Radiologists, as administrators and interpreters of screening mammography, are considered by some to be major contributors to the potential harms of screening, including overdiagnosis and overtreatment. In this article, we outline current efforts within the breast imaging community toward mitigating screening harms, including the widespread adoption of tomosynthesis and potentially adjusting screening frequency and thresholds for image-guided breast biopsy. However, the emerging field of breast radiomics may offer the greatest promise for reducing overdiagnosis by identifying imaging-based biomarkers strongly associated with tumor biology, and therefore helping prevent the harms of unnecessary treatment for indolent cancers.
Introduction
The recently revised breast cancer screening recommendations from the U.S. Preventive Services Task Force (USPSTF) and the American Cancer Society (ACS) have renewed the controversy around the potential benefits and harms of mammography among advocates and detractors of breast cancer screening . Although all authorities reiterate the mortality benefits of routine screening for the general population, they also now consider overdiagnosis and overtreatment among the potential harms of mammography. By definition, overdiagnosis is screen-detected cancer that would not have become clinically apparent during a patient’s lifetime . Although it is now fairly widely accepted in the medical community as a legitimate potential risk of screening, it is important to note that overdiagnosis is an event that cannot be directly observed.
Accordingly, precise measurement of overdiagnosis is a challenge that requires understanding not only the effects of screening but also knowledge of alternative causes of death among women prior to development of breast cancer symptoms . There is no consensus on the appropriate methods for estimating overdiagnosis in breast cancer. A recent systematic review and meta-analysis of the medical literature on the harms of mammography screening that accompanied the 2016 USPSTF recommendations found that methodologies used in overdiagnosis studies are highly variable, with approaches adjusting for lead time falling in the lower range of estimates . Regardless of the true magnitude, both the USPSTF and ACS now acknowledge overdiagnosis from mammography screening and the eventual downstream diagnostic and treatment cascades that follow the detection of indolent cancers as potential harms that should be communicated to patients during shared decision-making .
Although some have previously pointed to the breast imaging community as a major contributor to the problem of overdiagnosis , detection of a malignancy at screening would have limited impact on a patient’s health without subsequent intervention and treatment, sometimes referred to as overtreatment. Nevertheless, abnormal screening does launch a series of events as part of an integrated care pathway, where multiple disciplines contribute to diagnosis and treatment planning. After identifying abnormalities at screening and image-guided biopsy, pathologists assist in diagnosing breast malignancy. After the diagnosis of malignancy is made, including ductal carcinoma in situ (DCIS), treatment decisions are determined by a group of subspecialists, including surgeons, oncologists, and radiation oncologists.
As first-line physicians in a cascade of medical care that is well intentioned, many breast imagers aim to balance the known benefits with the potential harms when making a decision to recall patients from screening. The most effective approach by which breast imagers can mitigate overdiagnosis is, perhaps, the most exciting aspect of this controversial issue. Eliminating screening mammography is not a realistic or ethical option as it would lead to later stage breast cancer diagnoses and increased mortality, even in this era of improved therapies .
As members of multidisciplinary breast care teams with imaging expertise, it is imperative that radiologists engage in this issue by examining how current or emerging advanced breast imaging technologies can lessen the potential harms of overdiagnosis. In this article, we highlight recent advances and areas that warrant further investigation, with the hopes that breast imagers will take an active and leading role in a collaborative effort to decrease breast cancer overdiagnosis and overtreatment.
Adjusting Imaging Frequency and Thresholds
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New Image-based Screening Technologies
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The Potential of Radiomics
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Imaging Biomarkers for Malignancy Progression
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Shifting Treatment Paradigms Based on Imaging Features
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Conclusion
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Acknowledgments
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References
1. Siu A.L., U.S. Preventive Services Task Force: Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 2016; 164: pp. 279-296.
2. Oeffinger K.C., Fontham E.T., Etzioni R., et. al.: Breast cancer screening for women at average risk: 2015 guideline update from the American Cancer Society. JAMA 2015; 314: pp. 1599-1614.
