With breast cancer being one of the most widespread causes of death for women, there is an unmet need for its early detection. For this purpose, we propose a non-invasive approach based on X-ray scattering. We measured samples from 107 unique patients provided by the Breast Cancer Now Tissue Biobank, with the total dataset containing 2958 entries. Two different sample-to-detector distances, 2 and 16 cm, were used to access various structural biomarkers at distinct ranges of momentum transfer values. The biomarkers related to lipid metabolism are consistent with those of previous studies. Machine learning analysis based on the Random Forest Classifier demonstrates excellent performance metrics for cancer/non-cancer binary decisions. The best sensitivity and specificity values are 80% and 92%, respectively, for the sample-to-detector distance of 2 cm and 86% and 83% for the sample-to-detector distance of 16 cm.
乳腺癌作为女性最常见的致死原因之一，其早期检测需求尚未得到充分满足。为此，我们提出一种基于X射线散射技术的无创检测方法。本研究使用乳腺癌组织库提供的107例独立患者样本进行测量，数据集共包含2958条记录。通过设置2厘米和16厘米两种不同的样本-探测器距离，以获取不同动量转移值范围内的多种结构生物标志物。其中与脂质代谢相关的生物标志物与既往研究结果一致。基于随机森林分类器的机器学习分析显示，该方法在癌症/非癌症二元分类决策中表现出优异的性能指标：当样本-探测器距离为2厘米时，最佳敏感性与特异性分别为80%和92%；距离为16厘米时，敏感性与特异性分别达到86%和83%。
Vitacrystallography: Structural Biomarkers of Breast Cancer Obtained by X-ray Scattering
肿瘤(癌症)患者之家