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European Radiology
Published in: European Radiology 9/2013

01-09-2013 | BREAST

Diffusion-weighted MRI in pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer

Authors: Raphael Richard, Isabelle Thomassin, Marion Chapellier, Aurélie Scemama, Patricia de Cremoux, Mariana Varna, Sylvie Giacchetti, Marc Espié, Eric de Kerviler, Cedric de Bazelaire

Published in: European Radiology | Issue 9/2013

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Abstract

Purpose

To evaluate the accuracy of the apparent diffusion coefficient (ADC) provided by diffusion-weighted imaging (DWI) in predicting the response to neoadjuvant chemotherapy (NACT) at baseline in patients according to their breast tumour phenotypes.

Materials & methods

This retrospective study was approved by our institutional review board. One hundred eighteen consecutive women with locally advanced breast cancer who had undergone NACT followed by breast surgery were included. DWI was performed at 1.5 T less than 2 weeks before NACT. We studied the correlation between pretreatment ADC and response in pathology after surgery according to immunohistochemical features and intrinsic subtypes (luminal A, luminal B, HER2-enriched, and triple-negative tumours).

Results

After surgery, the pathologist recognized 24 complete responders (CRps) and 94 non-complete responders (NCRps). No difference was identified between the pretreatment ADCs of the CRp and NCRp patients. There were differences in pretreatment ADCs among the luminal A (1.001 ± 0.143 × 10−3 mm2/s), luminal B (0.983 ± 0.150 × 10−3 mm2/s), HER2-enriched (1.132 ± 0.216 × 10−3 mm2/s), and triple-negative (1.168 ± 0.245 × 10−3 mm2/s; P = 0.0003) tumour subtypes. In triple-negative tumours, the pretreatment ADC was higher in NCRp (1.060 ± 0.143 × 10−3 mm2/s) than in CRp patients (1.227 ± 0.271 × 10−3 mm2/s; P = 0.047).

