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Optimizing surgical strategy in locally advanced breast cancer: a comparative analysis between preoperative MRI and postoperative pathology after neoadjuvant chemotherapy

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Abstract

Purpose

In the treatment of breast cancer, neo-adjuvant chemotherapy is often used as systemic treatment followed by tumor excision. In this context, planning the operation with regard to excision margins relies on tumor size measured by MRI. The actual tumor size can be determined through pathologic evaluation. The aim of this study is to investigate the correlation and agreement between pre-operative MRI and postoperative pathological evaluation.

Methods

One hundred and ninety-three breast cancer patients that underwent neo-adjuvant chemotherapy and subsequent breast surgery were retrospectively included between January 2013 and July 2016. Preoperative tumor diameters determined with MRI were compared with postoperative tumor diameters determined by pathological analysis. Spearman correlation and Bland–Altman agreement methods were used. Results were subjected to subgroup analysis based on histological subtype (ER, HER2, ductal, lobular).

Results

The correlation between tumor size at MRI and pathology was 0.63 for the whole group, 0.39 for subtype ER + /HER2−, 0.51 for ER + /HER2 + , 0.63 for ER−/HER2 +, and 0.85 for ER−/HER2−. The mean difference and limits of agreement (LoA) between tumor size measured MRI vs. pathological assessment was 4.6 mm (LoA −27.0–36.3 mm, n = 195). Mean differences and LoA for subtype ER + /HER2− was 7.6 mm (LoA −31.3–46.5 mm, n = 100), for ER + /HER2 + 0.9 mm (LoA −8.5–10.2 mm, n = 33), for ER−/HER2+ −1.2 mm (LoA −5.1–7.5 mm, n = 21), and for ER−/HER− −0.4 mm (LoA −8.6–7.7 mm, n = 41).

Conclusion

HER2 + and ER−/HER2− tumor subtypes showed clear correlation and agreement between preoperative MRI and postoperative pathological assessment of tumor size. This suggests that MRI evaluation could be a suitable predictor to guide the surgical approach. Conversely, correlation and agreement for ER + /HER2− and lobular tumors was poor, evidenced by a difference in tumor size of up to 5 cm. Hence, we demonstrate that histological tumor subtype should be taken into account when planning breast conserving surgery after NAC.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F (2021) Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 Countries. CA Cancer J Clin 71:209–249. https://doi.org/10.3322/caac.21660

    Article  PubMed  Google Scholar 

  2. Early Breast Cancer Trialists’ Collaborative (2018) Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials. Lancet Oncol 19:27–39. https://doi.org/10.1016/S1470-2045(17)30777-5

    Article  Google Scholar 

  3. Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, Bonnefoi H, Cameron D, Gianni L, Valagussa P, Swain SM, Prowell T, Loibl S, Wickerham DL, Bogaerts J, Baselga J, Perou C, Blumenthal G, Blohmer J, Mamounas EP, Bergh J, Semiglazov V, Justice R, Eidtmann H, Paik S, Piccart M, Sridhara R, Fasching PA, Slaets L, Tang S, Gerber B, Geyer CE, Pazdur R, Ditsch N, Rastogi P, Eiermann W, von Minckwitz G (2014) Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet 384:164–172. https://doi.org/10.1016/S0140-6736(13)62422-8

    Article  PubMed  Google Scholar 

  4. Spring LM, Fell G, Arfe A, Sharma C, Greenup R, Reynolds KL, Smith BL, Alexander B, Moy B, Isakoff SJ, Parmigiani G, Trippa L, Bardia A (2020) Pathologic complete response after neoadjuvant chemotherapy and impact on breast cancer recurrence and survival: a comprehensive meta-analysis. Clin Cancer Res 26:2838–2848. https://doi.org/10.1158/1078-0432.CCR-19-3492

    Article  PubMed  PubMed Central  Google Scholar 

  5. Boughey JC, Ballman KV, McCall LM, Mittendorf EA, Symmans WF, Julian TB, Byrd D, Hunt KK (2017) Tumor biology and response to chemotherapy impact breast cancer-specific survival in node-positive breast cancer patients treated with neoadjuvant chemotherapy: long-term follow-up from ACOSOG Z1071 (Alliance). Ann Surg. https://doi.org/10.1097/SLA.0000000000002373

