文章：

犬爪X射线衍射癌症诊断技术

Canine Cancer Diagnostics by X-ray Diffraction of Claws

原文发布日期：30 June 2024

DOI: 10.3390/cancers16132422

类型: Article

开放获取: 是

英文摘要：

We report the results of X-ray diffraction (XRD) measurements of the dogs’ claws and show the feasibility of using this approach for early, non-invasive cancer detection. The obtained two-dimensional XRD patterns can be described by Fourier coefficients, which were calculated for the radial and circular (angular) directions. We analyzed these coefficients using the supervised learning algorithm, which implies optimization of the random forest classifier by using samples from the training group and following the calculation of mean cancer probability per patient for the blind dataset. The proposed algorithm achieved a balanced accuracy of 85% and ROC-AUC of 0.91 for a blind group of 68 dogs. The transition from samples to patients additionally improved the ROC-AUC by 10%. The best specificity and sensitivity values for 68 patients were 97.4% and 72.4%, respectively. We also found that the structural parameter (biomarker) most important for the diagnostics is the intermolecular distance.

摘要翻译： 

我们报告了犬爪X射线衍射（XRD）的测量结果，并展示了该方法用于早期无创癌症检测的可行性。所获得的二维XRD图谱可通过傅里叶系数进行描述，这些系数分别沿径向和圆周（角度）方向计算。我们采用监督学习算法对这些系数进行分析，该算法通过训练组样本优化随机森林分类器，并对盲测数据集计算每位患者的平均癌症概率。在包含68只犬的盲测组中，所提算法实现了85%的平衡准确率和0.91的ROC-AUC值。从样本分析转向患者个体分析后，ROC-AUC值额外提升了10%。针对68例患者的最佳特异性与敏感度分别为97.4%和72.4%。研究还发现，对诊断最重要的结构参数（生物标志物）是分子间距离。

原文链接：

Canine Cancer Diagnostics by X-ray Diffraction of Claws