Improving Risk Stratification and Surgical Decision-Making for Unruptured Cerebral Aneurysm: A Proof-of-Concept of Novel Morphological Parameters and Computational Hemodynamics

Background: Unruptured intracranial aneurysms (UIAs) represent a major challenge in neurosurgical practice. Rupture risk assessment traditionally relies on qualitative parameters, such as aneurysm size and shape, combined with surgical judgment and clinical expertise. However, these approaches may fail to account for the complex interplay between vascular morphology and hemodynamic forces that leads to aneurysm growth and rupture. Therefore, the development of reliable and quantitative parameters is essential to support neurosurgeons in balancing the risks of intervention against the natural history of the disease, thus optimizing decision-making for surgery. Methods: We developed an integrative framework based on a novel morphological parameter (MP), integrating multiple geometric descriptors into a single quantifiable index. To complement morphological assessment, patient-specific computational fluid dynamics (CFD) simulations were performed to evaluate hemodynamic factors known to influence aneurysm progression, thus analyzing structural and flow-related determinants of rupture risk. Results: In a cohort of 60 consecutive patients with MCA UIAs, MP showed strong concordance with the treatment decision made by an expert neurosurgeon regarding the indication for surgical clipping of aneurysms considered at risk of imminent rupture, providing an indirect, objective measure of UIA rupture risk stratification. CFD analyses confirmed that adverse hemodynamic conditions, including elevated intra-aneurysmal pressures and heterogeneous distribution of wall shear stress, correlated with unfavorable morphological features that were considered to indicate a higher risk of rupture by an expert neurosurgeon. Moreover, the integration of expert clinical judgment with quantitative indices may enhance the discrimination between aneurysms requiring early surgical intervention and those suitable for conservative management. Conclusions: This proof-of-concept study highlights the potential added value of combining morphological modelling and patient-specific hemodynamic analysis to support, rather than replace, expert neurosurgical judgment regarding the surgical management of unruptured MCA aneurysms. The proposed parameter (MP) shows concordance with expert operability decisions and may complement current neurosurgical evaluation as an ancillary decision-support tool, potentially contributing to safer operative strategies, more individualized patient management, and ultimately improved patient outcomes in the treatment of unruptured intracranial aneurysms.