    Article  PubMed  Google Scholar 

  6. Symmans WF, Wei C, Gould R, Yu X, Zhang Y, Liu M, Walls A, Bousamra A, Ramineni M, Sinn B, Hunt K, Buchholz TA, Valero V, Buzdar AU, Yang W, Brewster AM, Moulder S, Pusztai L, Hatzis C, Hortobagyi GN (2017) Long-term prognostic risk after neoadjuvant chemotherapy associated with residual cancer burden and breast cancer subtype. J Clin Oncol 35:1049–1060. https://doi.org/10.1200/JCO.2015.63.1010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Teshome M, Kuerer HM (2017) Breast conserving surgery and locoregional control after neoadjuvant chemotherapy. Eur J Surg Oncol 43:865–874. https://doi.org/10.1016/j.ejso.2017.02.002

    Article  CAS  PubMed  Google Scholar 

  8. Haque W, Verma V, Hatch S, Suzanne Klimberg V, Brian Butler E, Teh BS (2018) Response rates and pathologic complete response by breast cancer molecular subtype following neoadjuvant chemotherapy. Breast Cancer Res Treat 170:559–567. https://doi.org/10.1007/s10549-018-4801-3

    Article  CAS  PubMed  Google Scholar 

  9. Volders JH, Haloua MH, Krekel NM, Negenborn VL, Barbe E, Sietses C, Jozwiak K, Meijer S, van den Tol MP (2016) Neoadjuvant chemotherapy in breast-conserving surgery - Consequences on margin status and excision volumes: A nationwide pathology study. Eur J Surg Oncol 42:986–993. https://doi.org/10.1016/j.ejso.2016.02.252

    Article  CAS  PubMed  Google Scholar 

  10. Shin HJ, Kim HH, Ahn JH, Kim SB, Jung KH, Gong G, Son BH, Ahn SH (2011) Comparison of mammography, sonography, MRI and clinical examination in patients with locally advanced or inflammatory breast cancer who underwent neoadjuvant chemotherapy. Br J Radiol 84:612–620. https://doi.org/10.1259/bjr/74430952

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yeh E, Slanetz P, Kopans DB, Rafferty E, Georgian-Smith D, Moy L, Halpern E, Moore R, Kuter I, Taghian A (2005) Prospective comparison of mammography, sonography, and MRI in patients undergoing neoadjuvant chemotherapy for palpable breast cancer. AJR Am J Roentgenol 184:868–877. https://doi.org/10.2214/ajr.184.3.01840868

    Article  PubMed  Google Scholar 

  12. Scheel JR, Kim E, Partridge SC, Lehman CD, Rosen MA, Bernreuter WK, Pisano ED, Marques HS, Morris EA, Weatherall PT, Polin SM, Newstead GM, Esserman LJ, Schnall MD, Hylton NM (2018) MRI, clinical examination, and mammography for preoperative assessment of residual disease and pathologic complete response after neoadjuvant chemotherapy for breast cancer: ACRIN 6657 trial. AJR Am J Roentgenol 210:1376–1385. https://doi.org/10.2214/ajr.17.18323

    Article  PubMed  PubMed Central  Google Scholar 

  13. Marinovich ML, Macaskill P, Irwig L, Sardanelli F, Mamounas E, von Minckwitz G, Guarneri V, Partridge SC, Wright FC, Choi JH, Bhattacharyya M, Martincich L, Yeh E, Londero V, Houssami N (2015) Agreement between MRI and pathologic breast tumor size after neoadjuvant chemotherapy, and comparison with alternative tests: individual patient data meta-analysis. BMC Cancer 15:662. https://doi.org/10.1186/s12885-015-1664-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ballesio L, Gigli S, Di Pastena F, Giraldi G, Manganaro L, Anastasi E, Catalano C (2017) Magnetic resonance imaging tumor regression shrinkage patterns after neoadjuvant chemotherapy in patients with locally advanced breast cancer: Correlation with tumor biological subtypes and pathological response after therapy. Tumour Biol 39:1010428317694540. https://doi.org/10.1177/1010428317694540

    Article  CAS  PubMed  Google Scholar 

  15. Um E, Kang JW, Lee S, Kim HJ, Yoon TI, Sohn G, Chung IY, Kim J, Lee JW, Son BH, Ahn SH, Ko BS (2018) Comparing accuracy of mammography and magnetic resonance imaging for residual calcified lesions in breast cancer patients undergoing neoadjuvant systemic therapy. Clin Breast Cancer 18:e1087–e1091. https://doi.org/10.1016/j.clbc.2018.03.011

