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Sci Rep ; 13(1): 7147, 2023 05 02.
Artículo en Inglés | MEDLINE | ID: mdl-37130900

RESUMEN

Developing new capabilities to predict the risk of intracranial aneurysm rupture and to improve treatment outcomes in the follow-up of endovascular repair is of tremendous medical and societal interest, both to support decision-making and assessment of treatment options by medical doctors, and to improve the life quality and expectancy of patients. This study aims at identifying and characterizing novel flow-deviator stent devices through a high-fidelity computational framework that combines state-of-the-art numerical methods to accurately describe the mechanical exchanges between the blood flow, the aneurysm, and the flow-deviator and deep reinforcement learning algorithms to identify a new stent concepts enabling patient-specific treatment via accurate adjustment of the functional parameters in the implanted state.


Asunto(s)
Aneurisma Roto , Procedimientos Endovasculares , Aneurisma Intracraneal , Humanos , Aneurisma Intracraneal/cirugía , Stents , Resultado del Tratamiento , Hemodinámica , Procedimientos Endovasculares/métodos
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