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European Radiology

, Volume 28, Issue 5, pp 2058–2067 | Cite as

Can CT-based radiomics signature predict KRAS/NRAS/BRAF mutations in colorectal cancer?

  • Lei Yang
  • Di Dong
  • Mengjie Fang
  • Yongbei Zhu
  • Yali Zang
  • Zhenyu Liu
  • Hongmei Zhang
  • Jianming Ying
  • Xinming Zhao
  • Jie Tian
Gastrointestinal

Abstract

Objectives

To investigate whether CT-based radiomics signature can predict KRAS/NRAS/BRAF mutations in colorectal cancer (CRC).

Methods

This retrospective study consisted of a primary cohort (n = 61) and a validation cohort (n = 56) with pathologically confirmed CRC. Patients underwent KRAS/NRAS/BRAF mutation tests and contrast-enhanced CT before treatment. A total of 346 radiomics features were extracted from portal venous-phase CT images of the entire primary tumour. Associations between the genetic mutations and clinical background, tumour staging, and histological differentiation were assessed using univariate analysis. RELIEFF and support vector machine methods were performed to select key features and build a radiomics signature.

Results

The radiomics signature was significantly associated with KRAS/NRAS/BRAF mutations (P < 0.001). The area under the curve, sensitivity, and specificity for predicting KRAS/NRAS/BRAF mutations were 0.869, 0.757, and 0.833 in the primary cohort, respectively, while they were 0.829, 0.686, and 0.857 in the validation cohort, respectively. Clinical background, tumour staging, and histological differentiation were not associated with KRAS/NRAS/BRAF mutations in both cohorts (P>0.05).

Conclusions

The proposed CT-based radiomics signature is associated with KRAS/NRAS/BRAF mutations. CT may be useful for analysis of tumour genotype in CRC and thus helpful to determine therapeutic strategies.

Key Points

Key features were extracted from CT images of the primary colorectal tumour.

The proposed radiomics signature was significantly associated with KRAS/NRAS/BRAF mutations.

In the primary cohort, the proposed radiomics signature predicted mutations.

Clinical background, tumour staging, and histological differentiation were unable to predict mutations.

Keywords

Colorectal neoplasms Adenocarcinoma Mutation Diagnostic imaging ROC curve 

Abbreviations and Acronyms

AFP

Alpha fetoprotein

AUC

Area under curve

CA199

Carbohydrate antigen 199

CA242

Carbohydrate antigen 242

CA724

Carbohydrate antigen 724

CEA

Carcinoembryonic antigen

CI

Confidence interval

CRC

Colorectal cancer

CT

Computed tomography

EGFR

Epidermal growth factor receptor

18F-FDG PET/CT

Positron emession tomography/computerd tomography with 18F-fluorodexyglucose

FFPE

Formalin-fixed paraffin- embedded

GLCM

Gray-level co-occurrence matrix

GLRLM

Gray-level run-length matrix

ICCs

Intra-/inter-class correlation coefficients

NCCN

Nationgal comprehensive cancer network

NGS

Next-generation sequencing

OR

Odds ratio

PACS

Picture archiving and communication system

ROC

Receiver operating characteristic

SUV

Standardized uptake value

TPS

Tissue polypeptide specific antigen

3D

Three-dimensional

Notes

Funding

This study has received funding by the National Natural Science Foundation of China (grant numbers 81227901, 81771924, 61231004, 81501616, 81671851, 81527805, 81501549, 81671829 and 81671757), the National Key R&D Program of China (grant numbers 2017YFA0205200, 2017YFC1308700, 2017YFC1309100, and 2017YFC1308701), the Science and Technology Service Network Initiative of the Chinese Academy of Sciences (grant number KFJ-SW-STS-160), the Instrument Developing Project (grant number YZ201502), the Beijing Municipal Science and Technology Commission (grant number Z161100002616022), and the Youth Innovation Promotion Association CAS.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Jie Tian.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived in this study.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• diagnostic experimental

• performed at one institution

Supplementary material

330_2017_5146_MOESM1_ESM.docx (555 kb)
ESM 1 (DOCX 555 kb)

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  1. 1.Department of Diagnostic RadiologyNational Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
  2. 2.CAS Key Laboratory of Molecular Imaging, Institute of AutomationChinese Academy of SciencesBeijingChina
  3. 3.University of Chinese Academy of SciencesBeijingChina
  4. 4.Beijing Key Lab of Molecular ImagingBeijingChina
  5. 5.Department of PathologyNational Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
  6. 6.The State Key Laboratory of Management and Control for Complex Systems, Institute of AutomationChinese Academy of SciencesBeijingChina

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