For many imaging departments and practices, breast imaging comprises a high volume area. Demand for breast imaging services and the attendant necessary professional expertise continues to rise. Fortunately, with the introduction of digital mammography and other software tools, the practice of breast imaging can now be accomplished in a digital and paperless environment. In this article, the authors discuss three important filmless innovations in breast imaging: digital mammography, computer-assisted detection, and digital tomosynthesis.

Figure 1. Digital mammogram (1a), right and left cranial-caudal views, shows an area of asymmetry in the lateral right breast. The right and left medial-lateral oblique views (1b), show an area of asymmetry in the upper right breast.

DIGITAL MAMMOGRAPHY

Breast cancer is the most common cancer and second leading cause of death in American women. 1 Although present treatment methods including traditional surgical treatment and modern chemotherapy and radiotherapy provide epochal results to the patients, prevention and early detection are the best strategy to fight the disease. The role and importance of mammography in the early detection of breast cancer have been well documented by many large-scale cohort studies. 2,3 Although clinical breast examination and self-breast examination are recommended adjuncts to screening mammography, screening mammography is the only proven method to effectively reduce mortality from breast cancer. 4 The present American Cancer Society recommendation is annual screening mammography beginning at age 40.5

The rapid evolution of filmless radiology and picture archiving and communications systems (PACS) and the growing need for teleradiology have brought digital mammography into clinical practice (Figure 1). Digital mammography uses an electronic detector instead of a film-screen cassette to capture images. Digital mammography is expected to overcome the limitations of film-screen mammography by its ability to provide better contrast with reduced radiation dose, fewer repeated images, and reduced recall rates. Recently, the New England Journal of Medicine published the results of the Digital Mammographic Imaging Screening Trial (DMIST), which studied 42,760 patients who had both film and digital mammograms. The purpose of this study was to verify whether digital mammography could overcome the limitations of film-screen mammography by measuring small potential clinically important differences in diagnostic accuracy between the two modalities. Digital mammography was superior to film-screen mammography in detecting breast cancer in women younger than 50 years of age, in pre- and peri-menopausal women, and in women with dense breasts. 6 This finding differed from the results of previous studies showing no statistically significant difference between the two modalities for breast cancer detection. 7-9

Other advantages of digital mammography include: lower average radiation dose, lower image noise, and reduced image artifacts. Reduced processing time with near-real-time review by the technologist improves workflow and reduces the procedure time for preoperative needle/wire localization. Fewer recalls are reported with digital mammography, 7,8 and imaging of implants is also improved due to its wide dynamic range. Edge-enhancing software to visualize the skin and periphery of the breast tissue is another capability of digital mammography. 4 Finally, the environmental benefit of discontinuing the use of film developers is an important advantage.

Figure 2. Cranial-caudal (2a) and medial-lateral oblique (2b) digital mammograms with CAD markings identify the area of asymmetry (superior marking in each image) and one ‘false marking’ (inferior marking in each image).


One obstacle to implementing widespread digital mammography is its high cost. Besides the cost of the system itself, there are additional costs for the soft- copy review workstation and the image storage system (PACS). Compatibility and integration with various PACS are frequently an issue. Among the various manufacturers, the resolution for digital mammography detectors varies between 70 and 100 µm. Another issue relates to the varying sizes of the digital image detectors among the vendors. Some offer a 23×30 cm detector, but others make only small 19×23 cm detector, limiting the capability of performing digital mammography in patients with large breasts. 4 Soft-copy display on specialized mammography workstations is the preferred method of viewing digital mammograms for interpretation because many processing tools, such as window/level, peripheral equalization, and magnification, can be applied. Image magnification on the monitor has not yet been proven to be as accurate as true geometric magnification mammography, but the potential to reduce some patient recalls for magnification mammography has been suggested. 4

One of the most promising aspects of digital mammography is further extension of diagnostic capability with computer-assisted detection (CAD) applications and the development of cutting-edge technology such as tomosynthesis and contrast-enhanced digital mammography.

COMPUTER-ASSISTED DETECTION

Computer-assisted detection has been applied to breast cancer screening as a ” second opinion” or “spell check” strategy for digital or digitalized film-screen mammography (Figure 2). Previous studies have shown that prospective double reading of screening mammograms increases the detection rate of cancer from 4% to 15%10 and decreases the error rate. 10-13 The second reader could be human or machine, and there is good experience using human second readers in multiple retrospective and prospective trials. Experience using computers as the second reader is mainly based on retrospective studies with some prospective studies also reported. 14,15 A comparison of humans and CAD as a second reader 16 found increased sensitivity by both, with humans better than CAD. Using humans as a second reader has the associated issues of reader experience, limited resources, and cost-effectiveness.

CAD uses image processing algorithms and decision threshold parameters to detect features in an image likely to be of clinical significance. 17-19 CAD vision algorithms extend human perception by isolating, segmenting, enhancing, or suppressing different features of the image. 17-19 Using CAD as a second reader, the experienced radiologist can improve their opportunity to detect breast cancer at an early stage; studies have reported an increase in cancer detection rate and recall rate when CAD is utilized.

There are at least four commercially available FDA-approved CAD systems for use with digitized film mammograms. 20,21 Table 1, below, summarizes the changes in recall rate, cancer detection rate, and false-negative rate reported in the CAD literature.

The results from these studies fall into a wide range, perhaps explained by differing types of screening populations, expertise of the radiologist, CAD experience and training of the radiologist, and differences in CAD systems. 15,22-29 The false-marker rate for CAD ranges from 1.08 markers per routine four-view mammogram, as reported by Gur et al, 22 to 4.3 per four views as reported by Birdwell et al. 23

A study by Lou et al reported that CAD benefits less-experienced and low-volume radiologists more than the high-volume senior radiologist. 28 This same phenomenon was reported by Gur et al. 22 In another study, the authors concluded that CAD training and experience will influence the automaticity of human-CAD interaction, the perception and interpretation of early breast cancer, and CAD performance studies. 29 With knowledge and experience in CAD-assisted mammography reading, the readers can dismiss prompts marking normal areas while recognizing prompts marking potentially significant findings.

