Aetna considers annual mammography screening a medically necessary preventive service for women aged 40 and older. Annual screening is also considered medically necessary for younger women who are judged to be at high-risk by their primary care physician. Screening mammography for other women is considered experimental and investigational because its benefits in these other women are unproven.
Aetna considers screening mammography for men experimental and investigational, as the clinical benefits of such screening in men are unproven. Current guidelines from the U.S. Preventive Services Task Force and the American College of Radiology recommend such screening only for women. Aetna considers mammography medically necessary for surveillance of men with a prior history of breast cancer.
Aetna considers diagnostic mammography medically necessary for members with signs or symptoms of breast disease or history of breast cancer.
Note: Diagnostic mammography is covered regardless of whether the member has preventive services benefits
Aetna considers digital mammography an acceptable alternative to film mammography.
Aetna considers computer-aided detection (CAD) a medically necessary adjunct to mammography.
Aetna considers xeroradiography for breast imaging experimental and investigational because this method of radiography is obsolete.
Aetna considers breast tomosynthesis imaging experimental and investigational because of insufficient evidence of its effectiveness.
Aetna considers contrast-enhanced spectral mammography experimental and investigational because of insufficient evidence of its effectiveness.
This policy is based on the recommendations of the American Cancer Society, American College of Radiology, and the American College of Obstetricians and Gynecologists.
A mammogram is an x-ray of the breast. A screening mammography is one of several tools that are used for early detection of breast cancer in asymptomatic women. Other screening tools include the clinical breast examination and breast self-examination. Diagnostic mammography is used to diagnose breast cancer in women who have signs or symptoms of breast disease.
Screening mammography aims to reduce morbidity and mortality from breast cancer by early detection and treatment of occult malignancies. There is extensive evidence from a variety of well-conducted, randomized controlled studies that annual or biennial mammography is effective in reducing breast cancer mortality by 30 % in women aged 50 to 69 years. Data on women under age 50 are less clear. Results from the Canadian National Breast Screening Study (CNBSS) suggest that the contribution of mammography over good physical examinations to breast cancer mortality reduction may be less than has been assumed. This observation re-emphasizes a truism of screening -- that it is not necessary to detect cancers as early as possible to obtain a benefit -- it is only necessary to detect them early enough. What is early enough in any individual case is uncertain because there are insufficient outcomes data. This has made it difficult for professional societies to develop specific mammography screening recommendations for high-risk women.
The U.S. Preventive Services Task Force (USPSTF) revised their recommendations for mammography screening in 2009. Whereas they had formerly recommended routine screening every 1 to 2 years starting at age 40, they now recommend against routine screening for women aged 40 to 49 and biennial rather than annual screening for women aged 50 to 74. In their 2009 recommendations, the USPSTF recommend that women aged 40 to 49 consider their personal risk for developing breast cancer before deciding to participate in regular, biennial screening. The USPSTF concluded that the current evidence is insufficient to assess the additional benefits and harms of (i) screening mammography in women aged 75 years or older, (ii) clinical breast examination (CBE) beyond screening mammography in women aged 40 years or older, and (iii) either digital mammography or magnetic resonance imaging instead of film mammography as screening modalities for breast cancer. In addition, the USPSTF recommended against clinicians teaching women how to perform breast self-examination.
The American Medical Association (AMA), the Society of Breast Imaging (SBI), the American College of Radiology (ACR), and the American Cancer Society (ACS), all support screening with mammography and CBE beginning at age 40. Recent recommendations from the SBI and the ACR (2010) released after the 2009 USPSTF recommendations, which recommended that average-risk women wait until age 50 to undergo screening mammography, continue to support yearly screening mammography beginning at age 40 for women at average-risk for breast cancer. The American College of Obstetricians and Gynecologists (ACOG, 2000) supports screening with mammography beginning at age 40 and CBE beginning at age 19. The Canadian Task Force on Preventive Health Care (CTFPHC), the American Academy of Family Physicians (AAFP), and the American College of Preventive Medicine (ACPM) recommend beginning mammography for average-risk women at age 50. The AAFP and ACPM recommend that mammography in high-risk women begin at age 40, and AAFP recommends that all women aged 40 to 49 be counseled about the risks and benefits of mammography before making decisions about screening.
A 1997 Consensus Development Panel convened by the National Institutes of Health concluded that the evidence was insufficient to determine the benefits of mammography among women aged 40 to 49. This panel recommended that women aged 40 to 49 should be counseled about potential benefits and harms before making decisions about mammography. In 2001, the CTFPHC concluded there was insufficient evidence to recommend for or against mammography in women aged 40 to 49.
Organizations differ on their recommendations for the appropriate interval for mammography. Annual mammography is recommended by AMA, ACR, and ACS. Mammography every 1 to 2 years is recommended by AAFP, ACPM, and the CTFPHC. ACOG recommends mammography every 1 to 2 years for women aged 40 to 49 and annually for women aged 50 and older.
