Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL.
Department of Quantitative Health Sciences, Divisions of Clinical Trials and Biostatistics and Computational Biology, Mayo Clinic, Rochester, MN.
AJR Am J Roentgenol. 2021 Aug;217(2):326-335. doi: 10.2214/AJR.20.22794. Epub 2021 Jun 23.
Our previous work showed that variation measures, which represent breast architecture derived from mammograms, were significantly associated with breast cancer. For replication purposes, we examined the association of three variation measures (variation [V], which is measured in the image domain, and P and p [a normalized version of P], which are derived from restricted regions in the Fourier domain) with breast cancer risk in an independent population. We also compared these measures to volumetric density measures (volumetric percent density [VPD] and dense volume [DV]) from a commercial product. We examined 514 patients with breast cancer and 1377 control patients from a screening practice who were matched for age, date of examination, mammography unit, facility, and state of residence. Spearman rank-order correlation was used to evaluate the monotonic association between measures. Breast cancer associations were estimated using conditional logistic regression, after adjustment for age and body mass index. Odds ratios were calculated per SD increment in mammographic measure. These variation measures were strongly correlated with VPD (correlation, 0.68-0.80) but not with DV (correlation, 0.31-0.48). Similar to previous findings, all variation measures were significantly associated with breast cancer (odds ratio per SD: 1.30 [95% CI, 1.16-1.46] for V, 1.55 [95% CI, 1.35-1.77] for P, and 1.51 [95% CI, 1.33-1.72] for p). Associations of volumetric density measures with breast cancer were similar (odds ratio per SD: 1.54 [95% CI, 1.33-1.78] for VPD and 1.34 [95% CI, 1.20-1.50] for DV). When DV was included with each variation measure in the same model, all measures retained significance. Variation measures were significantly associated with breast cancer risk (comparable to the volumetric density measures) but were independent of the DV.
我们之前的工作表明,代表乳腺结构的变异度量与乳腺癌显著相关。为了验证目的,我们在一个独立的人群中检查了三种变异度量(V,在图像域中测量;P 和 p[傅里叶域中受限区域的归一化版本])与乳腺癌风险的关联。我们还将这些度量与来自商业产品的体积密度度量(体积百分比密度[VPD]和致密体积[DV])进行了比较。我们检查了来自筛查实践的 514 名乳腺癌患者和 1377 名对照患者,这些患者在年龄、检查日期、乳腺摄影单位、设施和居住州方面相匹配。使用 Spearman 等级相关来评估度量之间的单调关联。调整年龄和体重指数后,使用条件逻辑回归估计乳腺癌关联。每增加一个 SD 计算出的比值比就是在乳腺测量中。这些变异度量与 VPD 高度相关(相关系数为 0.68-0.80),但与 DV 不相关(相关系数为 0.31-0.48)。与之前的发现相似,所有变异度量都与乳腺癌显著相关(每增加一个 SD 的比值比:V 为 1.30[95%置信区间,1.16-1.46],P 为 1.55[95%置信区间,1.35-1.77],p 为 1.51[95%置信区间,1.33-1.72])。体积密度度量与乳腺癌的关联相似(每增加一个 SD 的比值比:VPD 为 1.54[95%置信区间,1.33-1.78],DV 为 1.34[95%置信区间,1.20-1.50])。当 DV 与同一模型中的每个变异度量一起包含时,所有度量都保留了显著性。变异度量与乳腺癌风险显著相关(与体积密度度量相当),但与 DV 无关。