Why the study?
Computational fluid dynamics results for intracranial aneurysm growth and rupture often conflict with real pathophysiological manifestations, leaving causes of modelling errors unclear.
This review highlights the methodological challenges and modelling errors in using computational fluid dynamics for intracranial aneurysm risk stratification and proposes potential solutions.
CFD inconsistencies with pathophysiology caution against clinical reliance for aneurysm risk; leaves open standardized validation in larger cohorts.
As a promising risk stratification tool, computational fluid dynamics plays an important role in the evaluation of the growth and rupture of intracranial aneurysms. However, many of the experimental results obtained with this tool are inconsistent with real pathophysiological manifestations, which has confused researchers and clinicians. These contradictory results may be due to the inconsistency of parameter definitions, the small amount of data, and the complexity and heterogeneity of the growth and rupture of intracranial aneurysms. In this paper, by summarizing the research results of computational fluid dynamics in recent years, the author tries to find out the broad causes of the problem of explicit modelling error and propose possible solutions.
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Wu et al. (2020) studied this question.
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