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Assessing response in breast cancer with dynamic contrast-enhanced magnetic resonance imaging: Are signal intensity–time curves adequate?

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Abstract

Quantitative DCE-MRI parameters including Ktrans (transfer constant min−1) can predict both response and outcome in breast cancer patients treated with neoadjuvant chemotherapy (NAC). Quantitative methods are time-consuming to calculate, requiring expensive software and interpretive expertise. For diagnostic purposes, signal intensity–time curves (SITCs) are used for tissue characterisation. In this study, we compare the ability of NAC-related changes in SITCs with Ktrans to predict response and outcomes. 73 women with primary breast cancer underwent DCE-MRI studies before and after two cycles of NAC. Patients received anthracycline and/or docetaxel-based chemotherapy. At completion of NAC, patients had local treatment with surgery & radiotherapy and further systemic treatments. SITCs for paired DCE-MRI studies were visually scored using a five-curve type classification schema encompassing wash-in and wash-out phases and correlated with Ktrans values and to the endpoints of pathological response, OS and DFS. 58 paired patients studies were evaluable. The median size by MRI measurement for 52 tumours was 38 mm (range 17–86 mm) at baseline and 26 mm (range 10–85 mm) after two cycles of NAC. Median baseline Ktrans (min−1) was 0.214 (range 0.085–0.469), and post-two cycles of NAC was 0.128 (range 0.013–0.603). SITC shapes were significantly related to Ktrans values both before (χ 2 = 43.3, P = 0.000) and after two cycles of NAC (χ 2 = 60.5, P = 0.000). Changes in curve shapes were significantly related to changes in Ktrans (χ 2 = 53.5, P = 0.000). Changes in curve shape were significantly correlated with clinical (P = 0.005) and pathological response (P = 0.005). Reductions in curve shape of ≥1 point were significant for overall improved survival using Kaplan–Meier analysis with a 5-year OS of 80.9 versus 68.6 % (P = 0.048). SITCs require no special software to generate and provide a useful method of assessing the effectiveness of NAC for primary breast cancer.

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Acknowledgments

We acknowledge the Breast Cancer Campaign and the Breast Cancer Research Trust for providing funding for this study.

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None to declare

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Authors and Affiliations

  1. Academic Department of Oncology, Mount Vernon Cancer Centre, Northwood, UK

    David K. Woolf, Sonia P. Li, Mei-Lin Ah-See & Andreas Makris

  2. Paul Strickland Scanner Centre, Mount Vernon Hospital, Northwood, UK

    Anwar R. Padhani, N. Jane Taylor, Andrew Gogbashian & James Stirling

  3. Royal United Hospital Bath, Bath, UK

    Mark J. Beresford

  4. CR-UK and EPSRC Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, UK

    David J. Collins

Authors
  1. David K. Woolf
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  2. Anwar R. Padhani
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  10. Andreas Makris
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Correspondence to David K. Woolf.

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Woolf, D.K., Padhani, A.R., Taylor, N.J. et al. Assessing response in breast cancer with dynamic contrast-enhanced magnetic resonance imaging: Are signal intensity–time curves adequate?. Breast Cancer Res Treat 147, 335–343 (2014). https://doi.org/10.1007/s10549-014-3072-x

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  • DOI: https://doi.org/10.1007/s10549-014-3072-x

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