PURPOSE To investigate the association between mammographic density (MD) phenotypes and both clinicopathologic features of breast cancer (BC) and tumor location. METHODS MD was measured for 297 BC-affected females using qualitative (visual method) and quantitative (fully automated area-based method) approaches. Radiologists' description, visible external markers, and surgical scar were used to establish the location of tumors. Binary logistic regression models were used to assess the association between MD phenotypes and BC clinicopathologic features. RESULTS Categorical and numerical MD measures showed no association with clinicopathologic features of BC (p > 0.05). Participants with higher BI-RADS scores [(51-75% glandular) and (> 75% glandular)] (p < 0.001), and percent density (PD) categories [PD (21-49%) and PD ≥ 50%] (p = 0.01) were more likely to have tumors emanating from dense areas. Additionally, tumors were commonly found in dense regions of the breast among patients with higher medians of PD (p = 0.001), dense area (DA) (p = 0.02), and lower medians of non-dense area (NDA) (p < 0.001). Adjusted logistic regression models showed that high BI-RADS density (> 75% glandular) has an almost fivefold increased odds of tumors developing within dense areas (OR 4.99, 95% CI 0.93-25.9; p = 0.05. PD (OR 1.02, 95% CI 1-1.03, p = 0.002) and NDA (OR 0.99, 95% CI 0.991-0.997, p < 0.001) had very small effect on tumor location. Compared to tumors within non-dense areas, tumors in dense areas tended to exhibit human epidermal growth factor receptor 2 positive (p = 0.05) and carcinoma in situ (p = 0.01) characteristics. CONCLUSION MD shows no significant association with clinicopathologic features of BC. However, BC was more likely to originate from dense tissue, with tumors in dense regions having human epidermal growth receptor 2 positive and carcinoma in situ characteristics.

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乳腺摄影密度是乳腺癌表型的标志吗？

目的探讨乳腺X线摄影密度（MD）表型与乳腺癌（BC）的临床病理特征和肿瘤位置之间的关系。方法采用定性（视觉方法）和定量（完全基于面积的方法）方法对297例受BC感染的女性进行MD测量。放射科医生的描述，可见的外部标记和手术疤痕被用于确定肿瘤的位置。二元逻辑回归模型用于评估MD表型与BC临床病理特征之间的关联。结果分类和数值MD测量结果均与BC的临床病理特征无关（p> 0.05）。BI-RADS分数较高的参与者[（51-75％腺体和（> 75％腺体）]（p <0.001），以及百分比密度（PD）类别[PD（21-49％）和PD≥50％] （p = 0。01）更有可能从密集区域散发肿瘤。此外，在PD中位数较高的患者（p = 0.001），PD中密度区域（p = 0.02）和非致密区域中位数（NDA）较低的患者中，常见于乳房密集区域的肿瘤（p < 0.001）。调整后的逻辑回归模型显示，高BI-RADS密度（> 75％的腺体）在致密区域内发生肿瘤的几率几乎增加了五倍（OR 4.99，95％CI 0.93-25.9； p =0.05。PD（OR 1.02，95） ％CI 1-1.03，p = 0.002）和NDA（OR 0.99，95％CI 0.991-0.997，p <0.001）对肿瘤位置的影响很小，与非密集区域的肿瘤相比，密集区域的肿瘤倾向于表现出人类表皮生长因子受体2阳性（p = 0.05）和原位癌（p = 0.01）特征。结论MD与BC的临床病理特征无显着相关性。然而，BC更可能起源于致密组织，致密区域的肿瘤具有人类表皮生长受体2阳性和原位癌特征。