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European Radiology
Published in: European Radiology 8/2022

10-03-2022 | Brainstem Infarction | Computed Tomography

A new scheme of global feature management improved the performance and stability of radiomics model: a study based on CT images of acute brainstem infarction

Authors: Yuefeng Li, Yuhang Xie, Yuhao Xu, Ningning Zhang, Guohai Li, Shenghong Ju

Published in: European Radiology | Issue 8/2022

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Abstract

Objective

The performance and stability of radiomics model caused by dimension reduction remain being confronted with major challenges. In this study, we aimed to propose a new scheme of global feature management independent of dimension reduction to improve it.

Methods

The non-contrast computed tomography (NCCT) images of acute brainstem infarction (ABI) from two medical centers were used as test and validation sets. A new scheme was constructed based on global feature management, and the traditional scheme dependent on dimension reduction was used as control. The radiomic features of NCCT images were extracted in Matlab R2013a. The performance of prediction model was evaluated by the generalized linear model (GLM) and multivariate logistic regression. And, the stability of radiomics model was evaluated with the difference of area under curve (AUC) between the test and validation sets.

Results

Compared with the traditional scheme, the new scheme presented a similar detection performance (AUC: 0.875 vs. 0.883), yet a better performance in predicting prognosis (AUC: 0.864, OR = 0.917, p = 0.021 vs. AUC:0.806, OR = 0.972, p = 0.007). All these results were well verified in an independent validation set. Moreover, the new scheme showed stronger stability in both the detection model (ΔAUC: 0.013 vs. 0.039) and prediction model (ΔAUC = 0.004 vs. 0.044).

Conclusion

Although there might be several limitations, this study proved that the scheme of global feature management independent of dimension reduction could be a powerful supplement to the radiomics methodology.

Key Points

• The new scheme (S wavelet ) presented similar detection performances for ABI with the traditional scheme.
• A better predictive performance for END was found in the new scheme (S wavelet ) compared with the traditional scheme.
• Stronger model stability was found in both the detection and prediction models based on the new scheme.
Appendix
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Metadata
Title
A new scheme of global feature management improved the performance and stability of radiomics model: a study based on CT images of acute brainstem infarction
Authors
Yuefeng Li
Yuhang Xie
Yuhao Xu
Ningning Zhang
Guohai Li
Shenghong Ju
Publication date
10-03-2022
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 8/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-022-08659-w

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