Rationale and Objectives: Breast density is a significant breast cancer risk factor that is measured from mammograms. However, uncertainty remains in both understanding its underlying physical properties as it relates to the breast and determining the optimal method for its measurement. A quantitative description of the information captured by the standard operator-assisted percentage of breast density (PD) measure was developed using full-field digital mammography (FFDM) images that were calibrated to adjust for interimage acquisition technique differences.Materials and Methods: The information captured by the standard PD measure was quantified by developing a similar measure of breast density (PDc) from calibrated mammograms automatically by applying a static threshold to each image. The specific threshold was estimated by first sampling the probability distributions for breast tissue in calibrated mammograms. A percent glandular (PG) measure of breast density was also derived from calibrated mammograms. The PD, PDc, and PG breast density measures were compared using both linear correlation (R) and quartile odds ratio measures derived from a matched case-control study.Results: The standard PD measure is an estimate of the number of pixel values above a fixed idealized x-ray attenuation fraction. There was significant correlation (P<.0001) between the PDc-PD (r = 0.78), PDc-PG (r = 0.87), and PD-PG (r = 0.71) measures of breast density. Risk estimates associated with the lowest to highest quartiles for the PDc measure (odds ratio [OR]: 1.0 ref., 3.4, 3.6, and 5.6), and the standard PD measure (OR 1.0 ref., 2.9, 4.8, and 5.1) were similar and greater than that of the calibrated PG measure (OR 1.0 ref., 2.0, 2.4, and 2.4).Conclusions: The information captured by the standard PD measure was quantified as it relates to calibrated mammograms and used to develop an automated method for measuring breast density. These findings represent an initial step for developing an automated measure built on an established calibration platform. A fully developed automated measure may be useful for both research- and clinical-based risk applications.

BACKGROUND:Calibrating mammograms to produce a standardized breast density measurement for breast cancer risk analysis requires an accurate spatial measure of the compressed breast thickness. Thickness inaccuracies due to the nominal system readout value and compression paddle orientation induce unacceptable errors in the calibration.METHOD:A thickness correction was developed and evaluated using a fully specified two-component surrogate breast model. A previously developed calibration approach based on effective radiation attenuation coefficient measurements was used in the analysis. Water and oil were used to construct phantoms to replicate the deformable properties of the breast. Phantoms consisting of measured proportions of water and oil were used to estimate calibration errors without correction, evaluate the thickness correction, and investigate the reproducibility of the various calibration representations under compression thickness variations.RESULTS:The average thickness uncertainty due to compression paddle warp was characterized to within 0.5 mm. The relative calibration error was reduced to 7% from 48-68% with the correction. The normalized effective radiation attenuation coefficient (planar) representation was reproducible under intra-sample compression thickness variations compared with calibrated volume measures.CONCLUSION:Incorporating this thickness correction into the rigid breast tissue equivalent calibration method should improve the calibration accuracy of mammograms for risk assessments using the reproducible planar calibration measure.

BACKGROUND:Breast density is a significant breast cancer risk factor. Currently, there is no standard method for measuring this important factor. Work presented here represents an essential component of an ongoing project that seeks to determine the appropriate method for calibrating (standardizing) mammography image data to account for the x-ray image acquisition influences. Longer term goals of this project are to make accurate breast density measurements in support of risk studies.METHODS:Logarithmic response calibration curves and effective x-ray attenuation coefficients were measured from two full field digital mammography (FFDM) systems with breast tissue equivalent phantom imaging and compared. Normalization methods were studied to assess the possibility of reducing the amount of calibration data collection. The percent glandular calibration map functional form was investigated. Spatial variations in the calibration data were used to assess the uncertainty in the calibration application by applying error propagation analyses.RESULTS:Logarithmic response curves are well approximated as linear. Measured effective x-ray attenuation coefficients are characteristic quantities independent of the imaging system and are in agreement with those predicted numerically. Calibration data collection can be reduced by applying a simple normalization technique. The calibration map is well approximated as linear. Intrasystem calibration variation was on the order of four percent, which was approximately half of the intersystem variation.CONCLUSION:FFDM systems provide a quantitative output, and the calibration quantities presented here may be used for data acquired on similar FFDM systems.

