Evidence Hub

Application of additively manufactured bone scaffold: a systematic review

Shi Q, Chen J, Chen J, Liu Y, Wang H

Biofabrication, 2024

Abstract

The application of additive manufacturing (AM) technology plays a significant role in various fields, incorporating a wide range of cutting-edge technologies such as aerospace, medical treatment, electronic information, and materials. It is currently widely adopted for medical services, national defense, and industrial manufacturing. In recent years, AM has also been extensively employed to produce bone scaffolds and implant materials. Through AM, products can be manufactured without being constrained by complex internal structures. AM is particularly advantageous in the production of macroscopically irregular and microscopically porous biomimetic bone scaffolds, with short production cycles required. In this paper, AM commonly used to produce bone scaffolds and orthopedic implants is overviewed to analyze the different materials and structures adopted for AM. The applications of antibacterial bone scaffolds and bone scaffolds in biologically relevant animal models are discussed. Also, the influence on the comprehensive performance of product mechanics, mass transfer, and biology is explored. By identifying the reasons for the limited application of existing AM in the biomedical field, the solutions are proposed. This study provides an important reference for the future development of AM in the field of orthopedic healthcare. In conclusion, various AM technologies, the requirements of bone scaffolds and the important role of AM in building bridges between biomaterials,…

How strong is the evidence?

Evidence Hub reads this as a systematic review, done in animal, not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free