Berg et al (2008) compared the diagnostic yield, defined as the proportion of women with positive screen test results and positive reference standard, and performance of screening with ultrasound plus mammography versus mammography alone in women at elevated risk of breast cancer. A total of 2,809 women, with at least heterogeneously dense breast tissue in at least 1 quadrant, were recruited from 21 sites to undergo mammographic and physician-performed ultrasonographic examinations in randomized order by a radiologist masked to the other examination results. Reference standard was defined as a combination of pathology and 12-month follow-up and was available for 2,637 (96.8 %) of the 2,725 eligible participants. Main outcome measures included diagnostic yield, sensitivity, specificity, and diagnostic accuracy (assessed by the area under the receiver operating characteristic curve) of combined mammography plus ultrasound versus mammography alone and the positive predictive value of biopsy recommendations for mammography plus ultrasound versus mammography alone. A total of 40 participants (41 breasts) were diagnosed with cancer: 8 suspicious on both ultrasound and mammography, 12 on ultrasound alone, 12 on mammography alone, and 8 participants (9 breasts) on neither. The diagnostic yield for mammography was 7.6 per 1,000 women screened (20 of 2,637) and increased to 11.8 per 1,000 (31 of 2,637) for combined mammography plus ultrasound; the supplemental yield was 4.2 per 1,000 women screened (95 % confidence interval [CI]: 1.1 to 7.2 per 1,000; p = 0.003 that supplemental yield is 0). The diagnostic accuracy for mammography was 0.78 (95 % CI: 0.67 to 0.87) and increased to 0.91 (95 % CI: 0.84 to 0.96) for mammography plus ultrasound (p = 0.003 that difference is 0). Of 12 supplemental cancers detected by ultrasound alone, 11 (92 %) were invasive with a median size of 10 mm (range of 5 to 40 mm; mean [SE], 12.6 [3.0] mm) and 8 of the 9 lesions (89 %) reported had negative nodes. The positive predictive value of biopsy recommendation after full diagnostic workup was 19 of 84 for mammography (22.6 %; 95 % CI: 14.2 % to 33 %), 21 of 235 for ultrasound (8.9 %, 95 % CI: 5.6 % to 13.3 %), and 31 of 276 for combined mammography plus ultrasound (11.2 %; 95 % CI: 7.8 % to 15.6 %). The authors concluded that adding a single screening ultrasound to mammography will yield an additional 1.1 to 7.2 cancers per 1,000 high-risk women, but it will also substantially increase the number of false positives.
Although digital mammography has not shown greater accuracy than film mammography, it has become standard of care. The Food and Drug Administration (FDA)'s initial market approval of digital mammography technology was based, in part, on studies that demonstrated its effectiveness in patients referred for further testing after an initial suspicious mammogram (FDA, 2004). In that setting, the FDA found the accuracy of digital technology was similar to that of screen film. Studies are currently underway to evaluate the effectiveness of digital mammography in screening of the general population.
Hendrick and colleagues (2008) retrospectively compared the accuracy for cancer diagnosis of digital mammography with soft-copy interpretation with that of screen-film mammography for each digital equipment manufacturer, by using results of biopsy and follow-up as the reference standard. The American College of Radiology Imaging Network Digital Mammographic Imaging Screening Trial (DMIST) collected screening mammography studies performed by using both digital and screen-film mammography in 49,528 women (mean age of 54.6 years; range of 19 to 92 years). Digital mammography systems from 4 manufacturers (Fischer, Fuji, GE, and Hologic) were used. For each digital manufacturer, a cancer-enriched reader set of women screened with both digital and screen-film mammography in DMIST was constructed. Each reader set contained all cancer-containing studies known for each digital manufacturer at the time of reader set selection, together with a subset of negative and benign studies. For each reader set, 6 or 12 experienced radiologists attended 2 randomly ordered reading sessions 6 weeks apart. Each radiologist identified suspicious findings and rated suspicion of breast cancer in identified lesions by using a 7-point scale. Results were analyzed according to digital manufacturer by using areas under the receiver operating characteristic curve (AUCs), sensitivity, and specificity for soft-copy digital and screen-film mammography. Results for Hologic digital are not presented owing to the fact that few cancer cases were available. The implemented design provided 80 % power to detect average AUC differences of 0.09, 0.08, and 0.06 for Fischer, Fuji, and GE, respectively. No significant difference in AUC, sensitivity, or specificity was found between Fischer, Fuji, and GE soft-copy digital and screen-film mammography. Large reader variations occurred with each modality. The authors concluded that no statistically significant differences were found between soft-copy digital and screen-film mammography for Fischer, Fuji, and GE digital mammography equipment.
Pisano and associates (2008) retrospectively compared the accuracy of digital versus film mammography in population subgroups of the DMIST defined by combinations of age, menopausal status, and breast density, by using either biopsy results or follow-up information as the reference standard. For analysis, AUCs for each modality were compared within each subgroup evaluated (age less than 50 versus 50 to 64 versus greater than or equal to 65 years; dense versus non-dense breasts at mammography; and pre- or peri-menopausal versus post-menopausal status for the 2 younger age cohorts) while controlling for multiple comparisons (p < 0.002 indicated a significant difference). All DMIST cancers were evaluated with respect to mammographic detection method (digital versus film versus both versus neither), mammographic lesion type (mass, calcifications, or other), digital machine type, mammographic and pathologic size and diagnosis, existence of prior mammographic study at time of interpretation, months since prior mammographic study, and compressed breast thickness. A total of 33 centers enrolled 49,528 women. Breast cancer status was determined for 42,760 women, the group included in this study. Pre- or peri-menopausal women younger than 50 years who had dense breasts at film mammography comprised the only subgroup for which digital mammography was significantly better than film (AUCs, 0.79 versus 0.54; p = 0.0015). Breast Imaging Reporting and Data System-based sensitivity in this subgroup was 0.59 for digital and 0.27 for film mammography. AUCs were not significantly different in any of the other subgroups. For women aged 65 years or older with fatty breasts, the AUC showed a non-significant tendency toward film being better than digital mammography (AUCs, 0.88 versus 0.70; p = 0.0025). The authors concluded that digital mammography performed significantly better than film for pre- and peri-menopausal women younger than 50 years with dense breasts, but film tended non-significantly to perform better for women aged 65 years or older with fatty breasts.
