论著摘要 |【Radiomics-CT】一项基于CT的影像组学的术前区分I-II期和III-IV期结肠直肠癌的研究开发与验证(双语版)

2018-05-21 10:44:05 admin
标签:   影像组学 CT 结直肠癌 分期

The development and validation of a CT-based radiomics signature for the preoperative discrimination of stage I-II and stage III-IV colorectal cancer.

发表日期: 2016.05.24   来源:Oncotarget. 2016 May 24;7(21):31401-12.

作者:

Liang C1,2, Huang Y1,2, He L1,3, Chen X4, Ma Z1,2, Dong D5, Tian J5, Liang C1, Liu Z1.

作者介绍:

1. Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.

2. Graduate College, Southern Medical University, Guangzhou, 510515, China.

3. School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510006, China.

4. Department of Radiology, The Affiliated Guangzhou First People' Hospital, Guangzhou Medical University, Guangzhou, 510180, China.

5. Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, 100190, China.

摘要

Abstact

目标

探讨影像组学对于原发性结直肠癌(CRC)术前分期(I-IIvs.III-IV)的预测能力。

Objective

To investigative the predictive ability of radiomics signature for preoperative staging (I-IIvs.III-IV) of primary colorectal cancer (CRC).

方法

本研究由494例连续的处于I-IV阶段的CRC患者(训练数据集:n = 286;验证队列,n = 208)组成。使用LASSO逻辑回归模型产生一个影像组学特征。探索了影像组学特征与CRC分期之间的关系。根据受试者工作特征(ROC)曲线探讨了影像组学特征的分类性能。

Methods

This study consisted of 494 consecutive patients (training dataset: n=286; validation cohort, n=208) with stage I-IV CRC. A radiomics signature was generated using LASSO logistic regression model. Association between radiomics signature and CRC staging was explored. The classification performance of the radiomics signature was explored with respect to the receiver operating characteristics(ROC) curve.

结果

基于16个特征的影像组学特征是CRC分期的独立预测因子,可以在训练和验证数据集中将CRC成功分类到I-II和III-IV期(p < 0.0001)。在训练和验证数据集中,III-IV期的影像组学特征中位数高于I-II期。至于CRC分期中的影像组学特征的分类表现,AUC为0.792(95%CI:0.741-0.853),敏感性为0.629,特异性为0.874。而验证数据集中的影像组学特征获得了0.708(95%CI:0.698-0.718)的AUC,灵敏度为0.611,特异性为0.680。

Results

The 16-feature-based radiomics signature was an independent predictor for staging of CRC, which could successfully categorize CRC into stage I-II and III-IV (p < 0.0001) in training and validation dataset. The median of radiomics signature of stage III-IV was higher than stage I-II in the training and validation dataset. As for the classification performance of the radiomics signature in CRC staging, the AUC was 0.792(95%CI:0.741-0.853) with sensitivity of 0.629 and specificity of 0.874. The signature in the validation dataset obtained an AUC of 0.708(95%CI:0.698-0.718) with sensitivity of 0.611 and specificity of 0.680.

结论

开发了一种影像组学特征标记,并将其作为I-II期和III-IV期CRC区分的重要预测指标,可作为CRC术前肿瘤分期的补充工具。

Conclusions

A radiomics signature was developed and validated to be a significant predictor for discrimination of stage I-II from III-IV CRC, which may serve as a complementary tool for the preoperative tumor staging in CRC.

关键词:

结直肠癌,计算断层,预测指标,影像组学,分期

Keywords:

colorectal cancer; computed tomography; predictor; radiomics signature; stage

阅读原文:PMID: 27120787  PMCID: PMC5058766  DOI: 10.18632/oncotarget.8919


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