Breast Cancer Research and Treatment

, Volume 91, Issue 1, pp 1–10 | Cite as

Role of dynamic contrast enhanced MRI in monitoring early response of locally advanced breast cancer to neoadjuvant chemotherapy

  • Martin D. Pickles
  • Martin Lowry
  • David J. Manton
  • Peter Gibbs
  • Lindsay W. Turnbull


Neoadjuvant chemotherapy has become the standard treatment for patients with locally advanced breast cancer; however a technique that can accurately differentiate responders from non-responders at an early time point during treatment has still to be identified. The purpose of this work was to evaluate the ability of pharmacokinetically modelled dynamic contrast-enhanced MRI data to predict and monitor response of patients diagnosed with locally advanced breast cancer to neoadjuvant chemotherapy, at an early time point during treatment. Sixty-eight patients with histology proven breast cancer underwent MRI examination prior to treatment, early during treatment and following the final cycle of chemotherapy. A two compartment pharmacokinetic model provided the kinetic parameters transfer constant (Ktrans), rate constant (Kep) and extracellular extravascular space (Ve) for a region of interest encompassing the whole lesion (ROIwhole) and a 3 × 3 pixel ‘hot-spot’ showing the greatest mean maximum percentage enhancement from within that region (ROIhs). Following treatment 48 patients were classified as responders and 20 as non-responders based on total tumour volume reduction. Tumour volume changes between the pre-treatment and early treatment time points demonstrated differences between responders and non-responders with percentage change revealing the most significant result (p < 0.001). Analysis based on ROIhsprovided more statistically significant differences between responders and non-responders then ROIwhole analysis. ROIhs analysis demonstrated differences between responders and non-responders both prior to and early during treatment. A highly significant reduction in both Ktrans and Kep (p < 0.001) was noted for responders between the pre-treatment and early treatment time points, while Ve significantly increased during the same time period for non-responders (p < 0.001). Quantification of dynamic contrast enhancement parameters provides a potential means for differentiating responders from non-responders early during their treatment, thereby allowing a prompt change in treatment if necessary.


