Impact of friction force and retrieval speed on in silico mechanical thrombectomies: a sensitivity analysis

TL;DR

This study investigates how variations in friction forces and retrieval speed affect the success of in silico mechanical thrombectomy procedures, emphasizing the importance of accurate friction modeling for realistic simulations.

Contribution

It provides a sensitivity analysis of friction coefficients and retrieval speeds in virtual thrombectomy, highlighting their impact on procedure outcomes and the need for precise friction parameter estimation.

Findings

Higher clot-vessel friction causes clot fragmentation and failure.

Lower stent-clot friction leads to clot slippage, higher causes fragmentation.

Higher stent-vessel friction results in stent compression and clot dislodgment.

Abstract

Background: Mechanical Thrombectomy (MT) is a widely accepted first-line treatment for Acute Ischemic Stroke (AIS) and it has been studied using in vitro and in silico models. Thrombectomy outcomes have been performed for patient-specific cases using in silico models. However, until now, in vivo friction coefficients for stent-vessel, stent-clot, and clot-vessel interactions are unknown, but in vitro experiments have been attempted with significant standard deviations. These interactions and friction coefficients have been considered an important aspect of thrombectomy success. Objectives: In the current study, we explored the influence of variation in friction forces for stent-vessel, stent-clot, and clot-vessel interactions using virtual mechanical thrombectomy (VMT). We have performed three simulations for each interaction and varied friction coefficients around the standard deviation observed in the past in vitro studies. Results: (i) clot-vessel friction: higher friction leads to clot fragmentation and VMT failure. (ii) stent-clot friction: it is susceptible to VMT outcomes, with lower values showing the slippage of the clot while higher values lead to fragmentation. (iii) stent-vessel friction: higher friction shows compression of the stent in curved vessels and dislodgment of clot from stent retriever (SR) due to its compression, which leads to VMT failure. (iv) retrieval speed (RS): higher RS (>30 mm/s) leads to significant stent compression and unrealistic behavior of the SR. Conclusions: Analysis of results proposes the necessity for calculating accurate friction factor values and their implementation into in silico models, due to their sensitivity towards thrombectomy outcomes. Such in silico models mimic in vivo thrombectomy more closely and can be used in mechanical thrombectomy planning, management, and decision-making.