Non-mass Enhancement in Breast MRI: Characterization with BI-RADS Descriptors and ADC Values

Breast Magnetic Resonance Imaging Non-mass Enhancement Diffusion-weighted Imaging.

Authors

  • Wolfgang Buchberger
    wolfgang.buchberger@umit.at
    1) Institute of Quality and Efficiency in Medicine, UMIT - University for Health Sciences, Medical Informatics and Technology, A-6060 Hall in Tirol, Austria. 3) Department of Radiology, Medical University of Innsbruck, A-6020 Innsbruck,, Austria
  • Willi Oberaigner Institute of Public Health, Medical Decision Making and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology, A-6060 Hall in Tirol,, Austria
  • Christian Kremser Department of Radiology, Medical University of Innsbruck, A-6020 Innsbruck,, Austria
  • Kurt Gautsch Radiology Institute Dr. Schöpf, A-6500 Landeck,, Austria
  • Uwe Siebert 2) Institute of Public Health, Medical Decision Making and HTA, UMIT - University for Health Sciences, Medical Informatics and Technology, A-6060 Hall in Tirol, Austria. 5) Harvard T. H. Chan School of Public Health, Center for Health Decision Science and Department of Health Policy and Management, Boston, MA 02115, United States. 6) Massachusetts General Hospital, Harvard Medical School, Institute for Technology Assessment and Department of Radiology, Boston, MA 02114,, United States
Vol. 3 No. 2 (2021): June
Research Articles

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Objectives: The purpose of this study was to assess the accuracy of contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging in distinguishing benign from malignant non-mass-like breast lesions. Methods: 103 lesions showing non-mass-like enhancement in 100 consecutive patients were analyzed. Distribution, internal enhancement patterns, and contrast kinetic curve patterns were classified according to the BI-RADS lexicon. Apparent diffusion coefficient (ADC) values were obtained from manually placed regions of interest (ROIs) on diffusion-weighted images. The optimal ADC value threshold for the distinction between benign and malignant lesions was determined by ROC analysis. Univariate and multivariate analyses were performed to identify independent predictors of malignancy, and the probability of malignancy was calculated for various combinations of findings. Histological diagnosis obtained by means of core needle biopsy was used as gold standard. Results: According to the univariate and multivariate analysis, odds ratios for malignancy were significantly elevated for clumped or clustered ring internal enhancement and low ADC values (p < 0.001), whereas distribution patterns and contrast kinetic patterns were not significantly correlated with benignity or malignancy. In non-mass lesions with homogeneous or heterogeneous internal enhancement and ADC values greater than 1.26×10-3mm2/s, no malignancy was detected, while all other combinations of findings had a probability of malignancy ranging from 22.2 to 76.6%. Conclusions: A combination of BI-RADS descriptors of internal enhancement and ADC values is useful for the differential diagnosis of lesions showing non-mass enhancement. Lesions with homogeneous or heterogeneous enhancement and high ADC can be followed up, while all other lesions should be biopsied.

 

Doi: 10.28991/SciMedJ-2021-0302-1

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