RESUMEN
BACKGROUND: Rates of durable aneurysm occlusion following coil embolization vary widely, and a better understanding of coil mass mechanics is desired. The goal of this study is to evaluate the impact of packing density and coil uniformity on aneurysm permeability. METHODS: Aneurysm models were coiled using either Guglielmi detachable coils or Target coils. The permeability was assessed by taking the ratio of microspheres passing through the coil mass to those in the working fluid. Aneurysms containing coil masses were sectioned for image analysis to determine surface area fraction and coil uniformity. RESULTS: All aneurysms were coiled to a packing density of at least 27%. Packing density, surface area fraction of the dome and neck, and uniformity of the dome were significantly correlated (p<0.05). Hence, multivariate principal components-based partial least squares regression models were used to predict permeability. Similar loading vectors were obtained for packing and uniformity measures. Coil mass permeability was modeled better with the inclusion of packing and uniformity measures of the dome (r(2)=0.73) than with packing density alone (r(2)=0.45). The analysis indicates the importance of including a uniformity measure for coil distribution in the dome along with packing measures. CONCLUSIONS: A densely packed aneurysm with a high degree of coil mass uniformity will reduce permeability.
Asunto(s)
Embolización Terapéutica/métodos , Aneurisma Intracraneal/terapia , Circulación Cerebrovascular , Humanos , Aneurisma Intracraneal/patología , Modelos Anatómicos , Permeabilidad , Resultado del TratamientoRESUMEN
This paper evaluates existing taxonomies aimed at characterizing the interaction between robots and their users and modifies them for health care applications. The modifications are based on existing robot technologies and user acceptance of robotics. Characterization of the user, or in this case the patient, is a primary focus of the paper, as they present a unique new role as robot users. While therapeutic and monitoring-related applications for robots are still relatively uncommon, we believe they will begin to grow and thus it is important that the spurring relationship between robot and patient is well understood.
