William R. Geiser

Radiation dosimetry in digital breast tomosynthesis: Report of AAPM Tomosynthesis Subcommittee Task Group 223

The radiation dose involved in any medical imaging modality that uses ionizing radiation needs to be well understood by the medical physics and clinical community. This is especially true of screening modalities. Digital breast tomosynthesis (DBT) has recently been introduced into the clinic and is being used for screening for breast cancer in the general population. Therefore, it is important that the medical physics community have the required information to be able to understand, estimate, and communicate the radiation dose levels involved in breast tomosynthesis imaging. For this purpose, the American Association of Physicists in Medicine Task Group 223 on Dosimetry in Tomosynthesis Imaging has prepared this report that discusses dosimetry in breast imaging in general, and describes a methodology and provides the data necessary to estimate mean breast glandular dose from a tomosynthesis acquisition. In an effort to maximize familiarity with the procedures and data provided in this Report, the methodology to perform the dose estimation in DBT is based as much as possible on that used in mammography dose estimation.

ACR–AAPM–SIIM Practice Guideline for Determinants of Image Quality in Digital Mammography

This guideline was developed collaboratively by individuals with recognized expertise in breast imaging, medical physics, and imaging informatics, representing the American College of Radiology (ACR), the American Association of Physicists in Medicine (AAPM), and the Society for Imaging Informatics in Medicine (SIIM), primarily for technical guidance. It is based on a review of the clinical and physics literature on digital mammography and the experience of experts and publications from the Image Quality Collaborative Workgroup [1–3]. For purposes of this guideline, digital mammography is defined as the radiographic examination of the breast utilizing dedicated electronic detectors to record the image (rather than screen film) and having the capability for image display on computer monitors. This guideline is specific to two-dimensional (2D) digital mammography since the vast majority of digital mammography performed in the USA is 2D. Although some three-dimensional technologies are in use, they are not addressed in this guideline since they continue to evolve and are not yet in widespread clinical use. In many parts of this guideline, the level of technical detail regarding the determinants of image quality for digital mammography is advanced, and is intended to provide radiologists, qualified medical physicists, regulators, and other support personnel directly involved in clinical implementation and oversight an expanded knowledge of the issues pertinent to assessing and maintaining digital mammography image quality from the acquisition, display, and data storage aspects of the process. Where basic technical requirements for digital mammography overlap with those for digital radiography in general, users are directed to consult the referenced ACR practice guidelines [4, 5]. All interested individuals are encouraged to review the ACR digital radiography guidelines. Additionally, this guideline includes input from industry, radiologists, and other interested parties in an attempt to represent the consensus of the broader community. It was further informed by input from another working group of the Integrating the Healthcare Enterprise (IHE) Initiative [6]. Furthermore, the ACR Subcommittee on Digital Mammography is developing a quality control (QC) manual for digital mammography. Analysis of image quality has meaning primarily in the context of a particular imaging task [7]. This guideline has been developed with reference to specific imaging tasks required by mammography, using the information available in the peer-reviewed medical literature regarding digital mammography acquisition, image processing and display, storage, transmission, and retrieval. Specifically, the imaging tasks unique to mammography that determine the essential characteristics of a high-quality mammogram are its ability to visualize the following features of breast cancer: The characteristic morphology of a mass. The shape and spatial configuration of calcifications. Distortion of the normal architecture of the breast tissue. Asymmetry between images of the left and right breast. The development of anatomically definable changes when compared with prior studies. The primary goal of mammography is to detect breast cancer, if it exists, by accurately visualizing these features. At the same time, it is important that these signs of breast cancer not be falsely identified if breast cancer is not present. Two aspects of digital image quality can be distinguished: technical and clinical. It is possible to make technical measurements describing the above attributes, and it may be possible to infer a connection between these technical measures and clinical image quality. The extent to which these features are rendered optimally with a digital mammography system using current technology depends on several factors and is the major focus of this guideline.

