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Early prediction of response to neoadjuvant chemotherapy in breast cancer patients: comparison of single-voxel 1H-magnetic resonance spectroscopy and 18F-fluorodeoxyglucose positron emission tomography

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Abstract

Objectives

To prospectively compare performances of single-voxel proton magnetic resonance spectroscopy (1H-MRS) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) in predicting pathologic response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

Methods

Thirty-five breast cancer patients who received NAC and subsequent surgery were prospectively enrolled. MRS and FDG-PET were performed before and after the 1st NAC cycle. Percentage changes of total choline-containing compounds (tCho) via MRS, and maximum and peak standardized uptake values (SUVmax, SUVpeak) and total lesion glycolysis (TLG) via FDG-PET were measured, and their performances in predicting pathologic complete response (pCR) were compared.

Results

Of the 35 patients, 6 showed pCR and 29 showed non-pCR. Mean % reductions of tCho, SUVmax, SUVpeak, and TLG of the pCR group were larger than those of the non-pCR group (-80.3 ± 13.9 % vs. -32.1 ± 49.4 %, P = 0.025; -54.7 ± 22.1 % vs. -26.3 ± 33.7 %, P = 0.058; -60.7 ± 18.3 % vs. -32.3 ± 23.3 %, P = 0.009; -89.5 ± 8.5 % vs. -52.6 ± 36.2 %, P = 0.020). Diagnostic accuracy (area under ROC curve; Az, 0.911) of the % reduction of tCho was comparable to those of %SUVmax (0.822), SUVpeak (0.862), and TLG (0.879) in distinguishing pCR from non-pCR (all P > 0.05).

Conclusion

MRS showed comparable performance to FDG-PET in early prediction of pCR in breast cancer patients.

Key points

• MRS can predict response to NAC in breast cancer post-1 st cycle.

• Changes in tCho and SUV after NAC reflect tumour cellularity changes.

• MRS can be an alternative to FDG-PET in predicting response to NAC.

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Abbreviations

NAC:

Neoadjuvant chemotherapy

H-MRS:

Proton magnetic resonance spectroscopy

FDG-PET:

18F- fluorodeoxyglucose positron emission tomography

pCR:

Pathologic complete response

MRI:

Magnetic resonance imaging

tCho:

Total choline-containing compounds

SUV:

Standardized uptake value

TLG:

Total lesion glycolysis

References

  1. Chia S, Swain SM, Byrd DR et al (2008) Locally advanced and inflammatory breast cancer. J Clin Oncol 26:786–790

    Article  PubMed  Google Scholar 

  2. Buchholz TA, Lehman CD, Harris JR et al (2008) Statement of the science concerning locoregional treatments after preoperative chemotherapy for breast cancer: a National Cancer Institute Conference. J Clin Oncol 26:791–797

    Article  PubMed  Google Scholar 

  3. Von Minckwitz G, Kaufmann M, Kuemmel S, for the GBG and AGO-B Study Groups et al (2011) Correlation of various pathologic complete response (pCR) definitions with long-term outcome and the prognostic value of pCR in various breast cancer subtypes: results from the German neoadjuvant meta-analysis. J Clin Oncol 29:1028

  4. Kaufmann M, von Minckwitz G, Mamounas EP et al (2012) Recommendations from an international consensus conference on the current status and future of neoadjuvant systemic therapy in primary breast cancer. Ann Surg Oncol 19:1508–1516

    Article  PubMed  Google Scholar 

  5. von Minckwitz G, Blohmer JU, Costa SD et al (2013) Response-guided neoadjuvant chemotherapy for breast cancer. J Clin Oncol 31:3623–3630

    Article  Google Scholar 

  6. Hylton NM, Blume JD, Bernreuter WK et al (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

    Article  PubMed  PubMed Central  Google Scholar 

  7. Rieber A, Brambs HJ, Gabelmann A, Heilmann V, Kreienberg R, Kuhn T (2002) Breast MRI for monitoring response of primary breast cancer to neoadjuvant chemotherapy. Eur Radiol 12:1711–1719

    Article  CAS  PubMed  Google Scholar 

  8. Rousseau C, Devillers A, Sagan C et al (2006) Monitoring of early response to neoadjuvant chemotherapy in stage II and III breast cancer by [18F]fluorodeoxyglucose positron emission tomography. J Clin Oncol 24:5366–5372

    Article  PubMed  Google Scholar 

  9. Schwarz-Dose J, Untch M, Tiling R et al (2009) Monitoring primary systemic therapy of large and locally advanced breast cancer by using sequential positron emission tomography imaging with [18F]fluorodeoxyglucose. J Clin Oncol 27:535–541

