European Radiology

, Volume 21, Issue 7, pp 1374–1382

Normal parenchymal enhancement patterns in women undergoing MR screening of the breast

  • Sanaz A. Jansen
  • Vicky C. Lin
  • Maryellen L. Giger
  • Hui Li
  • Gregory S. Karczmar
  • Gillian M. Newstead
Breast

Abstract

Objectives

To characterize the kinetic and morphological presentation of normal breast tissue on DCE-MRI in a large cohort of asymptomatic women, and to relate these characteristics to breast tissue density.

Methods

335 consecutive breast MR examinations in 229 asymptomatic women undergoing high-risk screening evaluations based on recommendations from the American Cancer Society including strong family history and genetic predisposition were selected for IRB-approved review (average age 49.2 ± 10.5 years). Breast tissue density was assessed on precontrast T2-weighted images. Parenchymal enhancement pattern (PEP) was qualitatively classified as minimal, homogeneous, heterogeneous or nodular. Quantitative analysis of parenchymal enhancement kinetics (PEK) was performed, including calculation of initial and peak enhancement percentages (E1, Epeak), the time to peak enhancement (Tpeak) and the signal enhancement ratio (SER).

Results

41.8% of examinations were classified as minimal, 13.7% homogeneous, 23.9% heterogeneous and 21.2% nodular PEP. Women with heterogeneously or extremely dense breasts exhibited a higher proportion of nodular PEP (44.2% (27/61)) and significantly higher E1, and Epeak (p < 0.003) compared with those with less dense breasts.

Conclusions

Qualitative and quantitative parenchymal enhancement characteristics vary by breast tissue density. In future work, the association between image-derived MR features of the normal breast and breast cancer risk should be explored.

