Cancer Research UK Genetic Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge, CB1 8RN, UK.
Breast Cancer Res. 2009;11(6):R80. doi: 10.1186/bcr2447. Epub 2009 Nov 11.
Mammographic breast density is one of the strongest known risk factors for breast cancer. We present a novel technique for estimating breast density based on 3D T1-weighted Magnetic Resonance Imaging (MRI) and evaluate its performance, including for breast cancer risk prediction, relative to two standard mammographic density-estimation methods.
The analyses were based on MRI (n = 655) and mammography (n = 607) images obtained in the course of the UK multicentre magnetic resonance imaging breast screening (MARIBS) study of asymptomatic women aged 31 to 49 years who were at high genetic risk of breast cancer. The MRI percent and absolute dense volumes were estimated using our novel algorithm (MRIBview) while mammographic percent and absolute dense area were estimated using the Cumulus thresholding algorithm and also using a 21-point Visual Assessment scale for one medio-lateral oblique image per woman. We assessed the relationships of the MRI and mammographic measures to one another, to standard anthropometric and hormonal factors, to BRCA1/2 genetic status, and to breast cancer risk (60 cases) using linear and Poisson regression.
MRI percent dense volume is well correlated with mammographic percent dense area (R = 0.76) but overall gives estimates 8.1 percentage points lower (P < 0.0001). Both show strong associations with established anthropometric and hormonal factors. Mammographic percent dense area, and to a lesser extent MRI percent dense volume were lower in BRCA1 carriers (P = 0.001, P = 0.010 respectively) but there was no association with BRCA2 carrier status. The study was underpowered to detect expected associations between percent density and breast cancer, but women with absolute MRI dense volume in the upper half of the distribution had double the risk of those in the lower half (P = 0.009).
The MRIBview estimates of volumetric breast density are highly correlated with mammographic dense area but are not equivalent measures; the MRI absolute dense volume shows potential as a predictor of breast cancer risk that merits further investigation.
乳腺密度是已知的最强乳腺癌风险因素之一。我们提出了一种基于 3D T1 加权磁共振成像（MRI）的估计乳腺密度的新方法，并评估了其性能，包括对乳腺癌风险的预测，与两种标准的乳腺密度估计方法相比。
该分析基于在英国多中心磁共振成像乳腺筛查（MARIBS）研究中获得的 MRI（n = 655）和乳腺 X 线摄影（n = 607）图像，这些女性年龄在 31 至 49 岁之间，具有乳腺癌的高遗传风险。使用我们的新算法（MRIBview）估计 MRI 的百分比和绝对致密体积，而使用 Cumulus 阈值算法和每位女性的一个中外斜位图像的 21 点视觉评估量表来估计乳腺 X 线摄影的百分比和绝对致密区域。我们使用线性和泊松回归评估 MRI 和乳腺 X 线摄影测量值之间的关系，以及与标准人体测量和激素因素、BRCA1/2 遗传状态和乳腺癌风险（60 例）的关系。
MRI 百分比致密体积与乳腺 X 线摄影百分比致密面积密切相关（R = 0.76），但总体估计值低 8.1 个百分点（P <0.0001）。两者均与既定的人体测量和激素因素有很强的关联。BRCA1 携带者的乳腺 X 线摄影百分比致密区域（P = 0.001）和较少程度的 MRI 百分比致密体积（P = 0.010）较低，但与 BRCA2 携带者状态无关。该研究没有足够的能力检测预期的百分比密度与乳腺癌之间的关联，但分布上半部分的绝对 MRI 致密体积较高的女性患乳腺癌的风险是下半部分的两倍（P = 0.009）。
MRIBview 对体积乳腺密度的估计与乳腺 X 线摄影致密区域高度相关，但不是等效的测量值；MRI 绝对致密体积作为乳腺癌风险预测指标具有潜力，值得进一步研究。
