Predicting mammographic density with linear ultrasound transducers - Behrens, Annika; Fasching, Peter; Schwenke, Eva; Gaß, Paul; Häberle, Lothar; Heindl, Felix; Heusinger, Katharina; Lotz, Laura; Lubrich, Hannah; Preuß, Caroline; Schneider, Michael; Schulz-Wendtland, Rüdiger; et al. (European Journal of Medical Research, 2023)
Background: High mammographic density (MD) is a risk factor for the development of breast cancer (BC). Changes in MD are influenced by multiple factors such as age, BMI, number of full-term pregnancies and lactating periods. To learn more about MD, it is important to establish non-radiation-based, alternative examination methods to mammography such as ultrasound assessments. 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 (12 MHz) linear probe of the VOLUSON® 730 Expert system (GE Medical Systems Kretztechnik GmbH & Co OHG, Austria). Gray level bins were calculated from ultrasound images to characterize mammographic density. Percentage 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 R 2, 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. Trial registration 325-19 B (Ethics Committee of the medical faculty at Friedrich Alexander University of Erlangen-Nuremberg, Erlangen, Germany).
CRIS-Team Scopus Importer:2023-10-13
Keywords: Breast cancer risk; Percent mammographic density; Ultrasound