3. Puliti D., Duffy S.W., Miccinesi G., et. al.: Overdiagnosis in mammographic screening for breast cancer in Europe: a literature review. J Med Screen 2012; 19: pp. 42-56.
4. Nelson H.D., Pappas M., Cantor A., et. al.: Harms of breast cancer screening: systematic review to update the 2009 U.S. Preventive Services Task Force recommendation. Ann Intern Med 2016; 164: pp. 256-267.
5. Welch H.G.: Responding to the challenge of overdiagnosis. Acad Radiol 2015; 22: pp. 945-946.
6. Birnbaum J., Gadi V.K., Markowitz E., et. al.: The effect of treatment advances on the mortality results of breast cancer screening trials: a microsimulation model. Ann Intern Med 2016; 164: pp. 236-243.
7. Jha S.: Can advanced imaging reduce overdiagnosis and overtreatment?. Acad Radiol 2015; 22: pp. 1007-1009.
8. Wells C.J., O’Donoghue C., Ojeda-Fournier H., et. al.: Evolving paradigm for imaging, diagnosis, and management of DCIS. J Am Coll Radiol 2013; 10: pp. 918-923.
9. Kim S.Y., Kim H.Y., Kim E.K., et. al.: Evaluation of malignancy risk stratification of microcalcifications detected on mammography: a study based on the 5th edition of BI-RADS. Ann Surg Oncol 2015; 22: pp. 2895-2901.
10. van Ravesteyn N.T., Stout N.K., Schechter C.B., et. al.: Benefits and harms of mammography screening after age 74 years: model estimates of overdiagnosis. J Natl Cancer Inst 2015; 107:
11. Houssami N.: Digital breast tomosynthesis (3D-mammography) screening: data and implications for population screening. Expert Rev Med Devices 2015; 12: pp. 377-379.
12. Friedewald S.M., Rafferty E.A., Rose S.L., et. al.: Breast cancer screening using tomosynthesis in combination with digital mammography. JAMA 2014; 311: pp. 2499-2507.
13. Esserman L.J., Thompson I.M., Reid B.: Overdiagnosis and overtreatment in cancer: an opportunity for improvement. JAMA 2013; 310: pp. 797-798.
14. Welch H.G., Black W.C.: Overdiagnosis in cancer. J Natl Cancer Inst 2010; 102: pp. 605-613.
15. Allegra C.J., Aberle D.R., Ganschow P., et. al.: NIH state-of-the-science conference statement: diagnosis and management of ductal carcinoma in situ (DCIS). NIH Consens State Sci Statements 2009; 26: pp. 1-27.
16. Marmot M.G., Altman D.G., Cameron D.A., et. al.: The benefits and harms of breast cancer screening: an independent review. Br J Cancer 2013; 108: pp. 2205-2240.
17. McDonald E.S., Oustimov A., Weinstein S.P., et. al.: Effectiveness of digital breast tomosynthesis compared with digital mammography: outcomes analysis from 3 years of breast cancer screening. JAMA Oncol 2016; Epub ahead of print
18. Berg W.A., Blume J.D., Cormack J.B., et. al.: Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer. JAMA 2008; 299: pp. 2151-2163.
19. Sprague B.L., Stout N.K., Schechter C., et. al.: Benefits, harms, and cost-effectiveness of supplemental ultrasonography screening for women with dense breasts. Ann Intern Med 2015; 162: pp. 157-166.
20. Kuhl C.K., Schrading S., Strobel K., et. al.: Abbreviated breast magnetic resonance imaging (MRI): first postcontrast subtracted images and maximum-intensity projection – a novel approach to breast cancer screening with MRI. J Clin Oncol 2014; 32: pp. 2304-2310.
21. Kumar V., Gu Y., Basu S., et. al.: Radiomics: the process and the challenges. Magn Reson Imaging 2012; 30: pp. 1234-1248.
22. Morris E., Feig S.A., Drexler M., et. al.: Implications of overdiagnosis: impact on screening mammography practices. Popul Health Manag 2015; 18: pp. S3-S11.
