Thin-film NiTi intrasaccular implant with flaps for aneurysm treatments
Source abstract
Abstract
Intracranial aneurysms are abnormal, balloon-like formations in the brain blood vessels. They carry a high risk of rupture, which can cause severe complications. Effective aneurysm treatments include reducing blood flow into the aneurysm sac. Coiling is an effective method of occluding the aneurysm sac. However, wide-neck aneurysms are associated with complications because large necks make it difficult to retain the coils securely in the aneurysm sac. This challenge can be overcome by using coil-assisting implants. This additional support avoids the risk of coils migrating into the parent artery avoiding such complications such as ischemic stroke. This study introduces a novel, coil-assisted implant design with flaps fabricated using micro-electromechanical system (MEMS) technology, which provides a higher degree of freedom in designing and prototyping. The designs contain a stable mechanical backbone with mobile thin flaps that allow secondary delivery of coils into the aneurysm sac. Mechanical tests are conducted to measure radial forces for secure anchoring in the aneurysm sac and compression forces to assess the hammering effect from pulsatile blood flow. Furthermore, the novel implants were tested and compared with a commercial braided implant in in-vitro environment using 3D-printed aneurysm models to understand their flow dynamics and coiling performance by using digital subtraction angiography. The findings showed that backbone/flap designs have greater mechanical stability, which enhances effectiveness compared to braided coil-assisting implants. Moreover, coiling was possible through mobile flaps, highlighting the potential for advancing the treatment of brain aneurysms.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Intracranial Aneurysms: Treatment and Complications · Shape Memory Alloy Transformations · Meningioma and schwannoma management
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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