Computer-aided detection and diagnosis (CAD) systems consist of computer programs that are designed to recognize patterns in images. CAD may be applied to digital mammograms or to plain film mammograms that have been digitized. CAD has been used for 2 different purposes: (i) to improve radiologists' ability to identify suspicious areas that may otherwise be overlooked on screening mammograms (detection), and (ii) to distinguish between benign and malignant lesions (diagnosis). The radiologist remains the reader and interpreter of the mammogram. CAD assists the radiologist by identifying areas warranting further review.
The American Cancer Society breast cancer screening guidelines (Smith et al, 2003) indicate that for digital mammography and CAD there is “some clinical evidence for effectiveness or equivalence to screen-film mammography for screening” (Evidence Level B).
Bennett et al (2006) assessed current evidence to ascertain if the accuracy of single reading with CAD compares with that of double reading. These researchers performed a literature review to identify studies where both protocols had been investigated and compared. They identified 8 studies that compared single reading with CAD against double reading, of which 6 reported on comparisons of both sensitivity and specificity. Of the 6 studies identified, 3 showed no differences in either sensitivity or specificity; 1 showed single reading with CAD had a higher sensitivity at the same specificity; 1 showed that single reading with CAD had a higher specificity at the same sensitivity. However, 1 study, in a real-life setting, showed that single reading with CAD had a higher sensitivity but a lower specificity. The authors concluded that as the majority of the studies were not in a real-life setting, used test sets, lacked sufficient training in the use of CAD and simulated double reading (using a protocol of recall if one suggests), current evidence is therefore limited as to the accuracy, in terms of sensitivity and specificity, of single reading with CAD in comparison with the most common practice in the United Kingdom of double reading using a protocol of consensus or arbitration.
Fenton and colleagues (2007) stated that CAD identifies suspicious findings on mammograms to assist radiologists. Since the FDA approved the technology in 1998, it has been disseminated into practice, but its effect on the accuracy of interpretation is unclear. These investigators determined the association between the use of CAD at mammography facilities and the performance of screening mammography from 1998 through 2002 at 43 facilities in 3 states. They had complete data for 222,135 women (a total of 429,345 mammograms), including 2,351 women who received a diagnosis of breast cancer within 1 year after screening. They calculated the specificity, sensitivity, and positive predictive value of screening mammography with and without CAD, as well as the rates of biopsy and breast-cancer detection and the overall accuracy, measured as the area under the receiver-operating-characteristic (ROC) curve. A total of 7 facilities (16 %) implemented CAD during the study period. Specificity decreased from 90.2 % before implementation to 87.2 % following implementation (p < 0.001), the positive predictive value decreased from 4.1 % to 3.2 % (p = 0.01), and the rate of biopsy increased by 19.7 % (p < 0.001). The increase in sensitivity from 80.4 % before implementation of CAD to 84.0 % after implementation was insignificant (p = 0.32). The change in the cancer-detection rate (including invasive breast cancers and ductal carcinomas in situ) was insignificant (4.15 cases per 1,000 screening mammograms before implementation and 4.20 cases after implementation, p = 0.90). Analyses of data from all 43 facilities showed that the use of CAD was associated with significantly lower overall accuracy than was non-use (area under the ROC curve, 0.871 versus 0.919; p = 0.005). The authors concluded that the use of CAD is associated with reduced accuracy of interpretation of screening mammograms. The increased rate of biopsy with the use of CAD is not clearly associated with improved detection of invasive breast cancer. This is in agreement with Bazzocchi et al (2007) who noted that there is still considerable variation among different studies in the level of benefit deriving from CAD. Thus, the role of these systems in clinical practice is still debated, and their real contribution to the overall management of the diagnostic process is still unclear.
An assessment of CAD in mammography screening by the Swedish Council on Health Technology Assessment (SBU, 2011) concluded that the scientific evidence is insufficient to determine whether CAD plus single reading by one breast radiologist would yield results that are at least equivalent to those obtained in standard practice, i.e. double reading where two breast radiologists independently read the x-ray images.
Screening film mammography has been shown to reduce the mortality rate from breast cancer; however, conventional mammography does not detect all breast cancers. A significant factor contributing to the limitations of mammography is the structure overlap that results on a 2-dimensional mammogram. Structure overlap not only obscures lesions, but can mimic abnormalities, thus contributing to reductions in both the sensitivity and specificity of mammography. A number of new imaging techniques and enhancements for digital mammography have recently become available or are likely to become available in the near future.
Breast tomosynthesis is a 3-dimensional imaging technique that involves acquiring 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 cine mode. While holding the breast stationary, images are acquired at a number of different x-ray source angles. Objects at different heights in the breast project differently for each angle. The data are then reconstructed to generate images that enhance objects from a given height by appropriate shifting of the projections relative to one another. Three important areas in tomosynthesis system requirements are: (i) detector efficiency and dose, (ii) field of view, and (iii) equipment geometry. While holding the breast stationary, an x-ray tube is rotated over a limited angular range and a series of low-dose exposures are made every few degrees, creating a series of digital images. The x-ray tube is rotated about +/-15 degrees, and 11 exposures are made every 3 degrees during a total scan of a few seconds. These individual images are then reconstructed into slices. There are 2 basic tomosynthesis system designs that 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 altenate method is to keep the detector stationary relative to the breast platform. The tomosynthesis reconstruction process consists of computing high-resolution images whose planes are parallel to the breast support plates. These images are reconstructed with slice separation of 1 mm; thus, a 5-cm compressed breast tomosynthesis study will have 50 reconstructed slices. The reconstructed tomosynthesis slices can be displayed similarly to computed tomography reconstructed slices. Proponents of breast tomosynthesis hope it will resolve many of the tissue overlap reading problems that are a major source of recalls and additional imaging in 2-D mammography examinations (Smith, 2005). Tomosynthesis is currently in clinical trials to evaluate its effectiveness. Initial pilot studies suggested that breast tomosynthesis has comparable or superior image quality to that of film-screen mammography and has the potential to decrease the recall rate when used adjunctively with digital screening mammography (Good et al, 2008; Chen et al, 2007; Poplack et al, 2007); however, further studies are needed to evaluate its effectiveness in clinical practice.
