DOI QR코드

DOI QR Code

Identification of Preoperative Magnetic Resonance Imaging Features Associated with Positive Resection Margins in Breast Cancer: A Retrospective Study

  • Kang, Jung-Hyun (Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Youk, Ji Hyun (Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Kim, Jeong-Ah (Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Gweon, Hye Mi (Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Eun, Na Lae (Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Ko, Kyung Hee (Department of Diagnostic Radiology, CHA Bundang Medical Center, CHA University) ;
  • Son, Eun Ju (Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine)
  • Received : 2017.08.15
  • Accepted : 2018.03.14
  • Published : 2018.10.01

Abstract

Objective: To determine which preoperative breast magnetic resonance imaging (MRI) findings and clinicopathologic features are associated with positive resection margins at the time of breast-conserving surgery (BCS) in patients with breast cancer. Materials and Methods: We reviewed preoperative breast MRI and clinicopathologic features of 120 patients (mean age, 53.3 years; age range, 27-79 years) with breast cancer who had undergone BCS in 2015. Tumor size on MRI, multifocality, patterns of enhancing lesions (mass without non-mass enhancement [NME] vs. NME with or without mass), mass characteristics (shape, margin, internal enhancement characteristics), NME (distribution, internal enhancement patterns), and breast parenchymal enhancement (BPE; weak, strong) were analyzed. We also evaluated age, tumor size, histology, lymphovascular invasion, T stage, N stage, and hormonal receptors. Univariate and multivariate logistic regression analyses were used to determine the correlation between clinicopathological features, MRI findings, and positive resection margins. Results: In univariate analysis, tumor size on MRI, multifocality, NME with or without mass, and segmental distribution of NME were correlated with positive resection margins. Among the clinicopathological factors, tumor size of the invasive breast cancer and in situ components were significantly correlated with a positive resection margin. Multivariate analysis revealed that NME with or without mass was an independent predictor of positive resection margins (odds ratio [OR] = 7.00; p < 0.001). Strong BPE was a weak predictor of positive resection margins (OR = 2.59; p = 0.076). Conclusion: Non-mass enhancement with or without mass is significantly associated with a positive resection margin in patients with breast cancer. In patients with NME, segmental distribution was significantly correlated with positive resection margins.

