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

OBJECTIVE 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. METHODS 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). RESULTS 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. CONCLUSIONS 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 util- ity of RRS in a real-world setting as an adjunctive tool for the management of UIAs.

Automated summary

The study explores the clinical utility of Rupture Resemblance Score (RRS) in guiding the management of unruptured intracranial aneurysms (UIAs), particularly in challenging cases. Results indicate that RRS helps identify high-risk UIAs by analyzing their morphology and hemodynamics and comparing the RRS with treatment decisions.