Helvie (2010) discussed recent developments in advanced derivative technologies associated with digital mammography. Digital breast tomosynthesis, its principles, development, and early clinical trials, were reviewed. Contrast-enhanced digital mammography and combined imaging systems with digital mammography and ultrasound were also discussed. Although all these methods are currently research programs, they hold promise for improving cancer detection and characterization if early results are confirmed by clinical trials.
Spangler and colleagues (2011) compared the ability of digital breast tomosynthesis and full field digital mammography (FFDM) to detect and characterize calcifications. A total of 100 paired examinations were performed utilizing FFDM and digital breast tomosynthesis: 20 biopsy-proven cancers, 40 biopsy-proven benign calcifications, and 40 randomly selected negative screening studies were retrospectively reviewed by 5 radiologists in a crossed multi-reader multi-modal observer performance study. Data collected included the presence of calcifications and forced Breast Imaging, Reporting and Data System (BI-RADS) scores. Receiver operator curve analysis using BI-RADS was performed. Overall calcification detection sensitivity was higher for FFDM (84 % [95 % CI: 79 % to 88 %]) than for digital breast tomosynthesis (75 % [95 % CI: 70 % to 80 %]). In the cancer cohort, 75 (76 %) of 99 interpretations identified calcification in both modes. Of those, a BI-RADS score less than or equal to 2 was rendered in 3 (4 %) and 9 (12 %) cases with FFDM and digital breast tomosynthesis, respectively. In the benign cohort, 123 (62 %) of 200 interpretations identified calcifications in both modes. Of those, a BI-RADS score greater than or equal to 3 was assigned in 105 (85 %) and 93 (76 %) cases with FFDM and digital breast tomosynthesis, respectively. There was no significant difference in the non-parametric computed AUC using the BI-RADS scores (FFDM, AUC = 0.76 and SD = 0.03; digital breast tomosynthesis, AUC = 0.72 and SD = 0.04 [p = 0.1277]). The authors concluded that in this small data set, FFDM appears to be slightly more sensitive than digital breast tomosynthesis for the detection of calcification. However, diagnostic performance as measured by AUC using BI-RADS was not significantly different. With improvements in processing algorithms and display, digital breast tomosynthesis could potentially be improved for this purpose.
On February 2011, the FDA approved the Selenia Dimensions 3D System (Digital Breast Tomosynthesis), a mammography device that provides digital 2D and 3D images for the screening and diagnosis of breast cancer.
Guidelines on breast cancer screening from the American College of Obstetricians and Gynecologists (ACOG, 2011) considered, but did not recommend, breast tomosynthesis. The guidelines concluded that "[c]olor Doppler ultrasonography, computer-aided detection, positron emission tomography, scintimammography, and digital breast tomosynthesis have shown promise in selected clinical situations or as adjuncts to mammography for breast cancer diagnosis. However, these technologies are not considered alternatives to routine mammography."
The ongoing TOMMY trial: (A comparison of TOMosynthesis with digital MammographY in the UK NHS Breast Screening Programme) will compare the accuracy of digital breast tomosynthesis (DBT) with standard digital full field mammography( FFDM) in the diagnosis of breast cancer. The aim of the trial is to assess whether DBT could improve upon digital mammography as a screening tool, particularly in certain groups of women, e.g. those with a family history of breast cancer, or women with dense breasts. The diagnostic accuracy of DBT, FFDM and DBT+FFDM will be evaluated in an independent retrospective reading study and compared to the final clinical outcome for each case.
Sahiner et al (2012) designed a computer-aided detection (CADe) system for clustered micro-calcifications in reconstructed DBT volumes and performed a preliminary evaluation of the CADe system. Institutional review board approval and informed consent were obtained in this study. A data set of 2-view DBT of 72 breasts containing micro-calcification clusters was collected from 72 subjects who were scheduled to undergo breast biopsy. Based on tissue sampling results, 17 cases had breast cancer and 55 were benign. A separate data set of 2-view DBT of 38 breasts free of clustered micro-calcifications from 38 subjects was collected to independently estimate the number of false-positives (FPs) generated by the CADe system. A radiologist experienced in breast imaging marked the biopsied cluster of micro-calcifications with a 3D bounding box using all available clinical and imaging information. A CADe system was designed to detect micro-calcification clusters in the reconstructed volume. The system consisted of pre-screening, clustering, and FP reduction stages. In the pre-screening stage, the conspicuity of micro-calcification-like objects was increased by an enhancement-modulated 3D calcification response function. An iterative thresholding and 3D object growing method was used to detect cluster seed objects, which were used as potential centers of micro-calcification clusters. In the cluster detection stage, micro-calcification candidates were identified using a 2nd iterative thresholding procedure, which was applied to the signal-to-noise ratio (SNR) enhanced image voxels with a positive calcification response. Starting with each cluster seed object as the initial cluster center, a dynamic clustering algorithm formed a cluster candidate by including micro-calcification candidates within a 3D neighborhood of the cluster seed object that satisfied the clustering criteria. The number, size, and SNR of the micro-calcifications in a cluster candidate and the cluster shape were used to reduce the number of FPs. The pre-screening stage detected a cluster seed object in 94 % of the biopsied micro-calcification clusters at a threshold of 100 cluster seed objects per DBT volume. After clustering, the detection sensitivity was 90 % at 15 marks per DBT volume. After FP reduction, at 85 % sensitivity, the average number of FPs estimated using the data set containing micro-calcification clusters was 3.8 per DBT volume, and that estimated using the data set free of micro-calcification clusters was 3.4. The detection performance for malignant micro-calcification clusters was superior to that for benign clusters. The authors concluded that these findings indicated the feasibility of the 3D approach to the detection of clustered micro-calcifications in DBT and that the newly designed enhancement-modulated 3D calcification response function is promising for pre-screening. They stated that further work is needed to assess the generalizability of this approach and to improve its performance.
