Information Systems and Health Care IV: Real-Time ROC Analysis to Evaluate Radiologists\u27 Performanceof Interpreting Mammograpny

This paper describes how to use Receiver Operator Characteristic (ROC) analysis to evaluate radiologists\u27 performance of interpreting digital mammograms in real-time. We developed an experimental testing system, which implemented a set of clinical lesion-matching rules to prepare raw ROC data. The system can automatically provide detailed evaluations of the performance, such as sensitivity, specificity, positive predictive value, negative predictive value, diagnostic accuracy, ROC curve, and area under the curve (Az). Based on a preliminary evaluation of the system, we found that ROC analysis is appropriate for a real-time computer application, directly using the raw data from a database, to evaluate the performance of radiology residents

Future Directions in Breast Imaging

Breast cancer imaging has improved dramatically over the last decade, with higher and more uniform quality standards for mammography, the increasing use of sonography and magnetic resonance imaging (MRI), and the widespread availability of imaging-guided percutaneous biopsy for clinically occult disease. This review paper describes the limitations that exist in the current state of the art for breast cancer imaging for detection and diagnosis. Four broad areas of future investigation are described in detail. First, we discuss the use of newer versions of mammography, such as digital mammography, with tomosynthesis and digital subtraction mammography. Secondly, new screening for occult disease might be improved through individualized strategies that stratify by patient risk, for example, through more rigorous screening with new and different tools for women at high risk. Third, the use of tools that might be useful for less invasive therapy of breast cancer with imaging to monitor the efficacy of the therapy is discussed. Finally, we describe the use of imaging to monitor and adjust neoadjuvant chemotherapy regimens in the course of therapy for advanced breast cancers when the risk of death is high

Digital Mammography

In digital mammography, the processes of image acquisition, display, and storage are separated, which allows optimization of each. Radiation transmitted through the breast is absorbed by an electronic detector, the response of which is faithful over a wide range of intensities. Once this information is recorded, it can be displayed by using computer image-processing techniques to allow arbitrary settings of image brightness and contrast, without the need for further exposure to the patient. In this article, the current state of the art in technology for digital mammography and data from clinical trials that support the use of the technology will be reviewed. In addition, several potentially useful applications that are being developed with digital mammography will be described

Issues to Consider in Converting to Digital Mammography

This paper will outline the reasons that many radiology practices are converting to digital mammography. In addition, we will provide basic information on the issues that must be considered in making the transformation. These include technical matters regarding image display, storage and retrieval, as well as clinical and ergonomic considerations

Two-Modality Mammography May Confer an Advantage Over Either Full-Field Digital Mammography or Screen-Film Mammography

To compare the cancer detection rate and ROC area under the curve of full-field digital mammography, screen-film mammography, and a combined technique that allowed diagnosis if a finding was suspicious on film, on digital, or both

Diffraction-Enhanced Imaging of Musculoskeletal Tissues Using a Conventional X-Ray Tube

In conventional projection radiography, cartilage and other soft tissues do not produce enough radiographic contrast to be distinguishable from each other. Diffraction-enhanced imaging (DEI) uses a monochromatic x-ray beam and a silicon crystal analyzer to produce images in which attenuation contrast is greatly enhanced and x-ray refraction at tissue boundaries can be detected. Here we test the efficacy of conventional x-ray tube-based DEI for the detection of soft tissues in experimental samples

Discrimination of benign from malignant breast lesions in dense breasts with model-based analysis of regions-of-interest using directional diffusion-weighted images.

BACKGROUND: There is an increasing interest in non-contrast-enhanced magnetic resonance imaging (MRI) for detecting and evaluating breast lesions. We present a methodology utilizing lesion core and periphery region of interest (ROI) features derived from directional diffusion-weighted imaging (DWI) data to evaluate performance in discriminating benign from malignant lesions in dense breasts. METHODS: We accrued 55 dense-breast cases with 69 lesions (31 benign; 38 cancer) at a single institution in a prospective study; cases with ROIs exceeding 7.50 cm RESULTS: The region-growing algorithm for 3D lesion model generation improved inter-observer variability over hand drawn ROIs (DSC: 0.66 vs 0.56 (p \u3c 0.001) with substantial agreement (DSC \u3e 0.8) in 46% vs 13% of cases, respectively (p \u3c 0.001)). The overall classifier improved discrimination over mean ADC, (ROC- area under the curve (AUC): 0.85 vs 0.75 and 0.83 vs 0.74 respectively for the two readers). CONCLUSIONS: A classifier generated from directional DWI information using lesion core and lesion periphery information separately can improve lesion discrimination in dense breasts over mean ADC and should be considered for inclusion in computer-aided diagnosis algorithms. Our model-based ROIs could facilitate standardization of breast MRI computer-aided diagnostics (CADx)

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

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- x 5k-pixel mammograms on two to four 2k- x 2.5k-pixel monitors is problematic because of the time spent in choosing which images 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 image 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 applicability of time-motion analysis to mammographic workstation design

Contrast Limited Adaptive Histogram Equalization image processing to improve the detection of simulated spiculations in dense mammograms

The purpose of this project was to determine whether Contrast Limited Adaptive Histogram Equalization (CLAHE) improves detection of simulated spiculations in dense mammograms. Lines simulating the appearance of spiculations, a common marker of malignancy when visualized with masses, were embedded in dense mammograms digitized at 50 micron pixels, 12 bits deep. Film images with no CLAHE applied were compared to film images with nine different combinations of clip levels and region sizes applied. A simulated spiculation was embedded in a background of dense breast tissue, with the orientation of the spiculation varied. The key variables involved in each trial included the orientation of the spiculation, contrast level of the spiculation and the CLAHE settings applied to the image. Combining the 10 CLAHE conditions, 4 contrast levels and 4 orientations gave 160 combinations. The trials were constructed by pairing 160 combinations of key variables with 40 backgrounds. Twenty student observers were asked to detect the orientation of the spiculation in the image. There was a statistically significant improvement in detection performance for spiculations with CLAHE over unenhanced images when the region size was set at 32 with a clip level of 2, and when the region size was set at 32 with a clip level of 4. The selected CLAHE settings should be tested in the clinic with digital mammograms to determine whether detection of spiculations associated with masses detected at mammography can be improved

Comparison of Acquisition Parameters and Breast Dose in Digital Mammography and Screen-Film Mammography in the American College of Radiology Imaging Network Digital Mammographic Imaging Screening Trial

The purpose of our study was to compare the technical performance of full-field digital mammography (FFDM) and screen-film mammography