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Updated: Oct 3, 2025

Quantification of Atherosclerosis in Mice

Quantification of Atherosclerosis in Mice

Published on: June 12, 2019

Recent Progress in in vitro Models for Atherosclerosis Studies.

Jun Chen¹, Xixi Zhang¹, Reid Millican²

¹Department of Biomedical Engineering, The University of Alabama at Birmingham, Birmingham, AL, United States.

Frontiers in Cardiovascular Medicine

|February 14, 2022

Summary

This review explores advanced in vitro models for studying atherosclerosis, a leading cause of cardiovascular disease. These models offer efficient and economical alternatives to animal studies for developing new treatments.

Keywords:

atherosclerosis disease models in vitro models and methods microfluidic chips tissue-engineered blood vessels

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Area of Science:

Biomedical Engineering
Cardiovascular Research
Cell Biology

Background:

Atherosclerosis, characterized by arterial hardening and narrowing, is a major cause of mortality.
Effective treatments for atherosclerosis necessitate robust in vitro models.
In vitro models offer advantages over animal models in terms of efficiency and cost.

Purpose of the Study:

To review recent advancements in in vitro models for atherosclerosis research.
To cover both traditional 2D and emerging 3D in vitro models.
To discuss the functions and future perspectives of these models.

Main Methods:

Review of traditional 2D in vitro models (tissue culture plates, cell sheets).
Discussion of advanced 2D microfluidic chip models.
Exploration of emerging 3D in vitro models (spheroids, hydrogels, engineered vessels, vessel-on-a-chip).

Main Results:

Atherosclerosis research benefits from diverse in vitro models.
2D models provide a foundational approach.
3D models, including microfluidic and organ-on-a-chip systems, offer enhanced complexity and physiological relevance.

Conclusions:

In vitro models are crucial for advancing atherosclerosis research and treatment development.
The field is rapidly evolving with the introduction of sophisticated 3D and microfluidic systems.
Future research should focus on further refining these models for greater predictive power.