Skaane and colleagues (2012) noted that DBT is a promising new technology. Some experimental clinical studies have shown positive results, but the future role and indications of this new technique, whether in a screening or clinical setting, need to be evaluated. These investigators compared DM and DBT in a side-by-side feature analysis for cancer conspicuity, and examined if there is a potential additional value of DBT to standard state-of-the-art conventional imaging work-up with respect to detection of additional malignancies. The study had ethics committee approval. A total of 129 women underwent 2D DM including supplementary cone-down and magnification views and breast ultrasonography if indicated, as well as DBT. The indication for conventional imaging in the clinical setting included a palpable lump in 30 (23 %), abnormal mammographic screening findings in 54 (42 %), and surveillance in 45 (35 %) of the women. The women were examined according to present guidelines, including spot-magnification views, ultrasonography, and needle biopsies, if indicated. The DBT examinations were interpreted several weeks after the conventional imaging without knowledge of the conventional imaging findings. In a later session, 3 radiologists performed a side-by-side feature analysis for cancer conspicuity in a sample of 50 cases. State-of-the-art conventional imaging resulted in needle biopsy of 45 breasts, of which 20 lesions were benign and a total of 25 cancers were diagnosed. The remaining 84 women were dismissed with a normal/definitely benign finding and without indication for needle biopsy. The subsequent DBT interpretation found suspicious findings in 4 of these 84 women, and these 4 women had to be called back for repeated work-up with knowledge of the tomosynthesis findings. These delayed work-ups resulted in 2 cancers (increasing the cancer detection by 8 %) and 2 FP findings. The side-by-side feature analysis showed higher conspicuity scores for tomosynthesis compared to conventional 2D for cancers presenting as spiculated masses and distortions. The authors concluded that DBT is a promising new technique. The authors’ preliminary clinical experience showed that there is a potential for increasing the sensitivity using this new technique, especially for cancers manifesting as spiculated masses and distortions.
Also, an UpToDate review on “Breast imaging: Mammography and ultrasonography” (Venkataraman, 2012) states that “Tomosynthesis is a modification of digital mammography and uses a moving x-ray source and digital detector. A three dimensional volume of data is acquired and reconstructed using computer algorithms to generate thin sections of images …. The examination has a slightly longer exposure time of 10 seconds per acquisition compared to standard digital mammography, which could increase the radiation dose per acquisition and increase the risk of motion artifacts. This technique shows promise in screening women with dense breast tissue and with high risk for breast cancer”.
Bernardi et al (2012a) stated that there is limited evidence on the role of 3D mammography with tomosynthesis in breast screening, although early studies suggested that it may improve specificity. These researchers prospectively evaluated the effect of integrating 3D mammography as a triage to assessment in 158 consecutive recalls to assessment (recalled in standard 2D-mammographic screening) in asymptomatic subjects. Radiologists provided 3D mammography-based opinion as to whether recall/assessment was warranted or unnecessary, and all subjects proceeded to assessment. 3D triage was positive (confirmed the need for assessment) in all 21 subjects with breast cancer (there were no false-negatives), and would have avoided recall in 102 of 137 (74.4 %) subjects with a negative/benign final outcome in whom 3D triage did not recommend recall. Proportion of true negative 3D triage (as a proxy for potential reduction in recalls) was slightly higher in dense than non-dense breasts, did not differ across age-groups, but was significantly associated with the type of lesion seen on imaging (being highest for distortions, asymmetric densities, and lesions with ill-defined margins). While the simulation design may have over-estimated the potential for 3D mammography triage to reduce recalls, this study clearly demonstrates its capability to improve breast screening specificity and to reduce recall rates. The authors stated that future studies of 3D mammography should further assess its role as a recall-reducing strategy in screening practice and should include formal cost-analysis.
Bernardi et al (2012b) supplemented the paucity of information available on logistical aspects of the application of 3D mammography in breast screening. These investigators prospectively examined the effect on radiographers' and radiologists' workload of implementing 3D mammography in screening by comparing image acquisition time and screen-reading time for 2D mammography with that of combined 2D+3D mammography. Radiologists' accuracy was also calculated. Average acquisition time (measured from start of first-view breast positioning to compression release at completion of last view) for 7 radiographers, based on 20 screening examinations, was longer for 2D+3D (4 min 3 s; range of 3 min 53 s to 4 min 18 s) than 2D mammography (3 min 13 s; range of 3 min 0 s to 3 min 26 s; p < 0.01). Average radiologists' reading time per screening examination (3 radiologists reading case-mix of 100 screens: 10 cancers, 90 controls) was longer for 2D+3D (77 s; range of 60 to 90 s) than for 2D mammography (33 s; range of 25 to 46 s; p < 0.01). 2D+3D screen-reading was associated with detection of more cancers and with substantially fewer recalls than 2D mammography alone. The authors concluded that relative to standard 2D mammography, combined 2D+3D mammography prolongs image acquisition time and screen-reading time (at initial implementation), and appears to be associated with improved screening accuracy. They stated that these findings provided relevant information to guide larger trials of integrated 3D mammography (2D+3D) and its potential implementation into screening practice.
