Background: Magnetic resonance imaging (MRI) has become a diagnostic and problem solving method for the breast examinations in addition to conventional breast examination methods. Diffusion-weighted imaging (DWI) adds valuable information to conventional MRI. Aims: Our aim was to show the impact of apparent diffusion coefficient (ADC) values acquired with DWI to differentiate benign and malignant breast lesions. Study Design: Diagnostic accuracy study. Methods: Forty-six women with 58 breast masses (35 malignant, 23 benign) were examined on a 1.5 T clinical MRI scanner. The morphologic characteristics of the lesions on conventional MRI sequences and contrast uptake pattern were assessed. ADC values of both lesions and normal breast parenchyma were measured. The ADC values obtained were statistically compared with the histopathologic results using Paired Samples t-Test. Results: Multiple lesions were detected in 12 (26%) of the patients, while only one lesion was detected in 34 (74%). Overall, 35 lesions out of 58 were histopathologically proven to be malignant. In the dynamic contrast-enhanced series, 5 of the malignant lesions were type 1, while 8 benign lesions revealed either type 2 or 3 time signal intensity curves (85% sensitivity, 56% spesifity). Mean ADC values were significantly different in malignant vs. benign lesions. (1.04±0.29x10-3 cm2/sec vs. 1.61±0.50x10-3 cm2/sec for the malignant and benign lesions, respectively, p=0.03). A cut-off value of 1.30x10-3 mm2/sec for ADC detected with receiver operating characteristic analysis yielded 89.1% sensitivity and 100% specificity for the differentiation between benign and malignant lesions. Conclusion: ADC values improve the diagnostic accuracy of solid breast lesions when evaluated with the conventional MRI sequences. Therefore, DWI should be incorporated to routine breast MRI protocol.
Apparent diffusion coefficient value breast magnetic resonance imaging diffusion-weighted imaging
Other ID | JA72ZZ42RE |
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Journal Section | Research Article |
Authors | |
Publication Date | May 1, 2016 |
Published in Issue | Year 2016 Volume: 33 Issue: 3 |