Audit of data from examination image headers collected for quality assurance in the ECOG-ACRIN EA1151 tomosynthesis mammographic imaging screening trial (TMIST).

PURPOSE: A comprehensive, centrally-monitored physics quality control (QC) program was developed for the Tomosynthesis Imaging Screening Trial (TMIST), a randomized controlled trial of digital breast tomosynthesis (TM) versus digital mammography (DM) for cancer screening. As part of the program, in addition to a set of phantom-based tests, de-identified data on image acquisition and processing parameters were captured from the DICOM headers of all individual patient images in the trial. These data were analyzed to assess the potential usefulness of header data from digital mammograms and tomosynthesis images of patients for quality assurance in breast imaging. METHODS: Data were automatically extracted from the headers of all de-identified patient mammograms and tomosynthesis images in the TMIST study. Image acquisition parameters and estimated radiation doses were tracked for individual sites, systems and across system types. These parameters included (among others) kV, target/filter use, number of acquired views per examination, AEC mode, compression thickness and force and detector temperature. Consistency of manually entered study data parameters (subject ID, screening time-point) from TMIST was evaluated. Preliminary observations from the program are presented. RESULTS: We report on data from 812 651 images from 135 525 examinations acquired between October, 2017 and December, 2022. Data came from 6 system models from 3 manufacturers. There was greater variability both in the number of views used and in the estimated (proxy) doses received in DM exams compared to TM. Mean proxy doses per examination varied among manufacturers from 2.76-4.54 mGy for DM and 3-4.84 mGy for the tomosynthesis component in the TM arm with maximum examination proxy doses of 20 and 26 mGy for DM and TM respectively. Mean proxy doses per examination for the combination examination in TM (tomosynthesis plus digital mammography) varied from 6.6 to 7.6 mGy among manufacturers with a maximum of 44.5 mGy. CONCLUSIONS: Overall, modern digital mammography and tomosynthesis systems used in TMIST have operated very reliably. Doses vary considerably due to variation in the number of views per examination, thickness and fibro-glandularity of the breast, and choices in the use of synthesized versus actual 2D mammography in the TM examination. These data may also be useful in predicting equipment problems. Header information is valuable not only for automated QC, but also for cross-checking accuracy and consistency of data in a clinical study.

Quality control for digital tomosynthesis in the ECOG-ACRIN EA1151 TMIST trial.

BACKGROUND: The Tomosynthesis Mammography Imaging Screening Trial (TMIST), EA1151 conducted by the Eastern Cooperative Oncology Group (ECOG)/American College of Radiology Imaging Network (ACRIN) is a randomized clinical trial designed to assess the effectiveness for breast cancer screening of digital breast tomosynthesis (TM) compared to digital mammography (DM). Equipment from multiple vendors is being used in the study. PURPOSE: For the findings of the study to be valid and capture the true capacities of the two technology types, it is important that all equipment is operated within appropriate parameters with regard to image quality and dose. A harmonized QC program was established by a core physics team. Since there are over 120 trial sites, a centralized, automated QC program was chosen as the most practical design. This report presents results of the weekly QC testing program. A companion paper will review quality monitoring based on data from the headers of the patient images. METHODS: Study images are collected centrally after de-identification using the "TRIAD" application developed by ACR. The core physics team devised and implemented a minimal set of quality control (QC) tests to evaluate the tomosynthesis and 2D mammography systems. Weekly, monthly and annual testing is performed by the site mammography technologists with images submitted directly to the physics core. The weekly physics QC tests are described: SDNR of a low-contrast mass object, artifact spread, spatial resolution, tracking of technical factors, and in-slice noise power spectra. RESULTS: As of December 31, 2022 (5 years), 145 sites with 411 machines had submitted QC data. A total of 136 742 TMIST participant screening imaging studies had been performed. The 5th and 95th percentile mean glandular doses for a single tomosynthesis exposure to a 4.0 cm thick PMMA phantom ("standard breast phantom") were 1.24 and 1.68 mGy respectively. The largest sources of QC non-conformance were: operator error, not following the QC protocol exactly, unreported software updates and preventive maintenance activities that affected QC setpoints. Noise power spectra were measured, however, standardization of performance targets across machine types and software revisions was difficult. Nevertheless, for each machine type, test measurement results were very consistent when the protocol was followed. Deviations in test results were mostly related to software and hardware changes. CONCLUSION: Most systems performed very consistently. Although this is a harmonized program using identical phantoms and testing protocols, it is not appropriate to apply universal threshold or target metrics across the machine types because the systems have different non-linear reconstruction algorithms and image display filters. It was found to be more useful to assess pass/fail criteria in terms of relative deviations from baseline values established when a system is first characterized and after equipment is changed. Generally, systems which needed repair failed suddenly, but in retrospect, for a few cases, drops in SDNR and increases in mAs were observed prior to tube failure. TMIST is registered as NCT03233191 by Clinicaltrials.gov.

