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Frictional force analysis of stent retriever devices using a realistic vascular model: Pilot study SCIE SCOPUS

Title
Frictional force analysis of stent retriever devices using a realistic vascular model: Pilot study
Authors
Kwak, YoungseokSon, WonsooKim, Byoung-JoonKim, MyungsooYoon, Sang-YoulPark, JaechanLim, JongkyeongKim, JoonwonKang, Dong-Hun
Date Issued
2022-08
Publisher
FRONTIERS MEDIA SA
Abstract
Objective: To date, no vascular model to analyze frictional forces between stent retriever devices and vessel walls has been designed to be similar to the real human vasculature. We developed a novel in vitro intracranial cerebrovascular model and analyzed frictional forces of three stent retriever devices. Methods: A vascular mold was created based on digital subtraction angiography of a patient's cerebral vessels. The vascular model was constructed using polydimethylsiloxane (PDMS, Dow Corning, Inc.) as a silicone elastomer. The vascular model was coated on its inner surface with a lubricating layer to create a low coefficient of friction (similar to 0.037) to closely approximate the intima. A pulsatile blood pump was used to produce blood flow inside the model to approximate real vascular conditions. The frictional forces of Trevo XP, Solitaire 2, and Eric 4 were analyzed for initial and maximal friction retrieval forces using this vascular model. The total pulling energy generated during the 3 cm movement was also obtained. Results: Results for initial retrieval force were as follows: Trevo, 0.09 +/- 0.04 N; Solitaire, 0.25 +/- 0.07 N; and Eric, 0.33 +/- 0.21 N. Results for maximal retrieval force were as follows: Trevo, 0.36 +/- 0.07 N; Solitaire, 0.54 +/- 0.06 N; and Eric, 0.80 +/- 0.13 N. Total pulling energy (N.cm) was 0.40 +/- 0.10 in Trevo, 0.65 +/- 0.10 in Solitaire, and 0.87 +/- 0.14 in Eric, respectively. Conclusions: Using a realistic vascular model, different stent retriever devices were shown to have statistically different frictional forces. Future studies using a realistic vascular model are warranted to assess SRT devices.
URI
https://oasis.postech.ac.kr/handle/2014.oak/117896
DOI
10.3389/fneur.2022.964354
ISSN
1664-2295
Article Type
Article
Citation
FRONTIERS IN NEUROLOGY, vol. 13, 2022-08
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김준원KIM, JOON WON
Dept of Mechanical Enginrg
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