BACKGROUND: Aortic diseases, including aortic aneurysms, are the 12th leading cause of death in the United States. The incidence of descending thoracic aortic aneurysms is estimated at 10.4 per 100,000 patient-years. Growing evidence suggests that stress measurements derived from structural analysis of aortic geometries predict clinical outcomes better than diameter alone. METHODS: Twenty-five patients undergoing clinical and radiologic surveillance for thoracic aortic aneurysms were retrospectively identified. Custom MATLAB algorithms were employed to extract aortic wall and intraluminal thrombus geometry from computed tomography angiography scans. The resulting reconstructions were loaded with 120 mm Hg of pressure using finite element analysis. Relationships among peak wall stress, aneurysm growth, and clinical outcome were examined. RESULTS: The average patient age was 71.6 ± 10.0 years, and average follow-up time was 17.5 ± 9 months (range, 6 to 43). The mean initial aneurysm diameter was 47.8 ± 8.0 mm, and the final diameter was 52.1 ± 10.0 mm. Mean aneurysm growth rate was 2.9 ± 2.4 mm per year. A stronger correlation (r = 0.894) was found between peak wall stress and aneurysm growth rate than between maximal aortic diameter and growth rate (r = 0.531). Aneurysms undergoing surgical intervention had higher peak wall stresses than aneurysms undergoing continued surveillance (300 ± 75 kPa versus 229 ± 47 kPa, p = 0.01). CONCLUSIONS: Computational peak wall stress in thoracic aortic aneurysms was found to be strongly correlated with aneurysm expansion rate. Aneurysms requiring surgical intervention had significantly higher peak wall stresses. Peak wall stress may better predict clinical outcome than maximal aneurysmal diameter, and therefore may guide clinical decision-making.
BACKGROUND:Aortic diseases, including aortic aneurysms, are the 12th leading cause of death in the United States. The incidence of descending thoracic aortic aneurysms is estimated at 10.4 per 100,000 patient-years. Growing evidence suggests that stress measurements derived from structural analysis of aortic geometries predict clinical outcomes better than diameter alone. METHODS: Twenty-five patients undergoing clinical and radiologic surveillance for thoracic aortic aneurysms were retrospectively identified. Custom MATLAB algorithms were employed to extract aortic wall and intraluminal thrombus geometry from computed tomography angiography scans. The resulting reconstructions were loaded with 120 mm Hg of pressure using finite element analysis. Relationships among peak wall stress, aneurysm growth, and clinical outcome were examined. RESULTS: The average patient age was 71.6 ± 10.0 years, and average follow-up time was 17.5 ± 9 months (range, 6 to 43). The mean initial aneurysm diameter was 47.8 ± 8.0 mm, and the final diameter was 52.1 ± 10.0 mm. Mean aneurysm growth rate was 2.9 ± 2.4 mm per year. A stronger correlation (r = 0.894) was found between peak wall stress and aneurysm growth rate than between maximal aortic diameter and growth rate (r = 0.531). Aneurysms undergoing surgical intervention had higher peak wall stresses than aneurysms undergoing continued surveillance (300 ± 75 kPa versus 229 ± 47 kPa, p = 0.01). CONCLUSIONS: Computational peak wall stress in thoracic aortic aneurysms was found to be strongly correlated with aneurysm expansion rate. Aneurysms requiring surgical intervention had significantly higher peak wall stresses. Peak wall stress may better predict clinical outcome than maximal aneurysmal diameter, and therefore may guide clinical decision-making.
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