Technical Note: Volumetric coverage in breast tomosynthesis images - Phantom QC results from the TMIST study.

PURPOSE: In the reconstruction of volume breast images from x-ray projections in breast tomosynthesis, some tomographic systems truncate the image data presented to the radiologist such that a non-negligible amount of tissue may be missing from the breast image. QC tests were conducted to determine if this problem existed in imaging in the TMIST study. METHODS: Test tools developed for TMIST containing small objects at known heights were used in routine weekly and annual QC testing of tomosynthesis units to assess the degree to which phantom material that was irradiated in imaging was excluded from the reconstructed image. Results from 318 tests on five system types from three manufacturers are reported. RESULTS: The presence and extent of this problem varied among system types. The cause was most frequently related to machine errors in the determination of breast thickness or to deflection of components during breast compression. In particular, the problem occurred when a compression paddle other than the one calibrated for tomosynthesis was used for the tests. This was also verified to have occurred in some clinical imaging. CONCLUSIONS: Missing volume can be avoided by intentionally reconstructing additional image slices above and below the presumed locations of the breast support and compression plate. A compression paddle which has been calibrated for tomosynthesis should be used both for clinical imaging and testing. The prevalence of this phenomenon suggests that more frequent testing for volume coverage may be advisable.

Reliability of automated breast density measurements.

PURPOSE: To estimate the reliability of a reference standard two-dimensional area-based method and three automated volumetric breast density measurements by using repeated measures. MATERIALS AND METHODS: Thirty women undergoing screening mammography consented to undergo a repeated left craniocaudal examination performed by a second technologist in this prospective institutional review board-approved HIPAA-compliant study. Breast density was measured by using an area-based method (Cumulus ABD) and three automated volumetric methods (CumulusV [University of Toronto], Volpara [version 1.4.5; Volpara Solutions, Wellington, New Zealand), and Quantra [version 2.0; Hologic, Danbury, Conn]). Discrepancy between the first and second breast density measurements (Δ1-2) was obtained for each algorithm by subtracting the second measurement from the first. The Δ1-2 values of each algorithm were then analyzed with a random-effects model to derive Bland-Altman-type limits of measurement agreement. RESULTS: Variability was higher for Cumulus ABD and CumulusV than for Volpara or Quantra. The within-breast density measurement standard deviations were 3.32% (95% confidence interval [CI]: 2.65, 4.44), 3.59% (95% CI: 2.86, 4.48), 0.99% (95% CI: 0.79, 1.33), and 1.64% (95% CI: 1.31, 1.39) for Cumulus ABD, CumulusV, Volpara, and Quantra, respectively. Although the mean discrepancy between repeat breast density measurements was not significantly different from zero for any of the algorithms, larger absolute breast density discrepancy (Δ1-2) values were associated with larger breast density values for Cumulus ABD and CumulusV but not for Volpara and Quantra. CONCLUSION: Variability in a repeated measurement of breast density is lowest for Volpara and Quantra; these algorithms may be more suited to incorporation into a risk model.

