Added Value of Quantitative Ultrasound and Machine Learning in BI-RADS 4-5 Assessment of Solid Breast Lesions.

The purpose of this study was to evaluate various combinations of 13 features based on shear wave elasticity (SWE), statistical and spectral backscatter properties of tissues, along with the Breast Imaging Reporting and Data System (BI-RADS), for classification of solid breast lesions at ultrasonography by means of random forests. One hundred and three women with 103 suspicious solid breast lesions (BI-RADS categories 4-5) were enrolled. Before biopsy, additional SWE images and a cine sequence of ultrasound images were obtained. The contours of lesions were delineated, and parametric maps of the homodyned-K distribution were computed on three regions: intra-tumoral, supra-tumoral and infra-tumoral zones. Maximum elasticity and total attenuation coefficient were also extracted. Random forests yielded receiver operating characteristic (ROC) curves for various combinations of features. Adding BI-RADS category improved the classification performance of other features. The best result was an area under the ROC curve of 0.97, with 75.9% specificity at 98% sensitivity.

Breast imaging reporting and data system lexicon for US: interobserver agreement for assessment of breast masses.

PURPOSE: To retrospectively evaluate the interobserver agreement of radiologists who used the Breast Imaging Reporting and Data System (BI-RADS) lexicon to characterize and categorize ultrasonographic (US) features of breast masses. MATERIALS AND METHODS: No institutional review board approval or patient consent was required. Five breast radiologists retrospectively independently evaluated 267 breast masses (113 benign and 154 malignant masses in 267 patients) by using the BI-RADS US lexicon. Reviewers were blinded to mammographic images, medical history, and pathologic findings. Interobserver agreement was assessed with the Aickin revised kappa statistic. RESULTS: Interobserver agreement varied from fair for evaluation of mass margins (kappa = 0.36) to moderate for evaluation of lesion boundary (kappa = 0.48), echo pattern (kappa = 0.58), and posterior acoustic features (kappa = 0.47) to substantial for evaluation of mass orientation (kappa = 0.70) and shape (kappa = 0.64). For small (< or =0.7 cm; n = 49) or malignant (n = 154) masses, low concordance was noted for margin descriptors (kappa = 0.30 and 0.28, respectively) and BI-RADS category (kappa = 0.21 and 0.26, respectively). Overall, only fair agreement was obtained for BI-RADS category (kappa = 0.30). Agreement for subdivisions 4a, 4b, and 4c of BI-RADS category 4 was fair (kappa = 0.33), fair (kappa = 0.32), and poor (kappa = 0.17), respectively. CONCLUSION: Reproducibility of US BI-RADS terminology is good except for margin evaluation. A trend toward lower concordance was noted for the evaluation of small masses and malignant lesions. Classification into subdivisions 4a, 4b, and 4c was poorly reproducible.