Showing papers on "Digital mammography published in 1997"

Diagnosis of Diseases of the Breast

Abstract: Introduction. History of Breast Imaging. Mammography: Performing the Examination. Equipment Selection. Positioning. Clinical Image Evaluation. Quality Control. Approach to the Evaluation of the Mammogram. Reporting and Communication. The Medical Audit: Statistical Basis of Clinical Outcomes Analysis. The Medical Audit: Practical Considerations. Legislation. Medicolegal Issues. Other Diagnostic Tools. Clinical Breast Examination and Breast Self Examination. Breast Sonography. Digital Mammography. MR Imaging of Breast Tumors. Mammographically-Guided Presurgical Needle Localization. Imaging-Guided Needle Biopsy. Sonographically-Guided Interventional Procedures. Cyst Aspiration and Pneumocystography. Galactography. Screening Mammography: Epidemiology of Breast Cancer. Screening Mammography: From Theory to Practice. Screening Guidelines and Controversies. The Normal Breast and Benign and Malignant Conditions: The Normal Breast. Benign Conditions. Noninvasive Carcinoma. Invasive Malignancies. The Male Breast. Managementof Breast Diseases and Post Treatment Evaluation: Treatment of Breast Disease. The Conservatively Treated Breast. The Augmented Breast. Reduction Mammoplasty.

Direct digital mammography image acquisition.

Abstract: Mammography is a branch of radiology which could benefit greatly from the assimilation of digital imaging technologies. Computerized enhancement techniques could be used to ensure optimum presentation of all clinical images. Beyond this it will facilitate powerful new clinical resources such as computer-assisted diagnosis, tele-mammography, plus digital image management and archiving. An essential precursor to all these advances is the availability of appropriate direct digital mammography (DDM) image-acquisition system(s) to capture high-quality breast X-ray image data at the outset. The only practical DDM image-acquisition system currently available is (photo-stimulable phosphor) computed radiography. Modern computed mammography (CM) uses similar radiation doses to the patient and produces equivalent, albeit different, image quality to screen-film mammography. Computed mammography offers superior rendition of the skin edge and sub-cutaneous tissue and dense parenchyma, while ensuring equivalent micro-calcification detectability. Meanwhile, a variety of new technical approaches to DDM are under active investigation and/or development which promise to supercede film-based mammography. These new (second generation) DDM technologies promise the radiologist superior image quality combined with significant dose savings compared with contemporary imaging systems. In this review we describe and compare the physical and clinical characteristics of CM and the various emerging DDM image-acquisition technologies.

System considerations in CCD-based x-ray imaging for digital chest radiography and digital mammography

Abstract: System modeling is used to investigate the effect of various system parameters on the image quality in CCD-based x-ray imaging systems. The systems considered consist of a typical phosphor-based scintillating screen coupled to a CCD through lens or fiberoptic taper. Two applications, chest radiography and mammography, are analyzed. For each application typical system characteristics and operating conditions are used to determine the detective quantum efficiency (DQE) as a function of spatial frequency, optical collection efficiency, optical demagnification factor, and electronic noise. The DQE is modeled by extending the analysis for storage phosphor systems. The calculations are done for typical exposure conditions (0.25 mR for chest and 10.0 mR for mammography); however, the exposure effects are also discussed. It was found that a reasonable DQE can be obtained for both applications through each coupling approach; however, the demagnification requirements and electronic noise limitations are more stringent for the digital mammography application.

Feature selection and classifiers for the computerized detection of mass lesions in digital mammography

Abstract: We have investigated various methods of feature selection for two different data classifiers used in the computerized detection of mass lesions in digital mammograms. Numerous features were extracted from abnormal and normal breast regions from a database consisting of 210 individual mammograms. A step-wise method, a genetic algorithm and individual feature analysis were employed to select a subset of features to be used with linear discriminants. Similar techniques were also employed for an artificial neural network classifier. In both tests the genetic algorithm was able to either outperform or equal the performance of other methods.

Computer-assisted reading of mammograms.

Abstract: Techniques developed in computer vision and automated pattern recognition can be applied to assist radiologists in reading mammograms. With the introduction of direct digital mammography this will become a feasible approach. A radiologist in breast cancer screening can use findings of the computer as a second opinion, or as a pointer to suspicious regions. This may increase the sensitivity and specificity of screening programs, and it may avoid the need for double reading. In this paper methods which have been developed for automated detection of mammographic abnormalities are reviewed. Programs for detecting microcalcification clusters and stellate lesions have reached a level of performance which makes application in practice viable. Current programs for recognition of masses and asymmetry perform less well. Large-scale studies still have to demonstrate if radiologists in a screening situation can deal with the relatively large number of false positives which are marked by computer programs, where the number of normal cases is much higher than in observer experiments conducted thus far.