Method of measuring NEQ as a quality control metric for digital mammography.

PURPOSE: Current quality control protocols for digital mammography rely on subjective assessments of image quality or simple measures that are not comparable between vendor platforms. The noise-equivalent quanta (NEQ) can be expressed in units of image quanta (fluence) for the spatial frequency range of interest, enabling comparisons between systems and x-ray spectra. The purpose of this work is to explore use of a simple phantom to measure the components of the noise-equivalent quanta of digital mammography systems for use in routine quality control. METHODS: A simple phantom is imaged on six mammography systems from different vendors. The phantom contains uniform regions for measurement of noise power spectrum (NPS), slanted edges for measurement of modulation transfer function (MTF), and objects of various thicknesses for measurement of contrast. Images were acquired at a range of dose levels on each system to examine how measurements scale with dose, and multiple images were taken at a single dose point to examine measurement reproducibility. RESULTS: The phantom and measurement methods show good reproducibility, with average coefficient of variation values of less than or equal to 15% on all systems evaluated. Measured MTF and NPS values are comparable to other published results when the increase in scattered radiation generated by placing the phantom on the breast support is accounted for. CONCLUSIONS: Measurement of the parameters required to calculate NEQ from a single image of a simple phantom is practical, and shows promise as a method of evaluating image quality for routine quality control of digital mammography systems.

Segmenting pectoralis muscle on digital mammograms by a Markov random field-maximum a posteriori model.

Accurate and automatic segmentation of the pectoralis muscle is essential in many breast image processing procedures, for example, in the computation of volumetric breast density from digital mammograms. Its segmentation is a difficult task due to the heterogeneity of the region, neighborhood complexities, and shape variability. The segmentation is achieved by pixel classification through a Markov random field (MRF) image model. Using the image intensity feature as observable data and local spatial information as a priori, the posterior distribution is estimated in a stochastic process. With a variable potential component in the energy function, by the maximum a posteriori (MAP) estimate of the labeling image, given the image intensity feature which is assumed to follow a Gaussian distribution, we achieved convergence properties in an appropriate sense by Metropolis sampling the posterior distribution of the selected energy function. By proposing an adjustable spatial constraint, the MRF-MAP model is able to embody the shape requirement and provide the required flexibility for the model parameter fitting process. We demonstrate that accurate and robust segmentation can be achieved for the curving-triangle-shaped pectoralis muscle in the medio-lateral-oblique (MLO) view, and the semielliptic-shaped muscle in cranio-caudal (CC) view digital mammograms. The applicable mammograms can be either "For Processing" or "For Presentation" image formats. The algorithm was developed using 56 MLO-view and 79 CC-view FFDM "For Processing" images, and quantitatively evaluated against a random selection of 122 MLO-view and 173 CC-view FFDM images of both presentation intent types.

Comparative performance of modern digital mammography systems in a large breast screening program.

PURPOSE: To compare physical measures pertaining to image quality among digital mammography systems utilized in a large breast screening program. To examine qualitatively differences in these measures and differences in clinical cancer detection rates between CR and DR among sites within that program. METHODS: As part of the routine quality assurance program for screening, field measurements are made of several variables considered to correlate with the diagnostic quality of medical images including: modulation transfer function, noise equivalent quanta, d' (an index of lesion detectability) and air kerma to allow estimation of mean glandular dose. In addition, images of the mammography accreditation phantom are evaluated. RESULTS: It was found that overall there were marked differences between the performance measures of DR and CR mammography systems. In particular, the modulation transfer functions obtained with the DR systems were found to be higher, even for larger detector element sizes. Similarly, the noise equivalent quanta, d', and the phantom scores were higher, while the failure rates associated with low signal-to-noise ratio and high dose were lower with DR. These results were consistent with previous findings in the authors' program that the breast cancer detection rates at sites employing CR technology were, on average, 30.6% lower than those that used DR mammography. CONCLUSIONS: While the clinical study was not large enough to allow a statistically powered system-by-system assessment of cancer detection accuracy, the physical measures expressing spatial resolution, and signal-to-noise ratio are consistent with the published finding that sites employing CR systems had lower cancer detection rates than those using DR systems for screening mammography.

