Breast Cancer Research and Treatment

, Volume 163, Issue 3, pp 605–613 | Cite as

Is breast compression associated with breast cancer detection and other early performance measures in a population-based breast cancer screening program?

  • Nataliia Moshina
  • Sofie Sebuødegård
  • Solveig HofvindEmail author



We aimed to investigate early performance measures in a population-based breast cancer screening program stratified by compression force and pressure at the time of mammographic screening examination. Early performance measures included recall rate, rates of screen-detected and interval breast cancers, positive predictive value of recall (PPV), sensitivity, specificity, and histopathologic characteristics of screen-detected and interval breast cancers.


Information on 261,641 mammographic examinations from 93,444 subsequently screened women was used for analyses. The study period was 2007–2015. Compression force and pressure were categorized using tertiles as low, medium, or high. χ 2 test, t tests, and test for trend were used to examine differences between early performance measures across categories of compression force and pressure. We applied generalized estimating equations to identify the odds ratios (OR) of screen-detected or interval breast cancer associated with compression force and pressure, adjusting for fibroglandular and/or breast volume and age.


The recall rate decreased, while PPV and specificity increased with increasing compression force (p for trend <0.05 for all). The recall rate increased, while rate of screen-detected cancer, PPV, sensitivity, and specificity decreased with increasing compression pressure (p for trend <0.05 for all). High compression pressure was associated with higher odds of interval breast cancer compared with low compression pressure (1.89; 95% CI 1.43–2.48).


High compression force and low compression pressure were associated with more favorable early performance measures in the screening program.


Mammography Breast cancer screening Early performance measures Breast compression 



We would like to thank Hilde Trå Hervig and Grethe Johansen, radiographers at the breast diagnostic center of Stavanger University Hospital, and Berit Hanestad, radiographer at the breast diagnostic center of Haukeland University Hospital, for help and support in collecting and processing the density data used in this study. We would also like to thank Kaitlyn Tsuruda, consultant at the Cancer Registry of Norway, for assistance with statistical analysis and epidemiologic insight in the study.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10549_2017_4214_MOESM1_ESM.doc (94 kb)
Online Appendix 1 (DOC 94 kb)
10549_2017_4214_MOESM2_ESM.doc (94 kb)
Online Appendix 2 (DOC 95 kb)
10549_2017_4214_MOESM3_ESM.doc (120 kb)
Online Appendix 3 (DOC 120 kb)


