OBJECTIVE: The purpose of our study was to assess the utility of the minimum apparent diffusion coefficient (ADC), average ADC, maximum ADC, and ADC difference value and to find optimum ADC parameters for differentiation between benign and malignant lesions in breast diffusion-weighted imaging (DWI). MATERIALS AND METHODS: Sixty-seven women with 75 masslike lesions (27 benign, 48 malignant) were examined with 3-T MRI. To assess heterogeneity within the lesion, the difference between minimum and maximum ADCs was recorded as the ADC difference value. Diagnostic performances of these parameters were compared by receiver operating characteristic (ROC) curve analysis. RESULTS: Each ADC parameter showed significant differences between malignant and benign lesions. The optimal cutoff levels for differentiating benign versus malignant lesions were determined by identifying the points where the sensitivity and specificity were equal on the ROC curves. According to ROC analyses, the following sensitivities and specificities were obtained: average ADC, 75.6% and 75.6%; minimum ADC, 85.5% and 85.5%; maximum ADC, 63.5% and 63.5%; ADC difference value, 70.1% and 70.1%. Minimum ADC had the largest area under the ROC curve (AUC) of 0.93. Minimum ADC combined with the ADC difference value improved the AUC to 0.95, with sensitivity and specificity of 89.1% and 89.1%. CONCLUSION: Minimum ADC may be an optimal DWI single parameter for differentiation between malignant and benign lesions of breast masses. Furthermore, the combination of the minimum ADC and ADC difference value significantly elevated diagnostic performance of breast DWI in comparison with average ADC.
OBJECTIVE: The purpose of our study was to assess the utility of the minimum apparent diffusion coefficient (ADC), average ADC, maximum ADC, and ADC difference value and to find optimum ADC parameters for differentiation between benign and malignant lesions in breast diffusion-weighted imaging (DWI). MATERIALS AND METHODS: Sixty-seven women with 75 masslike lesions (27 benign, 48 malignant) were examined with 3-T MRI. To assess heterogeneity within the lesion, the difference between minimum and maximum ADCs was recorded as the ADC difference value. Diagnostic performances of these parameters were compared by receiver operating characteristic (ROC) curve analysis. RESULTS: Each ADC parameter showed significant differences between malignant and benign lesions. The optimal cutoff levels for differentiating benign versus malignant lesions were determined by identifying the points where the sensitivity and specificity were equal on the ROC curves. According to ROC analyses, the following sensitivities and specificities were obtained: average ADC, 75.6% and 75.6%; minimum ADC, 85.5% and 85.5%; maximum ADC, 63.5% and 63.5%; ADC difference value, 70.1% and 70.1%. Minimum ADC had the largest area under the ROC curve (AUC) of 0.93. Minimum ADC combined with the ADC difference value improved the AUC to 0.95, with sensitivity and specificity of 89.1% and 89.1%. CONCLUSION: Minimum ADC may be an optimal DWI single parameter for differentiation between malignant and benign lesions of breast masses. Furthermore, the combination of the minimum ADC and ADC difference value significantly elevated diagnostic performance of breast DWI in comparison with average ADC.
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