Zhao et al (2012) noted that mammography is the primary imaging tool for screening and diagnosis of human breast cancers, but approximately 10 to 20 % of palpable tumors are not detectable on mammograms and only about 40 % of biopsied lesions are malignant. These researchers reported a high-resolution, low-dose phase contrast X-ray tomographic method for 3D diagnosis of human breast cancers. By combining phase contrast X-ray imaging with an image reconstruction method known as equally sloped tomography, these investigators imaged a human breast in 3D and identified a malignant cancer with a pixel size of 92 μm and a radiation dose less than that of dual-view mammography. According to a blind evaluation by 5 independent radiologists, this method can reduce the radiation dose and acquisition time by approximately 74 % relative to conventional phase contrast X-ray tomography, while maintaining high image resolution and image contrast. The authors concluded that these results demonstrated that high-resolution 3D diagnostic imaging of human breast cancers can, in principle, be performed at clinical compatible doses.
Houssami and Skaane (2013) stated that DBT, a 3D derivative of DM, reduces the effect of tissue superimposition and may improve mammographic interpretation. These investigators examined the evidence on the accuracy of DBT in clinical studies. Published studies of DBT were relatively small studies, mostly test-set observer (reader) studies or clinical series that included symptomatic and screen-recalled cases, and were generally enriched with cancers. With these limitations in mind, the evidence showed some consistent findings, summarized as follows: 2-view DBT has at least equal or better accuracy than standard 2-view DM, whereas 1-view DBT does not have better accuracy than standard DM; the addition of DBT to standard mammography (for mammographic interpretation or for assessment or triage of screen-recalled abnormalities) increases accuracy; improved accuracy from using DBT (relative to, or added to, DM) may be due to increased cancer detection or due to reduced false positive recalls, or both; and subjective interpretation of cancer conspicuity consistently found that cancers were equally or more conspicuous on DBT relative to DM. Preliminary data from population screening trials suggested that the integration of DBT with conventional DM (screen-reading using combined 2D + 3D mammography) may substantially improve breast cancer detection, although final results are not yet available, and many logistical issues need further evaluation to determine the potential implications and cost of combined 2D + 3D mammographic screening. At present, there is insufficient evidence to justify a change from standard DM to DBT however the available data strongly support investment in new large-scale population screening trials. These trials need to avoid the 'double' acquisitions required for 2D + 3D mammograms, and should therefore focus on evaluating integrated 2Dsynthetic + 3D mammography (where 2D-images are reconstructed from the DBT acquisition), and should consider using a randomized design.
Alakhras et al (2013) reviewed the major limitations in current mammography and described how these may be addressed by DBT. Digital breast tomosynthesis is a novel imaging technology in which an x-ray fan beam sweeps in an arc across the breast, producing tomographic images and enabling the production of volumetric, 3D data. It can reduce tissue overlap encountered in conventional 2D mammography, and thus has the potential to improve detection of breast cancer, reduce the suspicious presentations of normal tissues, and facilitate accurate differentiation of lesion types.
Also, an ACOG technology assessment on “Digital breast tomosynthesis” (2013) stated that this strategy of 2D plus 3D mammography would need to be compared to other potential strategies for comparative cost-effectiveness, such as the use of computer aided detection. Additional studies will be needed to confirm whether digital mammography with tomosynthesis is a cost-effective approach capable of replacing digital mammography alone as the first-line screening modality of choice for breast cancer screening. Furthermore, the ACOG technology assessment also noted the concern with the high-dose of radiation with breast tomosynthesis.
Poller et al (2012) stated that annual ultrasound screening may detect small, node-negative breast cancers that are not seen on mammography; and magnetic resonance imaging (MRI) may reveal additional breast cancers missed by both mammography and ultrasound screening. These researchers examined supplemental cancer detection yield of ultrasound and MRI in women at elevated risk for breast cancer. From April 2004 to February 2006, a total of 2,809 women at 21 sites with elevated cancer risk and dense breasts consented to 3 annual independent screens with mammography and ultrasound in randomized order. After 3 rounds of both screenings, 612 of 703 women who chose to undergo an MRI had complete data. The reference standard was defined as a combination of pathology (biopsy results that showed in-situ or infiltrating ductal carcinoma or infiltrating lobular carcinoma in the breast or axillary lymph nodes) and 12-month follow-up. Main outcome measures included cancer detection rate (yield), sensitivity, specificity, positive-predictive value (PPV3) of biopsies performed and interval cancer rate. A total of 2,662 women underwent 7,473 mammogram and ultrasound screenings, 110 of whom had 111 breast cancer events: 33 detected by mammography only, 32 by ultrasound only, 26 by both, and 9 by MRI after mammography plus ultrasound; 11 were not detected by any imaging screen. Among 4,814 incidence screens in the 2nd and 3rd years combined, 75 women were diagnosed with cancer. Supplemental incidence-screening ultrasound identified 3.7 cancers per 1,000 screens (95 % CI: 2.1 to 5.8; p < 0.001). Sensitivity for mammography plus ultrasound was 0.76 (95 % CI: 0.65 to 0.85); specificity, 0.84 (95 % CI: 0.83 to 0.85); and PPV3, 0.16 (95 % CI: 0.12 to 0.21). For mammography alone, sensitivity was 0.52 (95 % CI: 0.40 to 0.64); specificity, 0.91 (95 % CI: 0.90 to 0.92); and PPV3, 0.38 (95 % CI: 0.28 to 0.49; p < 0.001 all comparisons). Of the MRI participants, 16 women (2.6 %) had breast cancer diagnosed. The supplemental yield of MRI was 14.7 per 1,000 (95 % CI: 3.5 to 25.9; p = 0.004). Sensitivity for MRI and mammography plus ultrasound was 1.00 (95 % CI: 0.79 to 1.00); specificity, 0.65 (95 % CI: 0.61 to 0.69); and PPV3, 0.19 (95 % CI: 0.11 to 0.29). For mammography and ultrasound, sensitivity was 0.44 (95 % CI: 0.20 to 0.70, p = 0.004); specificity 0.84 (95 % CI: 0.81 to 0.87; p < 0.001); and PPV3, 0.18 (95 % CI: 0.08 to 0.34; p = 0.98). The number of screens needed to detect 1 cancer was 127 (95 % CI: 99 to 167) for mammography; 234 (95 % CI: 173 to 345) for supplemental ultrasound; and 68 (95 % CI: 39 to 286) for MRI after negative mammography and ultrasound results. The authors concluded that the addition of screening ultrasound or MRI to mammography in women at increased risk of breast cancer resulted in not only a higher cancer detection yield but also an increase in false-positive findings.