Conclusion

Pretreatment ADC can predict the response of breast cancer to NACT if tumour subtypes are considered.
Key Points
• Apparent diffusion coefficient helps clinicians to assess patients with breast cancer.
• Pretreatment ADC is related to tumour grade and hormone receptor status.
• Pretreatment ADC is lower in luminal A and B than in triple-negative tumours.
• Pretreatment ADC is higher in complete than in non-complete responders to neoadjuvant chemotherapy.
Literature
1.
Davidson NE, Morrow M (2005) Sometimes a great notion—an assessment of neoadjuvant systemic therapy for breast cancer. J Natl Cancer Inst 97:159–161PubMedCrossRef
2.
Chia S, Swain SM, Byrd DR, Mankoff DA (2008) Locally advanced and inflammatory breast cancer. J Clin Oncol 26:786–790PubMedCrossRef
3.
Rastogi P, Anderson SJ, Bear HD et al (2008) Preoperative chemotherapy: updates of National Surgical Adjuvant Breast and Bowel Project Protocols B-18 and B-27. J Clin Oncol 26:778–785PubMedCrossRef
4.
Fisher ER, Wang J, Bryant J, Fisher B, Mamounas E, Wolmark N (2002) Pathobiology of preoperative chemotherapy: findings from the National Surgical Adjuvant Breast and Bowel (NSABP) protocol B-18. Cancer 95:681–695PubMedCrossRef
5.
Perou CM, Sorlie T, Eisen MB et al (2000) Molecular portraits of human breast tumours. Nature 406:747–752PubMedCrossRef
6.
Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thurlimann B, Senn HJ (2011) Strategies for subtypes—dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol 22:1736–1747PubMedCrossRef
7.
Huober J, von Minckwitz G, Denkert C et al (2010) Effect of neoadjuvant anthracycline-taxane-based chemotherapy in different biological breast cancer phenotypes: overall results from the GeparTrio study. Breast Cancer Res Treat 124:133–140PubMedCrossRef
8.
Martincich L, Montemurro F, Cirillo S et al (2003) Role of magnetic resonance imaging in the prediction of tumor response in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy. Radiol Med 106:51–58PubMed
9.
Martincich L, Montemurro F, De Rosa G et al (2004) Monitoring response to primary chemotherapy in breast cancer using dynamic contrast-enhanced magnetic resonance imaging. Breast Cancer Res Treat 83:67–76PubMedCrossRef
10.
Partridge SC, Gibbs JE, Lu Y et al (2005) MRI measurements of breast tumor volume predict response to neoadjuvant chemotherapy and recurrence-free survival. AJR Am J Roentgenol 184:1774–1781PubMedCrossRef
11.
Yu HJ, Chen JH, Mehta RS, Nalcioglu O, Su MY (2007) MRI measurements of tumor size and pharmacokinetic parameters as early predictors of response in breast cancer patients undergoing neoadjuvant anthracycline chemotherapy. J Magn Reson Imaging 26:615–623PubMedCrossRef
12.
Loo CE, Teertstra HJ, Rodenhuis S et al (2008) Dynamic contrast-enhanced MRI for prediction of breast cancer response to neoadjuvant chemotherapy: initial results. AJR Am J Roentgenol 191:1331–1338PubMedCrossRef
13.
Padhani AR, Liu G, Koh DM et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125PubMed
14.
Park SH, Moon WK, Cho N et al (2012) Comparison of diffusion-weighted MR imaging and FDG PET/CT to predict pathological complete response to neoadjuvant chemotherapy in patients with breast cancer. Eur Radiol 22:18–25PubMedCrossRef
15.
Woodhams R, Kakita S, Hata H et al (2010) Identification of residual breast carcinoma following neoadjuvant chemotherapy: diffusion-weighted imaging–comparison with contrast-enhanced MR imaging and pathologic findings. Radiology 254:357–366PubMedCrossRef
16.
17.
Bogner W, Gruber S, Pinker K et al (2009) Diffusion-weighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis? Radiology 253:341–351PubMedCrossRef
18.
Pereira FP, Martins G, Figueiredo E et al (2009) Assessment of breast lesions with diffusion-weighted MRI: comparing the use of different b values. AJR Am J Roentgenol 193:1030–1035PubMedCrossRef
19.
Le Bihan D (1988) Intravoxel incoherent motion imaging using steady-state free precession. Magn Reson Med 7:346–351PubMedCrossRef
20.
Koh DM, Collins DJ (2007) Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 188:1622–1635PubMedCrossRef
21.
Bloom HJ, Richardson WW (1957) Histological grading and prognosis in breast cancer; a study of 1409 cases of which 359 have been followed for 15 years. Br J Cancer 11:359–377PubMedCrossRef
22.
Wolff AC, Hammond ME, Schwartz JN et al (2007) 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 25:118–145PubMedCrossRef
23.
Flaman JM, Frebourg T, Moreau V et al (1995) A simple p53 functional assay for screening cell lines, blood, and tumors. Proc Natl Acad Sci U S A 92:3963–3967PubMedCrossRef
24.
Waridel F, Estreicher A, Bron L et al (1997) Field cancerisation and polyclonal p53 mutation in the upper aero-digestive tract. Oncogene 14:163–169PubMedCrossRef
25.
Cheang MC, Chia SK, Voduc D et al (2009) Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst 101:736–750PubMedCrossRef
26.
Hugh J, Hanson J, Cheang MC et al (2009) Breast cancer subtypes and response to docetaxel in node-positive breast cancer: use of an immunohistochemical definition in the BCIRG 001 trial. J Clin Oncol 27:1168–1176PubMedCrossRef
27.
Penault-Llorca F, Andre F, Sagan C et al (2009) Ki67 expression and docetaxel efficacy in patients with estrogen receptor-positive breast cancer. J Clin Oncol 27:2809–2815PubMedCrossRef
28.
Chevallier B, Roche H, Olivier JP, Chollet P, Hurteloup P (1993) Inflammatory breast cancer. Pilot study of intensive induction chemotherapy (FEC-HD) results in a high histologic response rate. Am J Clin Oncol 16:223–228PubMedCrossRef
29.
Sataloff DM, Mason BA, Prestipino AJ, Seinige UL, Lieber CP, Baloch Z (1995) Pathologic response to induction chemotherapy in locally advanced carcinoma of the breast: a determinant of outcome. J Am Coll Surg 180:297–306PubMed
30.
Curigliano G, Goldhirsch A (2011) The triple-negative subtype: new ideas for the poorest prognosis breast cancer. J Natl Cancer Inst Monogr 2011:108–110PubMedCrossRef
31.
