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Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
MRI-visualized T2 hyperintense breast lesions: identifying clinical and imaging factors linked to malignant biopsy
Mary Beth Bissell1, Sareh Keshavarsi2, Rachel Fleming3
1Department of Radiology, Radiation Oncology and Medical Physics, University of Ottawa, 501 Smyth Rd, Ottawa, ON, K1S 2H6, Canada.
Purpose:
To determine the malignancy rate for MRI-guided breast biopsies performed for T2 hyperintense breast lesions and to assess additional clinical and MRI characteristics that can predict benign and malignant outcomes.
Methods:
A retrospective chart review of consecutive MRI-guided breast biopsies performed in two tertiary hospitals was conducted over two years. Biopsies performed for T2 hyperintense lesions were selected, and further lesion imaging characteristics and patient risk factors were collected. Univariate and multivariate modeling regression were used to determine additional imaging and patient factors associated with malignant outcomes for biopsies of T2 hyperintense lesions.
Results:
Out of 369 MRI-guided breast biopsies, 100 (27%) were performed for T2 hyperintense lesions. Two biopsy-proven benign lesions were excluded as the patient was lost on follow-up. With a study cohort of 98 lesions, the final pathology results were benign for 80 (80%) of these lesions, while 18 (18%) were malignant. Using multivariate logistic modeling, patient age > 50 (OR 5.99 (1.49, 24.08 95% CI), p < 0.05) and lesion size > 3 cm (OR 5.54 (1.54-18.7), p < 0.01) were found to be important predictors of malignant outcomes for MRI biopsies performed for T2 hyperintense lesions.
Conclusion:
Our study observed a high malignancy rate, challenging the assumption that T2 hyperintensity can be considered a benign imaging characteristic for otherwise suspicious MRI-detected lesions. Decision-making regarding tissue sampling should be made based on a thorough evaluation of more reliable additional demographic and imaging factors, including patient age and lesion size.