23. Allegra C.J., Aberle D.R., Ganschow P., et. al.: National Institutes of Health state-of-the-science conference statement: diagnosis and management of ductal carcinoma in situ September 22–24, 2009. J Natl Cancer Inst 2010; 102: pp. 161-169.
24. Masood S., Rosa M.: Borderline breast lesions: diagnostic challenges and clinical implications. Adv Anat Pathol 2011; 18: pp. 190-198.
25. Masood S.: Why the term “low-grade ductal carcinoma in situ” should be changed to “borderline breast disease”: diagnostic and clinical implications. Womens Health (Lond Engl) 2012; 8: pp. 57-62.
26. Masood S.: Raising the bar: a plea for standardization and quality improvement in the practice of breast pathology. Breast J 2006; 12: pp. 409-412.
27. Narod S.A., Iqbal J., Giannakeas V., et. al.: Breast cancer mortality after a diagnosis of ductal carcinoma in situ. JAMA Oncol 2015; 1: pp. 888-896.
28. Rosai J.: Borderline epithelial lesions of the breast. Am J Surg Pathol 1991; 15: pp. 209-221.
29. Staradub V.L., Messenger K.A., Hao N., et. al.: Changes in breast cancer therapy because of pathology second opinions. Ann Surg Oncol 2002; 9: pp. 982-987.
30. Elmore J.G., Longton G.M., Carney P.A., et. al.: Diagnostic concordance among pathologists interpreting breast biopsy specimens. JAMA 2015; 313: pp. 1122-1132.
31. National Comprehensive Cancer Network : NCCN clinical practice guidelines in oncology: breast cancer2011. Available at http://www.nccn.org/professionals/physician_gls/PDF/breast.pdf Accessed December 28, 2015
32. Sanders M.E., Schuyler P.A., Dupont W.D., et. al.: The natural history of low-grade ductal carcinoma in situ of the breast in women treated by biopsy only revealed over 30 years of long-term follow-up. Cancer 2005; 103: pp. 2481-2484.
33. Kerlikowske K., Molinaro A., Cha I., et. al.: Characteristics associated with recurrence among women with ductal carcinoma in situ treated by lumpectomy. J Natl Cancer Inst 2003; 95: pp. 1692-1702.
34. Leonard G.D., Swain S.M.: Ductal carcinoma in situ, complexities and challenges. J Natl Cancer Inst 2004; 96: pp. 906-920.
35. Cowell C.F., Weigelt B., Sakr R.A., et. al.: Progression from ductal carcinoma in situ to invasive breast cancer: revisited. Mol Oncol 2013; 7: pp. 859-869.
36. Allen M.D., Marshall J.F., Jones J.L.: alphavbeta6 Expression in myoepithelial cells: a novel marker for predicting DCIS progression with therapeutic potential. Cancer Res 2014; 74: pp. 5942-5947.
37. Unsworth A., Anderson R., Britt K.: Stromal fibroblasts and the immune microenvironment: partners in mammary gland biology and pathology?. J Mammary Gland Biol Neoplasia 2014; 19: pp. 169-182.
38. Kelley L., Silverstein M., Guerra L.: Analyzing the risk of recurrence after mastectomy for DCIS: a new use for the USC/Van Nuys Prognostic Index. Ann Surg Oncol 2011; 18: pp. 459-462.
39. MacAusland S.G., Hepel J.T., Chong F.K., et. al.: An attempt to independently verify the utility of the Van Nuys Prognostic Index for ductal carcinoma in situ. Cancer 2007; 110: pp. 2648-2653.
40. Rudloff U., Jacks L.M., Goldberg J.I., et. al.: Nomogram for predicting the risk of local recurrence after breast-conserving surgery for ductal carcinoma in situ. J Clin Oncol 2010; 28: pp. 3762-3769.
41. Yi M., Meric-Bernstam F., Kuerer H.M., et. al.: Evaluation of a breast cancer nomogram for predicting risk of ipsilateral breast tumor recurrences in patients with ductal carcinoma in situ after local excision. J Clin Oncol 2012; 30: pp. 600-607.
