Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany.
Biostatistics Unit, Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany.
Eur J Med Res. 2023 Sep 28;28(1):384. doi: 10.1186/s40001-023-01327-9.
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.
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.
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, 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.
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).
高乳房密度（MD）是乳腺癌（BC）发展的一个危险因素。MD 的变化受多种因素影响，如年龄、BMI、足月妊娠和哺乳期次数。为了更多地了解 MD，有必要建立非辐射的、替代乳房 X 光检查的方法，如超声评估。
我们分析了 168 名接受标准护理乳房 X 光检查并使用 VOLUSON 730 Expert 系统的高频（12 MHz）线性探头对乳房进行额外超声评估的患者的数据（GE Medical Systems Kretztechnik GmbH & Co OHG，奥地利）。从超声图像中计算灰度级箱以描述乳房密度。使用各种回归模型，通过灰度级箱预测百分比乳房密度（PMD）。
灰度级箱和 PMD 在一定程度上相关。Spearman's ρ 范围从 -0.18 到 0.32。随机森林模型是最准确的预测模型（交叉验证 R，0.255）。总体而言，与相应的乳房 X 光片相比，本研究中 VOLUSON 730 Expert 设备的超声图像显示出对 PMD 的预测能力有限。
在我们目前的工作中，使用超声成像无法可靠地预测 PMD。由于先前的研究显示出合理的相关性，预测能力似乎高度依赖于所使用的设备。确定可行的乳房非辐射成像方法及其预测能力仍然是一个重要的课题，需要进一步评估。试验注册号 325-19 B（Friedrich Alexander 大学 Erlangen-Nuremberg 医学院伦理委员会，德国）。