Computer analysis of mammography phantom images (CAMPI): An application to the measurement of microcalcification image quality of directly acquired digital images

Abstract: The purpose of this investigation was to apply the recently developed CAMPI (computer analysis of mammography phantom images) method to a Fischer Mammotest Stereotactic Digital Biopsy machine. Another aim was to further elucidate the nature of the empirically introduced CAMPI measures. Images of an American College of Radiology (ACR) accreditation phantom centered on the largest two speck groups were obtained on this machine under a variety of x-ray conditions. An additional measure, alternative SNR (ASNR) is introduced which is complementary to the SNR measure. Analyses of the Mammotest images revealed that the mAs and kVp dependencies of the CAMPI measures could be understood from basic imaging physics principles. It is shown that: (1) the measures reflect the expected linearity of the digital detector and Poisson photon statistics; (2) under automatic exposure control (AEC) conditions the signal (SIG) measure is proportional to subject contrast; and (3) under AEC conditions the noise (NOI) measure is proportional to the square root of the average absorbed photon energy. Correspondence with basic imaging physics principles shows that the measures are significantly free of artifacts. Precision of the CAMPI measures exceeds that of human observers by orders of magnitude. CAMPI measures are expected to be more relevant to clinical mammography than Fourier metrics as the measurements are done on objects of arbitrary shape and size that were designed by the manufacturer to resemble various detection tasks in mammography. It is concluded that CAMPI can perform objective and highly precise evaluations of phantom image quality in mammography. It could be used as a sophisticated quality control tool, as a replacement for the current ACR/MQSA phantom evaluation program, and to evaluate the rapidly evolving digital mammography technology.

Full-field direct digital telemammography: technical components, study protocols, and preliminary results

Abstract: The early detection of breast cancer increases the survival rate in women. Today, film-screen mammography is the most common and effective technique for the detection of breast cancer. However, the film-screen image recording system of current mammography has several technical limitations that can reduce the breast cancer diagnostic accuracy. A state-of-the-art technology, full-field direct digital mammography (FFDDM) has the potential to increase the sensitivity of clinical and screening examinations and emerge as a film-screen mammography replacement. It is believed that efficiently delivering the superior image quality of FFDDM to expert mammographers will significantly increase the diagnostic accuracy. This concept motivates the studies of FFDDM telemammography. We report the FFDDM telemammography project that is being conducted in our facility. The fundamental technology of the FFDDM system and the characteristics of FFDDM images are described. Our research approach is through three protocols: telediagnosis, teleconsultation and telemanagement. Each of these study protocols is defined. To conduct this project, an ATM network-based telemammography system is developed across two remote campuses in our facility. The architecture of this system is detailed. Unlike other medical imaging modalities, the matrix of an FFDDM image is huge. How to present the image information to mammographers via currently available display media is a challenging task. Our display approaches for the FFDDM images are described. Some preliminary study results from the current phase of this study are reported.

Image feature analysis for classification of microcalcifications in digital mammography: neural networks and genetic algorithms

Abstract: We have developed an image feature-based algorithm to classify microcalcifications associated with benign and malignant processes in digital mammograms for the diagnosis of breast cancer. The feature-based algorithm is an alternative approach to image based method for classification of microcalcifications in digital mammograms. Microcalcifications can be characterized by a number of quantitative variables describing the underling key features of a suspicious region such as the size, shape, and number of microcalcifications in a cluster. These features are calculated by an automated extraction scheme for each of the selected regions. The features are then used as input to a backpropagation neural network to make a decision regarding the probability of malignancy of a selected region. The initial selection of image features set is a rough estimation that may include redundant and non-discriminant features. A genetic algorithm is employed to select an optimal image feature set from the initial feature set and select an optimized structure of the neural network for the optimal input features. The performance of neural network is compared with that of radiologists in classifying the clusters of microcalcifications. Two set of mammogram cases are used in this study. The first set is from the digital mammography database from the Mammographic Image Analysis Society (MIAS). The second set is from cases collected at Georgetown University Medical Center (GUMC). The diagnostic truth of the cases have been verified by biopsy. The performance of the neural network system is evaluated by ROC analysis. The system of neural network and genetic algorithms improves performance of our previous TRBF neural network. The neural network system was able to classify benign and malignant microcalcifications at a level favorably compared to experienced radiologists. The use of the neural network system can be used to help radiologists reducing the number biopsies in clinical applications. Genetic algorithms are an effective tool to select optimal input features and structure of a backpropagation neural network. The neural network, combined with genetic algorithms, is able to effectively classify benign and malignant microcalcifications. The results of the neural network system can be used to help reducing the number of benign biopsies.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Optimization of tungsten x-ray spectra for digital mammography: a comparison of model to experiment

