Shared and Distinct Rupture Discriminants of Small and Large Intracranial Aneurysms

Abstract

<div class="section"> <a class="named-anchor" id="S1"> <!-- named anchor --> </a> <h5 class="section-title" id="d5113400e235">Background and Purpose</h5> <p id="P1">Many ruptured intracranial aneurysms (IAs) are small. Clinical presentations suggest that small and large IAs could have different phenotypes. It is unknown if small and large IAs have different characteristics that discriminate rupture. </p> </div><div class="section"> <a class="named-anchor" id="S2"> <!-- named anchor --> </a> <h5 class="section-title" id="d5113400e240">Methods</h5> <p id="P2">We analyzed morphologic, hemodynamic, and clinical parameters of 413 retrospectively collected IAs (training cohort; 102 ruptured IAs). Hierarchal cluster analysis was performed to determine a size cutoff to dichotomize the IA population into small and large IAs. We applied multivariate logistic regression to build rupture discrimination models for small IAs, large IAs, and an aggregation of all IAs. We validated the ability of these 3 models to predict rupture status in a second, independently collected cohort of 129 IAs (testing cohort; 14 ruptured IAs). </p> </div><div class="section"> <a class="named-anchor" id="S3"> <!-- named anchor --> </a> <h5 class="section-title" id="d5113400e245">Results</h5> <p id="P3">Hierarchal cluster analysis in the training cohort confirmed that small and large IAs are best separated at 5mm based on morphologic and hemodynamic features (area under the curve [AUC]=0.81). For small IAs (&lt;5mm), the resulting rupture discrimination model included undulation index, oscillatory shear index, previous subarachnoid hemorrhage (SAH), and absence of multiple IAs (AUC=0.84, 95% confidence interval[CI] 0.78-0.88); whereas for large IAs (≥5mm), the model included undulation index, low wall shear stress, previous SAH, and IA location (AUC=0.87, 95% CI 0.82-0.93). The model for the aggregated training cohort retained all the parameters in the size-dichotomized models. Results in the testing cohort showed that the size-dichotomized rupture discrimination model had higher sensitivity (64% vs. 29%) and accuracy (77% vs. 74%), marginally higher AUC (0.75, 95% CI 0.61-0.88 vs. 0.67, 95% CI 0.52-0.82), and similar specificity (78% vs. 80%) compared to the aggregate-based model. </p> </div><div class="section"> <a class="named-anchor" id="S4"> <!-- named anchor --> </a> <h5 class="section-title" id="d5113400e250">Conclusions</h5> <p id="P4">Small (&lt;5mm) and large (≥5mm) IAs have different hemodynamic and clinical, but not morphologic, rupture discriminants. Size-dichotomized rupture discrimination models performed better than the aggregate model. </p> </div>