Purpose: To evaluate the usefulness of apparent diŠusion coe‹cient (ADC) for the diŠerential diagnosis of breast tumors and to determine the relation between ADC and tumor cellularity.Materials and Methods: One hundred and thirty-six female patients (age range, 17-83 years; average age, 51.7 years) with 140 histologically proven breast tumors underwent diŠusion-weighted magnetic resonance (MR) imaging (DWI) using the spin-echo echo-planar technique, and the ADCs of the tumors were calculated using 3 diŠerent b values, 0, 500, and 1000 s/mm 2 . The diagnoses consisted ofˆbroadenoma (FA, n＝16), invasive ductal carcinoma, not otherwise speciˆed (IDC, n＝117), medullary carcinoma (ME, n＝3) and mucinous carcinoma (MU, n＝4). Tumor cellularity was calculated from surgical specimens. The ADCs of breast tumors and cellularity were compared between diŠerent histological types by analysis of variance and ScheŠe's post hoc test. The correlation between tumor cellularity and ADC was analyzed by Pearson correlation test.Results: Signiˆcant diŠerences were observed in ADCs between FA and all types of cancers (Pº0.05) and between MU and other types of cancers (Pº0.01) and in cellularity between FA and cancers except MU (Pº0.01) and between MU and other types of cancers (Pº0.01). There was an inverse correlation between ADC and tumor cellularity (Pº0.01, r 2 ＝0.451).Conclusions: The ADC may potentially help in diŠerentiating benign and malignant breast tumors. Tumor ADC correlates inversely with tumor cellularity.

A persistent or flat TIC pattern on dynamic contrast-enhanced MR images indicates benign disease, but there is added value from including the ADC value in the evaluation of tumors that show a plateau or washout TIC pattern.

Purpose:To evaluate the diagnostic accuracy of a combination of dynamic contrast-enhanced MR imaging (DCE-MRI) and diffusion-weighted MR imaging (DWI) in characterization of enhanced mass on breast MR imaging and to find the strongest discriminators between carcinoma and benignancy. Materials and Methods:We analyzed consecutive breast MR images in 270 patients; however, 13 lesions in 93 patients were excluded based on our criteria. We analyzed tumor size, shape, margin, internal mass enhancement, kinetic curve pattern, and apparent diffusion coefficient (ADC) values. We applied univariate and multivariate analyses to find the strongest indicators of malignancy and calculate a predictive probability for malignancy. We added the corresponding categories to these prediction probabilities for malignancy and calculated diagnostic accuracy when we consider category 4b, 4c, and 5 lesions as malignant and category 4a, 3, and 2 lesions as benign. In a validation study, 75 enhancing lesions in 71 patients were examined consecutively.Results: Irregular margin, heterogeneous internal enhancement, rim enhancement, plateau time-intensity curve (TIC) pattern, and washout TIC pattern were the strongest indicators of malignancy as well as past studies, and ADC values less than 1.1 ϫ 10 Ϫ3 mm 2 /s were also the strongest indicators of malignancy. In a validation study, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 92% (56/61), 86% (12/14), 97% (56/58), 71% (12/17), and 91% (68/75), respectively. Conclusion:The combination of DWI and DCE-MRI could produce high diagnostic accuracy in the characterization of enhanced mass on breast MR imaging.

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Several MR findings can be used to help determine the histologic grade of phyllodes breast tumors.