Predicting mammographic density with a linear ultrasound transducer

Objectives High percentage mammographic density (PMD) is a risk factor for the development of breast cancer (BC). Changes in PMD are influenced by multiple factors such as age, BMI, number of full-term pregnancies and lactating periods. To learn more about PMD, it is important to establish non-radiation based, alternative examination methods to mammography such as ultrasound assessments.

Materials and methods We analyzed data from 168 patients who underwent standard-of-care mammography and performed additional ultrasound assessment of the breast using a high frequency (12MHz) linear probe of the VOLUSON®​ 730 Expert system (GE Medical Systems Kretztechnik GmbH & Co OHG, Austria). Gray level histogram features were calculated from ultrasound images to characterize mammographic density. PMD was predicted by gray level bins using various regression models.

Results Gray level bins and PMD correlated to a certain extent. Spearman’s ρ ranged from -0.18 to 0.32. The random forest model turned out to be the most accurate prediction model (cross-validated R², 0.255). Overall, ultrasound images from the VOLUSON®​ 730 Expert device in this study showed limited predictive power for PMD when correlated with the corresponding mammograms.

Conclusions In our present work, no reliable prediction of PMD using ultrasound imaging could be observed. As previous studies showed a reasonable correlation, predictive power seems to be highly dependent on the device used. Identifying feasible non-radiation imaging methods of the breast and their predictive power remains an important topic and warrants further evaluation.

Publication History

Article published online:
21 June 2022