Keywords

Breast Magnetic resonance imaging Kinetics Normal Screening 

References

  1. 1.
    Warner E, Messersmith H, Causer P, Eisen A, Shumak R, Plewes D (2008) Systematic review: using magnetic resonance imaging to screen women at high risk for breast cancer. Ann Intern Med 148:671–679PubMedGoogle Scholar
  2. 2.
    Molleran V, Mahoney MC (2010) The BI-RADS breast magnetic resonance imaging lexicon. Magn Reson Imaging Clin N Am 18:171–185. doi:10.1016/j.mric.2010.02.001, viiPubMedCrossRefGoogle Scholar
  3. 3.
    Kuhl CK, Bieling HB, Gieseke J et al (1997) Healthy premenopausal breast parenchyma in dynamic contrast-enhanced MR imaging of the breast: normal contrast medium enhancement and cyclical-phase dependency. Radiology 203:137–144PubMedGoogle Scholar
  4. 4.
    Pfleiderer SO, Sachse S, Sauner D et al (2004) Changes in magnetic resonance mammography due to hormone replacement therapy. Breast Cancer Res 6:R232–R238. doi:10.1186/bcr779 PubMedCrossRefGoogle Scholar
  5. 5.
    Liu F, Peacock S, DeMartini W, Eby P, Lehman CD (2008) Background parenchymal enhancement on BREAST MRI: characterization and impact on diagnostic accuracy(ed)^(eds). Radiological Society of North America, ChicagoGoogle Scholar
  6. 6.
    Li H, Giger ML, Jansen SA, Lan L, Bhooshan N, Newstead GM (2009) Computerized breast parenchymal analysis on DCE-MRI.(ed)^(eds) SPIE Medical Imaging ConferenceGoogle Scholar
  7. 7.
    Boyd NF, Martin LJ, Yaffe MJ, Minkin S (2006) Mammographic density: a hormonally responsive risk factor for breast cancer. J Br Menopause Soc 12:186–193. doi:10.1258/136218006779160436 PubMedCrossRefGoogle Scholar
  8. 8.
    Boyd N, Martin L, Gunasekara A et al (2009) Mammographic density and breast cancer risk: evaluation of a novel method of measuring breast tissue volumes. Cancer Epidemiol Biomark Prev 18:1754–1762. doi:10.1158/1055-9965.EPI-09-0107 CrossRefGoogle Scholar
  9. 9.
    Boyd NF, Martin LJ, Bronskill M, Yaffe MJ, Duric N, Minkin S (2010) Breast tissue composition and susceptibility to breast cancer. J Natl Cancer Inst. doi:10.1093/jnci/djq239 Google Scholar
  10. 10.
    Delille JP, Slanetz PJ, Yeh ED, Kopans DB, Garrido L (2005) Physiologic changes in breast magnetic resonance imaging during the menstrual cycle: perfusion imaging, signal enhancement, and influence of the T1 relaxation time of breast tissue. Breast J 11(4):236–241. doi:10.1111/j.1075-122X.2005.21499.x PubMedCrossRefGoogle Scholar
  11. 11.
    Muller-Schimpfle M, Ohmenhauser K, Stoll P, Dietz K, Claussen CD (1997) Menstrual cycle and age: influence on parenchymal contrast medium enhancement in MR imaging of the breast. Radiology 203:145–149PubMedGoogle Scholar
  12. 12.
    Yager JD, Davidson NE (2006) Estrogen carcinogenesis in breast cancer. N Engl J Med 354:270–282. doi:10.1056/NEJMra050776 PubMedCrossRefGoogle Scholar
  13. 13.
    Saslow D, Boetes C, Burke W et al (2007) American Cancer Society guidelines for breast screening with MRI as an adjunct to mammography. CA Cancer J Clin 57:75–89PubMedCrossRefGoogle Scholar
  14. 14.
    Jansen SA, Shimauchi A, Zak L et al (2009) Kinetic curves of malignant lesions are not consistent across MRI systems: need for improved standardization of breast dynamic contrast-enhanced MRI acquisition. AJR Am J Roentgenol 193(3):832–839. doi:10.2214/AJR.08.2025 PubMedCrossRefGoogle Scholar
  15. 15.
    Esserman L, Hylton N, George T, Weidner N (1999) Contrast-enhanced magnetic resonance imaging to assess tumor histopathology and angiogenesis in breast carcinoma. Breast J 5:13–21PubMedCrossRefGoogle Scholar
  16. 16.
    Holm S (1979) A simple sequentially rejective multiple test procedure. Scand J Statist 6:65–70Google Scholar
  17. 17.
    Jansen SA, Newstead GM, Abe H, Shimauchi A, Schmidt RA, Karczmar GS (2007) Pure ductal carcinoma in situ: kinetic and morphologic MR characteristics compared with mammographic appearance and nuclear grade. Radiology 245:684–691. doi:10.1148/radiol.2453062061 PubMedCrossRefGoogle Scholar
  18. 18.
    Heywang-Kobrunner SH, Schlegel A, Beck R et al (1993) Contrast-enhanced MRI of the breast after limited surgery and radiation therapy. J Comput Assist Tomogr 17:891–900PubMedCrossRefGoogle Scholar
  19. 19.
    Wersebe A, Xydeas T, Clauss T et al (2001) Quantitative assessment of therapy related effects after breast conserving therapy with dynamic MRI of the breast. Rofo 173:1109–1117. doi:10.1055/s-2001-18887 PubMedGoogle Scholar
  20. 20.
    Boston RC, Schnall MD, Englander SA, Landis JR, Moate PJ (2005) Estimation of the content of fat and parenchyma in breast tissue using MRI T1 histograms and phantoms. Magn Reson Imaging 23:591–599. doi:10.1016/j.mri.2005.02.006 PubMedCrossRefGoogle Scholar
  21. 21.
    Nie K, Chang D, Chen JH, Hsu CC, Nalcioglu O, Su MY (2010) Quantitative analysis of breast parenchymal patterns using 3D fibroglandular tissues segmented based on MRI. Med Phys 37:217–226PubMedCrossRefGoogle Scholar
  22. 22.
    Lorenzen J, Sinkus R, Biesterfeldt M, Adam G (2003) Menstrual-cycle dependence of breast parenchyma elasticity: estimation with magnetic resonance elastography of breast tissue during the menstrual cycle. Invest Radiol 38:236–240. doi:10.1097/01.RLI.0000059544.18910.BD PubMedGoogle Scholar
  23. 23.
    Partridge SC, McKinnon GC, Henry RG, Hylton NM (2001) Menstrual cycle variation of apparent diffusion coefficients measured in the normal breast using MRI. J Magn Reson Imaging 14:433–438. doi:10.1002/jmri.1204 PubMedCrossRefGoogle Scholar
  24. 24.
