BACKGROUND AND PURPOSE: Hemodynamic factors are thought to play an important role in the initiation, growth, and rupture of cerebral aneurysms. This report describes a pilot clinical study of the association between intra-aneurysmal hemodynamic characteristics from computational fluid dynamic models and the rupture of cerebral aneurysms. METHODS: A total of 62 patient-specific models of cerebral aneurysms were constructed from 3D angiography images. Computational fluid dynamics simulations were performed under pulsatile flow conditions measured on a normal subject. The aneurysms were classified into different categories, depending on the complexity and stability of the flow pattern, the location and size of the flow impingement region, and the size of the inflow jet. The 62 models consisted of 25 ruptured and 34 unruptured aneurysms and 3 cases with unknown histories of hemorrhage. The hemodynamic features were analyzed for associations with history of rupture. RESULTS: A large variety of flow patterns was observed: 72% of ruptured aneurysms had complex or unstable flow patterns, 80% had small impingement regions, and 76% had small jet sizes. By contrast, unruptured aneurysms accounted for 73%, 82%, and 75% of aneurysms with simple stable flow patterns, large impingement regions, and large jet sizes, respectively. Aneurysms with small impingement sizes were 6.3 times more likely to have experienced rupture than those with large impingement sizes (P = .01). CONCLUSIONS: Image-based patient-specific numeric models can be constructed in an efficient manner that allows clinical studies of intra-aneurysmal hemodynamics. A simple flow characterization system was proposed, and interesting trends in the association between hemodynamic features and aneurysmal rupture were found. Simple stable patterns, large impingement regions, and jet sizes were more commonly seen with unruptured aneurysms. By contrast, ruptured aneurysms were more likely to have disturbed flow patterns, small impingement regions, and narrow jets.
BACKGROUND AND PURPOSE: Hemodynamic factors are thought to play an important role in the initiation, growth, and rupture of cerebral aneurysms. This report describes a pilot clinical study of the association between intra-aneurysmal hemodynamic characteristics from computational fluid dynamic models and the rupture of cerebral aneurysms. METHODS: A total of 62 patient-specific models of cerebral aneurysms were constructed from 3D angiography images. Computational fluid dynamics simulations were performed under pulsatile flow conditions measured on a normal subject. The aneurysms were classified into different categories, depending on the complexity and stability of the flow pattern, the location and size of the flow impingement region, and the size of the inflow jet. The 62 models consisted of 25 ruptured and 34 unruptured aneurysms and 3 cases with unknown histories of hemorrhage. The hemodynamic features were analyzed for associations with history of rupture. RESULTS: A large variety of flow patterns was observed: 72% of ruptured aneurysms had complex or unstable flow patterns, 80% had small impingement regions, and 76% had small jet sizes. By contrast, unruptured aneurysms accounted for 73%, 82%, and 75% of aneurysms with simple stable flow patterns, large impingement regions, and large jet sizes, respectively. Aneurysms with small impingement sizes were 6.3 times more likely to have experienced rupture than those with large impingement sizes (P = .01). CONCLUSIONS: Image-based patient-specific numeric models can be constructed in an efficient manner that allows clinical studies of intra-aneurysmal hemodynamics. A simple flow characterization system was proposed, and interesting trends in the association between hemodynamic features and aneurysmal rupture were found. Simple stable patterns, large impingement regions, and jet sizes were more commonly seen with unruptured aneurysms. By contrast, ruptured aneurysms were more likely to have disturbed flow patterns, small impingement regions, and narrow jets.
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Authors: J J Schneiders; H A Marquering; R van den Berg; E VanBavel; B Velthuis; G J E Rinkel; C B Majoie Journal: AJNR Am J Neuroradiol Date: 2014-02-20 Impact factor: 3.825