Recent Advances in Computational Modeling of Thrombosis

TL;DR

This review summarizes recent computational modeling strategies for thrombosis, highlighting their strengths, weaknesses, and future research directions in understanding blood clot formation across multiple scales.

Contribution

It provides a comprehensive classification and critical analysis of existing computational models for thrombosis, identifying gaps and proposing future research avenues.

Findings

Multiple modeling approaches exist, including continuum, system, discrete particles, and multi-scale methods.

No single model currently predicts both physiological and mechanical properties of blood clots.

Future research should focus on integrating models for comprehensive predictions.

Abstract

The study of thrombosis is crucial to understand and develop new therapies for diseases like deep vein thrombosis, diabetes related strokes, pulmonary embolism etc. The last two decades have seen an exponential growth in studies related to the blood clot formation using computational tools and through experiments. Despite of this growth, the complete mechanism behind thrombus formation and hemostasis is not known yet. The computational models and methods used in this context are diversified into different spatiotemporal scales, yet there is no single model which can predict both physiological and mechanical properties of the blood clots. In this review, we will attempt to list out all major strategies attempted by researchers so far to model the blood clot formation using existing computational techniques. This review classifies them into continuum level, system level, discrete particles and multi-scale methods. We will also discuss the strength and weakness of various methods and possible future directions in which the computational blood clot research can thrive.