实质分析通过乳腺X线摄影图像的纹理特征的表征，对评估乳腺癌风险表现出了良好的性能。然而，这种实践背后的工作原理尚未得到很好的理解。领域癌变是一种现象，与大量细胞中的遗传和表观遗传变化有关，使它们在出现可识别的癌症迹象之前走向恶性。有证据表明，它可以引起组织的生化和光学特性的变化。本研究的目的是研究由于领域癌变引起的扩展基因突变和表观遗传变化，以及它们对乳腺组织生物化学的影响，是否可以通过乳腺X线摄影图像的放射学模式来检测。设计了一个计算机模拟实验，其中涉及开发领域癌变模型来修改60个像素化虚拟乳房模型的光学组织特性。从这些模型中生成乳腺X线摄影图像，并与没有领域癌变的乳腺X线摄影图像进行比较。我们从乳房区域提取了33个纹理特征，以定量评估领域癌变模型的影响。我们使用t检验、Wilcoxon符号秩检验和Kolmogorov-Smirnov检验分析带有和不带有领域癌变的纹理特征的相似性和统计等价性，并使用套索正则化的多项式Logistic回归分析进行鉴别测试。通过对3.9%的乳房体积进行光学组织性质的修改，一些纹理特征开始无法显示相等性(p≤0.05)。在7.9％的体积修改情况下，高比例的纹理特征显示出显着的差异(p≤0.05)和不等效性。在这个级别上，纹理特征的多项式逻辑回归分析表明，在乳房有和没有领域癌变的情况下区分乳腺X线摄影图像具有统计显著的性能(AUC = 0.89，95％CI：0.75-1.00)。这些结果支持领域癌变是实质分析在乳腺癌风险评估中具有独特性能的可行工作原理。本文受版权保护。版权所有。

Parenchymal analysis has shown promising performance for the assessment of breast cancer risk through the characterization of the texture features of mammography images. However, the working principles behind this practice are yet not well understood. Field cancerization is a phenomenon associated with genetic and epigenetic alterations in large volumes of cells, putting them on a path of malignancy before the appearance of recognizable cancer signs. Evidence suggests that it can induce changes in the biochemical and optical properties of the tissue.The aim of this work was to study whether the extended genetic mutations and epigenetic changes due to field cancerization, and the impact they have on the biochemistry of breast tissues are detecTable in the radiological patterns of mammography images.An in silico experiment was designed, which implied the development of a field cancerization model to modify the optical tissue properties of a cohort of 60 voxelized virtual breast phantoms. Mammography images from these phantoms were generated and compared with images obtained from their non-modified counterparts, i.e. without field cancerization. We extracted 33 texture features from the breast area to quantitatively assess the impact of the field cancerization model. We analyzed the similarity and statistical equivalence of texture features with and without field cancerization using the t-test, Wilcoxon sign rank test and Kolmogorov-Smirnov test, and performed a discrimination test using multinomial logistic regression analysis with lasso regularization.With modifications of the optical tissue properties on 3.9% of the breast volume, some texture features started to fail to show equivalence (p\le0.05). At 7.9% volume modification, a high percent of texture features showed statistically significant differences (p\le0.05) and non-equivalence. At this level, multinomial logistic regression analysis of texture features showed a statistically significant performance in the discrimination of mammograms from breasts with and without field cancerization (AUC= 0.89, 95% CI: 0.75 - 1.00).These results support the idea that field cancerization is a feasible underlying working principle behind the distinctive performance of parenchymal analysis in breast cancer risk assessment. This article is protected by copyright. All rights reserved.This article is protected by copyright. All rights reserved.