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Rapid volume density analysis (RVDA) for automated breast ultrasound (ABUS) has been proposed as a more efficient method for estimating breast density. In the current experiment, ABUS images were obtained for 67 breasts from 40 patients. For each case, three rectangular volumes of interest (VOIs) were extracted, including the VOIs located at the 6 and 12 o’clock positions relative to the nipple in the anterior to posterior pass and the lateral position relative to the nipple in the lateral pass. The centers of these VOIs were defined to align with the center of nipple, and the depths reached the retromammary fat boundary. The fuzzy c-means classifier was applied to differentiate the fibroglandular and fat tissues to estimate the density. The classification results of the three VOIs were averaged to obtain the breast density. The density correlations between the RVDA and the ABUS methods were 0.98 and 0.96 using Pearson’s correlation and linear regression coefficients, respectively. The average computation times for RVDA and ABUS were 4.2 and 17.8 seconds, respectively, using an Intel® Core™2 2.66 GHz computer with 3.25 GB memory. In conclusion, the RVDA method offers a quantitative and efficient breast density estimation for ABUS.

Background Unexpected focal 18F-FDG breast uptakes are occasionally identified on PET/CT due to its increased use for cancer staging and follow-up. The need for their characterization has been suggested. Purpose To retrospectively evaluate the diagnostic value of ultrasonography (US) in distinguishing benign from malignant lesions for unexpected focal 18F-FDG uptakes in breast on PET/CT scans. Material and Methods Between April 2004 and January 2010, 27 focal 18F-FDG breast uptakes in 27 patients (age range 33–62 years; mean age 46 years) among 5214 patients who had undergone PET/CT scans were retrospectively analyzed. The American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BI-RADS) final assessment categories of the US and the maximum standardized uptake values (SUVs) of the lesions were compared between the benign and malignant lesions. Results Of the 27 lesions, 15 (56%) lesions were malignant. The rate of malignancy, according to the final assessment category on the US, was 0% (0 of 6) for category 3, 60% for category 4 (9 of 15), and 100% (6 of 6) for category 5 ( P = 0.001). The US evaluation revealed a sensitivity of 100% (15 of 15) and a specificity of 50% (6 of 12). The average maximum SUV of the malignant lesions was greater than that of the benign lesions (4.12 ± 1.94 vs. 1.94 ± 0.82; P = 0.001). Conclusion US evaluation of unexpected focal 18F-FDG uptakes on PET/CT scans can accurately distinguish benign lesions from malignant lesions.