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Diffusion-weighted imaging of breast lesions: Region-of-interest placement and different ADC parameters influence apparent diffusion coefficient values

  • Breast
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Abstract

Objectives

To investigate the influence of region-of-interest (ROI) placement and different apparent diffusion coefficient (ADC) parameters on ADC values, diagnostic performance, reproducibility and measurement time in breast tumours.

Methods

In this IRB-approved, retrospective study, 149 histopathologically proven breast tumours (109 malignant, 40 benign) in 147 women (mean age 53.2) were investigated. Three radiologists independently measured minimum, mean and maximum ADC, each using three ROI placement approaches:1 – small 2D-ROI, 2 – large 2D-ROI and 3 – 3D-ROI covering the whole lesion. One reader performed all measurements twice. Median ADC values, diagnostic performance, reproducibility, and measurement time were calculated and compared between all combinations of ROI placement approaches and ADC parameters.

Results

Median ADC values differed significantly between the ROI placement approaches (p < .001). Minimum ADC showed the best diagnostic performance (AUC .928–.956), followed by mean ADC obtained from 2D ROIs (.926–.94). Minimum and mean ADC showed high intra- (ICC .85–.94) and inter-reader reproducibility (ICC .74–.94). Median measurement time was significantly shorter for the 2D ROIs (p < .001).

Conclusions

ROI placement significantly influences ADC values measured in breast tumours. Minimum and mean ADC acquired from 2D-ROIs are useful for the differentiation of benign and malignant breast lesions, and are highly reproducible, with rapid measurement.

Key Points

• Region of interest placement significantly influences apparent diffusion coefficient of breast tumours.

• Minimum and mean apparent diffusion coefficient perform best and are reproducible.

• 2D regions of interest perform best and provide rapid measurement times.

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Abbreviations

ADC:

Apparent diffusion coefficient

AUC:

Area under the curve

CE:

Contrast enhanced

CI:

Confidence interval

DCIS:

Ductal carcinoma in situ

DWI:

Diffusion weighted imaging

EPI:

Echo planar imaging

ICC:

Intra-class correlation

IDC:

Invasive ductal carcinoma

ILC:

Invasive lobular carcinoma

IPC:

Intraductal papillary carcinoma

MPR:

Multiplanar reconstruction

MRI:

Magnetic resonance imaging

ROC:

Receiver operating characteristics

ROI:

Region of interest

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Acknowledgments

The scientific guarantor of this publication is Thomas Helbich. 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. This study has received funding by projects no. 13652 funded by Austrian National Bank ‘Jubilaeumsfond’ and no. 10029 funded by the Medical-Scientific Funds of the Mayor of Vienna.

One of the authors (Pascal Baltzer) has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Approval from the institutional animal care committee was not required because no animals were involved in this study. Some study subjects or cohorts have been previously reported in:

Pinker K, Bickel H, Helbich TH, et al. Combined contrast-enhanced magnetic resonance and diffusion-weighted imaging reading adapted to the "Breast Imaging Reporting and Data System" for multiparametric 3-T imaging of breast lesions. Eur Radiol. 2013;23(7):1791-802. (n = 85)

Pinker K, Bogner W, Baltzer P, et al. Improved diagnostic accuracy with multiparametric magnetic resonance imaging of the breast using dynamic contrast-enhanced magnetic resonance imaging, diffusion-weighted imaging and 3-dimensional proton magnetic resonance spectroscopic imaging. Investigative radiology. 2014;49(6):421-30. (n = 52)

Pinker K, Bogner W, Baltzer P, et al. Improved differentiation of benign and malignant breast tumours with multiparametric 18fluorodeoxyglucose positron emission tomography magnetic resonance imaging: a feasibility study. Clinical cancer research : an official journal of the American Association for Cancer Research. 2014;20(13):3540-9. (n = 39)

Bickel H, Pinker-Domenig K, Bogner W, et al. Quantitative apparent diffusion coefficient as a noninvasive imaging biomarker for the differentiation of invasive breast cancer and ductal carcinoma in situ. Investigative radiology. 2015;50(2):95-100. (n = 83)

Methodology: retrospective, diagnostic or prognostic study, performed at one institution.

Author information

Authors and Affiliations

  1. Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria

    Hubert Bickel, Katja Pinker, Stephan Polanec, Heinrich Magometschnigg, Georg Wengert, Claudio Spick, Thomas H. Helbich & Pascal Baltzer

  2. Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna – MR Center of Excellence, Vienna, Austria

    Wolfgang Bogner

  3. Department of Pathology, Medical University Vienna, Vienna, Austria

    Zsuzsanna Bago-Horvath

Authors
  1. Hubert Bickel
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Correspondence to Thomas H. Helbich.

Electronic supplementary material

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Supplemental Table 1

Results of the ROC analysis comparing the different measurement approaches. Note: Differences in the AUC are shown in the upper right triangle; the corresponding p-values are presented in the lower left triangle. Non-significant results are highlighted in gray. Abbreviations: ROC – receiver operating characteristics; AUC – area under the curve; Min – minimum; Max – maximum. (DOCX 74 kb)

Supplemental Table 2

Results of the ROC analysis comparing the different measurement approaches, divided by mass/non-mass enhancement. Note: Non-significant results are highlighted in gray. Abbreviations: ROC – receiver operating characteristics; AUC – area under the curve; SD – standard deviation; Min – minimum; Max – maximum. (DOCX 72 kb)

Supplemental Table 3

Results of the ROC analysis comparing the different measurement approaches in mass lesions only. Note: Differences in the AUC are shown in the upper right triangle; the corresponding p-values are presented in the lower left triangle. Non-significant results are highlighted in gray. Abbreviations: ROC – receiver operating characteristics; AUC – area under the curve; Min – minimum; Max – maximum. (DOCX 87 kb)

Supplemental Table 4

Results of the ROC analysis comparing the different measurement approaches in non-mass lesions only. Note: Differences in the AUC are shown in the upper right triangle; the corresponding p-values are presented in the lower left triangle. Non-significant results are highlighted in gray. Abbreviations: ROC – receiver operating characteristics; AUC – area under the curve; Min – minimum; Max – maximum (DOCX 84 kb)

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Bickel, H., Pinker, K., Polanec, S. et al. Diffusion-weighted imaging of breast lesions: Region-of-interest placement and different ADC parameters influence apparent diffusion coefficient values. Eur Radiol 27, 1883–1892 (2017). https://doi.org/10.1007/s00330-016-4564-3

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  • DOI: https://doi.org/10.1007/s00330-016-4564-3

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