    Article  PubMed  Google Scholar 

  10. Meisamy S, Bolan PJ, Baker EH et al (2004) Neoadjuvant chemotherapy of locally advanced breast cancer: predicting response with in vivo (1)H MR spectroscopy--a pilot study at 4 T. Radiology 233:424–431

    Article  PubMed  Google Scholar 

  11. Baek HM, Chen JH, Nie K et al (2009) Predicting pathologic response to neoadjuvant chemotherapy in breast cancer by using MR imaging and quantitative 1H MR spectroscopy. Radiology 251:653–662

    Article  PubMed  PubMed Central  Google Scholar 

  12. Danishad KKA, Sharma U, Sah RG, Seenu V, Parshad R, Jagannathan NR (2010) Assessment of therapeutic response of locally advanced breast cancer (LABC) patients undergoing neoadjuvant chemotherapy (NACT) monitored using sequential magnetic resonance spectroscopic imaging (MRSI). NMR Biomed 23:233–241

    CAS  PubMed  Google Scholar 

  13. Tozaki M, Sakamoto M, Oyama Y et al (2008) Monitoring of early response to neoadjuvant chemotherapy in breast cancer with (1)H MR spectroscopy: comparison to sequential 2-[18F]-fluorodeoxyglucose positron emission tomography. J Magn Reson Imaging 28:420–427

    Article  PubMed  Google Scholar 

  14. Cho N, Im SA, Park IA et al (2014) Breast cancer: early prediction of response to neoadjuvant chemotherapy using parametric response maps for MR imaging. Radiology 272:385–396

    Article  PubMed  Google Scholar 

  15. Tozaki M, Sakamoto M, Oyama Y, Maruyama K, Fukuma E (2010) Predicting pathological response to neoadjuvant chemotherapy in breast cancer with quantitative 1H MR spectroscopy using the external standard method. J Magn Reson Imaging 31:895–902

    Article  PubMed  Google Scholar 

  16. Wahl RL, Jacene H, Kasamon Y, Lodge MA (2009) From RECIST to PERCIST: evolving considerations for PET response criteria in solid tumors. J Nucl Med 50(Suppl 1):122S–150S

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Lopci E, Zucali PA, Ceresoli GL et al (2015) Quantitative analyses at baseline and interim PET evaluation for response assessment and outcome definition in patients with malignant pleural mesothelioma. Eur J Nucl Med Mol Imaging 42:667–675

    Article  PubMed  Google Scholar 

  18. Im HJ, Kim YK, Kim YI, Lee JJ, Lee WW, Kim SE (2013) Usefulness of combined metabolic-volumetric indices of (18)F-FDG PET/CT for the early prediction of neoadjuvant chemotherapy outcomes in breast cancer. Nucl Med Mol Imaging 47:36–43

    Article  CAS  PubMed  Google Scholar 

  19. Ogston KN, Miller ID, Payne S et al (2003) A new histological grading system to assess response of breast cancers to primary chemotherapy: prognostic significance and survival. Breast 12:320–327

    Article  PubMed  Google Scholar 

  20. Silver DP, Richardson AL, Eklund AC et al (2010) Efficacy of neoadjuvant Cisplatin in triple-negative breast cancer. J Clin Oncol 28:1145–1153

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Jung SY, Kim SK, Nam BH et al (2010) Prognostic impact of [18F] FDG-PET in operable breast cancer treated with neoadjuvant chemotherapy. Ann Surg Oncol 17:247–253

    Article  PubMed  Google Scholar 

  22. Connolly RM, Leal JP, Goetz MP et al (2015) TBCRC 008: early change in 18F-FDG uptake on PET predicts response to preoperative systemic therapy in human epidermal growth factor receptor 2-negative primary operable breast cancer. J Nucl Med 56:31–37

    Article  PubMed  Google Scholar 

  23. Ah-See ML, Makris A, Taylor NJ et al (2008) Early changes in functional dynamic magnetic resonance imaging predict for pathologic response to neoadjuvant chemotherapy in primary breast cancer. Clin Cancer Res 14:6580–6589

    Article  CAS  PubMed  Google Scholar 

  24. Li SP, Makris A, Beresford MJ et al (2011) Use of dynamic contrast-enhanced MR Imaging to predict survival in patients with primary breast cancer undergoing neoadjuvant chemotherapy. Radiology 260:68–78

    Article  PubMed  Google Scholar 

  25. Tateishi U, Miyake M, Nagaoka T et al (2012) Neoadjuvant chemotherapy in breast cancer: prediction of pathologic response with PET/CT and dynamic contrast-enhanced MR imaging--prospective assessment. Radiology 263:53–63

