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01-12-2021 | Intracranial Aneurysm | Original Article

A nomogram to predict rupture risk of middle cerebral artery aneurysm

Authors: Jinjin Liu, Yongchun Chen, Dongqin Zhu, Qiong Li, Zhonggang Chen, Jiafeng Zhou, Boli Lin, Yunjun Yang, Xiufen Jia

Published in: Neurological Sciences | Issue 12/2021

Abstract

Background

Determining the rupture risk of unruptured intracranial aneurysm is crucial for treatment strategy. The purpose of this study was to predict the rupture risk of middle cerebral artery (MCA) aneurysms using a machine learning technique.

Methods

We retrospectively reviewed 403 MCA aneurysms and randomly partitioned them into the training and testing datasets with a ratio of 8:2. A generalized linear model with logit link was developed using training dataset to predict the aneurysm rupture risk based on the clinical variables and morphological features manually measured from computed tomography angiography. To facilitate the clinical application, we further constructed an easy-to-use nomogram based on the developed model.

Results

Ruptured MCA aneurysm had larger aneurysm size, aneurysm height, perpendicular height, aspect ratio, size ratio, bottleneck factor, and height-width ratio. Presence of a daughter-sac was more common in ruptured than in unruptured MCA aneurysms. Six features, including aneurysm multiplicity, lobulations, size ratio, bottleneck factor, height-width ratio, and aneurysm angle, were adopted in the model after feature selection. The model achieved a relatively good performance with areas under the receiver operating characteristic curves of 0.77 in the training dataset and 0.76 in the testing dataset. The nomogram provided a visual interpretation of our model, and the rupture risk probability of MCA aneurysms can be directly read from it.

Conclusion

Our model can be used to predict the rupture risk of MCA aneurysm.

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Title: A nomogram to predict rupture risk of middle cerebral artery aneurysm
Authors: Jinjin Liu
Yongchun Chen
Dongqin Zhu
Qiong Li
Zhonggang Chen
Jiafeng Zhou
Boli Lin
Yunjun Yang
Xiufen Jia
Publication date: 01-12-2021
Publisher: Springer International Publishing
Keywords: Intracranial Aneurysm
Aneurysm
Aneurysm
CT Angiography
Published in: Neurological Sciences / Issue 12/2021
Print ISSN: 1590-1874
Electronic ISSN: 1590-3478
DOI: https://doi.org/10.1007/s10072-021-05255-6

Keynote webinar | Spotlight on medication adherence

Springer Medicine

A nomogram to predict rupture risk of middle cerebral artery aneurysm

Abstract

Background

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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