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Radiomics nomogram outperforms size criteria in discriminating lymph node metastasis in resectable esophageal squamous cell carcinoma

机译:辐射瘤NOM图优于鉴别可重置食管鳞状细胞癌中的鉴别淋巴结转移方面的尺寸标准

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ObjectivesTo determine the value of radiomics in predicting lymph node (LN) metastasis in resectable esophageal squamous cell carcinoma (ESCC) patients.MethodsData of 230 consecutive patients were retrospectively analyzed (154 in the training set and 76 in the test set). A total of 1576 radiomics features were extracted from arterial-phase CT images of the whole primary tumor. LASSO logistic regression was performed to choose the key features and construct a radiomics signature. A radiomics nomogram incorporating this signature was developed on the basis of multivariable analysis in the training set. Nomogram performance was determined and validated with respect to its discrimination, calibration and reclassification. Clinical usefulness was estimated by decision curve analysis.ResultsThe radiomics signature including five features was significantly associated with LN metastasis. The radiomics nomogram, which incorporated the signature and CT-reported LN status (i.e. size criteria), distinguished LN metastasis with an area under curve (AUC) of 0.758 in the training set, and performance was similar in the test set (AUC 0.773). Discrimination of the radiomics nomogram exceeded that of size criteria alone in both the training set (p 0.001) and the test set (p=0.005). Integrated discrimination improvement (IDI) and categorical net reclassification improvement (NRI) showed significant improvement in prognostic value when the radiomics signature was added to size criteria in the test set (IDI 17.3%; p0.001; categorical NRI 52.3%; p0.001). Decision curve analysis supported that the radiomics nomogram is superior to size criteria.ConclusionsThe radiomics nomogram provides individualized risk estimation of LN metastasis in ESCC patients and outperforms size criteria.Key Points center dot A radiomics nomogram was built and validated to predict LN metastasis in resectable ESCC.center dot The radiomics nomogram outperformed size criteria.center dot Radiomics helps to unravel intratumor heterogeneity and can serve as a novel biomarker for determination of LN status in resectable ESCC.
机译:ObjectiveSto确定可重复食管鳞状细胞癌(ESCC)患者预测淋巴结(LN)转移中的淋巴细胞组从整个原发性肿瘤的动脉相CT图像中提取了总共1576个射线组织特征。执行套索逻辑回归以选择关键特征并构建辐射瘤签名。结合该签名的辐射瘤NOM图是在训练集中的多变量分析的基础上开发的。确定并验证载体性能,并验证了其歧视,校准和重新分类。通过判定曲线分析估计临床有用性。包括五种特征的辐射瘤签名与LN转移显着相关。结合签名和CT报告的LN状态(即尺寸标准)的辐射瘤NOM图,将LN转移与训练集0.758的曲线(AUC)的区域区分开,并且在测试集中的性能相似(AUC 0.773) 。在训练集(P <0.001)和试验组中,在训练集中仅超过尺寸标准的歧视超出了大小标准(P = 0.005)。综合歧视改善(IDI)和分类净重新分类改善(NRI)在试验组中加入到尺寸标准时,预后值(IDI 17.3%; P <0.001分类NRI 52.3%; P <0.001 )。决策曲线分析支持辐射瘤NOM图优于尺寸标准。结论rucioMics NOM图提供了ESCC患者的LN转移的个性化风险估算,并且优于尺寸标准.Key点中心点建立并验证了RNICATION NOM图以预测可重型ESCC中的LN转移.Center点辐射罗米图优于大小标准.Center点辐射瘤有助于解开肿瘤内异质性,并且可以用作新的生物标志物,用于测定可重置的ESCC中的LN状态。

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