    Article  PubMed  Google Scholar 

  26. Pengel KE, Koolen BB, Loo CE et al (2014) Combined use of 18F-FDG PET/CT and MRI for response monitoring of breast cancer during neoadjuvant chemotherapy. Eur J Nucl Med Mol Imaging 41:1515–1524

    Article  CAS  PubMed  Google Scholar 

  27. Lim I, Noh WC, Park J et al (2014) The combination of FDG PET and dynamic contrast-enhanced MRI improves the prediction of disease-free survival in patients with advanced breast cancer after the first cycle of neoadjuvant chemotherapy. Eur J Nucl Med Mol Imaging 41:1852–1860

    Article  CAS  PubMed  Google Scholar 

  28. An YY, Kim SH, Kang BJ, Lee AW (2015) Treatment response evaluation of breast cancer after neoadjuvant chemotherapy and usefulness of the imaging parameters of MRI and PET/CT. J Korean Med Sci 30:808–815

    Article  PubMed  PubMed Central  Google Scholar 

  29. Aboagye EO, Bhujwalla ZM (1999) Malignant transformation alters membrane choline phospholipid metabolism of human mammary epithelial cells. Cancer Res 59:80–84

    CAS  PubMed  Google Scholar 

  30. Glunde K, Bhujwalla ZM, Ronen SM (2011) Choline metabolism in malignant transformation. Nat Rev Cancer 11:835–848

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Kolesnikov-Gauthier H, Vanlemmens L, Baranzelli MC et al (2012) Predictive value of neoadjuvant chemotherapy failure in breast cancer using FDG-PET after the first course. Breast Cancer Res Treat 131:517–525

    Article  CAS  PubMed  Google Scholar 

  32. Young H, Baum R, Cremerius U et al (1999) Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. European Organization for Research and Treatment of Cancer (EORTC) PET Study Group. Eur J Cancer 35:1773–1782

    Article  CAS  PubMed  Google Scholar 

  33. Begley JK, Redpath TW, Bolan PJ, Gilbert FJ (2012) In vivo proton magnetic resonance spectroscopy of breast cancer: a review of the literature. Breast Cancer Res 14:207

  34. Sardanelli F, Fausto A, Di Leo G, de Nijs R, Vorbuchner M, Podo F (2009) In vivo proton MR spectroscopy of the breast using the total choline peak integral as a marker of malignancy. AJR Am J Roentgenol 192:1608–1617

    Article  PubMed  Google Scholar 

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Acknowledgments

The scientific guarantor of this publication is Woo Kyung Moon. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2014R1A1A2053682), and by a grant (no. 03-2014-0320) from the Seoul National University Hospital Research Fund, and the Korea Healthcare Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (grant A070001). Some patients have been reported previously in Breast Cancer: Early Prediction of Response to Neoadjuvant Chemotherapy Using Parametric Response Maps for MR Imaging. Radiology 2014;272:385-396. No complex statistical methods were necessary for this paper. Institutional review board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Methodology: prospective, diagnostic or prognostic study, performed at one institution.

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Authors and Affiliations

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

    Nariya Cho, In Chan Song & Woo Kyung Moon

  2. Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 110-799, Republic of Korea

    Nariya Cho & Woo Kyung Moon

  3. Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea

    Nariya Cho & Woo Kyung Moon

  4. Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea

    Seock-Ah Im, Kyung-Hun Lee & Tae-Yong Kim

  5. Department of Nuclear Medicine, Seoul National College of Medicine, Seoul, Republic of Korea

    Keon Wook Kang, Hyunjong Lee, In Kook Chun & Hai-Jeon Yoon

  6. Cancer Research Institute, Seoul National University, Seoul, Republic of Korea

    Keon Wook Kang

  7. Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea

    In-Ae Park

  8. Department of Nuclear Medicine, School of Medicine, Kangwon National University, Chuncheon, Gangwon-do, Republic of Korea

    In Kook Chun

  9. Department of Nuclear Medicine, Ewha Woman’s University, Seoul, Republic of Korea

    Hai-Jeon Yoon

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  1. Nariya Cho
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Correspondence to Woo Kyung Moon.

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Cho, N., Im, SA., Kang, K.W. et al. Early prediction of response to neoadjuvant chemotherapy in breast cancer patients: comparison of single-voxel 1H-magnetic resonance spectroscopy and 18F-fluorodeoxyglucose positron emission tomography. Eur Radiol 26, 2279–2290 (2016). https://doi.org/10.1007/s00330-015-4014-7

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  • DOI: https://doi.org/10.1007/s00330-015-4014-7

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