Three-dimensional imaging of the breast promises significantly improved performance compared to standard mammography by reducing structured noise in mammograms caused by superposition of tissue. This work describes a new GE mammography tomosynthesis prototype that enables rapid acquisition of a sequence of low dose x-ray images of the breast at appropriate projection angles. Enabled by advanced tube and detector technology, the system acquires 21 projection images over a 60 degree angular range in approximately 8 seconds, and creates a 3D volumetric image from the projections. Initial images acquired with the system and characterization of the depth resolution of the system are presented.

A new mammography tomosynthesis prototype system that acquires 21 projection images over a 60 degree angular range in approximately 8 seconds has been developed and characterized. Fast imaging sequences are facilitated by a high power tube and generator for faster delivery of the x-ray exposure and a high speed detector read-out. An enhanced a-Si/CsI flat panel digital detector provides greater DQE at low exposure, enabling tomo image sequence acquisitions at total patient dose levels between 150% and 200% of the dose of a standard mammographic view. For clinical scenarios where a single MLO tomographic acquisition per breast may replace the standard CC and MLO views, total tomosynthesis breast dose is comparable to or below the dose in standard mammography. The system supports co-registered acquisition of x-ray tomosynthesis and 3-D ultrasound data sets by incorporating an ultrasound transducer scanning system that flips into position above the compression paddle for the ultrasound exam. Initial images acquired with the system are presented.

Tomosynthesis provides a major advance in image quality compared to conventional projection mammography by effectively eliminating the effects of superimposed tissue on anatomical structures of interest. Early tomosynthesis systems focused primarily on feasibility assessment by providing 3-dimensional images to determine performance advantages. However, tomosynthesis image quality depends strongly on three key parameters: 1) detector performance at low dose, 2) angular range and number of projections acquired in the tomosynthesis scan, and 3) reconstruction algorithm processing characteristics used to create slice images from the measured projections. In this work, a new GE mammography tomosynthesis research system was developed that incorporates key improvements in each of these three areas compared to an early feasibility prototype system in use at Massachusetts General Hospital from 2000 to 2004. The performance gains that can be achieved by these enhancements are characterized, and clinical images acquired with the system at the University of Michigan Cancer and Geriatrics Center are presented. The advanced research system also provides the ability to acquire mechanically co-registered x-ray tomosynthesis and ultrasound images of the breast, and initial dual modality images are also presented.

This paper on digital mammography image display is 1 of 3 papers written as part of an intersociety effort to establish image quality standards for digital mammography. The information included in this paper is intended to support the development of an American College of Radiology (ACR) guideline on image quality for digital mammography. The topics of the other 2 papers are digital mammography image acquisition and digital mammography image storage, transmission, and retrieval. The societies represented in compiling this document were the Radiological Society of North America, the ACR, the American Association of Physicists in Medicine, and the Society for Computer Applications in Radiology. These papers describe in detail what is known to improve image quality for digital mammography and make recommendations about how digital mammography should be performed to optimize the visualization of breast cancers using this imaging tool. Through the publication of these papers, the ACR is seeking input from industry, radiologists, and other interested parties on their contents so that the final ACR guideline for digital mammography will represent the consensus of the broader community interested in these topics.

This paper describes work aimed at combining 3D ultrasound with full-field digital mammography via a semi-automatic prototype ultrasound scanning mechanism attached to the digital mammography system gantry. Initial efforts to obtain high x-ray and ultrasound image quality through a compression paddle are proving successful. Registration between the x-ray mammogram and ultrasound image volumes is quite promising when the breast is stably compressed. This prototype system takes advantage of many synergies between the co-registered digital mammography and pulse-echo ultrasound image data used for breast cancer detection and diagnosis. In addition, innovative combinations of advanced US and X-ray applications are being implemented and tested along with the basic modes. The basic and advanced applications are those that should provide relatively independent information about the breast tissues. Advanced applications include x-ray tomosynthesis, for 3D delineation of mammographic structures, and non-linear elasticity and 3D color flow imaging by ultrasound, for mechanical and physiological information unavailable from conventional, non-contrast x-ray and ultrasound imaging.

