论著摘要 |【MR】多参数磁共振影像的影像组学特征作为晚期鼻咽癌中的新型预后因素(双语版)

2017-12-20 13:55:14 admin 1

Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma.

发表日期: 2017.08.1   来源:Clinical Cancer Research. 2017 Aug 1;23(15):4259-4269.

作者:

Zhang B1,2, Tian J3, Dong D33 , Gu D3, Dong Y1,4, Zhang L1,2, Lian Z1,2, Liu J1,2, Luo X1,2, Pei S1,2 , Mo X1,4, Huang W1,5, Ouyang F1,2, Guo B1,2, Liang L1,2, Chen W6, Liang C1, Zhang S7.

作者介绍:

1. Department of Radiology, Guangdong General Hospital/Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, P.R. China.

2. Graduate College, Southern Medical University, Guangzhou, Guangdong, P.R. China.

3. Key Laboratory of Molecular Imaging, Chinese Academy of Science, Beijing, P.R. China.

4. Shantou University Medical College, Guangdong, P.R. China.

5. School of Medicine, South China University of Technology, Guangzhou, Guangdong, P.R. China.

6. Department of Radiology, Huizhou Municipal Central Hospital, Huizhou, Guangdong, P.R. China.

7. Department of Radiology, Guangdong General Hospital/Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, P.R. China.

摘要

Abstact

目的

鉴定基于MRI的影像组学特征作为晚期鼻咽癌(NPC)患者的预后因素。

Purpose

To identify MRI-based radiomics as prognostic factors in patients with advanced nasopharyngeal carcinoma (NPC).

实验设计

纳入了118例晚期鼻咽癌患者(实验组:n = 88;验证组:n = 30)。从T2加权(T2-w)和对比增强T1加权(CET1-w)MRI中提取总共970个影像组学特征。应用最小绝对收缩和选择算子(LASSO)回归来选择无进展生存(PFS)诺模图的特征。评估诺模图辨别性和校准性。使用热图研究影像组学特征与临床数据之间的联系。

Experimental Design

One-hundred and eighteen patients (training cohort: n = 88; validation cohort: n = 30) with advanced NPC were enrolled. A total of 970 radiomics features were extracted from T2-weighted (T2-w) and contrast-enhanced T1-weighted (CET1-w) MRI. Least absolute shrinkage and selection operator (LASSO) regression was applied to select features for progression-free survival (PFS) nomograms. Nomogram discrimination and calibration were evaluated. Associations between radiomics features and clinical data were investigated using heatmaps.

结果

影像组学特征与PFS显著相关。从联合CET1-w和T2-w图像衍生的影像组学标记与仅来自CET1-w或T2-w图像的标记相比显示出更好的预后性能。一个影像组学诺模图将联合CET1-w和T2-w图像的影像组学标记与TNM分期系统相结合。这个诺模图在评估实验组中的PFS方面显著提高(C指数,0.761 vs. 0.514; P<2.68×10-9),优于TNM分期系统。另一个影像组学诺模图将所有临床数据的影像组学标记整合在一起,从而优于仅基于临床数据的一个诺模图(C指数,0.776 vs. 0.649; P <1.60×10-7)。校准曲线显示良好的一致性。结果在验证组中得到证实。热图显示了影像组学特征与肿瘤分期之间的关系。

Results

The radiomics signatures were significantly associated with PFS. A radiomics signature derived from joint CET1-w and T2-w images showed better prognostic performance than signatures derived from CET1-w or T2-w images alone. One radiomics nomogram combined a radiomics signature from joint CET1-w and T2-w images with the TNM staging system. This nomogram showed a significant improvement over the TNM staging system in terms of evaluating PFS in the training cohort (C-index, 0.761 vs. 0.514; P < 2.68 × 10−9). Another radiomics nomogram integrated the radiomics signature with all clinical data, and thereby outperformed a nomogram based on clinical data alone (C-index, 0.776 vs. 0.649; P < 1.60 × 10−7). Calibration curves showed good agreement. Findings were confirmed in the validation cohort. Heatmaps revealed associations between radiomics features and tumor stages.

结论

基于多参数MRI的影像组学诺模图在晚期NPC中预后能力得到提高。这些结果为精准医学提供了例证,并可能影响治疗策略。

Conclusions

Multiparametric MRI-based radiomics nomograms provided improved prognostic ability in advanced NPC. These results provide an illustrative example of precision medicine and may affect treatment strategies.

阅读原文:PMID: 28280088  DOI: 10.1158/1078-0432.CCR-16-2910


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