Skip to main content

Advertisement

Log in

The value of coronal view as a stand-alone assessment in women undergoing automated breast ultrasound

  • BREAST RADIOLOGY
  • Published:
La radiologia medica Aims and scope Submit manuscript

Abstract

Background

Aim of the study was to evaluate the value of automated breast ultrasound (AUS) in women with dense breast, in terms of reading times, diagnostic performance and interobserver agreement. The assessment of coronal images alone versus the complete multiplanar (MPR) views was evaluated.

Methods

Between August and October 2017, consecutive patients with dense breast that were referred to our Institute, for post-mammography ultrasound assessment, pre-operative assessment or follow-up of known benign lesions, were invited to undergo an additional study with AUS. Three radiologists, (5, 15 and 25 years of experience in breast imaging), reviewed the exams twice: first assessing reconstructed coronal images alone, second the complete MPR views. Reading times, diagnostic performance and interobserver agreement were assessed.

Results

One hundred eighty-eight women were included, for a total of 67 breast lesions, 25 (37%) malignant and 42 (63%) benign. Compared to MPR, coronal view was associated with: lower reading times, respectively, for the three readers: 83 ± 37, 84 ± 43 and 76 ± 30 versus 163 ± 109, 131 ± 57, 151 ± 42 s (p < 0.035); lower sensitivity: 44.8%, 62.1%, 55.2% versus 69.0% (p = 0.059), 65.5% (p = 0.063), 72.4% (p = 0.076), respectively; better specificity: 94.1%, 93.7%, 94.2% versus 89.5% (p = 0.093), 87.4% (p = 0.002), 91.6% (p = 0.383), respectively. Agreement between the most and the least experienced reader was fair to moderate for categorical variables and significant for continuous ones.

Conclusion

The coronal view allows significantly lower reading times, a valuable feature in the screening setting, but its diagnostic performance makes the complete multiplanar assessment mandatory.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Nelson HD (2009) Screening for breast cancer: an update for the U.S. preventive services task force. Ann Intern Med 151:727. https://doi.org/10.7326/0003-4819-151-10-200911170-00009

    Article  PubMed  PubMed Central  Google Scholar 

  2. Lauby-Secretan B, Scoccianti C, Loomis D et al (2015) Breast-cancer screening-viewpoint of the IARC working group. N Engl J Med 372:2353–2358. https://doi.org/10.1056/NEJMsr1504363

    Article  CAS  PubMed  Google Scholar 

  3. Harvey JA, Bovbjerg VE (2004) Quantitative assessment of mammographic breast density: relationship with breast cancer risk. Radiology 230:29–41

    Article  Google Scholar 

  4. Ciatto S, Visioli C, Paci E, Zappa M (2004) Breast density as a determinant of interval cancer at mammographic screening. Br J Cancer 90:393–396

    Article  CAS  Google Scholar 

  5. McCormack VA, Dos Santos SI (2006) Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomark Prev 15:1159–1169. https://doi.org/10.1158/1055-9965.EPI-06-0034

    Article  Google Scholar 

  6. Boyd NF, Guo H, Martin LJ et al (2007) Mammographic density and the risk and detection of breast cancer. N Engl J Med 356:227–236. https://doi.org/10.1056/NEJMoa062790

    Article  CAS  PubMed  Google Scholar 

  7. Tagliafico AS, Mariscotti G, Valdora F et al (2018) A prospective comparative trial of adjunct screening with tomosynthesis or ultrasound in women with mammography-negative dense breasts (ASTOUND-2). Eur J Cancer 104:39–46. https://doi.org/10.1016/j.ejca.2018.08.029

    Article  PubMed  Google Scholar 

  8. Berg WA, Zhang Z, Lehrer D et al (2012) Detection of breast cancer with addition of annual screening ultrasound or a single screening MRI to mammography in women with elevated breast cancer risk. JAMA J Am Med Assoc 307:1394–1404. https://doi.org/10.1001/jama.2012.388

    Article  CAS  Google Scholar 

  9. Wilczek B, Wilczek HE, Rasouliyan L, Leifland K (2016) Adding 3D automated breast ultrasound to mammography screening in women with heterogeneously and extremely dense breasts: report from a hospital-based, high-volume, single-center breast cancer screening program. Eur J Radiol 85:1554–1563. https://doi.org/10.1016/j.ejrad.2016.06.004

    Article  PubMed  Google Scholar 

  10. Brem RF, Tabár L, Duffy SW et al (2015) Assessing improvement in detection of breast cancer with three-dimensional automated breast US in women with dense breast tissue: the SomoInsight Study. Radiology 274:663–673. https://doi.org/10.1148/radiol.14132832

    Article  PubMed  Google Scholar 

  11. Dick DE, Elliott RD, Metz RL, Rojohn DS (1979) A new automated, high resolution ultrasound breast scanner. Ultrason Imaging 1:368–377. https://doi.org/10.1177/016173467900100407

    Article  CAS  PubMed  Google Scholar 

  12. Jackson VP, Kelly-Fry E, Rothschild PA et al (1986) Automated breast sonography using a 7.5-MHz PVDF transducer: preliminary clinical evaluation. Work in progress. Radiology 159:679–684. https://doi.org/10.1148/radiology.159.3.3517952

    Article  CAS  PubMed  Google Scholar 

  13. Rella R, Belli P, Giuliani M et al (2018) Automated breast ultrasonography (ABUS) in the screening and diagnostic setting: indications and practical use. Acad Radiol 25:1457–1470

    Article  Google Scholar 

  14. Golatta M, Baggs C, Schweitzer-Martin M et al (2015) Evaluation of an automated breast 3D-ultrasound system by comparing it with hand-held ultrasound (HHUS) and mammography. Arch Gynecol Obstet 291:889–895. https://doi.org/10.1007/s00404-014-3509-9