Measurement of focal spot size with slit camera using computed radiography and flat-panel based digital detectors

The purpose of this study was to evaluate the use of digital x-ray imaging detectors for the measurement of diagnostic x-ray tube focal spot size using a slit camera. Slit camera images of two focal spots for a radiographic x-ray tube were acquired with direct-exposure film (DF) (as specified by the National Electrical Manufacturers Association [NEMA] Standards Publication No. XR 5, 1992), computed radiography (CR) imaging plates, and an a-Si:H/CsI:Tl-based flat-panel (FP) detector. Images obtained with the CR and the FP were acquired over a broad range of detector entrance exposure levels. The DF slit images were evaluated according to NEMA specifications (visually, using a 7x magnifying glass with reticule) by six medical physicists. Additionally, the DF images were digitized and the focal spot sizes obtained from the digital profiles of the slit. The CR and the FP images were analyzed in a manner similar to the digitized DF images. It took less than 20 minutes for a complete CR or FP measurement of focal spot size in two dimensions. In comparison, a typical DF measurement with visual evaluation takes at least 60 minutes, in our experience. In addition to a great reduction in measurement time achieved by using digital detectors, the tube loading requirements were reduced to approximately 20 mAs compared with approximately 1000 mAs when using the DF technique. The calculated focal spot sizes for CR and FP differed from those of digitized DF by -2.4% to +4.8% (sigma=2.5%), far less than the -16.6% to +9.3% (sigma=8.1%) variability introduced by the visual evaluation of the slit image. In addition, the calculated focal spot sizes for the CR and the FP images maintained a coefficient of variation <1.0% over the broad range of exposure levels. Based upon these results, we conclude that (1) FP and CR detectors yield consistent results in measurements of x-ray tube focal spot sizes, (2) compared to DF, CR and FP significantly reduce measurement time and tube loading requirements, (3) CR and FP readily permit digital profile analysis, thereby eliminating observer error, and (4) unlike DF, CR and FP are independent of exposure level.

Ongoing quality control in digital radiography: Report of AAPM Imaging Physics Committee Task Group 151.

Quality control (QC) in medical imaging is an ongoing process and not just a series of infrequent evaluations of medical imaging equipment. The QC process involves designing and implementing a QC program, collecting and analyzing data, investigating results that are outside the acceptance levels for the QC program, and taking corrective action to bring these results back to an acceptable level. The QC process involves key personnel in the imaging department, including the radiologist, radiologic technologist, and the qualified medical physicist (QMP). The QMP performs detailed equipment evaluations and helps with oversight of the QC program, the radiologic technologist is responsible for the day-to-day operation of the QC program. The continued need for ongoing QC in digital radiography has been highlighted in the scientific literature. The charge of this task group was to recommend consistency tests designed to be performed by a medical physicist or a radiologic technologist under the direction of a medical physicist to identify problems with an imaging system that need further evaluation by a medical physicist, including a fault tree to define actions that need to be taken when certain fault conditions are identified. The focus of this final report is the ongoing QC process, including rejected image analysis, exposure analysis, and artifact identification. These QC tasks are vital for the optimal operation of a department performing digital radiography.

Challenges in Mammography: Part 1, Artifacts in Digital Mammography

OBJECTIVE Early detection of breast cancer is directly related to the radiologists ability to detect abnormalities visible only on mammograms. Artifacts on mammograms reduce image quality and may present clinical and technical difficulties for the radiologist, mammography technologist, medical physicist, and equipment service personnel. CONCLUSION In this article, we will illustrate the appearance of artifacts in full field digital mammography, review the causes of these artifacts, and discuss methods to eliminate artifacts in digital mammography.

How to Establish a Cost-Effective Mobile Mammography Program

OBJECTIVE The purpose of this article is to describe how to establish a cost-effective mobile mammography program on the basis of examples from a 20-year experience with film-screen and digital mammography units. CONCLUSION Mobile mammography programs can reduce many barriers to breast cancer screening faced by medically underserved women. Finding and maintaining resources, having appropriate equipment and infrastructure, and having a dedicated team with an efficient workflow are the key elements of establishing a cost-effective mobile mammography program.

Stereoscopic interpretation of low-dose breast tomosynthesis projection images

The purpose of this study was to evaluate stereoscopic perception of low-dose breast tomosynthesis projection images. In this Institutional Review Board exempt study, craniocaudal breast tomosynthesis cases (N = 47), consisting of 23 biopsy-proven malignant mass cases and 24 normal cases, were retrospectively reviewed. A stereoscopic pair comprised of two projection images that were ±4° apart from the zero angle projection was displayed on a Planar PL2010M stereoscopic display (Planar Systems, Inc., Beaverton, OR, USA). An experienced breast imager verified the truth for each case stereoscopically. A two-phase blinded observer study was conducted. In the first phase, two experienced breast imagers rated their ability to perceive 3D information using a scale of 1–3 and described the most suspicious lesion using the BI-RADS® descriptors. In the second phase, four experienced breast imagers were asked to make a binary decision on whether they saw a mass for which they would initiate a diagnostic workup or not and also report the location of the mass and provide a confidence score in the range of 0–100. The sensitivity and the specificity of the lesion detection task were evaluated. The results from our study suggest that radiologists who can perceive stereo can reliably interpret breast tomosynthesis projection images using stereoscopic viewing.

