A Mechano-Chemical Computational Model of Deep Vein Thrombosis

Abstract

Computational models of deep vein thrombosis (DVT) typically account for either the mechanical or biochemical factors involved in thrombus formation. Developing a model that accounts for both factors will improve our understanding of the coagulation process in this particular disease. The work presented in this study details the development of a CFD model that considers the biochemical reactions between thrombin and fibrinogen, pulsatile blood flow, and clot growth within a three-dimensional patient-specific common femoral vein. Thrombin is released into the bloodstream from an injury zone on the wall of the vein. The Michaelis–Menten equation is used to represent the conversion of thrombin and fibrinogen to fibrin, the final product of the coagulation process. The model development starts with a two-dimensional idealized geometry. At this stage, the model is used to conduct a parametric study to determine the effects of varying parameters such as inlet velocity, vein diameter, and peak thrombin concentration on the size and shape of the clot formed. Peak thrombin concentration is the key factor driving the initiation and propagation of clots in the vein. To demonstrate the potential use of the model, the two-dimensional model is then extended to an image-derived three-dimensional patient-specific geometry. Realistic clot growth was achieved using this model, and the clot was compared to a clot formed in vivo. The volume of the clot that formed in the patient was about 4% smaller than that formed in the simulation. This demonstrates that with further development and refinement, this model could be used for patient-specific interventional planning. The model provides a means for predicting clot formation under different physiological conditions in a non-invasive manner.

Computational Fluid Dynamics (CFD) Model for Analysing the Role of Shear Stress in Angiogenesis in Rheumatoid Arthritis

“…Significant advances in computing technology have improved the approximation of solutions for the Navier-Stokes equations, which describe fluid flow in a wide range of contexts [57][58][59][60][61][62][63][64][65][66][67]. As a result, CFD models have been developed for a plethora of applications, including biofluid flows [68][69][70][71]. The solvers compute pressure and velocity results, which can then be used to calculate quantities such as shear stress.…”