Three-Dimensional Morphological Change of Intracranial Aneurysms Before and Around Rupture

BACKGROUND AND OBJECTIVES: Patients with an unruptured intracranial aneurysm often undergo periodic imaging to detect potential aneurysm growth, which is associated with an increased rupture risk. Because prediction of rupture based on growth is moderate, morphological changes have gained interest as a risk factor for rupture. We studied 3-dimensional–quantified morphological changes over time during radiological monitoring before rupture and around rupture. METHODS: In this retrospective observational study, we identified aneurysms that ruptured during follow-up, with imaging available for at least 2 time points before rupture and one after rupture. For each time point, we obtained 8 morphological parameters: 2-dimensional size, volume, surface area, compactness 1 and 2, sphericity, elongation, and flatness. Morphological changes before rupture and around rupture were log-transformed, scaled, and analyzed with linear mixed-effects models. RESULTS: We included 16 aneurysms in 16 patients who were imaged between 2004 and 2021. In the time period before rupture (median follow-up duration 1200 days, IQR 736-1340), 3 size-related morphological parameters increased: 2-dimensional size (estimated mean change 0.44, 95% CI 0.24-0.65), volume (estimated mean change 0.34, 95% CI 0.12-0.56), and surface area (0.33, 95% CI 0.11-0.54). In the period around rupture (median follow-up duration 407 days, IQR 148-719), these parameters further increased. In addition, 5 morphological parameters (compactness 1 and 2, sphericity, elongation, and flatness) decreased around rupture but not before rupture. CONCLUSION: Change in aneurysm volume and surface area may be novel risk factors for rupture. Because most morphological parameters changed around but not before rupture, morphological changes during these 2 periods should be regarded as different processes. This implies that postrupture morphology should not be used as a surrogate for prerupture morphology in rupture prediction models.