A 3D visualization preference study was conducted on digital mammography tomosynthesis datasets. Two volume rendering [VR] techniques were used in the preference study, the Maximum Intensity Projection [MIP] and the Composite Ray Casting [CRC]. These techniques were presented side by side to experts in the field of digital mammography on dual high resolution monitors. The two techniques were presented using each of three different modes, the thick slice VR, tumbling along the azimuth direction, and tumbling along the elevation direction. Several phantoms and mastectomy specimens were imaged and reconstructed for this study. The experts ranked MIP higher than CRC, and tumbling along the elevation direction was selected as the best mode. In addition, the experts indicated that the MIP technique is better in displaying microcalcifications, and the CRC technique is better in showing masses.

Mammography is currently the best imaging method for breast cancer screening with demonstrated redaction in mortality. Mammography, however, can be improved because 10%-30% of the cancers may be missed or not detected early enough particularly in dense breasts. New technological developments in three-dimensional (3D) x-ray imaging of the breast may offer significant improvements over the standard two-dimensional (2D) mammography by reducing the problem of superimposed tissue structures and/or by providing more details on the morphology and distribution of abnormalities. Computer aided diagnosis (CAD) algorithms developed for digitized screen/film mammography and recently expanded to 2Ddigital mammography are expected to face an entirely new challenge in 3D mammography, the image characteristics of which may impact CAD design and performance significantly. In this work, we examined the properties of 3D tomosynthesis phantom images and studied the potential impact of different reconstruction methodologies on CAD algorithm performance. Algorithms developed for the enhancement, segmentation, and detection of calcification clusters in 2D digital mammography were evaluated.

This paper presents a preliminary study of CAD in breast tomosynthesis. The problem addressed is how to discriminate the objects on the in-focus plane from its blurred image superimposed on other planes. Instead of developing a preprocessing module to suppress the tomosynthesis artifacts in the reconstruction, we locate the object by utilizing the inherent 3D information in the reconstructed planar images. This study was done on tomosynthesis data of a stereo breast biopsy phantom (RMI 164A) reconstructed with the simple backprojection (or shift-and-add) method. The experimental results demonstrate the ability of the proposed method to identify the focal plane of objects. It can potentially be applied to remove the blurred out-of-plane structure and improve the clinical application of breast tomosynthesis.

Digital tomosynthesis mammography is an advanced x-ray application that provides detailed 3D information about the imaged breast. The involved 3D reconstruction step is a difficult problem due to incomplete data and the limited projection angle. In this preference study we compared results obtained with advanced reconstruction techniques, in particular ART (Algebraic Reconstruction Technique), FBP (Filtered Backprojection), OSBP (order statistics based backprojection), and GFBP (generalized filtered backprojection) in terms of their image quality. The 3D datasets were displayed slice-by-slice in “cine loop” mode. As observers we included radiologists, physicists and image processing experts. Phantom and mastectomy specimen datasets were included in the study. The results obtained with our dataset indicate that ART was overall preferred for the phantom datasets while GFBP was preferred for mastectomy specimen reconstructions.

The purpose of this study was to determine the impact of default image display, presentation protocol, and workstation configuration on the softcopy interpretation of mammograms. Results from ROC studies that compared film to softcopy mammography were analyzed for this purpose. On average, no difference in performance was observed between the two modalities. However, differences were identified in individual observer performance and the qualitative evaluation of the two platforms that were related to the system’s speed, the default grayscale display of the images, and possibly the CRT phosphor. Speed and default display were ranked as the top two impact factors on softcopy reading.