Recently, concerns have been raised regarding whether CAD-assisted interpretation has become a standard of care in mammography. There are medicolegal concerns that a lesion marked by CAD, but disregarded by the radiologist, which is ultimately found to be cancer, may constitute negligence by the radiologist. 30 This has led to controversy regarding whether the CAD marks on a particular mammogram should be saved. Because CAD marks may vary with repeated processing of the same images, 31,32 most experts believe that we should save the CAD marks.

One study utilizing CAD for breast MRI in patients undergoing chemotherapy suggested CAD may be helpful in assessing changes in MRI enhancement profiles of tumors before and following chemotherapy. 32

In summary, the aggregate of published studies strongly supports that after sufficient training and experience, CAD aids radiologists to notice features in mammograms that might indicate cancer and might otherwise be missed. To date, there is no evidence that CAD alone can be used as a primary interpretive tool. It is anticipated that, with new digital acquisition technologies for breast imaging, further refinements and advances in CAD systems will be forthcoming.

DIGITAL TOMOSYNTHESIS

Tomosynthesis is a technique for reconstructing arbitrary planes in an object from a series of projection radiographs. 33 In contrast to conventional tomography, which images only a single plane, tomosynthesis reconstructs an arbitrary number of planes from a single, limited-view scan. Breast tomosynthesis is a recently developed three-dimensional imaging technique that acquires images of a stationary compressed breast at multiple angles during a short scan. The individual images are then reconstructed into a series of thin high-resolution slices that can be displayed individually or in a dynamic cin mode. Because conventional mammography is a two-dimensional imaging modality, pathologies of interest are sometimes difficult to visualize because of overlapping tissues above and below the lesion. The image data collected by the detector comprises the total attenuation of all tissues overlying the detector. Tomosynthesis reduces the effects of tissue overlap by reconstructing data to enhance objects in given planes.

Figure 3. Tomosynthesis images from two different levels in the cranial-caudal (3a and 3b) and the medial-lateral oblique (3c and 3d) projections of area of focal asymmetry seen on digital mammogram (Figures 1 and 2), now clearly seen as a mass with architectural distortion.


With the breast compressed and held stationary, images are acquired at a number of different x-ray angles and at diminished x-ray exposures relative to conventional mammography. Typically, the x-ray tube is rotated over an arc of 30 degrees and images are made every 3 degrees. A total of 11-15 images are acquired during a single exposure equaling the radiation dose of one 2D mammography image. In general, more exposures will allow reconstructions with fewer artifacts. This must be balanced against the fact that for a given total examination dose, more exposures will equate to smaller signals for each of the individual images. The total time to acquire a set of tomosynthesis images is 5 to 10 seconds.

Following acquisition, tomosynthesis images, representing projections through the breast at varying angles, are reconstructed into slices of the breast that enhance objects at a given distance from the detector by shifting the projections relative to one another. In tomosynthesis images, objects at different heights above the image detector project differently in different projections. The slice thickness of the reconstructed images can be varied by the user, typically varying from 1 mm to 4 mm. The reconstructed tomosynthesis slices can be displayed similarly to CT reconstructed slices. The operator can view images one at a time or display them in a cin loop.

There are two basic tomosynthesis system designs, which differ in the motion of the detector during acquisition. One method moves the detector in concert with the x-ray tube, so as to maintain the shadow of the breast on the detector. An alternate method is to keep the detector stationary relative to the breast platform.

Digital breast tomosynthesis offers a number of exciting opportunities including the possibility of reduced breast compression, improved diagnostic and screening accuracy, 3D lesion localization, and contrast-enhanced 3D imaging. Tomosynthesis should resolve many of the tissue-overlap reading problems that are a major source for recalling women for additional diagnostic mammograms with conventional 2D mammography. Tomosynthesis may improve the specificity of screening for breast cancer with mammography if radiologists are able to better see lesion features that define a finding as benign by eliminating the effect of structure noise in breast images. This would reduce the number of breast biopsies performed on noncancerous lesions. The biopsy rate may also decrease through improved visualization of suspect objects. On the other hand, some pathologies that can be mammographically occult, such as lobular carcinoma, may be better discerned by the elimination of structure noise.

Other potential applications for tomosynthesis mammography include the use of contrast media while imaging. Researchers have studied mammography using IV-administered iodinated contrast agents, using either dual energy or pre- and post-contrast imaging, and they have observed enhancement of otherwise occult cancers and differentiation of benign from malignant tumors. 34 Contrast-enhanced mammography uses the basic biological principle that aggressive cancers are associated with increased vascularity and that contrast circulating in the blood will distribute in higher concentration to tumors. While this research is still in its infancy, contrast-enhanced tomosynthesis images might offer even greater malignant tumor to background uptake than observed with the 2D contrast imaging, and could conceivably supplant MRI gadolinium breast imaging.

In summary, the future of radiology is the fully digitized environment. Mammography is one of the last modalities to be fully electronic, but is developing rapidly. New digital technologies such as tomosynthesis and contrast-enhanced digital mammography will advance the diagnosis of breast cancer even further.

JeongMi Park, MD, is clinical professor of radiology; Megha Garg, MD, is clinical associate in radiology; Laurent Grignon, MS, is a medical student; and Laurie L. Fajardo, MD, MBA, is professor and chair, Department of Radiology, University of Iowa Carver College of Medicine, Iowa City.

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