Measurement of compressed breast thickness by optical stereoscopic photogrammetry.

The determination of volumetric breast density (VBD) from mammograms requires accurate knowledge of the thickness of the compressed breast. In attempting to accurately determine VBD from images obtained on conventional mammography systems, the authors found that the thickness reported by a number of mammography systems in the field varied by as much as 15 mm when compressing the same breast or phantom. In order to evaluate the behavior of mammographic compression systems and to be able to predict the thickness at different locations in the breast on patients, they have developed a method for measuring the local thickness of the breast at all points of contact with the compression paddle using optical stereoscopic photogrammetry. On both flat (solid) and compressible phantoms, the measurements were accurate to better than 1 mm with a precision of 0.2 mm. In a pilot study, this method was used to measure thickness on 108 volunteers who were undergoing mammography examination. This measurement tool will allow us to characterize paddle surface deformations, deflections and calibration offsets for mammographic units.

Accurate estimation of compressed breast thickness in mammography.

The determination of volumetric breast density (VBD) from mammograms requires an accurate knowledge of the thickness of the compressed breast. Previously, the authors described a technique for measuring local thicknesses using optical stereoscopic photogrammetry [A. H. Tyson, G. E. Mawdsley, and M. J. Yaffe, "Measurement of compressed breast thickness by optical stereoscopic photogrammetry," Med. Phys. 36(2), 569-576 (2009)]. Here, the authors describe the use of this tool to guide the development of a simpler, more practical field technique for the estimation of breast thickness and test its accuracy. Phantoms were constructed having similar shapes and compression characteristics to breasts of different sizes. These phantoms were compressed at different forces on several types of mammography units and their thickness under compression was measured using optical stereoscopic photogrammetry at many points of contact with the compression plate. A prediction equation was developed that uses the readout of compressed thickness and compression force provided by the mammography system to estimate local breast thickness. Using this approach, systems can be calibrated to an accuracy of better than 5 mm in thickness using a simple test object compared to an error of up to 15 mm associated with using only the thickness readout of the mammography machine. On the systems tested, the estimated value of VBD obtained using this method is significantly reduced from that determined using the constant thickness reported by the mammography machine.

Optimization of exposure parameters in full field digital mammography.

Optimization of exposure parameters (target, filter, and kVp) in digital mammography necessitates maximization of the image signal-to-noise ratio (SNR), while simultaneously minimizing patient dose. The goal of this study is to compare, for each of the major commercially available full field digital mammography (FFDM) systems, the impact of the selection of technique factors on image SNR and radiation dose for a range of breast thickness and tissue types. This phantom study is an update of a previous investigation and includes measurements on recent versions of two of the FFDM systems discussed in that article, as well as on three FFDM systems not available at that time. The five commercial FFDM systems tested, the Senographe 2000D from GE Healthcare, the Mammomat Novation DR from Siemens, the Selenia from Hologic, the Fischer Senoscan, and Fuji's 5000MA used with a Lorad M-IV mammography unit, are located at five different university test sites. Performance was assessed using all available x-ray target and filter combinations and nine different phantom types (three compressed thicknesses and three tissue composition types). Each phantom type was also imaged using the automatic exposure control (AEC) of each system to identify the exposure parameters used under automated image acquisition. The figure of merit (FOM) used to compare technique factors is the ratio of the square of the image SNR to the mean glandular dose. The results show that, for a given target/filter combination, in general FOM is a slowly changing function of kVp, with stronger dependence on the choice of target/filter combination. In all cases the FOM was a decreasing function of kVp at the top of the available range of kVp settings, indicating that higher tube voltages would produce no further performance improvement. For a given phantom type, the exposure parameter set resulting in the highest FOM value was system specific, depending on both the set of available target/filter combinations, and on the receptor type. In most cases, the AECs of the FFDM systems successfully identified exposure parameters resulting in FOM values near the maximum ones, however, there were several examples where AEC performance could be improved.

