Quantitative breast lesion classification based on multichannel distributions in shear-wave imaging

• A computer-aided diagnosis (CAD) system based on the quantified color distributions in shear wave elastography (SWE) was developed.
• The combination of the proposed CAD system using SWE features and BI-RADS assessment would provide a promising diagnostic suggestion.
• Spatial correlation was combined with the kPa-weighted color information as a feature to reduce the influence of noises far from tumor.

Background and objectivesA computer-aided diagnosis (CAD) system based on the quantified color distributions in shear-wave elastography (SWE) was developed to evaluate the malignancies of breast tumors.MethodsFor 57 benign and 31 malignant tumors, 18 SWE features were extracted from regions of interest (ROI), including the tumor and peritumoral areas. In the ROI, a histogram in each color channel was described using moments such as the mean, variance, skewness, and kurtosis. Moreover, three color channels were combined as a vector to evaluate tissue elasticity. The SWE features were then combined in a logistic regression classifier for breast tumor classification.ResultsThe performance of the CAD system achieved an accuracy of 81%. Combining the CAD system with a BI-RADS assessment obtained an Az improvement from 0.77 to 0.89 (p-value <0.05).ConclusionsThe combination of the proposed CAD system based on SWE features and the BI-RADS assessment would provide a promising diagnostic suggestion.