Abstract: Tungsten (W) target x-rays tubes are being studied for use in digital mammography to improve x-ray flux, reduce noise and increase tube heat capacity. A parametric model was developed for digital mammography to evaluate optimization of x-ray spectra for a particular sensor. The model computes spectra and mean glandular doses (MGD) for combinations of W target, beam filters, kVp, breast type and thickness. Two figures of merit were defined: (signal/noise)2/MGD and spectral quantum efficiency; these were computed as a means to approach optimization of object contrast. The model is derived from a combination of classic equations, XCOM from NBS, and published data. X-ray spectra were calculated and measured for filters of Al, Sn, Rh, Mo and Ag on a Eureka tube. (Signal/noise)2/MGD was measured for a filtered W target tube and a digital camera employing CsI scintillator optically coupled to a CCD for which the detective quantum efficiency (DQE) was known. A 3-mm thick acrylic disk was imaged on thickness of 3-8 cm of acrylic and the results were compared to the predictions of the model. The relative error between predicted and measured spectra was +/- 2 percent from 24 to 34 kVp. Calculated MGD as a function of breast thickness, half-value layer and beam filter compares very well to published data. Best performance was found for the following combinations: Mo filter with 30 mm breast, Ag filter with 45 mm, Sn filter for 60 mm, and Al filter for 75 mm thick breast. The parametric model agrees well with measurement and provides a means to explore optimum combinations of kVp and beam filter. For a particular detector, this data may be used with the DQE to estimate total system signal-to-noise ratio for a particular imaging task.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Multiscale segmentation and enhancement in mammograms

Abstract: A multiscale method for segmenting and enhancing lesions of various sizes in mammograms is presented. The method uses two stages. The first stage applies a multiscale automatic threshold estimator based on histogram moments to segment the mammogram at multilevels. The second stage converts the segmented image using pseudo-colour mapping to produce a colour image. An algorithm is presented as well as experimental results. Mammograms are digitalised using a table scanner with a transparency adapter and the algorithm is implemented in Borland C++ 4.02 on a 486 PC. The results are analogous to a breast map which provide an adequate basis for radiological breast tissue differentiation and analysis in digital mammography. Experimental results and judgments from radiological experts are very encouraging.

Medical image databases for CAD applications in digital mammography: design issues.

Abstract: The evaluation of algorithms' developed for computer assisted diagnosis in digital mammography requires image databases that allow relative comparisons and assessment of algorithms clinical value. A review of the literature indicates that there is no consensus on the guidelines of how databases should be established. Image selection is usually done based on subjective criteria or availability. The generation of common database(s) available to the research community makes relative evaluations of algorithms with similar properties easier. However, questions regarding the "right database size," the "right image resolution," and the "right contents" remain. In this paper, database issues are reviewed and discussed and possible remedies to the various problems are proposed.

A pilot study of eye movement during mammography interpretation: Eyetracker results and workstation design implications

Abstract: Digital mammography can potentially improve mammography image and interpretation quality. On-line interpretation from a workstation may improve interpretation logistics and increase availability of comparison images. Interpretation of eight 4k- × 5k-pixel mammograms on two to four 2k- × 2.5k-pixel monitors is problematic because of the time spent in choosing which images to display on which monitors, and zooming and roaming on individual images that are too large to display completely at full resolution. The authors used an eyetracker to measure radiologists viewing behavior during mammography interpretation with film on a viewbox. It was observed that a significant portion of the mammographers' time is spent viewing “comparison pairs” (typically two or more comparisons per case), such as the left mediolateral and craniocaudal images or old and new images. From the eyetracker measurements, we estimated that the number of images display, roam, and zoom operations decreases from an average of 64 for one monitor to 31 for four monitors, with the largest change going from one to two monitors. We also show that fewer monitors with a faster response time is superior to more monitors with a slower response time. Finally, the authors demonstrate the applicatity of time-motion analysis to mammographic workstation design.

