JOURNAL ARTICLE

Differentiation of breast tuberculosis and breast cancer using diffusion-weighted, T2-weighted and dynamic contrast-enhanced magnetic resonance imaging

D. P. RamaemaRichard Hift

Year: 2018 Journal:   South African Journal of Radiology Vol: 22 (2)Pages: 1377-1377   Publisher: AOSIS

Abstract

Background: The use of multi-parametric magnetic resonance imaging (MRI) in the evaluation of breast tuberculosis (BTB).Objectives: To evaluate the value of diffusion-weighted imaging (DWI), T2-weighted (T2W) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating breast cancer (BCA) from BTB.Method: We retrospectively studied images of 17 patients with BCA who had undergone preoperative MRI and 6 patients with pathologically proven BTB who underwent DCE-MRI during January 2014 to January 2015.Results: All patients were female, with the age range of BTB patients being 23–43 years and the BCA patients being 31–74 years. Breast cancer patients had a statistically significant lower mean apparent diffusion coefficient (ADC) value (1072.10 +/- 365.14), compared to the BTB group (1690.77 +/- 624.05, p = 0.006). The mean T2-weighted signal intensity (T2SI) was lower for the BCA group (521.56 +/- 233.73) than the BTB group (787.74 +/- 196.04, p = 0.020). An ADC mean cut-off value of 1558.79 yielded 66% sensitivity and 94% specificity, whilst the T2SI cut-off value of 790.20 yielded 83% sensitivity and 83% specificity for differentiating between BTB and BCA. The homogeneous internal enhancement for focal mass was seen in BCA patients only.Conclusion: Multi-parametric MRI incorporating the DWI, T2W and DCE-MRI may be a useful tool to differentiate BCA from BTB.

Keywords:
Medicine Magnetic resonance imaging Breast cancer Effective diffusion coefficient Nuclear medicine Diffusion MRI Breast MRI Dynamic contrast Radiology Cancer Mammography Internal medicine

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Citation History

Topics

Radiomics and Machine Learning in Medical Imaging
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging
MRI in cancer diagnosis
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging
Medical Imaging Techniques and Applications
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging

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