Currently, there are no recommendations to screen men at risk for hereditary breast cancer with mammography. Robson (2002) explained “There are no established guidelines for screening of men at risk for hereditary breast cancer. It is reasonable to suggest periodic self-examination and evaluation by a provider experienced in clinical breast examination. The utility of screening mammography in men is unknown, although it is technically possible in at least some individuals.” However, diagnostic mammography may be indicated in men with a breast mass on clinical examination (American Cancer Society, 2003).
Xeroradiography (Xerox Corporation, Stamford, CT) is an outmoded X-ray imaging method that had been used especially in mammographic screening for breast cancer. With Xeroradiography, X-rays pass through the body to an X-ray-sensitive metal plate. The plate is then processed through a unique photocopying-type machine, and the X-ray image transferred to paper rather than X-ray film. Unlike photographically recorded X-ray images, Xeroradiographs produce a “positive” image in which the denser elements appear darker. Unlike X-ray films, the Xeroradiographic image is a mirror image of the object. The primary advantage of Xeroradiography over conventional plain film mammography is that the former produces instant radiographs. However, Xeroradiography has become outmoded because the radiation exposure required is much higher than with conventional radiographs, and the Xeroradiographic image has a number of defects, such as excessive contrast and edge enhancement.
Fredenberg and colleagues (2010) noted that spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. The authors have investigated a photon-counting spectral imaging system with 2 energy bins for contrast-enhanced mammography. System optimization and the potential benefit compared to conventional non-energy-resolved absorption imaging were studied. A framework for system characterization was set up that included quantum and anatomical noise and a theoretical model of the system was benchmarked to phantom measurements. Optimal combination of the energy-resolved images corresponded approximately to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging in the phantom study. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, yielded only a minute improvement. In a simulation of a clinically more realistic case, spectral imaging was predicted to perform approximately 30 % better than absorption imaging for an average glandularity breast with an average level of anatomical noise. For dense breast tissue and a high level of anatomical noise, however, a rise in detectability by a factor of 6 was predicted. Another approximately 70 to 90 % improvement was found to be within reach for an optimized system. The authors concluded that contrast-enhanced spectral mammography is feasible and beneficial with the current system, and there is room for additional improvements. Inclusion of anatomical noise is essential for optimizing spectral imaging systems.
Schmitzberger et al (2011) demonstrated the feasibility of low-dose photon-counting tomosynthesis in combination with a contrast agent (contrast material-enhanced tomographic mammography) for the differentiation of breast cancer. All studies were approved by the institutional review board, and all patients provided written informed consent. A phantom model with wells of iodinated contrast material (3 mg of iodine per milliliter) 1, 2, 5, 10, and 15 mm in diameter was assessed. A total of 9 patients with malignant lesions and 1 with a high-risk lesion (atypical papilloma) were included (all women; mean age of 60.7 years). A multi-slit photon-counting tomosynthesis system was utilized (spectral imaging) to produce both low- and high-energy tomographic data (below and above the k edge of iodine, respectively) in a single scan, which allowed for dual-energy visualization of iodine. Images were obtained prior to contrast material administration and 120 and 480 seconds after contrast material administration. Four readers independently assessed the images along with conventional mammograms, ultrasonographic images, and magnetic resonance images. Glandular dose was estimated. Contrast agent was visible in the phantom model with simulated spherical tumor diameters as small as 5 mm. The average glandular dose was measured as 0.42 mGy per complete spectral imaging tomosynthesis scan of one breast. Because there were 3 time-points (prior to contrast medium administration and 120 and 480 seconds after contrast medium administration), this resulted in a total dose of 1.26 mGy for the whole procedure in the breast with the abnormality. Seven of 10 cases were categorized as Breast Imaging Reporting and Data System score of 4 or higher by all four readers when reviewing spectral images in combination with mammograms. One lesion near the chest wall was not captured on the spectral image because of a positioning problem. The authors concluded that the use of contrast-enhanced tomographic mammography has been demonstrated successfully in patients with promising diagnostic benefit. They stated that further studies are necessary to fully assess diagnostic sensitivity and specificity.
An American College of Obstetrician and Gynecologist technology assessment on “Digital breast tomosynthesis” (ACOG, 2013) noted that “Clinical data suggest that digital mammography with tomosynthesis produces a better image, improved accuracy, and lower recall rates compared with digital mammography alone. Further study will be necessary to confirm whether digital mammography with tomosynthesis is a cost-effective approach, capable of replacing digital mammography alone as the first-line screening modality of choice for breast cancer screening”.
