Skip to main content

Advertisement

SpringerLink
Log in

MR imaging features associated with distant metastasis-free survival of patients with invasive breast cancer: a case–control study

  • Epidemiology
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

Purpose

Preoperative breast magnetic resonance (MR) imaging features of primary breast cancers may have the potential to act as prognostic biomarkers by providing morphologic and kinetic features representing inter- or intra-tumor heterogeneity. Recent radiogenomic studies reveal that several radiologist-annotated image features are associated with genes or signal pathways involved in tumor progression, treatment resistance, and distant metastasis (DM). We investigate whether preoperative breast MR imaging features are associated with worse DM-free survival in patients with invasive breast cancer.

Methods

Of the 3536 patients with primary breast cancers who underwent preoperative MR imaging between 2003 and 2009, 147 patients with DM were identified and one-to-one matched with control patients (n = 147) without DM according to clinical–pathologic variables. Three radiologists independently reviewed the MR images of 294 patients, and the association of DM-free survival with MR imaging and clinical–pathologic features was assessed using Cox proportional hazard models.

Results

Of MR imaging features, rim enhancement (hazard ratio [HR], 1.83 [95% confidence interval, CI 1.29, 2.51]; p = 0.001) and peritumoral edema (HR, 1.48 [95% CI 1.03, 2.11]; p = 0.032) were the significant features associated with worse DM-free survival. The significant MR imaging features, however, were different between breast cancer subtypes and stages.

Conclusion

Preoperative breast MR imaging features of rim enhancement and peritumoral edema may be used as prognostic biomarkers that help predict DM risk in patients with breast cancer, thereby potentially enabling improved personalized treatment and monitoring strategies for individual patients.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) (2005) Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 365(9472):1687–1717

    Article  Google Scholar 

  2. Weigelt B, Peterse JL, van’t Veer LJ (2005) Breast cancer metastasis: markers and models. Nat Rev Cancer 5(8):591–602

    Article  CAS  PubMed  Google Scholar 

  3. Page DL (1991) Prognosis and breast cancer. recognition of lethal and favourable prognostic types. Am J Surg Pathol 15(4):334–349

    Article  CAS  PubMed  Google Scholar 

  4. 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(5):403–410

    Article  CAS  PubMed  Google Scholar 

  5. Slamon DJ, Leyland-Jones B, Shak S, Fuchs H, Paton V, Bajamonde A, Fleming T, Eiermann W, Wolter J, Pegram M, Baselga J, Norton L (2001) Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med 344(11):783–792

    Article  CAS  PubMed  Google Scholar 

  6. Klintman M, Bendahl PO, Grabau D, Lövgren K, Malmström P, Fernö M, South Sweden Breast Cancer Group (2010) The prognostic value of Ki67 is dependent on estrogen receptor status and histological grade in premenopausal patients with node-negative breast cancer. Mod Pathol 23(2):251–259

    Article  CAS  PubMed  Google Scholar 

  7. Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F, Talantov D, Timmermans M, Meijer-van Gelder ME, Yu J, Jatkoe T, Berns EM, Atkins D, Foekens JA (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365(9460):671–679

    Article  CAS  PubMed  Google Scholar 

  8. Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thürlimann B, Senn HJ, Panel members (2013) Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol 24(9):2206–2223

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Mauriac L, Keshaviah A, Debled M, Mouridsen H, Forbes JF, Thürlimann B, Paridaens R, Monnier A, Láng I, Wardley A, Nogaret JM, Gelber RD, Castiglione-Gertsch M, Price KN, Coates AS, Smith I, Viale G, Rabaglio M, Zabaznyi N, Goldhirsch A, BIG 1–98 Collaborative Group, International Breast Cancer Study Group (2007) Predictors of early relapse in postmenopausal women with hormone receptor-positive breast cancer in the BIG 1-98 trial. Ann Oncol 18(5):859–867

    Article  CAS  PubMed  Google Scholar 

  10. Goss PE, Ingle JN, Pritchard KI, Robert NJ, Muss H1, Gralow J, Gelmon K, Whelan T, Strasser-Weippl K, Rubin S, Sturtz K, Wolff AC, Winer E, Hudis C, Stopeck A, Beck JT, Kaur JS, Whelan K, Tu D, Parulekar WR (2016) Extending aromatase-inhibitor adjuvant therapy to 10 years. N Engl J Med 20;375(16):1590–1591

