reduced radiation dose by factors of five to ten times for the same SNRs as obtained from the conventional system. This performance was demonstrated in phantoms simulating a wide range of lesion sizes and microcalcifications in a variety of breast thicknesses. The high SNRs for very thick breast phantoms provide evidence that screening with less breast compression is possible while maintaining image quality. Contrast-enhanced digital mammography (CEDM) with monochromatic x-rays was shown to provide a simpler and more effective technique at substantially lower radiation dose. The MTF value at 20% was 9lp/mm. The monochromatic x-ray system is more sensitive for imaging a wide range of breast sizes and compositions than conventional broadband mammography. High image quality and lower dose are its hallmarks. It also makes CEDM much more effective than current methods developed for use with conventional broadband mammography systems.