    Article  PubMed  Google Scholar 

  16. Zhou J, Li G, Sheng F, Qiao P, Zhang H, Xing X (2016) Magnetic resonance imaging evaluation of residual tumors in breast cancer after neoadjuvant chemotherapy: surgical implications. Acta Radiol 57:529–537. https://doi.org/10.1177/0284185115597263

    Article  PubMed  Google Scholar 

  17. Diguisto C, Ouldamer L, Arbion F, Vildé A, Body G (2015) MRI evaluation of residual breast cancer after neoadjuvant chemotherapy: influence of patient, tumor and chemotherapy characteristics on the correlation with pathological response. Anticancer Res 35:581–585

    PubMed  Google Scholar 

  18. Williams M, Eatrides J, Kim J, Talwar H, Esposito N, Szabunio M, Ismail-Khan R, Kiluk J, Lee M, Laronga C, Khakpour N (2013) Comparison of breast magnetic resonance imaging clinical tumor size with pathologic tumor size in patients status post-neoadjuvant chemotherapy. Am J Surg 206:567–573. https://doi.org/10.1016/j.amjsurg.2013.02.006

    Article  PubMed  Google Scholar 

  19. Loo CE, Straver ME, Rodenhuis S, Muller SH, Wesseling J, Vrancken Peeters MJ, Gilhuijs KG (2011) Magnetic resonance imaging response monitoring of breast cancer during neoadjuvant chemotherapy: relevance of breast cancer subtype. J Clin Oncol 29:660–666. https://doi.org/10.1200/JCO.2010.31.1258

    Article  PubMed  Google Scholar 

  20. Wright FC, Zubovits J, Gardner S, Fitzgerald B, Clemons M, Quan ML, Causer P (2010) Optimal assessment of residual disease after neo-adjuvant therapy for locally advanced and inflammatory breast cancer–clinical examination, mammography, or magnetic resonance imaging? J Surg Oncol 101:604–610. https://doi.org/10.1002/jso.21559

    Article  CAS  PubMed  Google Scholar 

  21. Price ER, Wong J, Mukhtar R, Hylton N, Esserman LJ (2015) How to use magnetic resonance imaging following neoadjuvant chemotherapy in locally advanced breast cancer. World J Clin Cases 3:607–613. https://doi.org/10.12998/wjcc.v3.i7.607

    Article  PubMed  PubMed Central  Google Scholar 

  22. Mukhtar RA, Yau C, Rosen M, Tandon VJ (2013) Clinically meaningful tumor reduction rates vary by prechemotherapy MRI phenotype and tumor subtype in the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657). Ann Surg Oncol 20:3823–3830. https://doi.org/10.1245/s10434-013-3038-y

    Article  PubMed  PubMed Central  Google Scholar 

  23. De Los SJ, Bernreuter W, Keene K, Krontiras H, Carpenter J, Bland K, Cantor A, Forero A (2011) Accuracy of breast magnetic resonance imaging in predicting pathologic response in patients treated with neoadjuvant chemotherapy. Clin Breast Cancer 11:312–319. https://doi.org/10.1016/j.clbc.2011.06.007

    Article  Google Scholar 

  24. Gomez-Raposo C, Andreu M, Suarez-Garcia I, Esteban MI, Carballo M, Sereno-Moyano MF, Vazquez Osorio JL, Heras J, Zambrana Tevar F, Pelayo E, Lopez-Gomez M, Garcia de Santiago C, Merino Salvador M, Casado E (2012) Relevance of breast cancer subtypes for magnetic resonance imaging response monitoring during neoadjuvant chemotherapy. Clin Transl Oncol 14:486–488. https://doi.org/10.1007/s12094-012-0828-9

    Article  CAS  PubMed  Google Scholar 

  25. Kuzucan A, Chen JH, Bahri S, Mehta RS, Carpenter PM, Fwu PT, Yu HJ, Hsiang DJ, Lane KT, Butler JA, Feig SA, Su MY (2012) Diagnostic performance of magnetic resonance imaging for assessing tumor response in patients with HER2-negative breast cancer receiving neoadjuvant chemotherapy is associated with molecular biomarker profile. Clin Breast Cancer 12:110–118. https://doi.org/10.1016/j.clbc.2012.01.009