Radiologists' ability to discriminate computer-detected true and false positives from an automated scheme for the detection of clustered microcalcifications on digital mammograms

Abstract: There is evidence that computer-aided diagnosis (CAD) can be used to improve radiologists' performance. However, one of the potential drawbacks of CAD is that a computer-detected false positive may induce a false positive by a radiologist. To examine this issue, we performed two experiments to compare radiologists' false positives with those of the computer and to determine radiologists' ability to discriminate between the computer's true- and false-positive detections. In the first experiment, radiologists were shown 50 mammograms and on each film were asked to indicate 3 regions that could contain clustered microcalcifications, and using a 100-point scale, to give their level of confidence that microcalcifications were present in the region. In the second experiment, the radiologists were shown regions-of-interest, printed on film, containing either a computer-detected true cluster or a computer- detected false positive. The radiologists gave their confidence that there were actual clustered microcalcifications present. There was less than 1% overlap between false positives by the computer and radiologists. Furthermore, based on ROC analysis, radiologists were able to discriminate between computer true and false positives.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The detection of stellate lesions in digital mammography

Abstract: Breast cancer is a leading cause of fatality in women, with approximately 1 in 12 women affected by the disease during their lifetime1. Mass screening of women using x–ray mammography is currently the most effective method of early detection of the disease, which is essential for successful treatment2. Malignant breast lesions in x–ray mammograms are often characterised by abnormal patterns of linear structures. Architectural distortions and stellate lesions are examples of patterns frequently presenting with an appearance of radiating linear structures3. These malignancies can be extremely subtle and a significant proportion of them are undetected by radiologists. We have previously performed experiments which demonstrate that a radiologist’s performance can be improved by prompting the possible locations of abnormalities4. Attempts to detect stellate lesions automatically have generally concentrated on features of known importance, such as radiating linear structure concurrency, spread of focus and radial distance5,6,7. Recent work in our laboratory provides quantitive targets for clinically useful algorithm performance8. Most published techniques provide useful insight into the problem but fall well below the level of prompting accuracy that leads to an improvement in radiologists’ performance. This implies that existing methods are failing to fully exploit the available image evidence. We present an alternative approach that has a compact statistical representation of pattern structure, based on factor analysis, which completely encapsulates all patterns yet remains uncommitted to specific types of pattern. We present the results of an experiment in which the technique was applied to a set of 129 mammograms. We demonstrate how this generic technique can be used to detect abnormalities successfully with an accuracy of 0.23 false positives per image at a sensitivity of 80% for lesions with an effective diameter of 12mm. For lesions 16mm 0.06 false positives per image are obtained with the same sensitivity. These results compare favorably with existing methods, without the need for noise equalisation or any form of mammogram normalisation.

Evaluation of a CCD-based film digitizer for digital mammography

Abstract: Film digitalization is the process of mapping the optical densities of a radiographic film into a digital matrix. In this work, a film digitizer based on charge-coupled device was evaluated and optimized for digital mammography applications. The characteristics of the digital output were determined for various spatial resolutions and dynamic ranges. Furthermore, the reproducibility of the system was tested as needed for computer assisted diagnosis (CAD) applications. Practical and relevant to the application quality control procedures were established for the system that will allow early troubleshooting and close monitoring of image quality for consistent performance. Overall, the characteristics of the scanner matched the properties of the tested screen/films and its performance generally met digital mammography and CAD requirements.

Digitale Speicherfolienmammographie in Vergrößerungstechnik: Experimentelle Untersuchungen zur Ortsauflösung und zur Erkennbarkeit von Mikrokalk

Abstract: PURPOSE Since the routine use of storage phosphor systems for mammography has been limited by its inadequate spatial resolution of 5 linepairs/mm, a combination of a magnification mammography technique with storage phosphor plates was investigated to detect microcalcifications. MATERIAL AND METHODS A new mammography system with a microfocus tube using an anode of 0.05-0.12 mm allowed to obtain survey views of the breast with 1.7x magnification (m), and spot views with 4x magnification. The digital image receptor comprised a high resolution storage phosphor plate. To determine spatial resolution, contrast transfer curves were obtained, and the detection of microcalcifications was investigated by ROC (receiver operating characteristic) analysis. RESULTS Spatial resolution for digital survey views (m = 1.7) was 8 linepairs/mm and for spot views (m = 4) was 18 linepairs/mm. ROC analysis demonstrated a significantly higher performance of the digital magnification technique compared to the conventional screen-film mammography technique. CONCLUSIONS The limitations of digital mammography with respect to spatial resolution can be overcome by using a high magnification technique.