Iacconi C, Giannelli M, Marini C et al (2010) The role of mean diffusivity (MD) as a predictive index of the response to chemotherapy in locally advanced breast cancer: a preliminary study. Eur Radiol 20:303–308PubMedCrossRef
32.
Park SH, Moon WK, Cho N et al (2010) Diffusion-weighted MR imaging: pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer. Radiology 257:56–63PubMedCrossRef
33.
Li XR, Cheng LQ, Liu M et al (2012) DW-MRI ADC values can predict treatment response in patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy. Med Oncol 29:425–431PubMedCrossRef
34.
Fangberget A, Nilsen LB, Hole KH et al (2011) Neoadjuvant chemotherapy in breast cancer-response evaluation and prediction of response to treatment using dynamic contrast-enhanced and diffusion-weighted MR imaging. Eur Radiol 21:1188–1199PubMedCrossRef
35.
Nilsen L, Fangberget A, Geier O, Olsen DR, Seierstad T (2010) Diffusion-weighted magnetic resonance imaging for pretreatment prediction and monitoring of treatment response of patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy. Acta Oncol 49:354–360PubMedCrossRef
36.
Prevos R, Smidt ML, Tjan-Heijnen VC et al (2012) Pre-treatment differences and early response monitoring of neoadjuvant chemotherapy in breast cancer patients using magnetic resonance imaging: a systematic review. Eur Radiol 22:2607–2616PubMedCrossRef
37.
Park S, Koo JS, Kim MS et al (2012) Characteristics and outcomes according to molecular subtypes of breast cancer as classified by a panel of four biomarkers using immunohistochemistry. Breast 21:50–57PubMedCrossRef
38.
Carey LA, Dees EC, Sawyer L et al (2007) The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin Cancer Res 13:2329–2334PubMedCrossRef
39.
Wang S, Yang H, Tong F et al (2009) Response to neoadjuvant therapy and disease free survival in patients with triple-negative breast cancer. Gan To Kagaku Ryoho 36:255–258PubMed
40.
Rouzier R, Perou CM, Symmans WF et al (2005) Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin Cancer Res 11:5678–5685PubMedCrossRef
41.
Dent R, Trudeau M, Pritchard KI et al (2007) Triple-negative breast cancer: clinical features and patterns of recurrence. Clin Cancer Res 13:4429–4434PubMedCrossRef
42.
Yau C, Esserman L, Moore DH, Waldman F, Sninsky J, Benz CC (2010) A multigene predictor of metastatic outcome in early stage hormone receptor-negative and triple-negative breast cancer. Breast Cancer Res 12:R85PubMedCrossRef
43.
Kuo WH, Chang YY, Lai LC et al (2012) Molecular characteristics and metastasis predictor genes of triple-negative breast cancer: a clinical study of triple-negative breast carcinomas. PLoS One 7:e45831PubMedCrossRef
44.
Wenkel E, Geppert C, Schulz-Wendtland R et al (2007) Diffusion weighted imaging in breast MRI: comparison of two different pulse sequences. Acad Radiol 14:1077–1083PubMedCrossRef
45.
Woodhams R, Ramadan S, Stanwell P et al (2011) Diffusion-weighted imaging of the breast: principles and clinical applications. Radiographics 31:1059–1084PubMedCrossRef
46.
Razek AA, Gaballa G, Denewer A, Nada N (2010) Invasive ductal carcinoma: correlation of apparent diffusion coefficient value with pathological prognostic factors. NMR Biomed 23:619–623PubMedCrossRef
47.
Sasaki Y, Tsuda H (2009) Clinicopathological characteristics of triple-negative breast cancers. Breast Cancer 16:254–259PubMedCrossRef
48.
Tokunaga E, Okada S, Yamashita N et al (2012) High incidence and frequency of LOH are associated with aggressive features of high-grade HER2 and triple-negative breast cancers. Breast Cancer 19:161–169PubMedCrossRef
49.
Goble S, Bear HD (2003) Emerging role of taxanes in adjuvant and neoadjuvant therapy for breast cancer: the potential and the questions. Surg Clin N Am 83:943–971PubMedCrossRef
50.
Von Minckwitz G, Loibl S, Untch M (2012) What is the current standard of care for anti-HER2 neoadjuvant therapy in breast cancer? Oncology (Williston Park) 26:20–26
51.
Caudle AS, Gonzalez-Angulo AM, Hunt KK et al (2011) Impact of progression during neoadjuvant chemotherapy on surgical management of breast cancer. Ann Surg Oncol 18:932–938PubMedCrossRef
52.
Pickles MD, Gibbs P, Lowry M, Turnbull LW (2006) Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer. Magn Reson Imaging 24:843–847PubMedCrossRef
53.
Sharma U, Danishad KK, Seenu V, Jagannathan NR (2009) Longitudinal study of the assessment by MRI and diffusion-weighted imaging of tumor response in patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy. NMR Biomed 22:104–113PubMedCrossRef
54.
de Bazelaire C, Calmon R, Thomassin I et al (2011) Accuracy of perfusion MRI with high spatial but low temporal resolution to assess invasive breast cancer response to neoadjuvant chemotherapy: a retrospective study. BMC Cancer 11:361PubMedCrossRef
55.
Yankeelov TE, Lepage M, Chakravarthy A et al (2007) Integration of quantitative DCE-MRI and ADC mapping to monitor treatment response in human breast cancer: initial results. Magn Reson Imaging 25:1–13PubMedCrossRef
56.
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 14:6580–6589PubMedCrossRef
57.
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 28:320–328PubMedCrossRef
58.
Partridge SC, Ziadloo A, Murthy R et al (2010) Diffusion tensor MRI: preliminary anisotropy measures and mapping of breast tumors. J Magn Reson Imaging 31:339–347PubMedCrossRef
59.
Baltzer PA, Schafer A, Dietzel M et al (2011) Diffusion tensor magnetic resonance imaging of the breast: a pilot study. Eur Radiol 21:1–10PubMedCrossRef
Metadata
Title
Diffusion-weighted MRI in pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer
Authors
Raphael Richard
Isabelle Thomassin
Marion Chapellier
Aurélie Scemama
Patricia de Cremoux
Mariana Varna
Sylvie Giacchetti
Marc Espié
Eric de Kerviler
Cedric de Bazelaire
Publication date
01-09-2013
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 9/2013
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-013-2850-x

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