Keywords

References

  1. Fisher B, Anderson S, Bryant J, Margolese RG, Deutsch M, Fisher ER, et al. Twenty-year follow-up of a randomized trial comparing total mastectomy, lumpectomy, and lumpectomy plus irradiation for the treatment of invasive breast cancer. N Engl J Med 2002;347:1233-1241 https://doi.org/10.1056/NEJMoa022152
  2. Veronesi U, Cascinelli N, Mariani L, Greco M, Saccozzi R, Luini A, et al. Twenty-year follow-up of a randomized study comparing breast-conserving surgery with radical mastectomy for early breast cancer. N Engl J Med 2002;347:1227-1232 https://doi.org/10.1056/NEJMoa020989
  3. Singletary SE. Surgical margins in patients with early-stage breast cancer treated with breast conservation therapy. Am J Surg 2002;184:383-393 https://doi.org/10.1016/S0002-9610(02)01012-7
  4. Houssami N, Macaskill P, Marinovich ML, Dixon JM, Irwig L, Brennan ME, et al. Meta-analysis of the impact of surgical margins on local recurrence in women with early-stage invasive breast cancer treated with breast-conserving therapy. Eur J Cancer 2010;46:3219-3232 https://doi.org/10.1016/j.ejca.2010.07.043
  5. Park AY, Seo BK. Real-time MRI navigated ultrasound for preoperative tumor evaluation in breast cancer patients: technique and clinical implementation. Korean J Radiol 2016;17:695-705 https://doi.org/10.3348/kjr.2016.17.5.695
  6. Azu M, Abrahamse P, Katz SJ, Jagsi R, Morrow M. What is an adequate margin for breast-conserving surgery? Surgeon attitudes and correlates. Ann Surg Oncol 2010;17:558-563 https://doi.org/10.1245/s10434-009-0765-1
  7. Bani MR, Lux MP, Heusinger K, Wenkel E, Magener A, Schulz-Wendtland R, et al. Factors correlating with reexcision after breast-conserving therapy. Eur J Surg Oncol 2009;35:32-37 https://doi.org/10.1016/j.ejso.2008.04.008
  8. Lovrics PJ, Cornacchi SD, Farrokhyar F, Garnett A, Chen V, Franic S, et al. The relationship between surgical factors and margin status after breast-conservation surgery for early stage breast cancer. Am J Surg 2009;197:740-746 https://doi.org/10.1016/j.amjsurg.2008.03.007
  9. Park S, Park HS, Kim SI, Koo JS, Park BW, Lee KS. The impact of a focally positive resection margin on the local control in patients treated with breast-conserving therapy. Jpn J Clin Oncol 2011;41:600-608 https://doi.org/10.1093/jjco/hyr018
  10. Melstrom LG, Melstrom KA, Wang EC, Pilewskie M, Winchester DJ. Ductal carcinoma in situ: size and resection volume predict margin status. Am J Clin Oncol 2010;33:438-442 https://doi.org/10.1097/COC.0b013e3181b9cf31
  11. Seo M, Cho N, Bae MS, Koo HR, Kim WH, Lee SH, et al. Features of undiagnosed breast cancers at screening breast MR imaging and potential utility of computer-aided evaluation. Korean J Radiol 2016;17:59-68 https://doi.org/10.3348/kjr.2016.17.1.59
  12. Chen SQ, Huang M, Shen YY, Liu CL, Xu CX. Abbreviated MRI protocols for detecting breast cancer in women with dense breasts. Korean J Radiol 2017;18:470-475 https://doi.org/10.3348/kjr.2017.18.3.470
  13. Chung A, Saouaf R, Scharre K, Phillips E. The impact of MRI on the treatment of DCIS. Am Surg 2005;71:705-710
  14. Del Frate C, Borghese L, Cedolini C, Bestagno A, Puglisi F, Isola M, et al. Role of pre-surgical breast MRI in the management of invasive breast carcinoma. Breast 2007;16:469-481 https://doi.org/10.1016/j.breast.2007.02.004
  15. Schnall M. MR imaging evaluation of cancer extent: is there clinical relevance? Magn Reson Imaging Clin N Am 2006;14:379-381, vii https://doi.org/10.1016/j.mric.2006.07.005
  16. Wolff AC, Hammond ME, Schwartz JN, Hagerty KL, Allred DC, Cote RJ, et al. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol 2007;25:118-145
  17. Edge SB, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A, eds. AJCC cancer staging manual, 7th ed. New York, NY: Springer, 2010
  18. D'Orsi CJ, Sickles EA, Mendelson EB, Morris EA. ACR BI-RADS atlas, breast imaging reporting and data system. Reston, VA: American College of Radiology, 2013
  19. Camp ER, McAuliffe PF, Gilroy JS, Morris CG, Lind DS, Mendenhall NP, et al. Minimizing local recurrence after breast conserving therapy using intraoperative shaved margins to determine pathologic tumor clearance. J Am Coll Surg 2005;201:855-861 https://doi.org/10.1016/j.jamcollsurg.2005.06.274
  20. Turnbull L, Brown S, Harvey I, Olivier C, Drew P, Napp V, et al. Comparative effectiveness of MRI in breast cancer (COMICE) trial: a randomised controlled trial. Lancet 2010;375:563-571 https://doi.org/10.1016/S0140-6736(09)62070-5
  21. Houssami N, Turner R, Morrow M. Preoperative magnetic resonance imaging in breast cancer: meta-analysis of surgical outcomes. Ann Surg 2013;257:249-255 https://doi.org/10.1097/SLA.0b013e31827a8d17
  22. Pengel KE, Loo CE, Teertstra HJ, Muller SH, Wesseling J, Peterse JL, et al. The impact of preoperative MRI on breastconserving surgery of invasive cancer: a comparative cohort study. Breast Cancer Res Treat 2009;116:161-169 https://doi.org/10.1007/s10549-008-0182-3
  23. Mann RM, Loo CE, Wobbes T, Bult P, Barentsz JO, Gilhuijs KG, et al. The impact of preoperative breast MRI on the reexcision rate in invasive lobular carcinoma of the breast. Breast Cancer Res Treat 2010;119:415-422 https://doi.org/10.1007/s10549-009-0616-6
  24. Kim OH, Kim SJ, Lee JS. Enhancing patterns of breast cancer on preoperative dynamic contrast-enhanced magnetic resonance imaging and resection margin in breast conserving therapy. Breast Dis 2016;36:27-35 https://doi.org/10.3233/BD-150195
  25. Jang M, Kim SM, Yun BL, Kim SW, Kang EY, Park SY, et al. Magnetic resonance imaging factors predicting re-excision in breast cancer patients having undergone conserving therapy. J Korean Soc Magn Reson Med 2014;18:133-143 https://doi.org/10.13104/jksmrm.2014.18.2.133
  26. Sakamoto N, Tozaki M, Higa K, Tsunoda Y, Ogawa T, Abe S, et al. Categorization of non-mass-like breast lesions detected by MRI. Breast Cancer 2008;15:241-246 https://doi.org/10.1007/s12282-007-0028-6
  27. Tozaki M, Fukuda K. High-spatial-resolution MRI of nonmasslike breast lesions: interpretation model based on BIRADS MRI descriptors. AJR Am J Roentgenol 2006;187:330-337 https://doi.org/10.2214/AJR.05.0998
  28. Vag T, Baltzer PA, Dietzel M, Benndorf M, Gajda M, Camara O, et al. Kinetic characteristics of ductal carcinoma in situ (DCIS) in dynamic breast MRI using computer-assisted analysis. Acta Radiol 2010;51:955-961 https://doi.org/10.3109/02841851.2010.508171
  29. Dillon MF, Hill AD, Quinn CM, McDermott EW, O'Higgins N. A pathologic assessment of adequate margin status in breastconserving therapy. Ann Surg Oncol 2006;13:333-339 https://doi.org/10.1245/ASO.2006.03.098
  30. Miller AR, Brandao G, Prihoda TJ, Hill C, Cruz AB Jr, Yeh IT. Positive margins following surgical resection of breast carcinoma: analysis of pathologic correlates. J Surg Oncol 2004;86:134-140 https://doi.org/10.1002/jso.20059
  31. DiPiro PJ, Krajewski KM, Giardino AA, Braschi-Amirfarzan M, Ramaiya NH. Radiology consultation in the era of precision oncology: a review of consultation models and services in the tertiary setting. Korean J Radiol 2017;18:18-27 https://doi.org/10.3348/kjr.2017.18.1.18
  32. Seo M, Ryu JK, Jahng GH, Sohn YM, Rhee SJ, Oh JH, et al. Estimation of T2* relaxation time of breast cancer: correlation with clinical, imaging and pathological features. Korean J Radiol 2017;18:238-248 https://doi.org/10.3348/kjr.2017.18.1.238
  33. Park SY, Kang DK, Kim TH. Does background parenchymal enhancement on MRI affect the rate of positive resection margin in breast cancer patients? Br J Radiol 2015;88:20140638 https://doi.org/10.1259/bjr.20140638
  34. Millet I, Pages E, Hoa D, Merigeaud S, Curros Doyon F, Prat X, et al. Pearls and pitfalls in breast MRI. Br J Radiol 2012;85:197-207 https://doi.org/10.1259/bjr/47213729
  35. Giess CS, Yeh ED, Raza S, Birdwell RL. Background parenchymal enhancement at breast MR imaging: normal patterns, diagnostic challenges, and potential for falsepositive and false-negative interpretation. Radiographics 2014;34:234-247 https://doi.org/10.1148/rg.341135034
  36. Shimauchi A, Jansen SA, Abe H, Jaskowiak N, Schmidt RA, Newstead GM. Breast cancers not detected at MRI: review of false-negative lesions. AJR Am J Roentgenol 2010;194:1674-1679 https://doi.org/10.2214/AJR.09.3568

