Background. In a pathological examination of pancreaticoduodenectomy for pancreatic head adenocarcinoma, a resection margin without cancer cells in 1 mm is recognized as R0; a resection margin with cancer cells in 1 mm is recognized as R1. The preoperative identification of R0 and R1 is of great significance for surgical decision and prognosis. We conducted a preliminary radiomics study based on preoperative CT (computer tomography) images to evaluate a resection margin which was R0 or R1. Methods. We retrospectively analyzed 258 preoperative CT images of 86 patients (34 cases of R0 and 52 cases of R1) who were diagnosed as pancreatic head adenocarcinoma and underwent pancreaticoduodenectomy. The radiomics study consists of five stages: (i) delineate and segment regions of interest (ROIs); (ii) by solving discrete Laplacian equations with Dirichlet boundary conditions, fit the ROIs to rectangular regions; (iii) enhance the textures of the fitted ROIs combining wavelet transform and fractional differential; (iv) extract texture features from the enhanced ROIs combining wavelet transform and statistical analysis methods; and (v) reduce features using principal component analysis (PCA) and classify the resection margins using the support vector machine (SVM), and then investigate the associations between texture features and histopathological characteristics using the Mann–Whitney U-test. To reduce overfitting, the SVM classifier embedded a linear kernel and adopted the leave-one-out cross-validation. Results. It achieved an AUC (area under receiver operating characteristic curve) of 0.8614 and an accuracy of 84.88%. Setting in the Mann–Whitney U-test, two features of the run-length matrix, which are derived from diagonal sub-bands in wavelet decomposition, showed statistically significant differences between R0 and R1. Conclusions. It indicates that the radiomics study is rewarding for the aided diagnosis of R0 and R1. Texture features can potentially enhance physicians’ diagnostic ability.

中文翻译：

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胰头腺癌胰十二指肠切除术的鉴定：放射组学的初步研究。

背景。胰头腺癌胰十二指肠切除病理检查中，切缘1mm内无癌细胞为R0；1 mm 内有癌细胞的切除边缘被识别为 R1。术前鉴别R0和R1对手术决策和预后具有重要意义。我们基于术前 CT（计算机断层扫描）图像进行了初步放射组学研究，以评估 R0 或 R1 的切除边缘。方法. 我们回顾性分析了86例（34例R0和52例R1）被诊断为胰头腺癌并接受胰十二指肠切除术的258张术前CT图像。放射组学研究包括五个阶段：（i）描绘和分割感兴趣区域（ROI）；(ii) 通过求解具有 Dirichlet 边界条件的离散拉普拉斯方程，将 ROI 拟合到矩形区域；(iii) 结合小波变换和分数微分增强拟合 ROI 的纹理；(iv) 结合小波变换和统计分析方法从增强的 ROI 中提取纹理特征；(v) 使用主成分分析 (PCA) 减少特征并使用支持向量机 (SVM) 对切除边缘进行分类，U-测试。为了减少过拟合，SVM 分类器嵌入了一个线性核并采用了留一法交叉验证。结果。它实现了 0.8614 的 AUC（受试者工作特征曲线下面积）和 84.88% 的准确度。在Mann -Whitney U检验中，从小波分解中的对角子带导出的游程矩阵的两个特征在 R0 和 R1 之间显示出统计学上的显着差异。结论。这表明放射组学研究对 R0 和 R1 的辅助诊断是有益的。纹理特征可以潜在地提高医生的诊断能力。