Full-field direct digital telemammography : Preliminary

Abstract: Full-field direct digital mammography has many advantages over the conventional film/screen imaging detector Among these are larger dynamic range, lower scattering noise, and the possibility of using it for telemammography applications to alleviate the shortage of expert mammographers We are in the process of developing a full-field direct digital telemammography imaging chain to investigate its usefulness for telediagnosis, teleconsultation, and telemanagement This paper describes the first phase of a three-year research program to set up a full-field direct digital mammography (FFDDM) imaging chain at the Breast Imaging Section connecting the University of California, San Francisco Medical Center and the Mt Zion Hospital in the San Francisco Bay area The chain consists of two FFDDM system, and two 2,500 line two-monitor workstations An OC-3 155 Mbits/sec asynchronous transfer mode (ATM) communication network is used to connect the FFDDM and the two workstations The FFDDM is based on a slot scan CCD detector which can image a full breast with 3,100 X 3,870 pixels, and produce a direct digital image with 50 micron pixel size Preliminary results of the FFDDM demonstrate that it has a greater dynamic range and lower detector noise than that of a film-screen detector, and that the scattered radiation is reduced without using a grid However, the spatial resolution is less than that of the conventional screen/film system The 2K workstation can display simultaneously any two or four full-view mammographic images by either scrolling or subsampling on the two monitors Display of an image takes about 15 seconds from the RAID disks The ATM can transmit a 32 Mbyte digital mammogram from the FFDDM to the workstation in 3-4 seconds

Update in digital mammography.

Abstract: Digital mammography is a rapidly developing technology that has great potential to improve upon and ultimately replace conventional film-screen mammography for the early detection of breast cancer. This article reviews current progress in digital mammographic systems, computer-aided diagnostic programs, and artificial neural networks. Digital mammographic systems are currently in an investigational phase only. Large-scale clinical trials are needed in all areas of digital mammography before this exciting new technology can be implemented outside of research centers.

CAD system for full-digital mammography and its evaluation

Abstract: The purpose of this study is to develop a clinical intelligent workstation for computer-aided diagnosis (CAD) of breastcancer using full digital mammography. It consists of a clinical workstation and Fuji Computed Radiography 9000 System. Newimage processing methods to extract tumor masses and clustered microcalcifications have been developed and implemented inthe CAD system. A new filter called Iris Filter has been developed to detect tumor candidates. It realizes reliable detection oftumor candidates regardless of their sizes and their contrast against their background on mammograms. And a new methodbased on mathematical morphology has been developed to detect microcalcifications. It is adaptive to the imaging conditions ofmammograms. One thousand, two hundred and twelve CR images, which include 240 malignant tumors, were used to test theperformance of the system. The sensitivity for malignant tumors was 90. 5% and the average number of false positives per imagewere only 1.3. The true positive detection rate for clustered microcalcifications was 89.2% and the average number of falsepositives per image were 0.36. The high true positive rates and the low false positive detection characterize the proposed full-digital CAD system, which shows the possibility of practical application of computer aided diagnosis of breast cancer.Keywords: breast cancer, mammography, CAD, malignant tumors, microcalcijIcations, irisfilter. morphological processing

Workstation interface for ROC studies in digital mammography

Abstract: The goal of this project was the development of a workstation-user interface for evaluating computer assisted diagnosis (CAD) methods for digital mammography in receiver operating characteristic (ROC) experiments. Digital mammography poses significant and unique difficulties in the design and implementation of such an interface because multiple, large size images need to be handled at high- speeds. Furthermore, controls such as contrast, pan and zoom, and tools such as reporting forms, case information, and analysis of results need to be included. The software and hardware used to develop such a workstation and interface were based on Sun platforms and the Unix operating system. The software was evaluated by radiologists, and found to be user friendly, and comparable to standard mammography film reading in terms of display layout and speed. The software, as designed, will work on entry level workstations as well as high-end workstations with specialized hardware, thus being usable in either an educational, training, or clinical environment for annotation purposes using CAD techniques as well as primary diagnosis.