  1. 1.
    Perry N, Broeders M, de Wolf C, Tornberg S, Holland R, von Karsa L (2006) European guidelines for quality assurance in breast cancer screening and diagnosis, 4th edn. European Communities, LuxemburgGoogle Scholar
  2. 2.
    DeSantis CE, Bray F, Ferlay J, Lortet-Tieulent J, Anderson BO, Jemal A (2015) International variation in female breast cancer incidence and mortality rates. Cancer Epidemiol Biomarkers Prev 24:1495–1506. doi: 10.1158/1055-9965.epi-15-0535 CrossRefPubMedGoogle Scholar
  3. 3.
    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. doi: 10.1056/NEJMsr1504363 CrossRefPubMedGoogle Scholar
  4. 4.
    Kopans DB (2006) Mammography and the normal breast imaging. Lippincott Williams & Wilkins, London, pp 357–363Google Scholar
  5. 5.
    Yaffe MJ (2010) Basic physics of digital mammography. In: Bick U, Diekmann F (eds) Digital mammography. Springer, Berlin, pp 1–11CrossRefGoogle Scholar
  6. 6.
    Poulos A, Rickard M (1997) Compression in mammography and the perception of discomfort. Australas Radiol 41:247–252CrossRefPubMedGoogle Scholar
  7. 7.
    Miller D, Martin I, Herbison P (2002) Interventions for relieving the pain and discomfort of screening mammography. Cochrane Database Syst Rev. doi: 10.1002/14651858.cd002942 Google Scholar
  8. 8.
    Dibble SL, Israel J, Nussey B, Sayre JW, Brenner RJ, Sickles EA (2005) Mammography with breast cushions. Womens Health Issues 15:55–63. doi: 10.1016/j.whi.2004.12.001 CrossRefPubMedGoogle Scholar
  9. 9.
    Whelehan P, Evans A, Wells M, Macgillivray S (2013) The effect of mammography pain on repeat participation in breast cancer screening: a systematic review. Breast 22:389–394. doi: 10.1016/j.breast.2013.03.003 CrossRefPubMedGoogle Scholar
  10. 10.
    Saunders RS Jr, Samei E (2008) The effect of breast compression on mass conspicuity in digital mammography. Med Phys 35:4464–4473. doi: 10.1118/1.2977600 CrossRefPubMedGoogle Scholar
  11. 11.
    de Groot JE, Broeders MJ, Branderhorst W, den Heeten GJ, Grimbergen CA (2013) A novel approach to mammographic breast compression: improved standardization and reduced discomfort by controlling pressure instead of force. Med Phys 40:081901. doi: 10.1118/1.4812418 CrossRefPubMedGoogle Scholar
  12. 12.
    Branderhorst W, de Groot JE, Highnam R et al (2015) Mammographic compression–a need for mechanical standardization. Eur J Radiol 84:596–602. doi: 10.1016/j.ejrad.2014.12.012 CrossRefPubMedGoogle Scholar
  13. 13.
    de Groot JE, Branderhorst W, Grimbergen CA, den Heeten GJ, Broeders MJ (2015) Towards personalized compression in mammography: a comparison study between pressure- and force-standardization. Eur J Radiol 84:384–391. doi: 10.1016/j.ejrad.2014.12.005 CrossRefPubMedGoogle Scholar
  14. 14.
    Holland K, Sechopoulos I, den Heeten G, Mann RM, Karssemeijer N (2016) Performance of Breast Cancer Screening Depends on Mammographic Compression. In: Tingberg A, Lång K, Timberg P (eds) Breast imaging: 13th international workshop, IWDM 2016, Malmö, Sweden, June 19–22, 2016, proceedings. Springer, Cham, pp 183–189Google Scholar
  15. 15.
    Larsen IK, Smastuen M, Johannesen TB et al (2009) Data quality at the Cancer Registry of Norway: an overview of comparability, completeness, validity and timeliness. Eur J Cancer 45:1218–1231. doi: 10.1016/j.ejca.2008.10.037 CrossRefPubMedGoogle Scholar
  16. 16.
    Hofvind S, Geller B, Vacek PM, Thoresen S, Skaane P (2007) Using the European guidelines to evaluate the Norwegian Breast Cancer Screening Program. Eur J Epidemiol 22:447–455. doi: 10.1007/s10654-007-9137-y CrossRefPubMedGoogle Scholar
  17. 17.
    Matakina Technology Limited (2015) Volpara solutions—Volpara density. Accessed 1 Oct 2015
  18. 18.
    Elston CW, Ellis IO (1991) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 19:403–410CrossRefPubMedGoogle Scholar
  19. 19.
    Zeger SL, Liang KY (1992) An overview of methods for the analysis of longitudinal data. Stat Med 11:1825–1839CrossRefPubMedGoogle Scholar
  20. 20.
    Homish GG, Edwards EP, Eiden RD, Leonard KE (2010) Analyzing family data: a GEE approach for substance use researchers. Addict Behav 35:558–563. doi: 10.1016/j.addbeh.2010.01.002 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Helvie MA, Chan HP, Adler DD, Boyd PG (1994) Breast thickness in routine mammograms: effect on image quality and radiation dose. Am J Roentgenol 163:1371–1374CrossRefGoogle Scholar
  22. 22.
    Poulos A, McLean D, Rickard M, Heard R (2003) Breast compression in mammography: how much is enough? Australas Radiol 47:121–126CrossRefPubMedGoogle Scholar
  23. 23.
    Stuedal A, Ma H, Bernstein L, Pike MC, Ursin G (2008) Does breast size modify the association between mammographic density and breast cancer risk? Cancer Epidemiol Biomarkers Prev 17:621–627. doi: 10.1158/1055-9965.epi-07-2554 CrossRefPubMedGoogle Scholar
  24. 24.
    Carp SA, Selb J, Fang Q et al (2008) Dynamic functional and mechanical response of breast tissue to compression. Opt Express 16:16064–16078CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Dustler M, Andersson I, Brorson H et al (2012) Breast compression in mammography: pressure distribution patterns. Acta Radiol 53:973–980. doi: 10.1258/ar.2012.120238 CrossRefPubMedGoogle Scholar
  26. 26.
    Romsdahl MM, McGrath RG, Hoppe E, McGrew EA (1965) Experimental model for the study of tumor cells in the blood. Acta Cytol 9:141–145PubMedGoogle Scholar
  27. 27.
    Watmough DJ, Quan KM, Aspden RM, Mallard JR (1992) Study of tissue compression in breast phantoms: possible implications for the use of X-ray mammography as a method of imaging breast carcinoma. Eur J Surg Oncol 18:538–544PubMedGoogle Scholar
  28. 28.
    Watmough DJ, Quan KM, Aspden RM (1992) Unfavorable outcome of recent breast cancer screening trials: why? AJR Am J Roentgenol 159:1125–1126CrossRefPubMedGoogle Scholar
  29. 29.
    Watmough DJ, Quan KM, Aspden RM (1993) Breast compression: a preliminary study. J Biomed Eng 15:121–126CrossRefPubMedGoogle Scholar
  30. 30.
    Fornvik D, Andersson I, Dustler M et al (2013) No evidence for shedding of circulating tumor cells to the peripheral venous blood as a result of mammographic breast compression. Breast Cancer Res Treat 141:187–195. doi: 10.1007/s10549-013-2674-z CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Mercer CE, Hogg P, Lawson R, Diffey J, Denton ER (2013) Practitioner compression force variability in mammography: a preliminary study. Br J Radiol 86:20110596. doi: 10.1259/bjr.20110596 CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Waade GG, Moshina N, Saebuodegard S, Hogg P, Hofvind S (2017) Compression forces used in the Norwegian Breast Cancer Screening Program. Br J Radiol. doi: 10.1259/bjr.20160770 PubMedGoogle Scholar
  33. 33.
    Eklund GW, Cardenosa G, Parsons W (1994) Assessing adequacy of mammographic image quality. Radiology 190:297–307CrossRefPubMedGoogle Scholar
  34. 34.
    Eklund GW (2000) The art of mammographic positioning. In: Friedrich M, Sickles EA (eds) Radiological diagnosis of breast diseases. Springer, Berlin, pp 75–88. doi: 10.1007/978-3-642-60919-0_6 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Nataliia Moshina
    • 1
  • Sofie Sebuødegård
    • 1
  • Solveig Hofvind
    • 1
    • 2
    Email author
  1. 1.Cancer Registry of NorwayOsloNorway
  2. 2.Faculty of Health ScienceOslo and Akershus University College of Applied SciencesOsloNorway

Personalised recommendations