Automated breast ultrasound: basic principles and emerging clinical applications.

Automated breast ultrasound (ABUS) is a recently introduced ultrasonography technique, developed with the purpose to standardize breast ultrasonography and overcome some limitations of handheld ultrasound (HHUS), such as operator dependence and the considerable amount of medical time necessary to perform and interpret HHUS. This new ultrasonography technique separates the moment of image acquisition (that may be performed also by a technician) from that of its interpretation, increasing reproducibility, reducing operator-dependence and physician time. Moreover, multiplanar reconstructions, especially the coronal view, introduce new diagnostic information. ABUS, with those advantages, has the potential to be used as an adjunctive tool to screening mammography, especially in the dense breast, where mammography has a relatively low sensitivity. Women's awareness of risks related to breast density is a hot topic, especially in the USA where legislative breast density notification laws increase the demand for supplemental ultrasound screening. Therefore, ABUS might have the potential to respond to this need. The purpose of this article is to present a summary of current state-of-the-art of ABUS technology and applications, with an emphasis on breast cancer screening. This article discusses also how to overcome some ABUS limitations, in order to be familiar with the new technique.

Automated breast volume scanner (ABVS) in assessing breast cancer size: A comparison with conventional ultrasound and magnetic resonance imaging.

OBJECTIVES: To compare automated breast volume scanner (ABVS), ultrasound (US) and MRI in measuring breast cancer size, and evaluate the agreement between ABVS and US in assessing lesion location and sonographic features. METHODS: We retrospectively included 98 women with 100 index cancers who had undergone US and ABVS followed by 1.5T MRI. Images were interpreted by a pool of readers reporting lesion size, location and breast imaging reporting and data system (BI-RADS) features. Bland-Altman analysis (with logarithmic data transformation), intraclass correlation coefficient (ICC) and Cohen's kappa statistic were used for statistical analysis. RESULTS: MRI showed the best absolute agreement with histology in measuring cancer size (ICC 0.93), with LOA comparable to those of ABVS (0.63-1.99 vs. 0.52-1.73, respectively). Though ABVS and US had highly concordant measurements (ICC 0.95), ABVS showed better agreement with histology (LOA 0.52-1.73 vs. 0.45-1.86, respectively), corresponding to a higher ICC (0.85 vs. 0.75, respectively). Except for posterior features (k=0.39), the agreement between US and ABVS in attributing site and BI-RADS features ranged from substantial to almost perfect (k=0.68-0.85). CONCLUSIONS: ABVS performs better than US and approaches MRI in predicting breast cancer size. ABVS performs comparably to US in sonographic assessment of lesions. KEY POINTS: • ABVS approaches MRI in predicting breast cancer size. • ABVS is equivalent to US in localising and characterising breast cancer. • ABVS is more accurate than US in assessing breast cancer size. • ABVS has the potential to replace US in breast cancer staging.

Comparison between automated breast volume scanner (ABVS) versus hand-held ultrasound as a second look procedure after magnetic resonance imaging.

OBJECTIVES: To evaluate the agreement between automated breast volume scanner (ABVS) and conventional ultrasound (US) as a second-look (SL) tool for assessing additional findings found on MRI. METHODS: Over a 7-month period, we prospectively assigned to SL-US and SL-ABVS all patients undergoing 1.5 T breast MRI in whom additional findings were found. Five experienced breast radiologists independently interpreted SL-US and SL-ABVS in blinded sessions to evaluate the detection rate of MRI findings and assign them to BI-RADS categories. We calculated the agreement between the two methods in assessing MRI findings as significant (BI-RADS 3-5) versus not significant (BI-RADS 1-2), as well as their cancer detection rate. RESULTS: In a population of 131 patients, SL-ABVS and SL-US showed a comparable detection rate of MRI findings (69.3 vs. 71.5%) (p > 0.05; McNemar test), with an almost perfect agreement in assessing them as significant or not (k = 0.94). This translated into a comparably high cancer detection rate (83.8% for SL-ABVS vs. 87.0% for SL-US). Only 1/31 cancers was missed by SL-ABVS. CONCLUSIONS: SL-ABVS and SL-US are nearly equivalent in assessing the significance of MRI findings, leading to a comparable cancer detection rate. SL-ABVS has the potential to replace SL-US in the SL scenario. KEY POINTS: • SL-ABVS shows almost perfect agreement with SL-US in assessing MRI findings. • SL-ABVS shows a comparably high cancer detection rate with respect to SL-US. • SL-ABVS has the potential to replace SL-US in evaluating additional MRI findings.