Automated Measurement of Volumetric Mammographic Density: A Tool for Widespread Breast Cancer Risk Assessment
Automated Measurement of Volumetric Mammographic Density: A Tool for Widespread Breast Cancer Risk Assessment
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DOI：
10.1158/1055-9965.epi-13-1219
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发表时间：
2014-09-01
影响因子：
3.8
通讯作者：
Hall, Per
中科院分区：
文献类型：
--
作者：
Brand, Judith S.;Czene, Kamila;Hall, Per
简介：乳腺摄影密度是乳腺癌的一个强有力的危险因素，也是筛查灵敏度的一个重要决定因素，但由于缺乏客观和自动化的测量，其临床实用性受到阻碍。我们评估了性能的全自动容积法（Volpara）。方法：一项前瞻性队列研究包括41,102名妇女参加乳房X线摄影筛查，其中206人被诊断为乳腺癌后，中位随访15.2个月。根据原始数字乳腺X线照片估计密度体积百分比和绝对值。在队列的一个子集（N = 2，122）中进行基因分型。我们检查了侧面和视图的一致性，并比较了不同乳腺X射线摄影系统的密度分布。我们还研究了与既定的密度决定因素和乳腺癌risk.Results的关联：该方法显示出良好的协议的侧面和视图，和分布的百分比和绝对致密体积是相似的乳房X线摄影系统。体积密度与未生育、初次生育年龄、激素使用、良性乳腺疾病和乳腺癌家族史呈正相关，与年龄和绝经后状态呈负相关。ZNF 365基因中的rs 10995190也被观察到相关性（P < 1.0 x 10（-6））和乳腺癌风险[最高与最低四分位数的HR，2.93;95%置信区间，1.73-4.96和1.63（1.10-2.42）分别为百分比和绝对密度体积]。结论：在高通量环境中，Volpara表现良好，符合既定密度测量的行为。乳腺X线摄影体积密度的自动测量是广泛的乳腺癌风险评估的一个有前途的工具。(C)2014年AACR。
Introduction: Mammographic density is a strong risk factor for breast cancer and an important determinant of screening sensitivity, but its clinical utility is hampered due to the lack of objective and automated measures. We evaluated the performance of a fully automated volumetric method (Volpara).Methods: A prospective cohort study included 41,102 women attending mammography screening, of whom 206 were diagnosed with breast cancer after a median follow-up of 15.2 months. Percent and absolute dense volumes were estimated from raw digital mammograms. Genotyping was performed in a subset of the cohort (N = 2,122). We examined the agreement by side and view and compared density distributions across different mammography systems. We also studied associations with established density determinants and breast cancer risk.Results: The method showed good agreement by side and view, and distributions of percent and absolute dense volume were similar across mammography systems. Volumetric density was positively associated with nulliparity, age at first birth, hormone use, benign breast disease, and family history of breast cancer, and negatively with age and postmenopausal status. Associations were also observed with rs10995190 in the ZNF365 gene (P < 1.0 x 10(-6)) and breast cancer risk [HR for the highest vs. lowest quartile, 2.93;95% confidence interval, 1.73-4.96 and 1.63 (1.10-2.42) for percent and absolute dense volume, respectively].Conclusions: In a high-throughput setting, Volpara performs well and in accordance with the behavior of established density measures.Impact: Automated measurement of volumetric mammographic density is a promising tool for widespread breast cancer risk assessment. (C) 2014 AACR.