    Article  PubMed  Google Scholar 

  15. Chae EY, Cha JH, Kim HH, Shin HJ (2015) Comparison of lesion detection in the transverse and coronal views on automated breast sonography. J Ultrasound Med 34:125–135. https://doi.org/10.7863/ultra.34.1.125

    Article  PubMed  Google Scholar 

  16. Zanotel M, Bednarova I, Londero V et al (2018) Automated breast ultrasound: basic principles and emerging clinical applications. Radiol Med 123:1–2

    Article  Google Scholar 

  17. Park J, Chae EY, Cha JH et al (2018) Comparison of mammography, digital breast tomosynthesis, automated breast ultrasound, magnetic resonance imaging in evaluation of residual tumor after neoadjuvant chemotherapy. Eur J Radiol 108:261–268. https://doi.org/10.1016/j.ejrad.2018.09.032

    Article  PubMed  Google Scholar 

  18. Kelly KM, Dean J, Lee SJ, Comulada WS (2010) Breast cancer detection: radiologists’ performance using mammography with and without automated whole-breast ultrasound. Eur Radiol 20:2557–2564. https://doi.org/10.1007/s00330-010-1844-1

    Article  PubMed  PubMed Central  Google Scholar 

  19. Chang JM, Moon WK, Cho N et al (2011) Breast cancers initially detected by hand-held ultrasound: detection performance of radiologists using automated breast ultrasound data. Acta Radiol 52:8–14

    Article  Google Scholar 

  20. Wang HY, Jiang YX, Zhu QL et al (2012) Differentiation of benign and malignant breast lesions: a comparison between automatically generated breast volume scans and handheld ultrasound examinations. Eur J Radiol 81:3190–3200. https://doi.org/10.1016/j.ejrad.2012.01.034

    Article  PubMed  Google Scholar 

  21. Huppe AI, Inciardi MF, Redick M et al (2018) Automated breast ultrasound interpretation times: a reader performance study. Acad Radiol 25:1577–1581. https://doi.org/10.1016/j.acra.2018.03.010

    Article  PubMed  Google Scholar 

  22. Sickles EA, D’Orsi CJ (2013) ACR BI-RADS® follow-up and outcome monitoring. In: ACR BI-RADS® Atlas, Breast imaging reporting and data system, 5th ed. American College of Radiology, Reston

  23. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159. https://doi.org/10.2307/2529310

    Article  CAS  PubMed  Google Scholar 

  24. Sardanelli F, Aase HS, Álvarez M et al (2017) Position paper on screening for breast cancer by the European Society of Breast Imaging (EUSOBI) and 30 national breast radiology bodies from Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Israel, Lithuania, Moldova, The Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Spain, Sweden, Switzerland and Turkey. Eur Radiol 27:2737–2743. https://doi.org/10.1007/s00330-016-4612-z

    Article  PubMed  Google Scholar 

  25. Mussetto I, Gristina L, Schiaffino S et al (2020) Breast ultrasound: automated or hand-held? Exploring patients’ experience and preference. Eur Radiol Exp 4:12. https://doi.org/10.1186/s41747-019-0136-z

    Article  PubMed  PubMed Central  Google Scholar 

  26. Bernardi D, Ciatto S, Pellegrini M et al (2012) Application of breast tomosynthesis in screening: incremental effect on mammography acquisition and reading time. Br J Radiol. https://doi.org/10.1259/bjr/19385909

    Article  PubMed  PubMed Central  Google Scholar 

  27. Skaane P, Gullien R, Eben EB et al (2015) Interpretation of automated breast ultrasound (ABUS) with and without knowledge of mammography: a reader performance study. Acta Radiol 56:404–412. https://doi.org/10.1177/0284185114528835

    Article  PubMed  Google Scholar 

  28. Abdullah N, Mesurolle B, El-Khoury M, Kao E (2009) Breast imaging reporting and data system lexicon for US: interobserver agreement for assessment of breast masses. Radiology 252:665–672. https://doi.org/10.1148/radiol.2523080670

    Article  PubMed  Google Scholar 

  29. Zhang J, Lai XJ, Zhu QL et al (2012) Interobserver agreement for sonograms of breast lesions obtained by an automated breast volume scanner. Eur J Radiol 81:2179–2183. https://doi.org/10.1016/j.ejrad.2011.06.043

    Article  PubMed  Google Scholar 

  30. Maier A, Heil J, Lauer A et al (2017) Inter-rater reliability and double reading analysis of an automated three-dimensional breast ultrasound system: comparison of two independent examiners. Arch Gynecol Obstet 296:571–582. https://doi.org/10.1007/s00404-017-4473-y

    Article  PubMed  Google Scholar 

  31. Chen L, Chen Y, Diao XH et al (2013) Comparative study of automated breast 3-D ultrasound and handheld B-mode ultrasound for differentiation of benign and malignant breast masses. Ultrasound Med Biol 39:1735–1742. https://doi.org/10.1016/j.ultrasmedbio.2013.04.003

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Simone Schiaffino.

Ethics declarations

Conflict of interest

S. Schiaffino and M. Calabrese are on the speaker’s bureau for General Electric Healthcare (Paris, France).

Ethical approval

Local ethics committee approved this prospective study, and all subjects provided informed consent. The study is in accordance with the 1975 Declaration of Helsinki, revised in 2000.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schiaffino, S., Gristina, L., Tosto, S. et al. The value of coronal view as a stand-alone assessment in women undergoing automated breast ultrasound. Radiol med 126, 206–213 (2021). https://doi.org/10.1007/s11547-020-01250-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11547-020-01250-7

Keywords

Navigation