Stroke: Vascular and Interventional Neurology (Nov 2023)

Abstract 249: In‐silico Versus In‐Vitro Evaluation of a New Stent‐Retriever Design: A Novel Approach to Pre‐clinical Development

  • Sara M. Bridio,
  • Praneeta Konduri,
  • Shashvat M. Desai,
  • Nerea Arrarte Terreros,
  • Giulia Luraghi,
  • Kunakorn Atchaneeyasakul,
  • Virginia Fregona,
  • Jose F. Rodriguez Matas,
  • Francesca Berti,
  • Dileep R. Yavagal,
  • Albert Yoo,
  • Charles B. Majoie,
  • Ashutosh P. Jadhav,
  • Henk A. Marquering,
  • Francesco Migliavacca

DOI
https://doi.org/10.1161/SVIN.03.suppl_2.249
Journal volume & issue
Vol. 3, no. S2

Abstract

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Introduction In‐vitro evaluation (analysis in a bench top flow model) is the gold standard and a regulatory requirement for pre‐clinical investigation of devices being developed for endovascular thrombectomy (EVT). In‐silico evaluation (computer simulated analysis in a virtual stroke model) has the potential to test and optimize large number of stent‐retriever design variations in a relatively time and cost‐effective manner. Further, new design concepts can be tested across multiple anatomical scenarios. We aim to validate the utility of in‐silico evaluation when compared with in‐vitro evaluation for the SuperNova Stent‐retriever. Methods In‐silico analysis was performed using a virtual thrombectomy model, built using data from a fine‐grained finite‐element model, to estimate the probability of successful recanalization and emboli in new/distal territory. Neurovascular anatomy of the virtual model was built based on digital subtraction angiography of an in‐vitro model (Sim Agility, Mentice, Inc). Gravity Medical Technology’s SuperNova Stent‐retriever was the device under investigation‐ physical device for in‐vitro analysis and virtual replica for in‐silico analysis (built using finite element analysis incorporating various physical metrics of the stent‐retriever). Experiments performed for in‐vitro analysis were replicated for in‐silico analysis. Multiple thrombectomy scenarios were defined and validation analysis was performed. Data was analyzed using SPSS 23 (IBM, Armonk, NY) Results We defined multiple thrombectomy scenarios including 1 cm red blood clot in M1 artery, 2 cm bifurcation M1‐M2 red blood clot (Y‐shaped clot), 1 cm white blood clot in M1 artery, and 1 cm white blood clot in superior M2 artery. The figure below demonstrates a pictorial representation of the first scenario‐ 1 cm red blood clot in M1 artery followed by mechanical thrombectomy simulation using the SuperNova stent‐retriever. Per our in‐vitro analysis (10 thrombectomy experiments), the rate of first pass effect and the rate of complete recanalization after a maximum of 3 passes using SuperNova stent‐retriever was 50% and 90%, respectively. Complete data from in‐silico analysis is being generated and will be presented at the conference. Preliminary data suggests high degree of concordance. Conclusion In‐silico analysis has the potential to improve and expedite pre‐clinical thrombectomy device development. Further studies are required to better understand the scope and potential of this technology.