42. Kerlikowske K., Molinaro A.M., Gauthier M.L., et. al.: Biomarker expression and risk of subsequent tumors after initial ductal carcinoma in situ diagnosis. J Natl Cancer Inst 2010; 102: pp. 627-637.
43. Solin L.J., Gray R., Baehner F.L., et. al.: A multigene expression assay to predict local recurrence risk for ductal carcinoma in situ of the breast. J Natl Cancer Inst 2013; 105: pp. 701-710.
44. Schnitt S.J., Connolly J.L., Tavassoli F.A., et. al.: Interobserver reproducibility in the diagnosis of ductal proliferative breast lesions using standardized criteria. Am J Surg Pathol 1992; 16: pp. 1133-1143.
45. Miller N.A., Chapman J.A., Fish E.B., et. al.: In situ duct carcinoma of the breast: clinical and histopathologic factors and association with recurrent carcinoma. Breast J 2001; 7: pp. 292-302.
46. Virnig B.A., Tuttle T.M., Shamliyan T., et. al.: Ductal carcinoma in situ of the breast: a systematic review of incidence, treatment, and outcomes. J Natl Cancer Inst 2010; 102: pp. 170-178.
47. Jacobs M.A.: Multiparametric magnetic resonance imaging of breast cancer. J Am Coll Radiol 2009; 6: pp. 523-526.
48. Partridge S.C., McDonald E.S.: Diffusion weighted magnetic resonance imaging of the breast: protocol optimization, interpretation, and clinical applications. Magn Reson Imaging Clin N Am 2013; 21: pp. 601-624.
49. Le Bihan D., Breton E., Lallemand D., et. al.: MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986; 161: pp. 401-407.
50. Kuhl C.K., Schrading S., Bieling H.B., et. al.: MRI for diagnosis of pure ductal carcinoma in situ: a prospective observational study. Lancet 2007; 370: pp. 485-492.
51. Strobel K., Schrading S., Hansen N.L., et. al.: Assessment of BI-RADS category 4 lesions detected with screening mammography and screening US: utility of MR imaging. Radiology 2015; 274: pp. 343-351.
52. Rahbar H., Partridge S.C., Demartini W.B., et. al.: In vivo assessment of ductal carcinoma in situ grade: a model incorporating dynamic contrast-enhanced and diffusion-weighted breast MR imaging parameters. Radiology 2012; 263: pp. 374-382.
53. Jansen S.A., Fan X., Medved M., et. al.: Characterizing early contrast uptake of ductal carcinoma in situ with high temporal resolution dynamic contrast-enhanced MRI of the breast: a pilot study. Phys Med Biol 2010; 55: pp. N473-N485.
54. Li L., Wang K., Sun X., et. al.: Parameters of dynamic contrast-enhanced MRI as imaging markers for angiogenesis and proliferation in human breast cancer. Med Sci Monit 2015; 21: pp. 376-382.
55. Rahbar H., Parsian S., Lam D.L., et. al.: Can MRI biomarkers at 3 T identify low-risk ductal carcinoma in situ?. Clin Imaging 2016; 40: pp. 125-129.
56. Kim S.A., Cho N., Ryu E.B., et. al.: Background parenchymal signal enhancement ratio at preoperative MR imaging: association with subsequent local recurrence in patients with ductal carcinoma in situ after breast conservation surgery. Radiology 2014; 270: pp. 699-707.
57. Ashraf A.B., Daye D., Gavenonis S., et. al.: Identification of intrinsic imaging phenotypes for breast cancer tumors: preliminary associations with gene expression profiles. Radiology 2014; 272: pp. 374-384.
58. Mahrooghy M., Ashraf A.B., Daye D., et. al.: Pharmacokinetic tumor heterogeneity as a prognostic biomarker for classifying breast cancer recurrence risk. IEEE Trans Biomed Eng 2015; 62: pp. 1585-1594.
59. Sutton E.J., Oh J.H., Dashevsky B.Z., et. al.: Breast cancer subtype intertumor heterogeneity: MRI-based features predict results of a genomic assay. J Magn Reson Imaging 2015; 42: pp. 1398-1406.