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Neurological Sciences
Published in: Neurological Sciences 7/2022

24-02-2022 | Central Nervous System Trauma | Original Article

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

Authors: Rui-zhe Zheng, Zhi-jie Zhao, Xi-tao Yang, Shao-wei Jiang, Yong-de Li, Wen-jie Li, Xiu-hui Li, Yue Zhou, Cheng-jin Gao, Yan-bin Ma, Shu-ming Pan, Yang Wang

Published in: Neurological Sciences | Issue 7/2022

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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.
Appendix
Available only for authorised users
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Metadata
Title
Initial CT-based radiomics nomogram for predicting in-hospital mortality in patients with traumatic brain injury: a multicenter development and validation study
Authors
Rui-zhe Zheng
Zhi-jie Zhao
Xi-tao Yang
Shao-wei Jiang
Yong-de Li
Wen-jie Li
Xiu-hui Li
Yue Zhou
Cheng-jin Gao
Yan-bin Ma
Shu-ming Pan
Yang Wang
Publication date
24-02-2022
Publisher
Springer International Publishing
Published in
Neurological Sciences / Issue 7/2022
Print ISSN: 1590-1874
Electronic ISSN: 1590-3478
DOI
https://doi.org/10.1007/s10072-022-05954-8

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