    Partridge SC, Murthy RS, Ziadloo A, White SW, Allison KH, Lehman CD (2010) Diffusion tensor magnetic resonance imaging of the normal breast. Magn Reson Imaging 28(3):320–328. doi:10.1016/j.mri.2009.10.003 PubMedCrossRefGoogle Scholar
  25. 25.
    Hattangadi J, Park C, Rembert J et al (2008) Breast stromal enhancement on MRI is associated with response to neoadjuvant chemotherapy. AJR Am J Roentgenol 190:1630–1636. doi:10.2214/AJR.07.2533 PubMedCrossRefGoogle Scholar
  26. 26.
    Kuhl C (2007) The current status of breast MR imaging. Part I. Choice of technique, image interpretation, diagnostic accuracy, and transfer to clinical practice. Radiology 244:356–378. doi:10.1148/radiol.2442051620 PubMedCrossRefGoogle Scholar
  27. 27.
    Cubuk R, Tasali N, Narin B, Keskiner F, Celik L, Guney S (2010) Correlation between breast density in mammography and background enhancement in MR mammography. Radiol Med 115:434–441. doi:10.1007/s11547-010-0513-4 PubMedCrossRefGoogle Scholar
  28. 28.
    Ko ES, Lee BH, Choi HY, Kim RB, Noh WC (2010) Background enhancement in breast MR: correlation with breast density in mammography and background echotexture in ultrasound. Eur J Radiol. doi:10.1016/j.ejrad.2010.07.019 Google Scholar
  29. 29.
    Passaperuma K, Warner E, Hill KA, Gunasekara A, Yaffe MJ (2010) Is mammographic breast density a breast cancer risk factor in women with BRCA mutations? J Clin Oncol. doi:10.1200/JCO.2009.27.5933 PubMedGoogle Scholar
  30. 30.
    Boyd N, Martin L, Chavez S et al (2009) Breast-tissue composition and other risk factors for breast cancer in young women: a cross-sectional study. Lancet Oncol 10:569–580. doi:10.1016/S1470-2045(09)70078-6 PubMedCrossRefGoogle Scholar
  31. 31.
    Khazen M, Warren RM, Boggis CR et al (2008) A pilot study of compositional analysis of the breast and estimation of breast mammographic density using three-dimensional T1-weighted magnetic resonance imaging. Cancer Epidemiol Biomark Prev 17:2268–2274. doi:10.1158/1055-9965.EPI-07-2547 CrossRefGoogle Scholar
  32. 32.
    Lee NA, Rusinek H, Weinreb J et al (1997) Fatty and fibroglandular tissue volumes in the breasts of women 20–83 years old: comparison of X-ray mammography and computer-assisted MR imaging. AJR Am J Roentgenol 168:501–506PubMedGoogle Scholar
  33. 33.
    Thompson DJ, Leach MO, Kwan-Lim G et al (2009) Assessing the usefulness of a novel MRI-based breast density estimation algorithm in a cohort of women at high genetic risk of breast cancer: the UK MARIBS study. Breast Cancer Res 11(6):R80. doi:10.1186/bcr2447 PubMedCrossRefGoogle Scholar
  34. 34.
    Chen W, Giger ML, Bick U, Newstead GM (2006) Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI. Med Phys 33:2878–2887PubMedCrossRefGoogle Scholar
  35. 35.
    Collins MJ, Hoffmeister J, Worrell SW (2006) Computer-aided detection and diagnosis of breast cancer. Semin Ultrasound CT MR 27:351–355PubMedCrossRefGoogle Scholar
  36. 36.
    Hologic (2010) Hologic-Quantra Volumetric Assessment. http://www.hologic.com/en/breast-screening/volumetric-assessment/. Accessed January 31, 2011
  37. 37.
    Huo Z, Giger ML, Olopade OI et al (2002) Computerized analysis of digitized mammograms of BRCA1 and BRCA2 gene mutation carriers. Radiology 225:519–526PubMedCrossRefGoogle Scholar
  38. 38.
    Li H, Giger ML, Olopade OI, Margolis A, Lan L, Chinander MR (2005) Computerized texture analysis of mammographic parenchymal patterns of digitized mammograms. Acad Radiol 12:863–873. doi:10.1016/j.acra.2005.03.069 PubMedCrossRefGoogle Scholar
  39. 39.
    Jansen SA, Paunesku T, Fan X et al (2009) Ductal carcinoma in situ: x-ray fluorescence microscopy and dynamic contrast-enhanced MR imaging reveals gadolinium uptake within neoplastic mammary ducts in a murine model. Radiology 253(2):399–406. doi:10.1148/radiol.2533082026 PubMedCrossRefGoogle Scholar
  40. 40.
    Delille JP, Slanetz PJ, Yeh ED, Kopans DB, Halpern EF, Garrido L (2005) Hormone replacement therapy in postmenopausal women: breast tissue perfusion determined with MR imaging–initial observations. Radiology 235:36–41. doi:10.1148/radiol.2351040012 PubMedCrossRefGoogle Scholar
  41. 41.
    Heinig A, Lampe D, Kolbl H, Beck R, Heywang-Kobrunner SH (2002) Suppression of unspecific enhancement on breast magnetic resonance imaging (MRI) by antiestrogen medication. Tumori 88:215–223PubMedGoogle Scholar
  42. 42.
    Lorenzen J, Welger J, Lisboa BW, Krupski G, Adam G (2003) MR-imaging of the breast at 0.5 Tesla: menstrual-cycle dependency of parenchymal contrast enhancement in healthy volunteers with oral contraceptive use? Rofo 175:502–506. doi:10.1055/s-2003-38449 PubMedGoogle Scholar
  43. 43.
    Reichenbach JR, Przetak C, Klinger G, Kaiser WA (1999) Assessment of breast tissue changes on hormonal replacement therapy using MRI: a pilot study. J Comput Assist Tomogr 23:407–413PubMedCrossRefGoogle Scholar
  44. 44.
    Abitbol CL, Warady BA, Massie MD et al (1990) Linear growth and anthropometric and nutritional measurements in children with mild to moderate renal insufficiency: a report of the Growth Failure in Children with Renal Diseases Study. J Pediatr 116:S46–S54PubMedCrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2011

Authors and Affiliations

  • Sanaz A. Jansen
    • 1
  • Vicky C. Lin
    • 1
  • Maryellen L. Giger
    • 1
  • Hui Li
    • 1
  • Gregory S. Karczmar
    • 1
  • Gillian M. Newstead
    • 1
  1. 1.Department of RadiologyThe University of ChicagoChicagoUSA
  2. 2.Mouse Cancer Genetics ProgramNational Cancer InstituteFrederickUSA

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