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Role of DCE-MR in predicting breast cancer subtypes

  • BREAST RADIOLOGY
  • Published:
La radiologia medica Aims and scope Submit manuscript

Abstract

Objective

The purpose of this retrospective study is to find a correlation between dynamic contrast-enhanced MR features with histological, immunohistochemical and loco-regional characteristics of breast cancer.

Materials and methods

A total of 149 patients with histopathologically confirmed invasive breast carcinoma underwent MR imaging. Histological analysis included: histological features (histological type, necrosis, vascular invasion and Mib-1), immunohistochemical characterization (immunophenotype, receptor status, HER2-neu and grading) and loco-regional characteristics (T and N). The kinetic MR features analyzed were: curve type, maximum enhancement, time to peak, wash-in and wash-out rate, brevity of enhancement and area under curve.

Results

MRI kinetic parameters and immunohistological features were compared using chi square test, two-tailed student t test and Anova test, with p = 0.05 level of significance. Vascular invasion was shown to be significantly related to time to peak (p = 0.02). The immunohistotype was shown to be significantly related with maximum enhancement (p = 0.05), time to peak (p = 0.04) and wash-in rate (p = 0.01). ER status correlates with maximum and relative enhancement (p = 0.004 and p = 0.028), wash-in rate (p = 0.0018) and area under curve (p = 0.006). PR status was significantly related to time to peak (p = 0.048) and wash-in rate (p = 0.05).

Conclusion

Maximum enhancement absolute and relative, time to peak, wash-in rate and area under the curve significantly correlate with several prognostic factors, like ER status, immune profile and tumoral vascular invasion, and may predict the aggressiveness of the tumor.

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Authors and Affiliations

  1. Sc. Spec. Radiologia, Università Politecnica delle Marche, Ancona, Italy

    Marco Macchini & Martina Ponziani

  2. DiSCO, Università Politecnica delle Marche, Ancona, Italy

    Andrea Prochowski Iamurri

  3. Azienda Ospedaliero Universitaria Ospedali Riuniti Clinica di Oncologia, Università Politecnica delle Marche, Ancona, Italy

    Mirco Pistelli, Mariagrazia De Lisa & Rossana Berardi

  4. Azienda Ospedaliero Universitaria Ospedali Riuniti Clinica di Radiologia, Università Politecnica delle Marche, Ancona, Italy

    Gian Marco Giuseppetti

  5. Dipartimento Radiologia Clinica, Ospedali Riuniti Azienda Ospedaliero Universitaria Ospedali Riuniti, Via Tronto 10, 60126, Ancona, AN, Italy

    Gian Marco Giuseppetti

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  1. Marco Macchini
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  2. Martina Ponziani
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  5. Mariagrazia De Lisa
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Correspondence to Marco Macchini.

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All authors declare that they have no conflict of interest.

Research involving human participants and/or animals

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Informed consent for this retrospective study is waived.

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Macchini, M., Ponziani, M., Iamurri, A.P. et al. Role of DCE-MR in predicting breast cancer subtypes. Radiol med 123, 753–764 (2018). https://doi.org/10.1007/s11547-018-0908-1

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  • DOI: https://doi.org/10.1007/s11547-018-0908-1

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