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Development of a computational model for acute ischemic stroke recanalization through cyclic aspiration

  • Bryan C. GoodEmail author
  • Scott Simon
  • Keefe Manning
  • Francesco Costanzo
Original Paper
  • 24 Downloads

Abstract

Acute ischemic stroke (AIS), the result of embolic occlusion of a cerebral artery, is responsible for 87% of the 6.5 million stroke-related deaths each year. Despite improvements from first-generation thrombectomy devices for treating AIS, 80% of eligible stroke patients will either die or suffer a major disability. In order to maximize the number of patients with good outcomes, new AIS therapies need to be developed to achieve complete reperfusion on the first pass. One such therapy that has shown promise experimentally is the application of cyclic aspiration pressure, which led to higher recanalization rates at lower pressure magnitudes. In order to investigate AIS and cyclic aspiration recanalization, an improved computational modeling framework was developed, combining a viscoelastic thromboembolus model with a cohesive zone (CZ) model for the thromboembolus–artery interface. The model was first validated against experimental displacement data of a cyclically aspirated thromboembolus analog. The CZ model parameters, including the addition of a damage accumulation model, were then investigated computationally to determine their individual effects on the thromboembolus and CZ behavior. The relaxation time and the damage model critical opening length were shown to have the greatest effect on the CZ opening and led to increased displacement that accumulated with repeated loading. Additional simulations were performed with parameters relevant to AIS including internal carotid artery dimensions and thromboemboli mechanical properties. In these AIS cases, more upstream CZ opening was observed compared to the thromboembolus analog cases and greater displacement was achieved with the lower-frequency aspiration (0.5 vs 1 Hz).

Keywords

Acute ischemic stroke Thrombectomy Cyclic aspiration Computational modeling Cohesive zone 

Notes

Acknowledgements

The work presented in this study was partially supported by AHA Postdoctoral Fellowship 19POST34370040. Additionally, the authors would like to acknowledge undergraduate researchers Connor Foust and Josh Kugel for their help with experimental data collection.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no other conflicts of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Biomedical EngineeringPennsylvania State UniversityUniversity ParkUSA
  2. 2.Department of NeurosurgeryPenn State Hershey Medical CenterHersheyUSA
  3. 3.Department of SurgeryPenn State Hershey Medical CenterHersheyUSA
  4. 4.Department of Engineering Science and MechanicsPennsylvania State UniversityUniversity ParkUSA

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