  11. Grimm LJ (2016) Breast MRI radiogenomics: current status and research implications. J Magn Reson Imaging 43(6):1269–1278

    Article  PubMed  Google Scholar 

  12. Li SP, Makris A, Beresford MJ, Taylor NJ, Ah-See ML, Stirling JJ, d’Arcy JA, Collins DJ, Kozarski R, Padhani AR (2011) Use of dynamic contrast-enhanced MR imaging to predict survival in patients with primary breast cancer undergoing neoadjuvant chemotherapy. Radiology 260(1):68–78

    Article  PubMed  Google Scholar 

  13. Schmitz AM, Loo CE, Wesseling J, Pijnappel RM, Gilhuijs KG (2014) Association between rim enhancement of breast cancer on dynamic contrast-enhanced MRI and patient outcome: impact of subtype. Breast Cancer Res Treat 148(3):541–551

    Article  PubMed  Google Scholar 

  14. Uematsu T, Kasami M, Watanabe J (2014) Is evaluation of the presence of prepectoral edema on T2-weighted with fat-suppression 3 T breast MRI a simple and readily available noninvasive technique for estimation of prognosis in patients with breast cancer? Breast Cancer 21(6):684–692

    Article  PubMed  Google Scholar 

  15. Kim WH, Han W, Chang JM, Cho N, Park IA, Moon WK (2015) Location of triple-negative breast cancers: comparison with estrogen receptor-positive breast cancers on MR imaging. PLoS ONE 10(1):e0116344. doi:10.1371/journal.pone.0116344.eCollection

    Article  PubMed  PubMed Central  Google Scholar 

  16. Choi JS, Ko ES, Ko EY, Han BK, Nam SJ (2016) Background parenchymal enhancement on preoperative magnetic resonance imaging: association with recurrence-free survival in breast cancer patients treated with neoadjuvant chemotherapy. Medicine (Baltimore) 95(9):e3000. doi:10.1097/MD.0000000000003000

    Article  CAS  Google Scholar 

  17. van der Velden BH, Dmitriev I, Loo CE, Pijnappel RM, Gilhuijs KG (2015) Association between parenchymal enhancement of the contralateral breast in dynamic contrast-enhanced MR imaging and outcome of patients with unilateral invasive breast cancer. Radiology 276(3):675–685

    Article  PubMed  Google Scholar 

  18. Yi A, Cho N, Yang KS, Han W, Noh DY, Moon WK (2015) Breast cancer recurrence in patients with newly diagnosed breast cancer without and with preoperative MR imaging: a matched cohort study. Radiology 276(3):695–705

    Article  PubMed  Google Scholar 

  19. Morris EA, Comstock CE, Lee CH et al (2013) ACR BI-RADS Magnetic resonance imaging. In: ACR BI-RADS® Atlas (ed) Breast imaging reporting and data system. American College of Radiology, Reston

    Google Scholar 

  20. Baltzer PA, Yang F, Dietzel M, Herzog A, Simon A, Vag T, Gajda M, Camara O, Kaiser WA (2010) Sensitivity and specificity of unilateral edema on T2w-TSE sequences in MR-mammography considering 974 histologically verified lesions. Breast J 16(3):233–239

    Article  PubMed  Google Scholar 

  21. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33(1):159–174

    Article  CAS  PubMed  Google Scholar 

  22. Szabo BK, Aspelin P, Kristoffersen WM, Tot T, Bone B (2003) Invasive breast cancer: correlation of dynamic MR features with prognostic factors. Eur Radiol 13(11):2425–2435

    Article  PubMed  Google Scholar 

  23. Lee SH, Cho N, Kim SJ, Cha JH, Cho KS, Ko ES, Moon WK (2008) Correlation between high resolution dynamic MR features and prognostic factors in breast cancer. Korean J Radiol 9(1):10–18

