Breast density assessment via quantitative sound-speed measurement using conventional ultrasound transducers.

Abstract

Objectives: The aim is to assess the feasibility and accuracy of a novel quantitative ultrasound (US) method based on global speed-of-sound (g-SoS) measurement using conventional US machines, for breast density assessment in comparison to mammographic ACR (m-ACR) categories.

Materials and methods: In a prospective study, g-SoS was assessed in the upper-outer breast quadrant of 100 women, with 92 of them also having m-ACR assessed by two radiologists across the entire breast. For g-SoS, ultrasonic waves were transmitted from varying transducer locations and the image misalignments between these were then related analytically to breast SoS. To test reproducibility, two consecutive g-SoS acquisitions each were taken at two similar breast locations by the same operator.

Results: Measurements were found highly repeatable, with a mean absolute difference ± standard deviation of 3.16 ± 3.79 m/s. Multiple measurements were combined yielding a single g-SoS estimate per each patient, which strongly correlated to m-ACR categories (Spearman's = 0.773). The g-SoS values for categories A-D were 1459.6 ± 0.74, 1475.6 ± 15.92, 1515.6 ± 27.10, and 1545.7 ± 20.62, with all groups (except A-B) being significantly different from each other. Dense breasts (m-ACR C&D) were classified with 100% specificity at 78% sensitivity, with an area under the curve (AUC) of 0.931. Extremely dense breasts (m-ACR D) were classified with 100% sensitivity at 77.5% specificity (AUC = 0.906).

Conclusion: Quantitative g-SoS measurement of the breast was shown feasible and repeatable using conventional US machines, with values correlating strongly with m-ACR assessments.

Key points: Question Breast density is a strong predictor of risk for breast cancer, which frequently develops in dense tissue regions. Therefore, density assessment calls for refined non-ionizing methods. Findings Quantitative global speed-of-sound (g-SoS) measurement of the breast is shown to be feasible using conventional US machines, repeatable, and able to classify breast density with high accuracy. Clinical relevance Being effective in classifying dense breasts, where mammography has reduced sensitivity, g-SoS can help stratify patients for alternative modalities. Ideal day for mammography or MRI can be determined by monitoring g-SoS. Furthermore, g-SoS can be integrated into personalized risk assessment.