An UpToDate review on “Breast imaging: Mammography and ultrasonography” (Venkataraman and Slanetz, 2014) states that “At present, tomosynthesis is approved only to be performed in conjunction with a conventional mammogram. Hence, when performed in the screening setting, the patient is exposed to approximately twice the usual radiation dose, which sometimes is greater if the patient had dense or thick breasts. This technique shows promise in screening women with dense breast tissue and with high risk for breast cancer, although there are no prospective large studies to justify its routine use at the present time”.
A BlueCross BlueShield Association TEC Assessment, “Use of digital breast tomosynthesis with mammography for breast cancer screening or diagnosis” (BCNSA, 2014), concluded that “Improved health outcomes following the addition of breast tomosynthesis to screening or diagnostic mammography [has] not been demonstrated in the investigational setting. Based on the above, the addition of digital breast tomosynthesis to screening or diagnostic mammography does not meet the TEC criteria”.
National Cancer Institute’s Factsheet on “Mammograms” (NCI, 2014) states that “Three-dimensional (3D) mammography, also known as breast tomosynthesis, is a type of digital mammography in which x-ray machines are used to take pictures of thin slices of the breast from different angles and computer software is used to reconstruct an image. This process is similar to how a computed tomography (CT) scanner produces images of structures inside of the body. 3D mammography uses very low dose x-rays, but, because it is generally performed at the same time as standard two-dimensional (2D) digital mammography, the radiation dose is slightly higher than that of standard mammography. The accuracy of 3D mammography has not been compared with that of 2D mammography in randomized studies. Therefore, researchers do not know whether 3D mammography is better or worse than standard mammography at avoiding false-positive results and identifying early cancers”.
NCCN guidelines on breast cancer screening (NCCN, 2014) conclude: "Early studies show promise for tomosynthesis mammography. Two large trials showing a combined use of digital mammography and tomosynthesis showed improved cancer detection and decreased call back rates; of note, this is double the dose of radiation and is a factor in recommending this modality. Definitive studies are still pending."
An assessment by the Standing Committee on Screening of the Screening Section of the Australian Department of Health and Ageing (2013) stated that: "Whilst there is some evidence that DBT is at least as sensitive and specific as DM, it is not clear whether the use of DBT in large populations outside of a research setting would deliver the same results or whether the additional cost is justified. The issue of radiation dose also needs to be considered in terms of safety for women being screened.'
Allec et al (2011) noted that the accumulation of injected contrast agents allows the image enhancement of lesions through the use of contrast-enhanced mammography. In this technique, the combination of 2 acquired images is used to create an enhanced image. There exist several methods to acquire the images to be combined, which include dual energy subtraction using a single detection layer that suffers from motion artifacts due to patient motion between image acquisition. To mitigate motion artifacts, a detector composed of 2 layers may be used to simultaneously acquire the low and high energy images. In this work, these researchers evaluated both of these methods using amorphous selenium as the detection material to find the system parameters (tube voltage, filtration, photoconductor thickness and relative intensity ratio) leading to the optimal performance. They then compared the performance of the 2 detectors under the variation of contrast agent concentration, tumor size and dose. The detectability was found to be most comparable at the lower end of the evaluated factors. The single-layer detector not only led to better contrast, due to its greater spectral separation capabilities, but also had lower quantum noise. The single-layer detector was found to have a greater detectability by a factor of 2.4 for a 2.5 mm radius tumor having a contrast agent concentration of 1.5 mg ml(-1) in a 4.5 cm thick 50 % glandular breast. The authors stated that the inclusion of motion artifacts in the comparison is part of ongoing research efforts.
Furthermore, an UpToDate review on "MRI of the breast and emerging technologies" (Slanetz, 2013) states that "Emerging Imaging Technology for Breasr Cancer Detection -- Recognition of the limitations of mammography, ultrasound, and breast MRI has led to investigation of other breast imaging techniques including contrast-enhanced dual energy digital mammography, high-field strength MRI, magnetic resonance spectroscopy, diffusion weighted imaging, breast specific gamma imaging, and positron emission mammography". Contrast enhanced spectral mammography is not mentioned in this review.
CPT Codes / HCPCS Codes / ICD-9 Codes
CPT codes covered if selection criteria are met:
Computer-aided detection (computer algorithm analysis of digital image data for lesion detection) with further review for interpretation, with or without digitization of film radiographic images; diagnostic mammography (List separately in addition to code for primary procedure)
screening mammography (List separately in addition to code for primary procedure)
Screening mammography, bilateral (2-view film study of each breast)
CPT codes not covered for indications listed in the CPB:
77061 - 77062
Digital breast tomosynthesis
Screening digital breast tomosynthesis, bilateral (List separately in addition to code for primary procedure)
HCPCS codes covered if selection criteria are met:
Screening mammography, producing direct digital image, bilateral, all views
Diagnostic mammography, producing direct 2D digital image, bilateral, all views
Diagnostic mammography, producing direct 2D digital image, unilateral, all views
HCPCS codes not covered for indications listed in the CPB:
Diagnostic digital breast tomosynthesis, unilateral or bilateral (List separately in addition to G0204 or G0206)
ICD-9 codes covered if selection criteria are met:
174.0 - 174.9
Malignant neoplasm of female breast
Secondary malignant neoplasm of breast
Benign neoplasm of breast
Carcinoma in situ of breast
Neoplasm of uncertain behavior of breast
610.0 - 611.9
Disorders of breast
Personal history of malignant neoplasm of breast
Family history of malignant neoplasm of breast
Screening mammogram for high-risk patient
Other screening mammogram
The above policy is based on the following references:
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