论著摘要 |【CT】使用锥束CT图像的影像组学分析对非小细胞肺癌患者进行生存预测(双语版)

2017-12-19 11:25:48 admin 9

Survival prediction of non-small cell lung cancer patients using radiomics analyses of cone-beam CT images.

发表日期: 2017.05.12   来源Radiotherapy and Oncology. 2017 Jun;123(3):363-369.

作者

van Timmeren JE1, Leijenaar RTH2, van Elmpt W2, Reymen B2, Oberije C2, Monshouwer R3, Bussink J3, Brink C4, Hansen O5, Lambin P2.

作者介绍: 

1. Department of Radiation Oncology (MAASTRO), GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre (MUMC), The Netherlands.

2. Department of Radiation Oncology (MAASTRO), GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre (MUMC), The Netherlands.

3. Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands.

4. Institute of Clinical Research, University of Southern Denmark, Odense, Denmark; Laboratory of Radiation Physics, Odense University Hospital, Denmark.

5. Institute of Clinical Research, University of Southern Denmark, Odense, Denmark; Laboratory of Radiation Physics, Odense University Hospital, Denmark; Department of Oncology, Odense University Hospital, Denmark.

目的和背景

在本研究中,我们研究了断层CT和锥束CTCBCT)提取影像组学特征的互换性。此外,一个先前基于CT的预后影像组学标记的非小细胞肺癌(NSCLC)患者使用CBCT的特征进行了验证。

Background and purpose

In this study we investigated the interchangeability of planning CT and cone-beam CT (CBCT) extracted radiomic features. Furthermore, a previously described CT based prognostic radiomic signature for non-small cell lung cancer (NSCLC) patients using CBCT based features was validated.

材料与方法

研究对象包括132位患者的训练数据集和分别有62位和94I-IVNSCLC患者的两个验证数据集。通过对CTCBCT提取的特征进行线性回归来评估互换性。在对先前发表的影像组学标记进行模型验证之前,应用两步校正。

Material and methods

One training dataset of 132 and two validation datasets of 62 and 94 stage IIV NSCLC patients were included. Interchangeability was assessed by performing a linear regression on CT and CBCT extracted features. A two-step correction was applied prior to model validation of a previously published radiomic signature.

结果

13.3%149/1119)的影像组学特征,包括先前发表的影像组学标记的所有特征,在联运成像技术之间显示出高于0.85R2值。对于影像组学特征,Kaplan-Meier曲线在具有高和低预后值的两种模式的组间差异显著。数据集1CT数据Harrell一致性指数为0.69CBCT0.66

Results

13.3% (149 out of 1119) of the radiomic features, including all features of the previously published radiomic signature, showed an R2 above 0.85 between intermodal imaging techniques. For the radiomic signature, KaplanMeier curves were significantly different between groups with high and low prognostic value for both modalities. Harrells concordance index was 0.69 for CT and 0.66 for CBCT models for dataset 1.

结论

结果表明,从CTCBCT图像提取的影像组学的子集可以使用简单的线性回归互换。此外,先前开发的影像组学标记对三个CBCT组的整体生存具有预后价值,显示了CBCT影像组学作为预后成像生物标志物的潜力。

Conclusions

The results show that a subset of radiomic features extracted from CT and CBCT images are interchangeable using simple linear regression. Moreover, a previously developed radiomics signature has prognostic value for overall survival in three CBCT cohorts, showing the potential of CBCT radiomics to be used as prognostic imaging biomarker.

关键词:

计算机断层扫描,锥束CT,非小细胞肺癌,影像组学,生存预测

Keywords: 

Computed tomography; Cone-beam CT; Non-small cell lung cancer; Radiomics; Survival prediction

阅读原文:PMID:28506693  DOI:10.1016/j.radonc.2017.04.016


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