    Article  PubMed  PubMed Central  Google Scholar 

  26. Ranganathan P, Pramesh CS, Aggarwal R (2017) Common pitfalls in statistical analysis: Measures of agreement. Perspect Clin Res 8:187–191. https://doi.org/10.4103/picr.PICR_123_17

    Article  PubMed  PubMed Central  Google Scholar 

  27. Kim J, Han B-K, Ko EY, Ko ES, Choi JS, Park KW (2022) Prediction of pathologic complete response on MRI in patients with breast cancer receiving neoadjuvant chemotherapy according to molecular subtypes. Eur Radiol 32:4056–4066. https://doi.org/10.1007/s00330-021-08461-0

    Article  CAS  PubMed  Google Scholar 

  28. Weber JJ, Jochelson MS, Eaton A, Zabor EC, Barrio AV, Gemignani ML, Pilewskie M, Van Zee KJ, Morrow M, El-Tamer M (2017) MRI and prediction of pathologic complete response in the breast and axilla after neoadjuvant chemotherapy for breast cancer. J Am Coll Surg 225:740–746. https://doi.org/10.1016/j.jamcollsurg.2017.08.027

    Article  PubMed  PubMed Central  Google Scholar 

  29. Marinovich ML, Macaskill P, Irwig L, Sardanelli F, von Minckwitz G, Mamounas E, Brennan M, Ciatto S, Houssami N (2013) Meta-analysis of agreement between MRI and pathologic breast tumour size after neoadjuvant chemotherapy. Br J Cancer 109:1528–1536. https://doi.org/10.1038/bjc.2013.473

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Vriens BE, de Vries B, Lobbes MB, van Gastel SM, van den Berkmortel FW, Smilde TJ, van Warmerdam LJ, de Boer M, van Spronsen DJ, Smidt ML, Peer PG, Aarts MJ, Tjan-Heijnen VC (2016) Ultrasound is at least as good as magnetic resonance imaging in predicting tumour size post-neoadjuvant chemotherapy in breast cancer. Eur J Cancer 52:67–76. https://doi.org/10.1016/j.ejca.2015.10.010

    Article  PubMed  Google Scholar 

  31. van Ramshorst MS, van der Voort A, van Werkhoven ED, Mandjes IA, Kemper I, Dezentje VO, Oving IM, Honkoop AH, Tick LW, van de Wouw AJ, Mandigers CM, van Warmerdam LJ, Wesseling J, Vrancken Peeters MT, Linn SC, Sonke GS (2018) Neoadjuvant chemotherapy with or without anthracyclines in the presence of dual HER2 blockade for HER2-positive breast cancer (TRAIN-2): a multicentre, open-label, randomised, phase 3 trial. Lancet Oncol 19:1630–1640. https://doi.org/10.1016/S1470-2045(18)30570-9

    Article  PubMed  Google Scholar 

  32. The Netherlands Cancer Institute Neo Adjuvant Chemotherapy in Triple Negative Breast Cancer (neo-TN). https://clinicaltrials.gov/ct2/show/NCT01057069. Accessed 2022/11/27

  33. Interaal Kanker Centrum Nederland Landelijke richtlijn mammacarcinoom. https://www.oncoline.nl/borstkanker. Accessed 2019/22/09

  34. Wilson ARM, Marotti L, Bianchi S, Biganzoli L, Claassen S, Decker T, Frigerio A, Goldhirsch A, Gustafsson EG, Mansel RE, Orecchia R, Ponti A, Poortmans P, Regitnig P, Rosselli Del Turco M, Rutgers EJT, van Asperen C, Wells CA, Wengström Y, Cataliotti L (2013) The requirements of a specialist Breast Centre. Eur J Cancer 49:3579–3587. https://doi.org/10.1016/j.ejca.2013.07.017

    Article  CAS  PubMed  Google Scholar 

  35. Altman DG, Bland JM (1983) Measurement in Medicine: The Analysis of Method Comparison Studies. Journal of the Royal Statistical Society. Series D (The Statistician) 32:307–317. https://doi.org/10.2307/2987937

    Article  Google Scholar 

  36. Straver ME, Loo CE, Rutgers EJ, Oldenburg HS, Wesseling J, Vrancken Peeters MJ, Gilhuijs KG (2010) MRI-model to guide the surgical treatment in breast cancer patients after neoadjuvant chemotherapy. Ann Surg 251:701–707. https://doi.org/10.1097/SLA.0b013e3181c5dda3

