健康信息学的进步:对内侧开刃高胫骨截骨术和外侧半月板撕裂的有限元分析。

IF 2.6 4区 工程技术 Q1 Mathematics
Lin Chen, Mingjun Wang, Zhanyu Wu, Jinbo Sun, Jianglong Li, Chun Chen, Chuan Ye
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引用次数: 0

摘要

膝关节内侧间室骨关节炎可通过内侧开刃高胫骨截骨术(MOWHTO)得到有效治疗。但 MOWHTO 治疗轻度外侧半月板撕裂的可行性和安全性尚不清楚。本研究探讨了在外侧半月板损伤的 MOWHTO 过程中调整膝关节负重线比率(WBLr)的可行性和安全性。我们使用一名健康成年男性的下肢计算机断层扫描和膝关节磁共振成像图像创建了一个正常的精细元素(FE)模型。在此基础上,我们生成了 9 个 MOWHTO 操作(WBLr:40-80%)的 FE 模型和 15 个不同外侧半月板损伤的模型。在所有情况下都施加了 650N 的压缩载荷以计算 von Mises 应力(VMS),并将 WBLr 为 77.5% 时完整外侧半月板的最大 VMS 作为校正上限应力。我们的实验结果表明,轻微的外侧半月板撕裂可以承受 MOWHTO,而严重的撕裂则不能。我们的研究结果扩大了 MOWHTO 的应用范围,并为外侧半月板损伤患者的实际决策提供了理论指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancements in health informatics: finite element insights into medial open-wedge high tibial osteotomy and lateral meniscal tears.

Knee medial compartment osteoarthritis is effectively treated by a medial open-wedge high tibial osteotomy (MOWHTO). The feasibility and safety of MOWHTO for mild lateral meniscal tears are unknown. This study examined the feasibility and safety of knee joint weight-bearing line ratio (WBLr) adjustment during MOWHTO with lateral meniscal injuries. We used a healthy adult male's lower extremities computed tomography scans and knee joint magnetic resonance imaging images to create a normal fine element (FE) model. Based on this model, we generated nine FE models for the MOWHTO operation (WBLr: 40-80%) and 15 models for various lateral meniscal injuries. A compressive load of 650N was applied to all cases to calculate the von Mises stress (VMS), and the intact lateral meniscus' maximal VMS at 77.5% WBLr was accepted as the corrective upper limit stress. Our experimental results show that mild lateral meniscal tears can withstand MOWHTO, while severe tears cannot. Our findings expand the use of MOWHTO and provide a theoretical direction for practical decisions in patients with lateral meniscal injuries.

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来源期刊
Mathematical Biosciences and Engineering
Mathematical Biosciences and Engineering 工程技术-数学跨学科应用
CiteScore
3.90
自引率
7.70%
发文量
586
审稿时长
>12 weeks
期刊介绍: Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing. MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).
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