Objective: To describe magnetic resonance imaging (MRI) and ultrasonography findings of breast stromal fibrosis (SF) and compare apparent diffusion coefficient (ADC) stromal fibrosis values with breast cancer and normal parenchyma.

Methods: 45 patients (ages 22‒74) with histopathologically proven SF who underwent MRI were included in this study. Their MRI and ultrasonography features were examined and categorized. The mean ADC values for SF, contralateral normal parenchyma, and breast malignancy of the control group values were calculated and compared among each other.

Results: The vast majority of SF on sonography showed features suggestive of malignancy: (1) irregular in shape 25/45 (55%); (2) indistinct in margin 27/45 (60%); and (3) hypoechoic 39/45 (87%) with posterior acoustic shadowing 11/45 (24%). An SF MRI showed a mass in 12/45 (26%) and non-mass enhancement in 33/45 (74%), mostly with irregular (8/12; 67%) shape. Non-mass lesions showed heterogeneous (12/33), clumped (9/33), and homogenous (9/33) enhancement. The initial SF contrast uptake rate varied between slow (57%), rapid (22%), and medium (21%). Delayed SF enhancement may be persistent (66%) or plateau (34%). Small cysts were located around/near 21 (47%) of lesions. Ductal ectasia was found in 14 (31%) of all patients. Mean ADCs of parenchyma, SF, and malignancy were 1.32 ± 0.32, 1.23 ± 0.25, and 0.99 ± 0.24 × 10 mm sec, respectively.

Conclusion: SF often mimics breast carcinoma on imaging and leads the radiology‒pathology disagreement. In terms of distinguishing SF from malignancy, ADC could be a significant and promising value in diffusion-weighted MRI along with conventional sequences. Slow initial uptake with delayed persistent contrast enhancement in a non-mass lesion with relatively higher ADC values are very helpful for differentiating SF from malignancy. The presence of small cysts and ductal ectasia were common findings around/near the SF. Advances in knowledge: A quantitative analysis for measuring ADC values along with additional MRI features can be very helpful in distinguishing SF from malignant lesions.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190782PMC
http://dx.doi.org/10.1259/bjr.20170706DOI Listing

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