    Article  PubMed  Google Scholar 

  37. Moreno A, Escobedo A, Benito E, Serra JM, Gumà A, Riu F (2002) Pathologic changes related to cmf primary chemotherapy in breast cancer. Breast Cancer Res Treat 75:119–125. https://doi.org/10.1023/A:1019607924403

    Article  CAS  PubMed  Google Scholar 

  38. Kim TH, Kang DK, Yim H, Jung YS, Kim KS, Kang SY (2012) Magnetic resonance imaging patterns of tumor regression after neoadjuvant chemotherapy in breast cancer patients: correlation with pathological response grading system based on tumor cellularity. J Comput Assisted Tomography. https://doi.org/10.1097/RCT.0b013e318246abf3

    Article  Google Scholar 

  39. Hylton NM, Blume JD, Bernreuter WK, Pisano ED, Rosen MA, Morris EA, Weatherall PT, Lehman CD, Newstead GM, Polin S, Marques HS, Esserman LJ, Schnall MD (2012) Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy–results from ACRIN 6657/I-SPY TRIAL. Radiology 263:663–672. https://doi.org/10.1148/radiol.12110748

    Article  PubMed  PubMed Central  Google Scholar 

  40. Eom HJ, Cha JH, Choi WJ, Chae EY, Shin HJ, Kim HH (2017) Predictive clinicopathologic and dynamic contrast-enhanced mri findings for tumor response to neoadjuvant chemotherapy in triple-negative breast cancer. AJR Am J Roentgenol 208:W225–W230. https://doi.org/10.2214/AJR.16.17125

    Article  PubMed  Google Scholar 

  41. Ko ES, Han BK, Kim RB, Ko EY, Shin JH, Hahn SY, Nam SJ, Lee JE, Lee SK, Im YH, Park YH (2013) Analysis of factors that influence the accuracy of magnetic resonance imaging for predicting response after neoadjuvant chemotherapy in locally advanced breast cancer. Ann Surg Oncol 20:2562–2568. https://doi.org/10.1245/s10434-013-2925-6

    Article  PubMed  Google Scholar 

  42. Taydas O, Durhan G, Akpinar MG, Basaran Demirkazik F (2019) Comparison of MRI and US in tumor size evaluation of breast cancer patients receiving neoadjuvant chemotherapy. Eur J Breast Health 15:119–124. https://doi.org/10.5152/ejbh.2019.4547

    Article  PubMed  PubMed Central  Google Scholar 

  43. Chen JH, Bahri S, Mehta RS, Carpenter PM, McLaren CE, Chen WP, Fwu PT, Hsiang DJ, Lane KT, Butler JA, Su MY (2014) Impact of factors affecting the residual tumor size diagnosed by MRI following neoadjuvant chemotherapy in comparison to pathology. J Surg Oncol 109:158–167. https://doi.org/10.1002/jso.23470

    Article  PubMed  Google Scholar 

  44. Guarneri V, Pecchi A, Piacentini F, Barbieri E, Dieci MV, Ficarra G, Tazzioli G, Frassoldati A, Battista R, Canossi B, Mauri C, D’Amico R, Conte P, Torricelli P (2011) Magnetic resonance imaging and ultrasonography in predicting infiltrating residual disease after preoperative chemotherapy in stage II-III breast cancer. Ann Surg Oncol 18:2150–2157. https://doi.org/10.1245/s10434-011-1590-x

    Article  PubMed  Google Scholar 

  45. Lee HJ, Song IH, Seo AN, Lim B, Kim JY, Lee JJ, Park IA, Shin J, Yu JH, Ahn JH, Gong G (2015) Correlations between molecular subtypes and pathologic response patterns of breast cancers after neoadjuvant chemotherapy. Ann Surg Oncol 22:392–400. https://doi.org/10.1245/s10434-014-4054-2

    Article  PubMed  Google Scholar 

  46. McGuire KP, Toro-Burguete J, Dang H, Young J, Soran A, Zuley M, Bhargava R, Bonaventura M, Johnson R, Ahrendt G (2011) MRI staging after neoadjuvant chemotherapy for breast cancer: does tumor biology affect accuracy? Ann Surg Oncol 18:3149–3154. https://doi.org/10.1245/s10434-011-1912-z