Conspicuity of Microcalcifications on Digital Screening Mammograms Using Varying Degrees of Monitor Zooming

RATIONALE AND OBJECTIVES American College of Radiology guidelines suggest that digital screening mammographic images should be viewed at the full resolution at which they were acquired. This slows interpretation speed. The aim of this study was to examine the effect of various levels of zooming on the detection and conspicuity of microcalcifications. MATERIALS AND METHODS Six radiologists viewed 40 mammographic images five times in different random orders using five different levels of zooming: full resolution (100%) and 30%, 61%, 88%, and 126% of that size. Thirty-three images contained microcalcifications varying in subtlety, all associated with breast cancer. The clusters were circled. Seven images contained no malignant calcifications but also had randomly placed circles. The radiologists graded the presence or absence and visual conspicuity of any calcifications compared to calcifications in a reference image. They also counted the microcalcifications. RESULTS The radiologists saw the microcalcifications in 94% of the images at 30% size and in either 99% or 100% of the other tested levels of zooming. Conspicuity ratings were worst for the 30% size and fairly similar for the others. Using the 30% size, two radiologists failed to see the microcalcifications on either the craniocaudal or mediolateral oblique view taken from one patient. Interobserver agreement regarding the number of calcifications was lowest for the 30% images and second lowest for the 100% images. CONCLUSIONS Images at 30% size should not be relied on alone for systematic scanning for microcalcifications. The other four levels of magnification all performed well enough to warrant further testing.

Comparison of slot scanning digital mammography system with full-field digital mammography system

The purpose of this study was to evaluate and compare microcalcification detectability of two commercial full-field digital mammography (DM) systems. The first unit was a flat panel based DM system (FFDM) which employed an anti-scatter grid method to reject scatter, and the second unit was a charge-coupled device-based DM system (SSDM) which used scanning slot imaging geometry to reduce scatter radiation. Both systems have comparable scatter-to-primary ratios. In this study, 125-160 and 200-250 microm calcium carbonate grains were used to simulate microcalcifications and imaged by both DM systems. The calcium carbonate grains were overlapped with a 5-cm-thick 50% adipose/50% glandular simulated breast tissue slab and an anthropomorphic breast phantom (RMI 165, Gammex) for imaging at two different mean glandular dose levels: 0.87 and 1.74 mGy. A reading study was conducted with seven board certified mammographers with images displayed on review workstations. A five-point confidence level rating was used to score each detection task. Receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (A(z)) was used to quantify and compare the performances of these two systems. The results showed that with the simulated breast tissue slab (uniform background), the SSDM system resulted in higher A(z)s than the FFDM system at both MGD levels with the difference statistically significant at 0.87 mGy only. With the anthropomorphic breast phantom (tissue structure background), the SSDM system performed better than the FFDM system at 0.87 mGy but worse at 1.74 mGy. However, the differences were not found to be statistically significant.

Trend of Contrast Detection Threshold with and without Localization

Published information on contrast detection threshold is based primarily on research using a location-known methodology. In previous work on testing the Digital Imaging and Communications in Medicine (DICOM) Grayscale Standard Display Function (GSDF) for perceptual linearity, this research group used a location-unknown methodology to more closely reflect clinical practice. A high false-positive rate resulted in a high variance leading to the conclusion that the impact on results of employing a location-known methodology needed to be explored. Fourteen readers reviewed two sets of simulated mammographic background images, one with the location-unknown and one with the location-known methodology. The results of the reader study were analyzed using Reader Operating Characteristic (ROC) methodology and a paired t test. Contrast detection threshold was analyzed using contingency tables. No statistically significant difference was found in GSDF testing, but a highly statistical significant difference (p value <0.0001) was seen in the ROC (AUC) curve between the location-unknown and the location-known methodologies. Location-known methodology not only improved the power of the GSDF test but also affected the contrast detection threshold which changed from +3 when the location was unknown to +2 gray levels for the location-known images. The selection of location known versus unknown in experimental design must be carefully considered to ensure that the conclusions of the experiment reflect the study’s objectives.