We previously reported on 2" x 2" and 4" x 4" size imagers. direct digital radiography X-ray detectors, based on photoconductive polycrystalline mercuric iodide deposited on a flat panel thin film transistor (TFT) array, as having great potential for use in medical imaging, NDE, and security applications. Recently we successfully upgraded our mercuric iodide deposition technique to 20 cm x 25 cm size, the size required in common NDE and security imaging applications. A TFT array with a pixel pitch of 127 microns was used for this imager. The mercuric iodide direct conversion layers were vacuum deposited onto TFT array by Physical Vapor Deposition (PVD).In addition to successful imager scale up, more sophisticated, non-TFT based detectors were developed in order to improve analysis methods of the mercuric iodide photoconductor. Measurements on mercuric iodide photoconductor were performed using a 36 x 6 electrode array on a 10 cm x 10 cm substrate (total of 216 measurement points). The array is formed by 36 palladium stripes on the glass substrate, upon which the mercuric iodide is deposited, and 6 palladium stripes that are deposited on top of the mercuric iodide layer. These two sets of electrodes are oriented at 90 degrees to each other to create the measurement matrix. These detectors were evaluated in radiographic mode, continuous fluoroscopic mode and pulsed fluoroscopic mode. Mercuric iodide coatings with thickness ranging between 140 microns and 300 microns were tested using beams with energies between 40 kVp and 100 kVp utilizing exposure ranges typical for both fluoroscopic and radiographic imaging.Diagnostic quality radiographic and fluroscopic images at up to 15 pulses per second were demonstrated. We evaluated the dark current, sensitivity and MTF characteristics. The MTF is determined primarily by the aperture and pitch of the TFT array with Nyquist frequency of similar to3.93 mm(-1) (127 micron pixel pitch). The MTF curve of a good quality HgI2 imager is very close to the theoretical sinc function. Image lag characteristics of mercuric iodide appear adequate for fluoroscopic rates.

This paper investigated the use of the Breast Imaging Reporting And Data System (BIRADS) Lexicon in ROC mammography experiments. Analysis was based on data from parallel ROC experiments performed at two Institutions with different readers and databases to compare film to digitized mammography. Seven readers participated in the studies and read approximately 200 cases each in two formats: film and digital or softcopy. Reporting was done using BIRADS categories 1 through 5. Training was done with a separate set of cases and included detailed review of the relationship between BIRADS and a standard ROC discrete 5-point rating scale. The results from both sites showed equivalency between film and softcopy mammography. Decisions using the BIRADS categories showed no unsampled ROC regions and no degenerate data. Fits yielded smooth ROC curves that correlated to clinical practice. In a qualitative evaluation, all observers indicated preference in using the BIRADS classes instead of a discrete or continuous rating scheme. Familiarity with the rating process seems to relieve some of the bias associated with the interpretation of digitized mammograms from computer monitors (softcopy reading). Our results suggested that BIRADS categories can be used in comparative ROC studies because they represent a scale familiar to the reader that can be followed consistently and they provide a rating approach that accounts for both positive and negative cases to be evaluated and categorized.

RATIONALE AND OBJECTIVES:The authors developed and evaluated a method of computer-aided diagnosis (CAD) for mass detection with full-field digital mammography (FFDM).MATERIALS AND METHODS:The new CAD method for FFDM employs adaptive, nonlinear multiscale processing and hybrid classification methods. The major strategies are (a) to "standardize" the mammographic image before it is input to the analysis modules, (b) to adapt the segmentation of suspicious regions adapt to accommodate different characteristics of masses and mammograms, and (c) to use combined "hard" and "soft" decision making in discriminating between mass and normal tissue regions. Two data sets of diagnostic FFDM mammograms were used. The training data set includes 36 normal and 24 abnormal mammograms (34 masses), and the testing data set includes 24 normal and 10 abnormal mammograms (10 masses). The tumors in this diagnostic database were more subtle and difficult to detect than those in screening databases the authors have used before.RESULTS:With the limited database and a partial optimization, a sensitivity of 91% was obtained in training, with a false-positive rate of 3.21 per image. At this trained operating point of the CAD system, six of 10 subtle masses were detected in testing.CONCLUSION:The CAD algorithms developed in screen-film mammography can be modified for FFDM. More data analysis and system optimization and evaluation will be needed before CAD can be integrated efficiently into the performance of FFDM.