Integrated distortion correction and reconstruction technique for digital mosaic mammography

Abstract: Investigations in the area of digital mammography have been limited by the resolution of the sensor devices employed. We have proposed a multiple camera or mosaic architecture in which adjacent sensors observe an overlapping field of view. Such a technique can deliver extremely high resolution while simultaneously maintaining a moderate cost for the resultant instrument. However, this technique's clinical efficacy will be limited by the ability to accurately and precisely reconstruct a single continuous image from multiple CCD sensors. We present an integrated algorithm which will correct distortions introduced by the camera while addressing the problem of image reconstruction or 're- stitching.' Such a technique will minimize pixel loss by limiting image re-sampling to a single incident. Custom designed calibration screens were employed for the calculation of camera distortion and intra-camera disparity. A parallel digital signal processor architecture has been developed to accelerate system performance when employing a large number of camera inputs. We present a quantitative evaluation of our reconstruction technique and an analysis with respect to similar methods of image reconstruction. We have previously constructed and presented a prototype imager for digital radiography based upon a similar sensor architecture. The algorithm presented will significantly enhance the feasibility of our multiple camera architecture for both digital radiography and mammography. We believe that such a methodology will enhance diagnostic accuracy at a moderate cost when compared with system of similar imaging resolution.

Mammographic feature generator for evaluation of image analysis algorithms

Abstract: We introduce a mammographic feature generator which can be used to evaluate image analysis algorithms for digital mammography. Several types of calcifications and focal lesions may be generated, synthetic noise may be added, and the features may be embedded in to a digital mammogram. As an application we demonstrate the use of the generator in comparing the performance of two feature extraction algorithms.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

ROC comparison between digital mammography and screen-film using an anthropomorphic breast phantom

Abstract: Mass lesion detection performance of a LoRAD Digital Spot Mammography (DSM) system was compared with a Kodak Min R screen-film combination exposed either in front of the DSM, or in the Bucky of a GE 600T mammography unit Low-contrast objects simulating small masses were superimposed on an RMI 165 anthropomorphic breast phantom and radiographs obtained at 28 kVp and an mAs value, which resulted in a mean film density of approximately 11 DSM images were obtained at the same radiation exposure as used with screen-film Fully masked radiographs were viewed on a mammography light box, and the DSM images were viewed on the DSM monitor in a darkened room Of the 64 regions of interest (ROI) in each type of image, 28 (44%) contained the test object For each imaging modality, six radiologists and six scientists assessed the probability of a simulated mass being present in each ROI The resultant data were used to plot receiver operating characteristic (ROC) curves of twelve readers for each of the three imaging modalities investigated There was no significant difference in reader performance between the screen-film combination exposed in front of the DSM system and exposed in the GE 600T system Both screen-film imaging systems resulted in the same average area under the ROC curve, Az, of 078 At the same level of radiation exposure, the DSM had an average ROC area, Az, of 071 which was significantly inferior to the average performance achieved using screen-film (p less than 0005) For this detection task, there were no significant differences in performance between the radiologists and scientists Reader performance was found to improve with the number of images read, demonstrating an observer learning curve for this specific detection task© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering Downloading of the abstract is permitted for personal use only

ROC study of screen-film mammography and storage phosphor digital mammography: analysis of nonconcordant classifications and implications for the approval of digital mammography systems

Abstract: A recently completed ROC study of digital mammography using a 100 micron pixel storage phosphor receptor showed that digital mammography and conventional screen film mammography were essentially equivalent in areas under the ROC curve. In this study, there were 24 biopsy proven breast cancer cases, 25 benign biopsy cases and 48 clinically normal breast images each with matched screen film and storage phosphor images. Fifteen of the 24 cancer cases were 10 mm or less in size. Of these 10 presented with microcalcifications as the sign of disease. Six radiologists not involved with the research program and without prior experience with digital mammography and who met qualification criteria under the Mammography Quality Standards Act of 1992 served as readers. This poster looks at the cases in which there was variance between the radiologists ROC classification system for the digital and screen film system in order to analyze case specific discrepancies that may indicate benefits or deficits of the digital system. Aspects of the ROC ratings are also analyzed including an evaluation of the different thresholds used by radiologists on the digital and screen film systems, the distribution of ROC ratings in normal and abnormal cases, the effect of using different gold standards of proof on the results and the effect of substituting an ACR BIRADS category agreement study as proposed by the FDA compared to the ROC study outcome.