Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Breast Cancer Res. 2019 Oct 28;21(1):118. doi: 10.1186/s13058-019-1198-9.
Given that breast cancer and normal dense fibroglandular tissue have similar radiographic attenuation, we examine whether automated volumetric density measures identify a differential change between breasts in women with cancer and compare to healthy controls.
Eligible cases (n = 1160) had unilateral invasive breast cancer and bilateral full-field digital mammograms (FFDMs) at two time points: within 2 months and 1-5 years before diagnosis. Controls (n = 2360) were matched to cases on age and date of FFDMs. Dense volume (DV) and volumetric percent density (VPD) for each breast were assessed using Volpara™. Differences in DV and VPD between mammograms (median 3 years apart) were calculated per breast separately for cases and controls and their difference evaluated by using the Wilcoxon signed-rank test. To simulate clinical practice where cancer laterality is unknown, we examined whether the absolute difference between breasts can discriminate cases from controls using area under the ROC curve (AUC) analysis, adjusting for age, BMI, and time.
Among cases, the VPD and DV between mammograms of the cancerous breast decreased to a lesser degree (- 0.26% and - 2.10 cm) than the normal breast (- 0.39% and - 2.74 cm) for a difference of 0.13% (p value < 0.001) and 0.63 cm (p = 0.002), respectively. Among controls, the differences between breasts were nearly identical for VPD (- 0.02 [p = 0.92]) and DV (0.05 [p = 0.77]). The AUC for discriminating cases from controls using absolute difference between breasts was 0.54 (95% CI 0.52, 0.56) for VPD and 0.56 (95% CI, 0.54, 0.58) for DV.
There is a small relative increase in volumetric density measures over time in the breast with cancer which is not found in the normal breast. However, the magnitude of this difference is small, and this measure alone does not appear to be a good discriminator between women with and without breast cancer.
由于乳腺癌和正常致密纤维腺体组织的放射密度衰减相似,我们研究了自动容积密度测量是否能识别出癌症患者双侧乳房的差异变化,并与健康对照组进行比较。
符合条件的病例(n=1160)患有单侧浸润性乳腺癌,且在诊断前 2 个月内和 1-5 年内进行了双侧全视野数字化乳腺摄影术(FFDM)。对照组(n=2360)按年龄和 FFDM 日期与病例匹配。使用 Volpara 评估每侧乳房的致密体积(DV)和容积百分比密度(VPD)。分别计算病例和对照组每侧乳房两次 FFDM(中位时间间隔 3 年)的 DV 和 VPD 差异,并使用 Wilcoxon 符号秩检验进行评估。为了模拟临床实践中对癌症侧别的未知情况,我们使用 ROC 曲线下面积(AUC)分析,调整年龄、BMI 和时间,来检查乳房之间的绝对差异是否可以区分病例和对照组。
在病例中,与正常乳房相比(-0.39%和-2.74cm),癌症乳房的 VPD 和 DV 在两次 FFDM 之间的下降幅度较小(-0.26%和-2.10cm),差异为 0.13%(p 值<0.001)和 0.63cm(p=0.002)。在对照组中,VPD(-0.02 [p=0.92])和 DV(0.05 [p=0.77])之间的乳房差异几乎相同。使用乳房之间的绝对差异来区分病例和对照组的 AUC 为 VPD 0.54(95%CI 0.52,0.56)和 DV 0.56(95%CI,0.54,0.58)。
在患有癌症的乳房中,随着时间的推移,容积密度测量值会有一个小的相对增加,而在正常乳房中则不会发现这种增加。然而,这种差异的幅度很小,单独使用该指标似乎不能很好地区分患有和不患有乳腺癌的女性。