论著摘要 |【Radiomics-CT】术前预测结肠直肠癌中淋巴结转移的影像组学诺模图的开发和验证(双语版)

2018-02-26 11:54:13 admin
标签:  影像组学 淋巴结 癌细胞转移 诺模图 直肠癌

Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer.

发表日期: 2016.06.20   来源:J Clin Oncol. 2016 Jun 20;34(18):2157-64.

作者:

Huang YQ1, Liang CH1, He L1, Tian J1, Liang CS1 , Chen X1, Ma ZL1, Liu ZY1.

作者介绍:

1. Yan-qi Huang, Chang-hong Liang, Lan He, Cui-shan Liang, Ze-lan Ma, and Zai-yi Liu, Guangdong General Hospital, Guangdong Academy of Medical Sciences; Yan-qi Huang, Cui-shan Liang, and Ze-lan Ma, Southern Medical University; Lan He, School of Medicine, South China University of Technology; Xin Chen, Affiliated Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou; and Jie Tian, Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, People's Republic of China.

摘要

Abstact

目的

开发和验证用于术前预测结直肠癌(CRC)患者淋巴结转移(LN)的影像组学诺模图。

Purpose

To develop and validate a radiomics nomogram for preoperative prediction of lymph node (LN) metastasis in patients with colorectal cancer (CRC).

患者和方法

预测模型是从326例临床病理证实的CRC患者组中进行开发,2007年1月至2010年4月收集数据。从CRC门静脉期计算机断层扫描(CT)中提取影像组学特征。LASSO回归模型用于数据维数缩减,特征选择和影像组学特征建立。多变量逻辑回归分析用于开发预测模型,纳入了影像组学特征,CT报告淋巴结转移状态和独立的临床病理危险因素,并用影像组学诺模图呈现。在其校准,鉴别和临床有用性方面对诺模图的表现进行了评估。评估其内部验证。独立验证组包含2010年5月至2011年12月连续的200例患者。

Patients and Methods

The prediction model was developed in a primary cohort that consisted of 326 patients with clinicopathologically confirmed CRC, and data was gathered from January 2007 to April 2010. Radiomic features were extracted from portal venous-phase computed tomography (CT) of CRC. Lasso regression model was used for data dimension reduction, feature selection, and radiomics signature building. Multivariable logistic regression analysis was used to develop the predicting model, we incorporated the radiomics signature, CT-reported LN status, and independent clinicopathologic risk factors, and this was presented with a radiomics nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Internal validation was assessed. An independent validation cohort contained 200 consecutive patients from May 2010 to December 2011.

结果

由24个选定特征组成的影像组学标记特征与淋巴结状态显著相关(主要组和验证组的P值均 < 0.001)。个体化预测诺模图中包含的预测因子包括影像组学特征,CT报告淋巴结转移状态和癌胚抗原水平。组织学分级添加到诺模图中未能显示出增加的预后价值。该模型显示出良好的校准性和良好的区分性,C指数为0.736(内部验证组C指数0.759到0.766)。在验证队列中应用诺模图仍然得到良好的校准性和很好的区分性(C指数,0.778 [95%CI,0.769〜0.787])。决策曲线分析表明影像组学诺模图在临床上是有用的。

Results

The radiomics signature, which consisted of 24 selected features, was significantly associated with LN status (P < .001 for both primary and validation cohorts). Predictors contained in the individualized prediction nomogram included the radiomics signature, CT-reported LN status, and carcinoembryonic antigen level. Addition of histologic grade to the nomogram failed to show incremental prognostic value. The model showed good discrimination, with a C-index of 0.736 (C-index, 0.759 and 0.766 through internal validation), and good calibration. Application of the nomogram in the validation cohort still gave good discrimination (C-index, 0.778 [95% CI, 0.769 to 0.787]) and good calibration. Decision curve analysis demonstrated that the radiomics nomogram was clinically useful.

结论

本研究展示了包括影像组学特征,CT报告淋巴结转移状态和临床危险因素的影像组学诺模图,可方便地用于促进直结肠癌患者术前淋巴结转移的个体化预测。

Conclusions

This study presents a radiomics nomogram that incorporates the radiomics signature, CT-reported LN status, and clinical risk factors, which can be conveniently used to facilitate the preoperative individualized prediction of LN metastasis in patients with CRC.

阅读原文:PMID: 27138577  DOI: 10.1200/JCO.2015.65.9128


慧影医疗科技(北京)有限公司

地点:北京市海淀区中关村东升科技园B2-C103

电话:400-890-9020

邮箱:radcloud@huiyihuiying.com

关闭
图片
图片