breast cancer Kep Ktrans neoadjuvant pharmacokinetic response Ve 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Booser, DJ, Hortobagyi, GN. 1992Treatment of locally advanced breast-cancerSemin Oncol19278285PubMedGoogle Scholar
  2. 2.
    Kuerer, HM, Newman, LA, Buzdar, AU, Dhingra, K, Hunt, KK, Buchholz, TA, Binkley, SM, Strom, EA, Ames, FC, Ross, MI, Feig, BW, McNeese, , Hortobagyi, GN, Singletary, SE. 1998Pathologic tumor response in the breast following neoadjuvant chemotherapy predicts axillary lymph node statusCancer J Scientific Am4230236Google Scholar
  3. 3.
    Kuerer, HM, Singletary, SE, Buzdar, AU, Ames, FC, Valero, V, Buchholz, TA, Ross, MI, Pusztai, L, Hortobagyi, GN, Hunt, KK. 2003Surgical conservation planning after neoadjuvant chemotherapy for stage II and operable stage III breast carcinomaAm J Surg182601608CrossRefGoogle Scholar
  4. 4.
    Feldman, LD, Hortobagyi, GN, Buzdar, AU, Ames, FC, Blumenschein, GR. 1986Pathological assessment of response to induction chemotherapy in breast-cancerCancer Res4625782581PubMedGoogle Scholar
  5. 5.
    Cocquyt, VF, Villeirs, GM, Blondeel, PN, Depypere, HT, Mortier, MM, Serreyn, RF, Broecke, R, Belle, SJP 2002Assessment of response to preoperative chemotherapy in patients with stage II and III breast cancer: the value of MRIBreast11306315CrossRefGoogle Scholar
  6. 6.
    Gilles, R, Guinebretiere, JM, Toussaint, C, Spielman, M, Rietjens, M, Petit, JY, Contesso, G. 1994Local advanced breast-cancer – Contrast-enhanced subtraction MR-imaging of response to preoperative chemotherapyRadiology191633638PubMedGoogle Scholar
  7. 7.
    Trecate, G, Ceglia, E, Stabile, F, Tesoro-Tess, JD, Mariani, G, Zambetti, M, Musumeci, R. 1999Locally advanced breast cancer treated with primary chemotherapy: comparison between magnetic resonance imaging and pathologic evaluation of residual diseaseTumori85220228PubMedGoogle Scholar
  8. 8.
    Drew, PJ, Kerin, MJ, Mahapatra, T, Malone, C, Monson, JRT, Turnbull, LW, Fox, JN. 2001Evaluation of response to neoadjuvant chemoradiotherapy for locally advanced breast cancer with dynamic contrast-enhanced MRI of the breastEuropean J Surg Oncol27617620CrossRefGoogle Scholar
  9. 9.
    Padhani, AR. 2002Functional MRI for anticancer therapy assessmentEur J Cancer3821162127CrossRefPubMedGoogle Scholar
  10. 10.
    Hayes, C, Padhani, AR, Leach, MO. 2002Assessing changes in tumour vascular function using dynamic contrast-enhanced magnetic resonance imagingNMR Biomed15154163CrossRefPubMedGoogle Scholar
  11. 11.
    Brix, G, Semmler, W, Port, R, Schad, LR, Layer, G, Lorenz, WJ. 1991Pharmacokinetic parameters in CNS Gd-DTPA enhanced MR imagingJ Compu Assis Tomogr15621628CrossRefGoogle Scholar
  12. 12.
    Therasse, P, Arbuck, SG, Eisenhauer, EA, Wanders, J, Kaplan, RS, Rubinstein, L, Verweij, J, Glabbeke, M, Oosterom, AT, Christian, MC, Gwyther, SG. 2000New guidelines to evaluate the response to treatment in solid tumorsJ Nat Cancer Ins92205216CrossRefGoogle Scholar
  13. 13.
    Bland, JM, Altman, DG. 1986Statistical-methods for assessing agreement between 2 methods of clinical measurementLancet1307310PubMedGoogle Scholar
  14. 14.
    George, ML, Dzik-Jurasz, ASK, Padhani, AR, Brown, G, Tait, DM, Eccles, SA, Swift, RI. 2001Non-invasive methods of assessing angiogenesis and their value in predicting response to treatment in colorectal cancerBr J Surg8816281636CrossRefPubMedGoogle Scholar
  15. 15.
    Padhani AR, Hayes C, Assersohn L, Powles TJ, Leach MO, Husband JE: Response of breast carcinoma to chemotherapy – MR permeanbility changes using histogram analysis. Proceedings of the 8th International Society for Magnetic Resonance in Medicine. Denver, April 1–7 2000, p 2160Google Scholar
  16. 16.
    Wasser, K, Klein, SK, Fink, C, Junkermann, H, Sinn, HP, Zuna, I, Knopp, MV, Delorme, S. 2003Evaluation of neoadjuvant chemotherapeutic response of breast cancer using dynamic MRI with high temporal resolutionEur Radiol138087PubMedGoogle Scholar
  17. 17.
    Delille, JP, Slaneta, PJ, Yeh, ED, Halpern, EF, Kopans, DB, Garrido, L. 2003Invasive ductal breast carcinoma response to neoadjuvant chemotherapy: Noninvasive monitoring with functional MR imaging – Pilot studyRadiology2286369PubMedGoogle Scholar
  18. 18.
    Hawighorst, H, Knopp, MV, Debus, J, Hoffmann, U, Grandy, M, Griebel, J, Zuna, I, Essig, M, Schoenberg, SO, Vries, A, Brix, G, Kaick, GV. 1998Pharmacokinetic MRI for assessment of malignant glioma response to stereotactic radiotherapy: initial resultsJ Magn Reson Imaging8783788PubMedGoogle Scholar
  19. 19.
    Loncaster, JA, Carrington, BM, Sykes, JR, Jones, AP, Todd, SM, Cooper, R, Buckley, DL, Davidson, SE, Logue, JP, Hunter, RD, West, CML 2002Prediction of radiotherapy outcome using dynamic contrast enhanced MRI of carcinoma of the cervixInt J Radiat Oncol Biol Phy54759767CrossRefGoogle Scholar
