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European Radiology

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01-05-2021 | Intracranial Aneurysm | Imaging Informatics and Artificial Intelligence

A preliminary investigation of radiomics differences between ruptured and unruptured intracranial aneurysms

Authors: Chubin Ou, Winston Chong, Chuan-Zhi Duan, Xin Zhang, Michael Morgan, Yi Qian

Published in: European Radiology | Issue 5/2021

Abstract

Objectives

Prediction of intracranial aneurysm rupture is important in the management of unruptured aneurysms. The application of radiomics in predicting aneurysm rupture remained largely unexplored. This study aims to evaluate the radiomics differences between ruptured and unruptured aneurysms and explore its potential use in predicting aneurysm rupture.

Methods

One hundred twenty-two aneurysms were included in the study (93 unruptured). Morphological and radiomics features were extracted for each case. Statistical analysis was performed to identify significant features which were incorporated into prediction models constructed with a machine learning algorithm. To investigate the usefulness of radiomics features, three models were constructed and compared. The baseline model A was constructed with morphological features, while model B was constructed with addition of radiomics shape features and model C with more radiomics features. Multivariate analysis was performed for the ten most important variables in model C to identify independent risk factors. A simplified model based on independent risk factors was constructed for clinical use.

Results

Five morphological features and 89 radiomics features were significantly associated with rupture. Model A, model B, and model C achieved the area under the receiver operating characteristic curve of 0.767, 0.807, and 0.879, respectively. Model C was significantly better than model A and model B (p < 0.001). Multivariate analysis identified two radiomics features which were used to construct the simplified model showing an AUROC of 0.876.

Conclusions

Radiomics signatures were different between ruptured and unruptured aneurysms. The use of radiomics features, especially texture features, may significantly improve rupture prediction performance.

Key Points

• Significant radiomics differences exist between ruptured and unruptured intracranial aneurysms.

• Radiomics shape features can significantly improve rupture prediction performance over conventional morphology-based prediction model. The inclusion of histogram and texture radiomics features can further improve the performance.

• A simplified model with two variables achieved a similar level of performance as the more complex ones. Our prediction model can serve as a promising tool for the risk management of intracranial aneurysms.

Available only for authorised users

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Title: A preliminary investigation of radiomics differences between ruptured and unruptured intracranial aneurysms
Authors: Chubin Ou
Winston Chong
Chuan-Zhi Duan
Xin Zhang
Michael Morgan
Yi Qian
Publication date: 01-05-2021
Publisher: Springer Berlin Heidelberg
Keywords: Intracranial Aneurysm
Aneurysm
Aneurysm
Published in: European Radiology / Issue 5/2021
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-020-07325-3

Keynote webinar | Spotlight on medication adherence

Springer Medicine

A preliminary investigation of radiomics differences between ruptured and unruptured intracranial aneurysms

Abstract

Objectives

Methods

Results

Conclusions

Key Points

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objectives

Methods

Results

Conclusions

Key Points

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