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Initial CT-based radiomics nomogram for predicting in-hospital mortality in patients with traumatic brain injury: a multicenter development and validation study

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Abstract

Objective

To develop and validate a radiomic prediction model using initial noncontrast computed tomography (CT) at admission to predict in-hospital mortality in patients with traumatic brain injury (TBI).

Methods

A total of 379 TBI patients from three cohorts were categorized into training, internal validation, and external validation sets. After filtering the unstable features with the minimum redundancy maximum relevance approach, the CT-based radiomics signature was selected by using the least absolute shrinkage and selection operator (LASSO) approach. A personalized predictive nomogram incorporating the radiomic signature and clinical features was developed using a multivariate logistic model to predict in-hospital mortality in patients with TBI. The calibration, discrimination, and clinical usefulness of the radiomics signature and nomogram were evaluated.

Results

The radiomic signature consisting of 12 features had areas under the curve (AUCs) of 0.734, 0.716, and 0.706 in the prediction of in-hospital mortality in the internal and two external validation cohorts. The personalized predictive nomogram integrating the radiomic and clinical features demonstrated significant calibration and discrimination with AUCs of 0.843, 0.811, and 0.834 in the internal and two external validation cohorts. Based on decision curve analysis (DCA), both the radiomic features and nomogram were found to be clinically significant and useful.

Conclusion

This predictive nomogram incorporating the CT-based radiomic signature and clinical features had maximum accuracy and played an optimized role in the early prediction of in-hospital mortality. The results of this study provide vital insights for the early warning of death in TBI patients.

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Funding

We gratefully acknowledge the following funding source: the National Natural Science Foundation of China (81772111 and 81871458), the China Postdoctoral Science Foundation (No. 2017M611585), the Biomedical and Engineering Cross Youth Fund of Shanghai Jiao Tong University (No. YG2021QN43), and the Shanghai Science Committee (No.19411968200).

Author information

Author notes

  1. Rui-zhe Zheng, Zhi-jie Zhao, and Xi-tao Yang are contributed equally in this work

Authors and Affiliations

  1. Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China

    Rui-zhe Zheng

  2. Department of Neurosurgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Zhi-jie Zhao

  3. Department of Interventional Radiology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Xi-tao Yang

  4. Department of Emergency, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Shao-wei Jiang, Yong-de Li, Wen-jie Li, Cheng-jin Gao, Shu-ming Pan & Yang Wang

  5. Department of Neurosurgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Xiu-hui Li & Yan-bin Ma

  6. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China

    Yue Zhou

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  1. Rui-zhe Zheng
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Corresponding authors

Correspondence to Yan-bin Ma, Shu-ming Pan or Yang Wang.

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Ethical approval

In this study, all patients enrolled in this study have signed the broad consent, which permits the researchers to engage in research use of identifiable biospecimens and identifiable data during the pre-operative period and future follow-up without the requirement to obtain additional consent for future storage, maintenance, or research uses, so long as the future activities are within the scope of the broad consent. The study protocol and the application form were fully reviewed, and we have certified that this study did not raise any issues of patient risk or cause any harm to patient. We have also certified that the study was strictly in accordance with the Declaration of Helsinki and International Ethical Guidelines for Health-related Research Involving Humans.

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The authors declare no competing interests.

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Zheng, Rz., Zhao, Zj., Yang, Xt. et al. Initial CT-based radiomics nomogram for predicting in-hospital mortality in patients with traumatic brain injury: a multicenter development and validation study. Neurol Sci 43, 4363–4372 (2022). https://doi.org/10.1007/s10072-022-05954-8

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  • DOI: https://doi.org/10.1007/s10072-022-05954-8

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