Background Numerous studies have evaluated the rupture risk of intracranial aneurysms using morphological parameters because of their good predictive capacity. However, the limitation of current morphological parameters is that they do not always allow evaluation of irregularities of intracranial aneurysms. The purpose of this study is to propose a new morphological parameter that can quantitatively describe irregularities of intracranial aneurysms and to evaluate its performance regarding rupture risk prediction.
Methods In a retrospective study, conventional morphological parameters (aspect ratio, bottleneck ratio, height-to-width ratio, volume to ostium ratio, and size ratio) and a newly proposed morphological parameter (mass moment of inertia) were calculated for 125 intracranial aneurysms (80 unruptured and 45 ruptured aneurysms). Additionally, hemodynamic parameters (wall shear stress and strain) were calculated using computational fluid dynamics and fluid–structure interaction. Artificial neural networks trained with each parameter were used for rupture risk prediction.
Results All components of the mass moment of inertia (Ixx, Iyy, and Izz) were significantly higher in ruptured cases than in unruptured cases (p values for Ixx, Iyy, and Izz were 0.032, 0.047, and 0.039, respectively). When the conventional morphological and hemodynamic parameters as well as the mass moment of inertia were considered together, the highest performance for rupture risk prediction was obtained (sensitivity 96.3%; specificity 85.7%; area under the receiver operating characteristic curve 0.921).
Conclusions The mass moment of inertia would be a useful parameter for evaluating aneurysm irregularity and hence its risk of rupture. The new approach described here may help clinicians to predict the risk of aneurysm rupture more effectively.
Data availability statement
No data are available.
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HY and K-CC are joint first authors.
Contributors HDY and KC-C contributed equally to this work as co-first authors. JHO and YBK contributed equally to this work as co-corresponding authors. JJK, HDY, and KC-C gathered the data and collaboratively drafted the manuscript. JHO and YBK conceptualized the study and supervised the work within their respective specialties. All authors approved the final version of the manuscript. JHO and YBK are guarantors of this work.
Funding This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT). (No. 2020R1A2C1011918) It was also supported by the NRF grant funded by the Korea government (MSIT). (No. 2021R1F1A1049435)
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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