    Article  PubMed  Google Scholar 

  47. Kim S-Y, Cho N, Park I-A, Kwon BR, Shin SU, Kim SY, Lee SH, Chang JM, Moon WK (2018) Dynamic contrast-enhanced breast MRI for evaluating residual tumor size after neoadjuvant chemotherapy. Radiology 289:327–334. https://doi.org/10.1148/radiol.2018172868

    Article  PubMed  Google Scholar 

  48. Marinovich ML, Houssami N, Macaskill P, Sardanelli F, Irwig L, Mamounas EP, von Minckwitz G, Brennan ME, Ciatto S (2013) Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after neoadjuvant therapy. JNCI 105:321–333. https://doi.org/10.1093/jnci/djs528

    Article  CAS  PubMed  Google Scholar 

  49. Fukuda T, Horii R, Gomi N, Miyagi Y, Takahashi S, Ito Y, Akiyama F, Ohno S, Iwase T (2016) Accuracy of magnetic resonance imaging for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy: association with breast cancer subtype. Springerplus 5:152. https://doi.org/10.1186/s40064-016-1800-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Negrão EMS, Souza JA, Marques EF, Bitencourt AGV (2019) Breast cancer phenotype influences MRI response evaluation after neoadjuvant chemotherapy. Eur J Radiol 120:108701. https://doi.org/10.1016/j.ejrad.2019.108701

    Article  PubMed  Google Scholar 

  51. Chen J-H, Bahri S, Mehta RS, Kuzucan A, Yu HJ, Carpenter PM, Feig SA, Lin M, Hsiang DJ, Lane KT (2011) Breast cancer: evaluation of response to neoadjuvant chemotherapy with 3.0-T MR imaging. Radiology 261:735–743. https://doi.org/10.1148/radiol.11110814

    Article  PubMed  PubMed Central  Google Scholar 

  52. Denis F, Desbiez-Bourcier AV, Chapiron C, Arbion F, Body G, Brunereau L (2004) Contrast enhanced magnetic resonance imaging underestimates residual disease following neoadjuvant docetaxel based chemotherapy for breast cancer. Eur J Surg Oncol 30:1069–1076. https://doi.org/10.1016/j.ejso.2004.07.024

    Article  CAS  PubMed  Google Scholar 

  53. Lyou CY, Cho N, Kim SM, Jang M, Park JS, Baek SY, Moon WK (2011) Computer-aided evaluation of breast MRI for the residual tumor extent and response monitoring in breast cancer patients receiving neoadjuvant chemotherapy. Korean J Radiol 12:34–43. https://doi.org/10.3348/kjr.2011.12.1.34

    Article  PubMed  PubMed Central  Google Scholar 

  54. Sogani J, Mango VL, Keating D, Sung JS, Jochelson MS (2021) Contrast-enhanced mammography: past, present, and future. Clin Imaging 69:269–279. https://doi.org/10.1016/j.clinimag.2020.09.003

    Article  PubMed  Google Scholar 

  55. Bernardi D, Vatteroni G, Acquaviva A, Valentini M, Sabatino V, Bolengo I, Pellegrini M, Fantò C, Trimboli RM (2022) Contrast-enhanced mammography versus MRI in the evaluation of neoadjuvant therapy response in patients with breast cancer: a prospective study. AJR Am J Roentgenol 219:884–894. https://doi.org/10.2214/ajr.22.27756

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Surgical Oncology, Isala Zwolle, Dokter Van Heesweg 2, 8025 AB, Zwolle, the Netherlands

    K. K. Rajan, C. Boersma, M. A. Beek, T. A. Berendsen, A. B. Francken & E. M. Noorda

  2. Department of Pathology, Isala Zwolle, Zwolle, the Netherlands

    J. van der Starre-Gaal

  3. Department of Radiology, Isala Zwolle, Zwolle, the Netherlands

    M. van ’t Veer-ten Kate

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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by ABF, CB and EMN. The first draft of the manuscript was written by KKR and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Rajan, K.K., Boersma, C., Beek, M.A. et al. Optimizing surgical strategy in locally advanced breast cancer: a comparative analysis between preoperative MRI and postoperative pathology after neoadjuvant chemotherapy. Breast Cancer Res Treat 203, 477–486 (2024). https://doi.org/10.1007/s10549-023-07122-8

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