Accuracy of soft-copy digital mammography versus that of screen-film mammography according to digital manufacturer: ACRIN DMIST retrospective multireader study.

PURPOSE: To retrospectively compare the accuracy for cancer diagnosis of digital mammography with soft-copy interpretation with that of screen-film mammography for each digital equipment manufacturer, by using results of biopsy and follow-up as the reference standard. MATERIALS AND METHODS: The primary HIPAA-compliant Digital Mammographic Imaging Screening Trial (DMIST) was approved by the institutional review board of each study site, and informed consent was obtained. The approvals and consent included use of data for future HIPAA-compliant retrospective research. The American College of Radiology Imaging Network DMIST collected screening mammography studies performed by using both digital and screen-film mammography in 49 528 women (mean age, 54.6 years; range, 19-92 years). Digital mammography systems from four manufacturers (Fischer, Fuji, GE, and Hologic) were used. For each digital manufacturer, a cancer-enriched reader set of women screened with both digital and screen-film mammography in DMIST was constructed. Each reader set contained all cancer-containing studies known for each digital manufacturer at the time of reader set selection, together with a subset of negative and benign studies. For each reader set, six or 12 experienced radiologists attended two randomly ordered reading sessions 6 weeks apart. Each radiologist identified suspicious findings and rated suspicion of breast cancer in identified lesions by using a seven-point scale. Results were analyzed according to digital manufacturer by using areas under the receiver operating characteristic curve (AUCs), sensitivity, and specificity for soft-copy digital and screen-film mammography. Results for Hologic digital are not presented owing to the fact that few cancer cases were available. The implemented design provided 80% power to detect average AUC differences of 0.09, 0.08, and 0.06 for Fischer, Fuji, and GE, respectively. RESULTS: No significant difference in AUC, sensitivity, or specificity was found between Fischer, Fuji, and GE soft-copy digital and screen-film mammography. Large reader variations occurred with each modality. CONCLUSION: No statistically significant differences were found between soft-copy digital and screen-film mammography for Fischer, Fuji, and GE digital mammography equipment.

Design and characterization of a digital image acquisition system for whole-specimen breast histopathology.

We have developed a digital histopathology imaging system capable of producing a three-dimensional (3D) representation of histopathology from an entire lumpectomy specimen. The system has the potential to improve the accuracy of surgical margin assessment in the treatment of breast cancer by providing finer sampling and 3D visualization. A scanning light microscope was modified to allow digital photomicrography of a stack of large (up to 120x170 mm2) histology slides cut serially through the entire specimen. The images are registered and displayed in 2D and 3D. The design of the system, which reduces or eliminates the appearance of 'tiling' and 'seam' artefacts inherent in the scanning method, is described and its resolution, contrast/noise and coverage properties are characterized through measurements of the modulation transfer function (MTF), depth of field (DOF) and signal difference to noise ratio (SDNR). The imaging task requires a lateral resolution of 5 microm, an SDNR of 5 between relevant features, 'tiling artefact' at a level below the detectability threshold of the eye, and 'seam artefact' of less than 5-10 microm. The tests demonstrate that the system is largely adequate for the imaging task, although further optimizations are required to reduce the degradation of coverage incurred by seam artefact.

Lag and ghosting in a clinical flat-panel selenium digital mammography system.

