Machine Learning-Based Prediction of Small Intracranial Aneurysm Rupture Status Using CTA-Derived Hemodynamics: A Multicenter Study

Machine Learning-Based Prediction of Small Intracranial Aneurysm Rupture Status Using CTA-Derived Hemodynamics: A Multicenter Study

Small intracranial aneurysms are being increasingly detected while the rupture risk is not well-understood. We aimed to develop rupture-risk models of small aneurysms by combining clinical, morphologic, and hemodynamic information based on machine learning techniques and to test the models in extern...

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Veröffentlicht in:American journal of neuroradiology : AJNR 2021-04, Vol.42 (4), p.648-654
Hauptverfasser: Shi, Z, Chen, G Z, Mao, L, Li, X L, Zhou, C S, Xia, S, Zhang, Y X, Zhang, B, Hu, B, Lu, G M, Zhang, L J
Format: Artikel
Sprache:eng
Schlagworte:
Adult Brain
Aneurysm, Ruptured - diagnostic imaging
Functional
Hemodynamics
Humans
Intracranial Aneurysm - diagnostic imaging
Machine Learning
Retrospective Studies
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Zusammenfassung:Small intracranial aneurysms are being increasingly detected while the rupture risk is not well-understood. We aimed to develop rupture-risk models of small aneurysms by combining clinical, morphologic, and hemodynamic information based on machine learning techniques and to test the models in external validation datasets. From January 2010 to December 2016, five hundred four consecutive patients with only small aneurysms (
ISSN:0195-6108
1936-959X
DOI:10.3174/ajnr.A7034