A data-driven model to identify high-risk aneurysms and guide management decisions: the Rupture Resemblance Score

Previous studies have found that ruptured intracranial aneurysms (RIAs) have distinct morphological and hemodynamic characteristics, including higher size ratio and oscillatory shear index and lower wall shear stress. Unruptured intracranial aneurysms (UIAs) that possess similar characteristics to RIAs may be at a higher risk of rupture than those UIAs that do not. The authors previously developed the Rupture Resemblance Score (RRS), a data-driven computer model that can objectively gauge the similarity of UIAs to RIAs in terms of morphology and hemodynamics. The authors aimed to explore the clinical utility of RRS in guiding the management of UIAs, especially for challenging cases such as small UIAs.

Between September 2018 and June 2019, the authors retrospectively collected consecutive challenging cases of incidentally identified UIAs that were discussed during their weekly multidisciplinary neurovascular conference. From patient 3D digital subtraction angiography, they reconstructed the aneurysm geometry and performed computer-assisted 3D morphology analysis and computational fluid dynamics simulation. They calculated RRS for every UIA case and compared it against the treatment decision made at the neurovascular conference as well as the recommendation based on the unruptured intracranial aneurysm treatment score (UIATS).

Forty-seven patients with 79 UIAs, 90% of which were < 7 mm in size, were included in this study. The mean RRS (range 0.0-1.0) was 0.24 ± 0.31. At the conferences, treatment was endorsed for 45 of the UIAs (57%). These cases had significantly higher RRSs than the 34 cases suggested for observation (0.33 ± 0.34 vs 0.11 ± 0.19, p < 0.001). The UIATS-based recommendations were "observation" for 24 UIAs (30%), "treatment" for 21 UIAs (27%), and "not definitive" for 34 UIAs (43%). These "not definitive" cases were stratified by RRS based on similarity to RIAs.

Although not a rupture predictor, RRS is a data-driven model that gauges the similarity of UIAs to RIAs in terms of morphology and hemodynamics. In cases in which the UIATS-based recommendation is not definitive, RRS provides additional stratification to assist the identification of high-risk UIAs. The current study highlights the clinical utility of RRS in a real-world setting as an adjunctive tool for the management of UIAs.