We present measurements of lag and ghosting in a FDA-approved digital mammography system that uses a dielectric/selenium based detector structure. Lag is the carryover of signal from a previous image, whereas ghosting is the reduction of sensitivity caused by previous exposure history of the detector. Data from six selenium units were acquired. For the type of selenium detector tested, and under typical clinical usage conditions, the lag was as high as 0.15% of source signal and the ghosting could be as high as 15%. The amount of lag and ghosting varied from unit to unit. Results were compared with data acquired on a phosphor-based full-field digital mammography system. Modifications in the technology of the selenium detectors appear to have resulted in a marked decrease in both lag and ghosting effects in more recent systems.

Quality control for digital mammography in the ACRIN DMIST trial: part I.

The Digital Mammography Imaging Screening Trial, conducted by the American College of Radiology Imaging Network, is a clinical trial designed to compare the accuracy of full-field digital mammography (FFDM) versus screen-film mammography in a screening population. Five FFDM systems from four manufacturers (Fischer, Fuji, General Electric, and Lorad) were employed in the study at 35 clinical sites. A core physics team devised and implemented tests to evaluate these systems. A detailed description of physics and quality control tests is presented, including estimates of: mean glandular dose, modulation transfer function (MTF), 2D noise power spectra, and signal-to-noise ratio (SNR). The mean glandular doses for the standard breast ranged from 0.79 to 2.98 mGy, with 1.62 mGy being the average across all units and machine types. For the five systems evaluated, the MTF dropped to 50% at markedly different percentages (22% to 87%) of the Nyquist limit, indicating that factors other than detector element (del) size have an important effect on spatial resolution. Noise power spectra and SNR were measured; however, we found that it was difficult to standardize and compare these between units. For each machine type, the performance as measured by the tests was very consistent, and no predictive benefit was seen for many of the tests during the 2-year period of the trial. It was found that, after verification of proper operation during acceptance testing, if systems failed they generally did so suddenly rather than through gradual deterioration of performance. Because of the relatively short duration of this study further, investigation of the long-term failure characteristics of these systems is advisable.

Quality control for digital mammography: part II. Recommendations from the ACRIN DMIST trial.

The Digital Mammography Imaging Screening Trial (DMIST), conducted under the auspices of the American College of Radiology Imaging Network (ACRIN), is a clinical trial designed to compare the accuracy of digital versus screen-film mammography in a screening population [E. Pisano et al., ACRIN 6652-Digital vs. Screen-Film Mammography, ACRIN (2001)]. Part I of this work described the Quality Control program developed to ensure consistency and optimal operation of the digital equipment. For many of the tests, there were no failures during the 24 months imaging was performed in DMIST. When systems failed, they generally did so suddenly rather than through gradual deterioration of performance. In this part, the utility and effectiveness of those tests are considered. This suggests that after verification of proper operation, routine extensive testing would be of minimal value. A recommended set of tests is presented including additional and improved tests, which we believe meet the intent and spirit of the Mammography Quality Standards Act regulations to ensure that full-field digital mammography systems are functioning correctly, and consistently producing mammograms of excellent image quality.

A volumetric method for estimation of breast density on digitized screen-film mammograms.

A method is described for the quantitative volumetric analysis of the mammographic density (VBD) from digitized screen-film mammograms. The method is based on initial calibration of the imaging system with a tissue-equivalent plastic device and the subsequent correction for variations in exposure factors and film processing characteristics through images of an aluminum step wedge placed adjacent to the breast during imaging. From information about the compressed breast thickness and technique factors used for taking the mammogram as well as the information from the calibration device, VBD is calculated. First, optical sensitometry is used to convert images to Log relative exposure. Second, the images are corrected for x-ray field inhomogeneity using a spherical section PMMA phantom image. The effectiveness of using the aluminum step wedge in tracking down the variations in exposure factors and film processing was tested by taking test images of the calibration device, aluminum step wedge and known density phantoms at various exposure conditions and also at different times over one year. Results obtained on known density phantoms show that VBD can be estimated to within 5% accuracy from the actual value. A first order thickness correction is employed to correct for inaccuracy in the compression thickness indicator of the mammography units. Clinical studies are ongoing to evaluate whether VBD can be a better indicator for breast cancer risk.