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VOLUME 56 , ISSUE 4 ( October-December, 2022 ) > List of Articles

RESEARCH ARTICLE

Breast Density Assessment with High-resolution Ultrasonography: A Reliability Study

Deeksha Bhalla, Tulika Singh, Veenu Singla, Shruti Kumar

Keywords : BI-RADS, Breast density, Breast neoplasms, Mammography, Mass screening, Ultrasonography

Citation Information : Bhalla D, Singh T, Singla V, Kumar S. Breast Density Assessment with High-resolution Ultrasonography: A Reliability Study. J Postgrad Med Edu Res 2022; 56 (4):160-164.

DOI: 10.5005/jp-journals-10028-1587

License: CC BY-NC 4.0

Published Online: 31-12-2022

Copyright Statement:  Copyright © 2022; The Author(s).


Abstract

Objective: To determine the accuracy of ultrasonic (US) assessment of breast density vs mammography, and its interobserver reliability. Methods: One hundred consecutive adult women were scanned using a high-frequency ultrasound transducer in the upper outer quadrant of a single breast. Breast density was recorded as one of four categories: < 25%, 25–50%, 50–75%, and > 75% by two radiologists. Digital mammography was performed on the same day and density was assigned to one of four breast imaging-reporting and data system (BI-RADS) categories by a third radiologist. Cohen's Kappa was used to compute inter-rater reliability for US assessment and intermodality agreement among mammographic and US density. Results: The most frequent mammographic density group was ACR B (43%). US density category B had the highest frequency of readings (49% and 51% readings of radiologists 1 and 2, respectively). Excellent interobserver agreement was seen for the measurements of US density; k = 0.968 [95% confidence interval (CI): 0.925–1]. Substantial intermodality agreement was seen for both radiologists 1 and 2; k = 0.675 (95% CI: 0.552–0.798) and 0.673 (95% CI: 0.551–0.796) respectively (p < 0.001). The US overestimated breast density in 14.5%, while underestimation was seen in 6.5% of cases. Conclusion: The US provides accurate and reproducible estimates of breast density. This enables personalized screening, particularly in young women and high-density breasts.


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  1. D’Orsi CJ, Sickles EA, Bassett LW et al. ACR BI-RADS® Atlas, Breast imaging reporting and data system. Rest VA Am Coll Radiol 2013;39–48.
  2. Peres J. Studies support risk-based mammography screening. J Natl Cancer Inst 2012;104(19):1428–1430. DOI: 10.1093/jnci/djs430
  3. Boyd NF. Mammographic density and risk of breast cancer. Am Soc Clin Oncol Educ Book 2013. DOI: 10.1200/EdBook_AM.2013.33.e57
  4. Nakajima E, Iwase T, Miyagi Y, et al. Association of parity and infant feeding method with breast density on mammography. Acad Radiol 2020;27(2):e24–e26. DOI: 10.1016/j.acra.2019.03.020
  5. Byrne C, Ursin G, Martin CF, et al. Mammographic density change with estrogen and progestin therapy and breast cancer risk. J Natl Cancer Inst 2017;109(9):djx001. DOI: 10.1093/jnci/djx001
  6. Ooms EA, Zonderland HM, Eijkemans MJ, et al. Mammography: interobserver variability in breast density assessment. Breast 2007;16(6):568–576. DOI: 10.1016/j.breast.2007.04.007
  7. Kaizer L, Fishell EK, Hunt JW, et al. Ultrasonographically defined parenchymal patterns of the breast: relationship to mammographic patterns and other risk factors for breast cancer. Br J Radiol 1988;61(722):118–124. DOI: 10.1259/0007-1285-61-722-118
  8. Blend R, Rideout DF, Kaizer L, et al. Parenchymal patterns of the breast defined by real time ultrasound. Eur J Cancer Prev 1995;4(4):293–298. DOI: 10.1097/00008469-199508000-00004
  9. Kim WH, Moon WK, Kim SJ, et al. Ultrasonographic assessment of breast density. Breast Cancer Res Treat 2013;138(3):851–859. DOI: 10.1007/s10549-013-2506-1
  10. Mandelblatt JS, Stout NK, Schechter CB, et al. Collaborative Modeling of the benefits and harms associated with different U.S. Breast cancer screening strategies. Ann Intern Med 2016;164(4):215–225. DOI: 10.7326/M15-1536
  11. Sharpe RE Jr, Levin DC, Parker L, et al. The effect of the controversial US Preventive Services Task Force Recommendations on the use of screening mammography. J Am Coll Radiol 2016;13(11S):e58–e61. DOI: 10.1016/j.jacr.2016.09.025
  12. Jørgensen KJ, Gøtzsche PC, Kalager M, et al. Breast Cancer Screening in Denmark: acohort study of tumor size and overdiagnosis. Ann Intern Med 2017;166(5):313–323. DOI: 10.7326/M16-0270
  13. Smetana GW, Elmore JG, Lee CI, et al. Should this woman with dense breasts receive supplemental breast cancer screening?: grand rounds discussion from Beth Israel Deaconess Medical Center. Ann Intern Med 2018;169(7):474–484. DOI: 10.7326/M18-1822
  14. Boyd N, Berman H, Zhu J, et al. The origins of breast cancer associated with mammographic density: a testable biological hypothesis. Breast Cancer Res 2018;20(1):17. DOI: 10.1186/s13058-018-0941-y
  15. Saulsberry L, Pace LE, Keating NL. The impact of breast density notification laws on supplemental breast imaging and breast biopsy. J Gen Intern Med 2019;34(8):1441–1451. DOI: 10.1007/s11606-019-05026-2
  16. Shawky MS, Martin H, Hugo HJ, et al. Mammographic density: a potential monitoring biomarker for adjuvant and preventative breast cancer endocrine therapies. Oncotarget 2017;8(3):5578–5591. DOI: 10.18632/oncotarget.13484
  17. Kim J, Han W, Moon HG, et al. Breast density change as a predictive surrogate for response to adjuvant endocrine therapy in hormone receptor positive breast cancer. Breast Cancer Res 2012;14(4):R102. DOI: 10.1186/bcr3221
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