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Behrens, Annika; Fasching, Peter A.; Schwenke, Eva; Gass, Paul; Häberle, Lothar; Heindl, Felix; Heusinger, Katharina; Lotz, Laura; Lubrich, Hannah; Preuß, Caroline; Schneider, Michael O.; Schulz-Wendtland, Rüdiger; Stumpfe, Florian M.; Uder, Michael; Wunderle, Marius; Zahn, Anna L.; Hack, Carolin C.; Beckmann, Matthias W.; Emons, Julius

Predicting mammographic density with linear ultrasound transducers

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  • Medientyp: E-Artikel
  • Titel: Predicting mammographic density with linear ultrasound transducers
  • Beteiligte: Behrens, Annika; Fasching, Peter A.; Schwenke, Eva; Gass, Paul; Häberle, Lothar; Heindl, Felix; Heusinger, Katharina; Lotz, Laura; Lubrich, Hannah; Preuß, Caroline; Schneider, Michael O.; Schulz-Wendtland, Rüdiger; Stumpfe, Florian M.; Uder, Michael; Wunderle, Marius; Zahn, Anna L.; Hack, Carolin C.; Beckmann, Matthias W.; Emons, Julius
  • Erschienen: Springer Science and Business Media LLC, 2023
  • Erschienen in: European Journal of Medical Research
  • Sprache: Englisch
  • DOI: 10.1186/s40001-023-01327-9
  • ISSN: 2047-783X
  • Schlagwörter: General Medicine
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>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.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>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<jats:sup>®</jats:sup> 730 Expert system (GE Medical Systems Kretztechnik GmbH &amp; 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.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>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 <jats:italic>R</jats:italic><jats:sup>2</jats:sup>, 0.255). Overall, ultrasound images from the VOLUSON<jats:sup>®</jats:sup> 730 Expert device in this study showed limited predictive power for PMD when correlated with the corresponding mammograms.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>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.</jats:p> <jats:p><jats:italic>Trial registration</jats:italic> 325-19 B (Ethics Committee of the medical faculty at Friedrich Alexander University of Erlangen-Nuremberg, Erlangen, Germany).</jats:p> </jats:sec>
  • Zugangsstatus: Freier Zugang