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An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study

  • Imaging Informatics and Artificial Intelligence
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

To explore whether radiomics features extracted from pre-treatment magnetic resonance imaging (MRI) can predict the overall survival (OS) in patients with hypopharyngeal squamous cell carcinoma.

Methods

A total of 190 patients with hypopharyngeal squamous cell carcinoma were eligibly enrolled from two institutions. Radiomics features were extracted from contrast-enhanced axial T1-weighted (CE-T1WI) sequence. The least absolute shrinkage selection operator (LASSO) algorithm was applied to establish a radiomics score correlated with OS. Multivariate logistic regression analysis was applied to determine the independent risk factors, which was combined with radiomics score to build the final radiomics nomogram.

Results

A radiomics score with 6 CE-T1WI features for OS prediction was constructed and validated; its integration with specific clinicopathologic factors (N stage) showed a better prediction performance in the training, internal validation, and external validation cohorts (C-index 0.78, 0.75, and 0.75). Calibration curves determined a good agreement between the predicted and actual overall survival.

Conclusions

The radiomics-clinical nomogram and radiomics score might be non-invasive and reliable methods for the risk stratification in patients with hypopharyngeal squamous cell carcinoma.

Key Points

• An MRI-based radiomics model was constructed to evaluate of OS in patients with hypopharyngeal squamous cell carcinoma.

• A radiomics-clinical nomogram that combined radiomics features and clinical characteristics was established.

• Multi-cohort study validated the predictive performance of the radiomics-clinical nomogram to stratify patients with high risk in clinical practice.

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Abbreviations

CE-T1WI:

Contrast-enhanced T1-weighted sequence

C-index:

Harrell’s concordance index

CT:

Computed tomography

HNC:

Head and neck cancer

LASSO:

The least absolute shrinkage and selection operator

LMR:

Lymphocyte-to-monocyte ratio

MRI:

Magnetic resonance imaging

NLR:

Neutrophil-to-lymphocyte ratio

OS:

Overall survival

PACS:

Picture Archiving and Communication System

PLR:

Platelet-to-lymphocyte ratio

ROI:

Region of interest

TNM:

The Tumor, Node, Metastasis staging system

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (Nos. 82073009, 81974424, 81874133, 81773243, 81772903 and 81602684), the National Key Research and Development Program of China (2020YFC1316900, 2020YFC1316901), the Natural Science Foundation of Hunan Province (Nos. 2019JJ40481, 2019JJ50944, 2018JJ2630 and 2017JJ3488), the Huxiang Young Talent Project (No. 2018RS3024) and Young Scientist Research Fund of **angya Hospital (No. 2018Q019).

Funding

This study was supported by the National Natural Science Foundation of China (Nos. 82073009, 81974424, 81874133, 81773243, 81772903 and 81602684), the National Key Research and Development Program of China (2020YFC1316900, 2020YFC1316901), the Natural Science Foundation of Hunan Province (Nos. 2019JJ40481, 2019JJ50944, 2018JJ2630 and 2017JJ3488), the Huxiang Young Talent Project (No. 2018RS3024) and Young Scientist Research Fund of **angya Hospital (No. 2018Q019).

Author information

Author notes

  1. Juan Chen and Shanhong Lu contributed equally to this work.

Authors and Affiliations

  1. Department of Otolaryngology-Head and Neck Surgery, **angya Hospital, Central South University, 87 **angya Road, Changsha, 410008, Hunan, China

    Juan Chen, Shanhong Lu, Guo Li, Yan Gao, Donghai Huang, **n Zhang, Yuanzheng Qiu & Yong Liu

  2. Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, 410008, Hunan, China

    Juan Chen, Shanhong Lu, Guo Li, Yan Gao, Donghai Huang, **n Zhang, Yuanzheng Qiu & Yong Liu

  3. Clinical Research Center for Pharyngolaryngeal Diseases and Voice Disorders in Hunan Province, Changsha, 410008, Hunan, China

    Juan Chen, Shanhong Lu, Guo Li, Yan Gao, Donghai Huang, **n Zhang, Yuanzheng Qiu & Yong Liu

  4. Department of Radiology, **angya Hospital, Central South University, Changsha, 410008, Hunan, China

    Yitao Mao

  5. College of Computer and Information Engineering, Hunan University of Technology and Business, Changsha, 410205, Hunan, China

    Lei Tan

  6. Department of Head and Neck Surgery, The Affiliated Tumor Hospital of **angya Medical School, Hunan Cancer Hospital, Central South University, Changsha, 410013, Hunan, China

    **qing Tan

  7. National Clinical Research Center for Geriatric Disorders (**angya Hospital), **angya Road, Changsha, 410008, Hunan, China

    Donghai Huang, **n Zhang, Yuanzheng Qiu & Yong Liu

Authors
  1. Juan Chen
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  2. Shanhong Lu
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Corresponding authors

Correspondence to Yuanzheng Qiu or Yong Liu.

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Guarantor

The guarantor of this publication is Yuanzheng Qiu.

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

One of the authors (Yan Gao) has significant statistical expertise.

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Written informed consent was waved by the Institutional Review Board.

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Institutional Review Board approval was obtained.

Methodology

  • retrospective

  • diagnostic or prognostic study

  • performed at multiple institution

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Chen, J., Lu, S., Mao, Y. et al. An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study. Eur Radiol 32, 1548–1557 (2022). https://doi.org/10.1007/s00330-021-08292-z

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