AI Summary & Key Takeaways
AI InsightOverall, 35 lesions out of 58 were histopathologicallyproven to be malignant.
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Abstract
Background: Magnetic resonance imaging (MRI)has become a diagnostic and problem solving methodfor the breast examinations in addition to conventionalbreast examination methods. Diffusion-weightedimaging (DWI) adds valuable information to conventionalMRI.Aims: Our aim was to show the impact of apparentdiffusion coefficient (ADC) values acquired withDWI 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 Tclinical MRI scanner. The morphologic characteristicsof the lesions on conventional MRI sequences andcontrast uptake pattern were assessed. ADC valuesof both lesions and normal breast parenchyma weremeasured. The ADC values obtained were statisticallycompared with the histopathologic results usingPaired Samples t-Test.Results: Multiple lesions were detected in 12 (26%)of the patients, while only one lesion was detected in34 (74%). Overall, 35 lesions out of 58 were histopathologicallyproven to be malignant. In the dynamiccontrast-enhanced series, 5 of the malignant lesionswere type 1, while 8 benign lesions revealed eithertype 2 or 3 time signal intensity curves (85% sensitivity,56% spesifity). Mean ADC values were significantlydifferent in malignant vs. benign lesions.(1.04±0.29x10-3 cm2/sec vs. 1.61±0.50x10-3 cm2/secfor the malignant and benign lesions, respectively,p=0.03). A cut-off value of 1.30x10-3 mm2/sec forADC detected with receiver operating characteristicanalysis yielded 89.1% sensitivity and 100% specificityfor the differentiation between benign and malignantlesions.Conclusion: ADC values improve the diagnostic accuracyof solid breast lesions when evaluated with theconventional MRI sequences. Therefore, DWI shouldbe incorporated to routine breast MRI protocol.