Recent advancement in finite element analysis of spinal interbody cages: A review

有限元法 脊柱融合术 生物力学 退行性椎间盘病 固定(群体遗传学) 计算机科学 生物医学工程 医学 结构工程 工程类 外科 解剖 腰椎 环境卫生 人口
作者
Ruofan Wang,Zenghui Wu
出处
期刊:Frontiers in Bioengineering and Biotechnology [Frontiers Media SA]
卷期号:11: 1041973-1041973 被引量:18
标识
DOI:10.3389/fbioe.2023.1041973
摘要

Finite element analysis (FEA) is a widely used tool in a variety of industries and research endeavors. With its application to spine biomechanics, FEA has contributed to a better understanding of the spine, its components, and its behavior in physiological and pathological conditions, as well as assisting in the design and application of spinal instrumentation, particularly spinal interbody cages (ICs). IC is a highly effective instrumentation for achieving spinal fusion that has been used to treat a variety of spinal disorders, including degenerative disc disease, trauma, tumor reconstruction, and scoliosis. The application of FEA lets new designs be thoroughly “tested” before a cage is even manufactured, allowing bio-mechanical responses and spinal fusion processes that cannot easily be experimented upon in vivo to be examined and “diagnosis” to be performed, which is an important addition to clinical and in vitro experimental studies. This paper reviews the recent progress of FEA in spinal ICs over the last six years. It demonstrates how modeling can aid in evaluating the biomechanical response of cage materials, cage design, and fixation devices, understanding bone formation mechanisms, comparing the benefits of various fusion techniques, and investigating the impact of pathological structures. It also summarizes the various limitations brought about by modeling simplification and looks forward to the significant advancement of spine FEA research as computing efficiency and software capabilities increase. In conclusion, in such a fast-paced field, the FEA is critical for spinal IC studies. It helps in quantitatively and visually demonstrating the cage characteristics after implanting, lowering surgeons’ learning costs for new cage products, and probably assisting them in determining the best IC for patients.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
柯彦完成签到 ,获得积分10
刚刚
孤独含蕾完成签到,获得积分10
1秒前
zlzlzl发布了新的文献求助10
1秒前
Coco完成签到,获得积分10
1秒前
2秒前
Hyp发布了新的文献求助10
3秒前
yaya完成签到,获得积分10
3秒前
3秒前
4秒前
bkagyin应助sher采纳,获得10
5秒前
6秒前
孙敬涵发布了新的文献求助10
8秒前
9秒前
9秒前
无极微光应助锦鲤大王采纳,获得20
11秒前
木林森发布了新的文献求助10
11秒前
11秒前
13秒前
15秒前
无极微光应助无情的傲玉采纳,获得20
16秒前
Lyeming完成签到,获得积分10
16秒前
17秒前
爆米花应助wang采纳,获得10
17秒前
小格发布了新的文献求助10
17秒前
Huanghong完成签到,获得积分10
17秒前
可靠小懒虫完成签到,获得积分10
17秒前
Ran完成签到 ,获得积分10
18秒前
豆豆发布了新的文献求助10
18秒前
18秒前
你好完成签到,获得积分10
18秒前
aaaa发布了新的文献求助10
20秒前
21秒前
长至发布了新的文献求助10
23秒前
不想起昵称完成签到 ,获得积分10
23秒前
危险份子完成签到,获得积分10
24秒前
温柔元风发布了新的文献求助10
24秒前
25秒前
慕青应助不太入门的脑筋采纳,获得10
25秒前
DAY完成签到 ,获得积分10
26秒前
Epicat发布了新的文献求助10
26秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 3000
VASCULITIS(血管炎)Rheumatic Disease Clinics (Clinics Review Articles) —— 《风湿病临床》(临床综述文章) 1000
Feldspar inclusion dating of ceramics and burnt stones 1000
What is the Future of Psychotherapy in a Digital Age? 801
The Psychological Quest for Meaning 800
Digital and Social Media Marketing 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5977003
求助须知:如何正确求助?哪些是违规求助? 7335589
关于积分的说明 16009095
捐赠科研通 5116513
什么是DOI,文献DOI怎么找? 2746558
邀请新用户注册赠送积分活动 1714799
关于科研通互助平台的介绍 1623747