    Article  PubMed  PubMed Central  Google Scholar 

  24. Matsubayashi R, Matsuo Y, Edakuni G, Satoh T, Tokunaga O, Kudo S (2000) Breast masses with peripheral rim enhancement on dynamic contrast-enhanced MR images: correlation of MR findings with histologic features and expression of growth factors. Radiology 217(3):841–848

    Article  CAS  PubMed  Google Scholar 

  25. Uematsu T (2015) Focal breast edema associated with malignancy on T2-weighted images of breast MRI: peritumoral edema, prepectoral edema, and subcutaneous edema. Breast Cancer 22(1):66–70

    Article  PubMed  Google Scholar 

  26. Yamamoto S, Han W, Kim Y, Du L, Jamshidi N, Huang D, Kim JH, Kuo MD (2015) Breast cancer: radiogenomic biomarker reveals associations among dynamic contrast-enhanced MR imaging, long noncoding RNA, and metastasis. Radiology 275(2):384–392

    Article  PubMed  Google Scholar 

  27. Bae MS, Shin SU, Ryu HS, Han W, Im SA, Park IA, Noh DY, Moon WK (2016) Pretreatment MR imaging features of triple-negative breast cancer: association with response to neoadjuvant chemotherapy and recurrence-free survival. Radiology 281(2):392–400

    Article  PubMed  Google Scholar 

  28. Rao A, Net J, Brandt K, Huang E, Freymann J, Burnside E, Kirby J, Morris E, Bonaccio E, Giger M, Jaffe C, Ganott M, Sutton E, Le-Petross H, Zuley M, Dogan B, Whitman G (2015) TU-CD-BRB-07: identification of associations between radiologist-annotated imaging features and genomic alterations in breast invasive carcinoma, a TCGA phenotype research group study. Med Phys 42:3603–3604. doi:10.1118/1.4925592

    Article  Google Scholar 

  29. Zhu Y, Li H, Guo W, Drukker K, Lan L, Giger ML, Ji Y (2015) Deciphering genomic underpinnings of quantitative MRI-based radiomic phenotypes of invasive breast carcinoma. Sci Rep 5:17787

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Cancer Genome Atlas Network (2012) Comprehensive molecular portraits of human breast tumours. Nature 490(7418):61–70

    Article  Google Scholar 

  31. Schrading S, Kuhl CK (2008) Mammographic, US, and MR imaging phenotypes of familial breast cancer. Radiology 246(1):58–70

    Article  PubMed  Google Scholar 

  32. Tanis PJ, van Rijk MC, Nieweg OE (2005) The posterior lymphatic network of the breast rediscovered. J Surg Oncol 91(3):195–198

    Article  PubMed  Google Scholar 

  33. Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, Pietenpol JA (2011) Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 121(7):2750–2767

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Bae MS, Park SY, Song SE, Kim WH, Lee SH, Han W, Park IA, Noh DY, Moon WK (2015) Heterogeneity of triple-negative breast cancer: mammographic, US, and MR imaging features according to androgen receptor expression. Eur Radiol 25(2):419–427

    Article  PubMed  Google Scholar 

Download references

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2014R1A1A2055402).

Author information

Authors and Affiliations

  1. Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea

    Sung Eun Song, Sung Ui Shin & Woo Kyung Moon

  2. Department of Radiology, Korea University College of Medicine, Seoul, Korea

    Sung Eun Song

  3. Department of Surgery, Seoul National University Hospital and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea

    Hyeong-Gon Moon

  4. Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea

    Han Suk Ryu

  5. Division of Clinical Bioinformatics, Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea

    Kwangsoo Kim

Authors
  1. Sung Eun Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sung Ui Shin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hyeong-Gon Moon
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Han Suk Ryu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kwangsoo Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Woo Kyung Moon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Woo Kyung Moon.

Ethics declarations

Conflict of interest

The authors declare no potential conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

For this type of study formal consent is not required.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 18 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, S.E., Shin, S.U., Moon, HG. et al. MR imaging features associated with distant metastasis-free survival of patients with invasive breast cancer: a case–control study. Breast Cancer Res Treat 162, 559–569 (2017). https://doi.org/10.1007/s10549-017-4143-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-017-4143-6

Keywords

Search

Navigation