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BioMed Research International
Volume 2015 (2015), Article ID 410560, 8 pages
Research Article

Acoustic Radiation Force Impulse Technology in the Differential Diagnosis of Solid Breast Masses with Different Sizes: Which Features Are Most Efficient?

1Department of Ultrasound, Shanghai First People’s Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
2Department of Pathology, Shanghai First People’s Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
3School of Mathematics and Science, Shanghai Normal University, Shanghai 200234, China

Received 26 February 2015; Revised 8 June 2015; Accepted 9 June 2015

Academic Editor: Robert A. Vierkant

Copyright © 2015 Min Bai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Purpose. To evaluate diagnostic performance of acoustic radiation force impulse (ARFI) technology for solid breast masses with different sizes and determine which features are most efficient. Materials and Methods. 271 solid breast masses in 242 women were examined with ARFI, and their shear wave velocities (SWVs), Virtual Touch tissue imaging (VTI) patterns, and area ratios (ARs) were measured and compared with their histopathological outcomes. Receiver operating characteristic curves (ROC) were calculated to assess diagnostic performance of ARFI for small masses (6–14 mm) and big masses (15–30 mm). Results. SWV of mass was shown to be positively associated with mass size (). For small masses, area under ROC (Az) of AR was larger than that of SWV () and VTI pattern (); no significant difference was found between Az of SWV and that of VTI pattern (). For big masses, Az of VTI pattern was less than that of SWV () and AR (); no significant difference was identified between Az of SWV and that of AR (). Conclusions. For big masses, SWV and AR are both efficient measures; nevertheless, for small masses, AR seems to be the best feature.