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Radiogenomics of neuroblastoma in pediatric patients: CT-based radiomics signature in predicting MYCN amplification

European Radiology volume 31, pages 3080–3089 (2021)Cite this article

Abstract

Objectives

To construct a CT-based radiomics signature and assess its performance in predicting MYCN amplification (MNA) in pediatric patients with neuroblastoma.

Methods

Seventy-eight pediatric patients with neuroblastoma were recruited (55 in training cohort and 23 in test cohort). Radiomics features were extracted automatically from the region of interest (ROI) manually delineated on the three-phase computed tomography (CT) images. Selected radiomics features were retained to construct radiomics signature and a radiomics score (rad-score) was calculated by using the radiomics signature–based formula. A clinical model was established with clinical factors, including clinicopathological data, and CT image features. A combined nomogram was developed with the incorporation of a radiomics signature and clinical factors. The predictive performance was assessed by receiver operating characteristics curve (ROC) analysis and decision curve analysis (DCA).

Results

The radiomics signature was constructed using 7 selected radiomics features. The clinical radiomics nomogram, which was based on the radiomics signature and two clinical factors, showed superior predictive performance compared with the clinical model alone (area under the curve (AUC) in the training cohort: 0.95 vs. 0.82, the test cohort: 0.91 vs. 0.70). The clinical utility of clinical radiomics nomogram was confirmed by DCA.

Conclusions

This proposed CT-based radiomics signature was able to predict MNA. Combining the radiomics signature with clinical factors outperformed using clinical model alone for MNA prediction.

Key Points

• A CT-based radiomics signature has the ability to predict MYCN amplification (MNA) in neuroblastoma.

• Both pre- and post-contrast CT images are valuable in predicting MNA.

• Associating the radiomics signature with clinical factors improved the predictive performance of MNA, compared with clinical model alone.

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Abbreviations

AIC:

Akaike information criterion

AUC:

Area under the curve

CI:

Confidence interval

CT:

Computed tomography

DCA:

Decision curve analysis

GLRLM:

Gray level run length matrix

ICCs:

Inter-/intra-observer class correlation coefficients

INRGSS:

International Neuroblastoma Risk Group Staging System

LASSO:

Least absolute shrinkage and selection operator

MDCT:

Multidetector computed tomography

MNA:

MYCN amplification

MRMR:

Maximum relevance minimum redundancy

OR:

Odds ratio

Rad-score:

Radiomics score

ROC:

Receiver operator characteristic

ROI:

Region of interest

SMOTE:

Synthetic minority oversampling technique

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Funding

This study has received from the National Key Research and Development Program of China (No. 2017YFC0109003).

Author information

Affiliations

  1. Department of Radiology, Xinhua Hospital affiliated of Shanghai Jiao Tong University School of Medicine, No.1665 Kongjiang Road, Yangpu District, Shanghai City, 200082, China

    Wu Haoting, Wu Chenqing, Zheng Hui, Wang Lei & Wang Dengbin

  2. Department of Pathology, Xinhua Hospital affiliated of Shanghai Jiao Tong University School of Medicine, No.1665 Kongjiang Road, Yangpu District, Shanghai City, 200082, China

    Guan Wenbin

  3. GE Healthcare, Pudong New Town, No.1, Huatuo Road, Shanghai, 210000, China

    Duan Shaofeng

Authors
  1. Wu Haoting
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  2. Wu Chenqing
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  3. Zheng Hui
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  4. Wang Lei
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  5. Guan Wenbin
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  6. Duan Shaofeng
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  7. Wang Dengbin
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Corresponding author

Correspondence to Wang Dengbin.

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Guarantor

The scientific guarantor of this publication is Dengbin Wang, MD, PhD, the chief of department of radiology, Xinhua hospital affiliated to Shanghai Jiao Tong University School of Medicine.

Conflict of interest

One of the authors of this manuscript (Shaofeng Duan) is an employee of GE Healthcare. The remaining authors declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

Shaofeng Duan kindly provided statistical advice for this manuscript.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

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Wu, H., Wu, C., Zheng, H. et al. Radiogenomics of neuroblastoma in pediatric patients: CT-based radiomics signature in predicting MYCN amplification. Eur Radiol 31, 3080–3089 (2021). https://doi.org/10.1007/s00330-020-07246-1

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  • DOI: https://doi.org/10.1007/s00330-020-07246-1

Keywords

  • Radiogenomics
  • Neuroblastoma
  • Multidetector computed tomography