Cited by

  1. Re: Identification of Preoperative Magnetic Resonance Imaging Features Associated with Positive Resection Margins in Breast Cancer? vol.20, pp.6, 2019, https://doi.org/10.3348/kjr.2019.0044
  2. Redefining Eligibility by Analyzing Canceled Intraoperative Radiotherapy as a Boost for Patients Undergoing Breast-Conserving Treatment vol.26, pp.13, 2018, https://doi.org/10.1245/s10434-019-07819-5
  3. Preoperative Magnetic Resonance Imaging Features Associated with Positive Resection Margins in Patients with Invasive Lobular Carcinoma vol.21, pp.8, 2018, https://doi.org/10.3348/kjr.2019.0674
  4. Characteristics of Recent Articles Published in the Korean Journal of Radiology Based on the Citation Frequency vol.21, pp.12, 2020, https://doi.org/10.3348/kjr.2020.1322
  5. Diagnostic Accuracy of Nonmass Enhancement at Breast MRI in Predicting Tumor Involvement of the Nipple: A Prospective Study in a Single Institution vol.301, pp.1, 2018, https://doi.org/10.1148/radiol.2021204136
  6. Raman spectroscopy and artificial intelligence to predict the Bayesian probability of breast cancer vol.11, pp.1, 2018, https://doi.org/10.1038/s41598-021-85758-6