Wagner Tobias, Cockmartin Lesley, Wang Yao-Kuan, Marshall Nicholas, Bosmans Hilde
Department of Imaging and Pathology, Division of Medical Physics & Quality Assessment, KU Leuven, Leuven, Belgium.
Department of Imaging and Pathology, Division of Medical Physics & Quality Assessment, UZ Leuven, Leuven, Belgium.
Eur Radiol. 2025 Jan 31. doi: 10.1007/s00330-025-11383-w.
Investigate the impact of mammography device grouped by vendor on volumetric breast density and propose a method that mitigates biases when determining the proportion of high-density women.
Density grade class and volumetric breast density distributions were obtained from mammographic images from three different vendor devices in different centers using breast density evaluation software in a retrospective study. Density distributions were compared across devices with a Mann-Whitney U test and breast density thresholds corresponding to distribution percentiles calculated. A method of matching density percentiles is proposed to determine women at potentially high risk while mitigating possible bias due to the device used for screening.
2083 (mean age 59 ± 5.4), 531 (mean age 58.8 ± 5.7) and 244 (mean age 60.7 ± 6.0) screened women were evaluated on three vendor devices, respectively. Both the density grade distribution and the volumetric breast density were different between Vendor 1 and Vendor 2 data (p < 0.001) and between Vendor 1 and Vendor 3 data (p < 0.001). Between Vendor 2 and Vendor 3, no significant difference was observed (p = 0.67 for density grade, p = 0.29 for volumetric density). To recruit the top 10% of women with extremely dense breasts required respective density thresholds of 16.1%, 13.6% and 13.8% for the three vendor devices.
Density grade class and volumetric breast density distributions differ between devices grouped by vendor and can result in statistically different breast density distributions. Percentile-dependent density thresholds can ensure unbiased selection of high-risk women.
Question Does the use of x-ray systems from different vendors influence breast density evaluation and the resulting selection of high-risk women during breast cancer screening? Findings Statistically significant differences were observed between breast density distributions of different vendors; a method of matching via percentiles is proposed to prevent biased density evaluations. Clinical relevance Measured breast density distributions differed between X-ray devices. A workaround is proposed that determines density thresholds corresponding to a specified population, allowing the same proportion of women to be selected with a density algorithm.
研究按供应商分组的乳腺钼靶设备对乳腺体积密度的影响，并提出一种在确定高密度女性比例时减轻偏差的方法。
在一项回顾性研究中，使用乳腺密度评估软件从不同中心的三种不同供应商设备的乳腺钼靶图像中获取密度等级分类和乳腺体积密度分布。使用曼-惠特尼U检验比较不同设备之间的密度分布，并计算对应于分布百分位数的乳腺密度阈值。提出了一种匹配密度百分位数的方法，以确定潜在高风险女性，同时减轻因用于筛查的设备导致的可能偏差。
分别在三种供应商设备上对2083名（平均年龄59±5.4岁）、531名（平均年龄58.8±5.7岁）和244名（平均年龄60.7±6.0岁）接受筛查的女性进行了评估。供应商1和供应商2的数据之间以及供应商1和供应商3的数据之间，密度等级分布和乳腺体积密度均存在差异（p<0.001）。在供应商2和供应商3之间，未观察到显著差异（密度等级p=0.67，体积密度p=0.29）。对于这三种供应商设备，招募乳腺极度致密的前10%女性所需的密度阈值分别为16.1%、13.6%和13.8%。
按供应商分组的设备之间，密度等级分类和乳腺体积密度分布存在差异，可能导致乳腺密度分布在统计学上有所不同。依赖百分位数的密度阈值可确保无偏差地选择高风险女性。
问题不同供应商的X射线系统在乳腺癌筛查期间对乳腺密度评估以及由此产生的高风险女性选择有影响吗？研究结果在不同供应商的乳腺密度分布之间观察到具有统计学意义的差异；提出了一种通过百分位数进行匹配的方法，以防止密度评估出现偏差。临床意义不同X射线设备测得的乳腺密度分布存在差异。提出了一种变通方法，该方法确定对应于特定人群的密度阈值，从而允许使用密度算法选择相同比例的女性。
