Development of a computational model for macroscopic predictions of device-induced thrombosis

Joshua O. Taylor, Richard S. Meyer, Steven Deutsch, Keefe B. Manning

Research output: Contribution to journalArticlepeer-review

53 Scopus citations


While cardiovascular device-induced thrombosis is associated with negative patient outcomes, the convoluted nature of the processes resulting in a thrombus makes the full thrombotic network too computationally expensive to simulate in the complex geometries and flow fields associated with devices. A macroscopic, continuum computational model is developed based on a simplified network, which includes terms for platelet activation (chemical and mechanical) and thrombus deposition and growth in regions of low wall shear stress (WSS). Laminar simulations are performed in a two-dimensional asymmetric sudden expansion geometry and compared with in vitro thrombus size data collected using whole bovine blood. Additionally, the predictive power of the model is tested in a flow cell containing a series of symmetric sudden expansions and contractions. Thrombi form in the low WSS area downstream of the asymmetric expansion and grow into the nearby recirculation region, and thrombus height and length largely remain within 95 % confidence intervals calculated from the in vitro data for 30 min of blood flow. After 30 min, predicted thrombus height and length are 0.94 and 4.32 (normalized by the 2.5 mm step height). Importantly, the model also correctly predicts locations of thrombus deposition observed in the in vitro flow cell of expansions and contractions. As the simulation results, which rely on a greatly reduced model of the thrombotic network, are still able to capture the macroscopic behavior of the full network, the model shows promise for timely predictions of device-induced thrombosis toward optimizing and expediting the device development process.

Original languageEnglish (US)
Pages (from-to)1713-1731
Number of pages19
JournalBiomechanics and Modeling in Mechanobiology
Issue number6
StatePublished - Dec 1 2016

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Modeling and Simulation
  • Mechanical Engineering


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