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Apparent diffusion coefficient mapping using diffusion-weighted MRI: impact of background parenchymal enhancement, amount of fibroglandular tissue and menopausal status on breast cancer diagnosis

  • Breast
  • Published:
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Abstract

Objectives

To investigate the impact of background parenchymal enhancement (BPE), amount of fibroglandular tissue (FGT) and menopausal status on apparent diffusion coefficient (ADC) values in differentiation between malignant and benign lesions.

Methods

In this HIPAA-compliant study, mean ADC values of 218 malignant and 130 benign lesions from 288 patients were retrospectively evaluated. The differences in mean ADC values between benign and malignant lesions were calculated within groups stratified by BPE level (high/low), amount of FGT (dense/non-dense) and menopausal status (premenopausal/postmenopausal). Sensitivities and specificities for distinguishing malignant from benign lesions within different groups were compared for statistical significance.

Results

The mean ADC value for malignant lesions was significantly lower compared to that for benign lesions (1.07±0.21 x 10−3 mm2/s vs. 1.53±0.26 x 10−3 mm2/s) (p<0.0001). Using the optimal cut-off point of 1.30 x 10−3 mm2/s, an area under the curve of 0.918 was obtained, with sensitivity and specificity both of 87 %. There was no statistically significant difference in sensitivities and specificities of ADC values between different groups stratified by BPE level, amount of FGT or menopausal status.

Conclusions

Differentiation between benign and malignant lesions on ADC values is not significantly affected by BPE level, amount of FGT or menopausal status.

Key Points

• ADC allows differentiation between benign and malignant lesions.

• ADC is useful for breast cancer diagnosis despite different patient characteristics.

• BPE, FGT or menopause do not significantly affect sensitivity and specificity.

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Abbreviations

ADC:

Apparent diffusion coefficient

AUC:

Area under the curve

BIRADS:

Breast Imaging Reporting and Data System

BPE:

Background parenchymal enhancement

DWI:

Diffusion-weighted imaging

DCE:

Dynamic contrast-enhancement

FGT:

Fibroglandular tissue

MRI:

Magnetic resonance imaging

ROC:

Receiving operator characteristic

SD:

Standard deviation

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Acknowledgements

We would like to thank Joanne Chin for technical editing.

Funding

This study has received funding by Memorial Sloan Kettering Cancer Center Support Grant / NIH Core Grant (P30 CA008748), DOD BCRP W81XWH-09-1-0042 grant, and the Breast Cancer Research Foundation grant of Memorial Sloan Kettering Cancer Center.

Author information

Author notes

  1. Joao V. Horvat and Manuela Durando contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Joao V. Horvat, Manuela Durando, Soledad Milans, Jessica Massler, Girard Gibbons, Katja Pinker, Elizabeth A. Morris & Sunitha B. Thakur

  2. Department of Diagnostic Imaging and Radiotherapy, A. O. U. Città della Salute e della Scienza di Torino, Turin, Italy

    Manuela Durando

  3. Hospital de Clínicas, University of the Republic, Montevideo, Uruguay

    Soledad Milans

  4. Department of Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Sujata Patil

  5. Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Jessica Massler

  6. Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Dilip Giri

  7. Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria

    Katja Pinker

  8. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 00 East 66th Street, New York, NY, 10065, USA

    Sunitha B. Thakur

Authors
  1. Joao V. Horvat
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  2. Manuela Durando
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  7. Dilip Giri
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  9. Elizabeth A. Morris
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  10. Sunitha B. Thakur
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Corresponding author

Correspondence to Sunitha B. Thakur.

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Guarantor

The scientific guarantor of this publication is Sunitha B. Thakur.

Conflict of interest

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.

Statistics and biometry

One of the authors has significant statistical expertise (Sujata Patil).

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

Some study subjects or cohorts have been previously reported in Durando M, Gennaro L, Cho GY et al (2016) Quantitative apparent diffusion coefficient measurement obtained by 3.0Tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer. Eur J Radiol 85:1651-1658. However, different data were used in a different context.

Methodology

• retrospective

• observational

• performed at one institution

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Horvat, J.V., Durando, M., Milans, S. et al. Apparent diffusion coefficient mapping using diffusion-weighted MRI: impact of background parenchymal enhancement, amount of fibroglandular tissue and menopausal status on breast cancer diagnosis. Eur Radiol 28, 2516–2524 (2018). https://doi.org/10.1007/s00330-017-5202-4

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  • DOI: https://doi.org/10.1007/s00330-017-5202-4

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