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Assessing the usefulness of a novel MRI-based breast density estimation algorithm in a cohort of women at high genetic risk of breast cancer: the UK MARIBS study

机译:评估一种基于MRI的新型乳腺密度估算算法在乳腺癌高遗传风险人群中的有用性:英国MARIBS研究

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IntroductionMammographic 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.MethodsThe 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.ResultsMRI 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).ConclusionsThe 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.
机译:简介乳腺钼靶X射线摄影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)估算乳房密度的新技术,并相对于两种标准的乳腺X线密度估算方法评估了其性能,包括乳腺癌风险预测的方法。在英国多中心磁共振成像乳房筛查(MARIBS)研究中,对31岁至49岁无乳腺癌风险高的无症状女性进行了研究,获得了655例)和乳房X线照片(n = 607)。使用我们的新算法(MRIBview)估算MRI百分比和绝对密度,同时使用Cumulus阈值算法和21点视觉评估量表对每位女性的一副中斜图像评估乳房X线照片的百分比和绝对密度。我们使用线性和Poisson回归评估了MRI和乳腺X线摄影测量之间,标准人体测量学和激素因素,BRCA1 / 2遗传状况以及乳腺癌风险(60例)之间的关系。乳房X射线照片的致密面积百分比(R = 0.76),但总体而言估计要低8.1个百分点(P <0.0001)。两者都显示出与已建立的人体测量和荷尔蒙因素有很强的联系。在BRCA1携带者中,乳房X线照片的致密区域百分比和MRI的致密百分比较低(分别为P = 0.001,P = 0.010),但与BRCA2携带者状态无关。该研究不足以检测密度百分比与乳腺癌之间的预期关联,但是在分布的上半部分具有MRI绝对密度绝对值的女性中,下半部分具有较高的风险(P = 0.009)。乳房密度与乳房X光检查的密集区域高度相关,但不是等效的度量; MRI的绝对致密量显示出潜在的乳腺癌风险预测指标,值得进一步研究。

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