Rahbar Kareem, Gubern-Merida Albert, Patrie James T, Harvey Jennifer A
Roper Radiologists, P.A., Charleston, South Carolina.
Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
Acad Radiol. 2017 Dec;24(12):1561-1569. doi: 10.1016/j.acra.2017.06.002. Epub 2017 Jul 25.
The purpose of this study was to evaluate discrepancy in breast composition measurements obtained from mammograms using two commercially available software methods for systematic trends in overestimation or underestimation compared to magnetic resonance-derived measurements.
An institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study was performed to calculate percent breast density (PBD) by quantifying fibroglandular volume and total breast volume derived from magnetic resonance imaging (MRI) segmentation and mammograms using two commercially available software programs (Volpara and Quantra). Consecutive screening MRI exams from a 6-month period with negative or benign findings were used. The most recent mammogram within 9 months was used to derive mean density values from "for processing" images at the per breast level. Bland-Altman statistical analyses were performed to determine the mean discrepancy and the limits of agreement.
A total of 110 women with 220 breasts met the study criteria. Overall, PBD was not different between MRI (mean 10%, range 1%-41%) and Volpara (mean 10%, range 3%-29%); a small but significant difference was present in the discrepancy between MRI and Quantra (4.0%, 95% CI: 2.9 to 5.0, P < 0.001). Discrepancy was highest at higher breast densities, with Volpara slightly underestimating and Quantra slightly overestimating PBD compared to MRI. The mean discrepancy for both Volpara and Quantra for total breast volume was not significantly different from MRI (p = 0.89, 0.35, respectively). Volpara tended to underestimate, whereas Quantra tended to overestimate fibroglandular volume, with the highest discrepancy at higher breast volumes.
Both Volpara and Quantra tend to underestimate PBD, which is most pronounced at higher densities. PBD can be accurately measured using automated volumetric software programs, but values should not be used interchangeably between vendors.
本研究的目的是评估使用两种商用软件方法从乳房X线照片获得的乳房成分测量值与磁共振成像测量值相比在高估或低估方面的系统趋势差异。
进行了一项经机构审查委员会批准、符合《健康保险流通与责任法案》的回顾性研究，通过使用两种商用软件程序（Volpara和Quantra）对磁共振成像（MRI）分割和乳房X线照片得出的纤维腺体体积和乳房总体积进行量化，计算乳房密度百分比（PBD）。使用了连续6个月内筛查结果为阴性或良性的MRI检查。使用9个月内最近的乳房X线照片从每个乳房水平的“待处理”图像中得出平均密度值。进行Bland-Altman统计分析以确定平均差异和一致性界限。
共有110名女性的220个乳房符合研究标准。总体而言，MRI（平均10%，范围1%-41%）和Volpara（平均10%，范围3%-29%）之间的PBD没有差异；MRI和Quantra之间的差异存在微小但显著的差异（4.0%，95%CI：2.9至5.0，P < 0.001）。在较高乳房密度时差异最大，与MRI相比，Volpara略微低估PBD，而Quantra略微高估PBD。Volpara和Quantra在乳房总体积方面的平均差异与MRI没有显著差异（分别为p = 0.89，0.35）。Volpara倾向于低估，而Quantra倾向于高估纤维腺体体积，在较高乳房体积时差异最大。
Volpara和Quantra都倾向于低估PBD，在较高密度时最为明显。使用自动容积软件程序可以准确测量PBD，但不同供应商的值不应互换使用。
