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评估 LIBRA 软件在乳腺癌风险预测中全自动乳腺密度评估的应用。

Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction.

机构信息

From the Department of Radiology, University of Pennsylvania, Philadelphia, Pa (A.G., E.F.C., D.K.); Department of Radiology, University of Minnesota, Minneapolis, Minn (C.D.K.); Departments of Health Sciences Research (C.G.S., M.R.J., A.D.N., S.J.W., C.M.V.), Diagnostic Radiology (K.R.B., C.B.H.), Information Technology (F.F.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905; and Department of Medicine and Epidemiology, University of California, San Francisco, San Francisco, Calif (K.K.).

出版信息

Radiology. 2020 Jul;296(1):24-31. doi: 10.1148/radiol.2020192509. Epub 2020 May 12.

Abstract

Background The associations of density measures from the publicly available Laboratory for Individualized Breast Radiodensity Assessment (LIBRA) software with breast cancer have primarily focused on estimates from the contralateral breast at the time of diagnosis. Purpose To evaluate LIBRA measures on mammograms obtained before breast cancer diagnosis and compare their performance to established density measures. Materials and Methods For this retrospective case-control study, full-field digital mammograms in for-processing (raw) and for-presentation (processed) formats were obtained (March 2008 to December 2011) in women who developed breast cancer an average of 2 years later and in age-matched control patients. LIBRA measures included absolute dense area and area percent density (PD) from both image formats. For comparison, dense area and PD were assessed by using the research software (Cumulus), and volumetric PD (VPD) and absolute dense volume were estimated with a commercially available software (Volpara). Density measures were compared by using Spearman correlation coefficients (), and conditional logistic regression (odds ratios [ORs] and 95% confidence intervals [CIs]) was performed to examine the associations of density measures with breast cancer by adjusting for age and body mass index. Results Evaluated were 437 women diagnosed with breast cancer (median age, 62 years ± 17 [standard deviation]) and 1225 matched control patients (median age, 61 years ± 16). LIBRA PD showed strong correlations with Cumulus PD ( = 0.77-0.84) and Volpara VPD ( = 0.85-0.90) ( < .001 for both). For LIBRA, the strongest breast cancer association was observed for PD from processed images (OR, 1.3; 95% CI: 1.1, 1.5), although the PD association from raw images was not significantly different (OR, 1.2; 95% CI: 1.1, 1.4; = .25). Slightly stronger breast cancer associations were seen for Cumulus PD (OR, 1.5; 95% CI: 1.3, 1.8; processed images; = .01) and Volpara VPD (OR, 1.4; 95% CI: 1.2, 1.7; raw images; = .004) compared with LIBRA measures. Conclusion Automated density measures provided by the Laboratory for Individualized Breast Radiodensity Assessment from raw and processed mammograms correlated with established area and volumetric density measures and showed comparable breast cancer associations. © RSNA, 2020

摘要

背景 来自公开的个体化乳腺放射密度评估(LIBRA)软件的密度测量值与乳腺癌的关联主要集中在诊断时对侧乳房的估计值上。目的 评估 LIBRA 对乳腺癌诊断前获得的乳腺 X 线照片的测量值,并将其与已建立的密度测量值进行比较。材料与方法 本回顾性病例对照研究于 2008 年 3 月至 2011 年 12 月期间入组,对平均 2 年后确诊为乳腺癌的女性和年龄匹配的对照患者进行全视野数字化乳腺 X 线摄影术的原始(未处理)和常规处理(已处理)图像。LIBRA 测量值包括两种图像格式的绝对致密区面积和面积百分比密度(PD)。为了比较,使用研究软件(Cumulus)评估致密区面积和 PD,使用商业软件(Volpara)估计容积 PD(VPD)和绝对致密体积。通过 Spearman 相关系数()比较密度测量值,并通过条件逻辑回归(比值比[OR]和 95%置信区间[CI]),在调整年龄和体重指数后,检查密度测量值与乳腺癌的关联。结果 评估了 437 名确诊为乳腺癌的女性(中位年龄 62 岁±17[标准差])和 1225 名匹配的对照患者(中位年龄 61 岁±16)。LIBRA PD 与 Cumulus PD( = 0.77-0.84)和 Volpara VPD( = 0.85-0.90)均具有很强的相关性(均<0.001)。对于 LIBRA,处理后的图像 PD 与乳腺癌的相关性最强(OR,1.3;95%CI:1.1,1.5),尽管原始图像 PD 相关性无显著差异(OR,1.2;95%CI:1.1,1.4; =.25)。与 LIBRA 测量值相比,Cumulus PD(OR,1.5;95%CI:1.3,1.8;处理后的图像; =.01)和 Volpara VPD(OR,1.4;95%CI:1.2,1.7;原始图像; =.004)与乳腺癌的相关性略强。结论 来自个体化乳腺放射密度评估的原始和处理后的乳腺 X 线片的自动密度测量值与已建立的面积和容积密度测量值相关,并且与乳腺癌的相关性相当。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a78d/7325699/a05cb6751bf1/radiol.2020192509.VA.jpg

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