  20. 20.
    Ah-See MW, Taylor NJ, Makris A, Burcombe J, Stirling JJ, Cladd HJ, Leach MO, Padhani A: Preliminary evaluation of multi-functional MRI to predict response to neoadjuvant chemotherapy in primary breast cancer. American Society of Clinical Oncology 39th Annual Meeting, Chicago, 31 May-3 June 2003, p 556Google Scholar
  21. 21.
    Ah-See MW, Makris A, Taylor NJ, Harrison M, Richman P, Arcy JAD, Burcombe RJ, Pittam MR, Ravichandran D, Stirling JJ, Cladd HJ, Leach MO, Padhani AR: Multi-functional magnetic resonance imaging predicts for clinico-pathological response to neoadjuvant chemotherapy in primary breast cancer. 26th Annual San Antonio Breast Cancer Symposium, San Antonio, 3–6 December 2003, p 252Google Scholar
  22. 22.
    Galbraith, SM, Maxwell, RJ, Lodge, MA, Tozer, GM, Wilson, J, Taylor, NJ, Stirling, JJ, Sena, L, Padhani, AR, Rustin, GJS 2003Combretastatin A4 phosphate has tumor antivascular activity in rat and man as demonstrated by dynamic magnetic resonance imagingJ Clin Oncol2128312842CrossRefPubMedGoogle Scholar
  23. 23.
    Yamashita, Y, Baba, T, Baba, Y, Nishimura, R, Ikeda, S, Takahashi, M, Ohtake, H, Okamura, H 2000Dynamic contrast-enhanced MR imaging of uterine cervical cancer: pharmacokinetic analysis with histopathologic correlation and its importance in predicting the outcome of radiation therapyRadiology216803809PubMedGoogle Scholar
  24. 24.
    Wasser, K, Sinn, HP, Fink, C, Klein, SK, Junkermann, H, Ludemann, HP, Zuna, I, Delorme, S 2003Accuracy of tumor size measuremen in breast cancer using MRI is influenced by histological regression induced by neoadjuvant chemotherapyEur Radiol1312131223PubMedGoogle Scholar
  25. 25.
    Knowles, HJ, Harris, AL 2001Hypoxia and oxidative stress in breast cancer – Hypoxia and tumourigenesisBreast Cancer Res3318322CrossRefPubMedGoogle Scholar
  26. 26.
    Pugh, CW, Gleadle, J, Maxwell, PH 2001Hypoxia and oxidative stress in breast cancer – Hypoxia signalling pathwaysBreast Cancer Res3313317CrossRefPubMedGoogle Scholar
  27. 27.
    Seagroves, TN, Ryan, HE, Lu, H, Wouters, BG, Knapp, M, Thibault, P, Laderoute, K, Johnson, RS 2001Transcription factor HIF-1 is a necessary mediator of the Pasteur effect in mammalian cellsMol Cell Biol2134363444CrossRefPubMedGoogle Scholar
  28. 28.
    Loncaster, JA, Carrington, BM, Sykes, JR, Jones, AP, Todd, SM, Cooper, R, Buckley, DL, Davidson, SE, Logue, JP, Hunter, RD, West, CML 2002Prediction of radiotherapy outcome using dynamic contrast enhanced MRI of carcinoma of the cervixInt J Radiat Oncol Biol Phys54759767CrossRefPubMedGoogle Scholar
  29. 29.
    Gullino, PM, Grantham, FH, Smith, SH 1965The interstitial water space of tumoursCancer Res25727731PubMedGoogle Scholar
  30. 30.
    Jakobsen, I, Lyng, H, Kaalhus, O, Rofstad, EK 1995MRI of human tumor xenografts In-Vivo – proton relaxation-times and extracellular tumor volumeMagn Reson Imaging13693700CrossRefPubMedGoogle Scholar
  31. 31.
    Mussurakis, S, Buckley, DL, Horsman, A 1997Dynamic MRI of invasive breast cancer: assessment of three region-of-interest analysis methodsJ Comput Assist Tomogr21431438CrossRefPubMedGoogle Scholar
  32. 32.
    Liney, GP, Gibbs, P, Hayes, C, Leach, MO, Turnbull, LW 1999Dynamic contrast-enhanced MRI in the differentiation of breast tumors: user-defined versus semi-automated region-of-interest analysisJ Magn Reson Imaging10945949CrossRefPubMedGoogle Scholar
  33. 33.
    Su, MY, Cheung, YC, Fruehauf, JP, Yu, H, Nalcioglu, O, Mechetner, E, Kyshtoobayeva, A, Chen, SC, Hsueh, S, McLaren, CE, Wan, YL 2003Correlation of dynamic contrast enhancement MRI parameters with microvessel density and VEGF for assessment of angiogenesis in breast cancerJ Magn Reson Imaging18467477CrossRefPubMedGoogle Scholar
  34. 34.
    Buckley, DL, Drew, PJ, Mussurakis, S, Monson, JRT, Horsman, A 1997Microvessel density in invasive breast cancer assessed by dynamic Gd-DTPA enhanced MRIJ Magn Reson Imaging7461464PubMedGoogle Scholar
  35. 35.
    Kuhl, CK 2000MRI of breast tumorsEur Radiol104658CrossRefPubMedGoogle Scholar
  36. 36.
    Boetes, C, Strijk, SP, Holland, R, Barentsz, JO, VanderSluis, RF, Ruijs, JHJ 1997False-negative MR imaging of malignant breast tumorsEur Radiol712311234CrossRefPubMedGoogle Scholar
  37. 37.
    Tofts, PB. 2003Quantitative MRI of the BrainJohn Wiley & Sons LtdChichester341364Google Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  • Martin D. Pickles
    • 1
    • 2
  • Martin Lowry
    • 1
  • David J. Manton
    • 1
  • Peter Gibbs
    • 1
  • Lindsay W. Turnbull
    • 1
  1. 1.Post-graduate Medical School, Division of Cancer, Centre for Magnetic Resonance InvestigationsUniversity of HullUK
  2. 2.Centre for Magnetic Resonance InvestigationsHull Royal InfirmaryHullUK

Personalised recommendations